feat: implement monitoring bootstrap #190
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WalkthroughThe changes introduce comprehensive monitoring capabilities to the Changes
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Actionable comments posted: 16
🧹 Outside diff range and nitpick comments (20)
controllers/greptimedbcluster/deployers/config/pipeline.yaml (2)
1-6: LGTM! Consider adding fallback timestamp formats for robustness.The date processor configuration is correct for parsing ISO 8601 formatted timestamps with microsecond precision. The format string accurately matches the example provided.
For improved robustness, consider adding fallback timestamp formats. This can help handle slight variations in timestamp formats that might occur. For example:
processors: - date: fields: - timestamp formats: - "%Y-%m-%dT%H:%M:%S.%6fZ" - "%Y-%m-%dT%H:%M:%S%z" - "%Y-%m-%dT%H:%M:%SZ"This change would allow the processor to handle timestamps with and without microseconds, as well as with different timezone representations.
8-28: LGTM! Consider grouping related fields for improved readability.The transformation rules are well-structured and comprehensive, covering all relevant log fields. The categorization into tags, fulltext, and timestamp types is logical and should facilitate efficient querying.
For improved readability and maintainability, consider grouping related fields together. For example:
transform: - fields: - level - target - module_path - file type: string index: tag - fields: - pod - pod_ip - namespace - cluster - role type: string index: tag - fields: - message - err type: string index: fulltext - field: timestamp type: time index: timestampThis grouping makes it easier to understand the purpose of each set of fields at a glance.
controllers/greptimedbcluster/deployers/config/config.go (1)
21-25: Add documentation for embedded files.The embedded files
VectorConfigTemplateandDefaultPipelineare correctly declared and associated with their respective YAML files. This approach of embedding configuration files is beneficial for deployment and distribution.However, it would be helpful to add documentation comments explaining the purpose and content of these embedded files. This will improve code readability and maintainability.
Consider adding documentation comments above each embedded file declaration, for example:
// VectorConfigTemplate contains the default configuration template for Vector. //go:embed vector-config-template.yaml var VectorConfigTemplate embed.FS // DefaultPipeline contains the default pipeline configuration. //go:embed pipeline.yaml var DefaultPipeline embed.FScontrollers/constant/constant.go (2)
35-36: LGTM: Well-defined constant for default vector config name.The
DefaultVectorConfigNameconstant is clearly named and appropriately valued. It provides a centralized definition for the default vector configuration name, which will improve consistency and maintainability.Consider expanding the comment to briefly explain what "vector" refers to in this context, as it might not be immediately clear to all developers working on the project.
31-39: Summary: Excellent additions for monitoring and logging configuration.The new constants (
LogsTableName,DefaultVectorConfigName, andDefaultLogsVolumeName) are well-defined and appropriately commented. They enhance the configuration capabilities for monitoring and logging in the GreptimeDB application. These additions will likely improve code consistency and maintainability when implementing the monitoring bootstrap feature.As these constants are related to monitoring and logging, ensure that they are used consistently across the codebase, especially in any new monitoring or logging modules being implemented. Consider creating a separate constants file for monitoring-specific constants if the number of such constants grows significantly in the future.
controllers/greptimedbcluster/deployers/config/vector-config-template.yaml (4)
1-16: LGTM! Sources are well-configured with a minor suggestion.The 'sources' section is well-structured for both logs and metrics collection. The use of environment variables for dynamic configuration is a good practice.
Consider adding a
glob_minimum_cooldownsetting to the 'logs' source to prevent excessive polling of the filesystem. This can be particularly useful in high-volume logging scenarios. For example:sources: logs: type: file data_dir: /logs include: - /logs/*.* max_read_bytes: 536870912 glob_minimum_cooldown_ms: 1000 # Add this lineThis setting adds a 1-second cooldown between file system polls, which can help reduce CPU usage.
17-51: LGTM! Transforms are well-structured with a suggestion for error handling.The 'transforms' section is well-designed, adding valuable context to both logs and metrics. The use of conditional checks for optional fields in 'transform_logs' is a good practice.
Consider adding error handling to the JSON parsing in 'transform_logs'. If an invalid JSON is encountered, the current setup might cause the event to be dropped silently. Here's a suggested modification:
transforms: transform_logs: type: remap inputs: - logs source: | parsed = parse_json(.message) if !is_null(parsed) { . = parsed # ... rest of the transformation ... } else { .parsing_error = "Failed to parse JSON" .raw_message = .message } # ... rest of the fields ...This change ensures that events with invalid JSON are not lost and allows for easier debugging of parsing issues.
52-66: LGTM! Sinks are properly configured with a suggestion for performance optimization.The 'sinks' section is well-structured, correctly routing logs and metrics to their respective destinations. The use of template variables for endpoints and table names provides good flexibility.
Consider adding batch settings to both sinks to optimize performance, especially for high-volume data. Here's a suggested modification:
sinks: sink_greptimedb_logs: type: greptimedb_logs table: {{ .LogsTableName }} pipeline_name: {{ .PipelineName }} compression: gzip inputs: - transform_logs endpoint: {{ .LoggingService }} batch: max_events: 1000 timeout_secs: 1 sink_greptimedb_metrics: type: prometheus_remote_write inputs: - add_metrics_labels endpoint: {{ .MetricService }} batch: max_events: 1000 timeout_secs: 1These batch settings will send data in larger chunks, reducing the number of network requests and potentially improving overall performance.
1-66: Overall, excellent Vector configuration for comprehensive observability.This Vector configuration file is well-structured and provides a robust setup for collecting, processing, and forwarding both logs and metrics. The use of template variables and environment variables ensures flexibility and adaptability across different deployment scenarios.
Key strengths:
- Clear separation of concerns between sources, transforms, and sinks.
- Effective use of JSON parsing and field extraction for logs.
- Addition of valuable context (pod, namespace, cluster) to both logs and metrics.
- Proper use of compression for log data transmission.
The suggestions provided earlier (adding
glob_minimum_cooldown, error handling for JSON parsing, and batch settings for sinks) are minor optimizations that can further enhance the configuration's robustness and performance.As the observability requirements grow, consider splitting this configuration into separate files for logs and metrics. This separation can improve maintainability and allow for independent scaling of log and metric processing pipelines if needed in the future.
go.mod (1)
Line range hint
1-96: Summary of dependency updatesThe changes in this
go.modfile primarily involve updating dependencies to newer versions, which is generally a good practice for security and feature improvements. Here's a summary of the key changes:
- Added a new retry library:
github.com/avast/retry-go v3.0.0+incompatible- Updated
github.com/stretchr/testifyto v1.9.0- Updated
golang.org/x/netto v0.25.0- Updated
google.golang.org/protobufto v1.34.1While these updates are beneficial, it's crucial to thoroughly test the application to ensure compatibility with the new versions. Pay special attention to the newly added retry library, as there might be more modern alternatives available.
To maintain the health of your dependencies:
- Regularly update dependencies to their latest stable versions.
- Use a dependency management tool like
dependabotto automate this process.- Maintain a comprehensive test suite to quickly identify any issues introduced by dependency updates.
- Consider setting up a CI/CD pipeline that automatically runs tests when dependencies are updated.
controllers/common/common.go (2)
264-266: LGTM: Clear logs pipeline naming function with potential for optimization.The
LogsPipelineNamefunction is well-implemented and follows the expected naming convention for logs pipelines.For potential optimization, consider using
strings.Joinorfmt.Sprintffor string concatenation, especially if this function is called frequently:import ( "fmt" "strings" ) func LogsPipelineName(namespace, name string) string { // Option 1: Using strings.Join return strings.Join([]string{namespace, name, "logs"}, "-") // Option 2: Using fmt.Sprintf // return fmt.Sprintf("%s-%s-logs", namespace, name) }This change could improve performance for frequent calls, although the current implementation is perfectly acceptable for most use cases.
260-266: Overall: Good additions for monitoring and logging support.These new utility functions,
MonitoringServiceNameandLogsPipelineName, are well-implemented additions to the common package. They provide clear, focused functionality that will likely be used in the monitoring and logging components of the GreptimeDB operator. The changes are non-intrusive and maintain the existing code structure, which is a positive approach to extending functionality.As the operator's functionality expands, consider grouping related utility functions into sub-packages if the common package grows too large. This could improve organization and maintainability in the long term. For now, the current structure is appropriate.
controllers/greptimedbcluster/deployers/frontend.go (1)
281-284: LGTM: Monitoring configuration added correctly.The addition of Vector configuration and sidecar for monitoring is well-implemented. This change enhances the monitoring capabilities of the frontend component when enabled.
Consider extracting the condition
b.Cluster.GetMonitoring() != nil && b.Cluster.GetMonitoring().GetVector() != nilinto a separate method for improved readability. For example:func (b *frontendBuilder) isVectorMonitoringEnabled() bool { return b.Cluster.GetMonitoring() != nil && b.Cluster.GetMonitoring().GetVector() != nil }Then use it in the
generatePodTemplateSpecmethod:if b.isVectorMonitoringEnabled() { b.AddVectorConfigVolume(podTemplateSpec) b.AddVectorSidecar(podTemplateSpec, v1alpha1.FrontendComponentKind) }This would make the code more readable and easier to maintain.
controllers/greptimedbcluster/controller.go (1)
71-71: LGTM! Consider adding a comment for the monitoring deployer.The addition of the
NewMonitoringDeployeraligns well with the PR objective of implementing monitoring bootstrap. This change enhances the GreptimeDBCluster's capabilities by introducing monitoring functionality.Consider adding a brief comment above this line to explain the purpose of the monitoring deployer, similar to the comments you might have for other deployers. This would improve code readability and maintainability.
+// Add monitoring deployer to set up monitoring resources deployers.NewMonitoringDeployer(mgr),docs/api-references/docs.md (4)
338-339: Consider enhancing field descriptions in MonitoringSpec.The new MonitoringSpec section is well-structured and consistent with the existing documentation style. To improve clarity, consider expanding on the descriptions of the following fields:
standalone: Briefly explain what this standalone GreptimeDB instance is used for in the context of monitoring.logsCollection: Mention the purpose of log collection in the monitoring setup.vector: Provide a brief explanation of what the vector instance is used for in this context.These additions would help users better understand the purpose and functionality of each component in the monitoring configuration.
463-477: Enhance the description of LogPipeline.The LogPipeline section is well-structured and consistent with the documentation style. To improve clarity, consider expanding the description of the
datafield. For example:"The content of the pipeline configuration file in YAML format. This configuration defines how logs are processed and routed within the monitoring system."
This addition would provide users with a better understanding of the purpose and importance of the log pipeline configuration.
524-538: Expand on the purpose of LogsCollectionSpec.The LogsCollectionSpec section is well-structured and follows the documentation style. To provide more context for users, consider expanding the description of this specification. For example:
"LogsCollectionSpec defines the configuration for collecting and processing logs from the GreptimeDB cluster. This specification allows users to set up a centralized logging system for better monitoring and troubleshooting of the cluster."
Additionally, you could enhance the description of the
pipelinefield to clarify its relationship with the LogPipeline specification:"The specification of the log pipeline, which defines how logs are collected, processed, and routed. This field references the LogPipeline specification."
These additions would help users better understand the purpose and functionality of the logs collection feature.
885-900: Enhance VectorSpec field descriptions.The VectorSpec section is well-structured and consistent with the documentation style. To provide more context for users, consider expanding the descriptions of the fields:
image: Add information about what Vector is and its role in the monitoring setup. For example: "The container image for the Vector instance. Vector is a high-performance observability data pipeline that collects, transforms, and routes logs and metrics."
resource: Clarify what kind of resources are being specified. For example: "The compute resources (such as CPU and memory) required for the Vector instance."These additions would help users better understand the purpose of the Vector instance and how to configure it properly.
controllers/greptimedbcluster/deployers/monitoring.go (1)
153-154: Adjust log level within retry loop to reduce log noiseLogging warnings on each retry attempt could clutter the logs. Consider lowering the log level to reduce noise during retries.
Apply this diff:
- klog.Warningf("failed to create pipeline: %v", err) + klog.V(2).Infof("Retry attempt failed to create pipeline: %v", err)controllers/greptimedbcluster/deployers/flownode.go (1)
263-266: Add comments to improve code readabilityConsider adding comments to explain the purpose of adding the Vector configuration volume and sidecar. This enhances code readability and helps future maintainers understand the monitoring setup.
Apply this diff to include explanatory comments:
+ // Add Vector configuration volume and sidecar for monitoring if enabled if b.Cluster.GetMonitoring() != nil && b.Cluster.GetMonitoring().GetVector() != nil { b.AddVectorConfigVolume(podTemplateSpec) b.AddVectorSidecar(podTemplateSpec, v1alpha1.FlownodeComponentKind) }
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⛔ Files ignored due to path filters (1)
go.sumis excluded by!**/*.sum
📒 Files selected for processing (18)
- apis/v1alpha1/greptimedbcluster_types.go (5 hunks)
- apis/v1alpha1/zz_generated.deepcopy.go (6 hunks)
- controllers/common/common.go (1 hunks)
- controllers/constant/constant.go (1 hunks)
- controllers/greptimedbcluster/controller.go (1 hunks)
- controllers/greptimedbcluster/deployers/common.go (3 hunks)
- controllers/greptimedbcluster/deployers/config/config.go (1 hunks)
- controllers/greptimedbcluster/deployers/config/pipeline.yaml (1 hunks)
- controllers/greptimedbcluster/deployers/config/vector-config-template.yaml (1 hunks)
- controllers/greptimedbcluster/deployers/datanode.go (3 hunks)
- controllers/greptimedbcluster/deployers/flownode.go (1 hunks)
- controllers/greptimedbcluster/deployers/frontend.go (1 hunks)
- controllers/greptimedbcluster/deployers/meta.go (1 hunks)
- controllers/greptimedbcluster/deployers/monitoring.go (1 hunks)
- docs/api-references/docs.md (6 hunks)
- go.mod (3 hunks)
- pkg/deployer/builder.go (4 hunks)
- pkg/deployer/constants.go (1 hunks)
🧰 Additional context used
🪛 Markdownlint
docs/api-references/docs.md
638-638: null
Link fragments should be valid(MD051, link-fragments)
🔇 Additional comments (36)
controllers/greptimedbcluster/deployers/config/pipeline.yaml (1)
1-28: Overall, the pipeline configuration looks good and is ready for use.The
pipeline.yamlfile is well-structured and comprehensive, covering both log processing and indexing configurations. It should effectively handle timestamp extraction and field indexing for the GreptimeDB monitoring system.The minor suggestions provided (adding fallback timestamp formats and grouping related fields) are optional improvements that could enhance robustness and readability, but the current configuration is already functional and well-designed.
pkg/deployer/constants.go (1)
20-21: LGTM! Consider verifying Kubernetes configurations.The new constants
EnvPodNamespaceandEnvRoleare correctly defined and follow the existing naming conventions. These additions align with the PR objective of implementing monitoring bootstrap.To ensure these new environment variables are properly utilized, please run the following script to check for their usage in Kubernetes deployment files:
This will help confirm that the new environment variables are correctly set in the Kubernetes configurations.
✅ Verification successful
Verified Kubernetes configurations.
The environment variables
POD_NAMESPACEandROLEare correctly utilized in the Kubernetes deployment files.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify the usage of new environment variables in Kubernetes deployment files. # Test: Search for the new environment variables in yaml files echo "Searching for POD_NAMESPACE usage:" rg --type yaml 'POD_NAMESPACE' echo "Searching for ROLE usage:" rg --type yaml 'ROLE'Length of output: 522
controllers/greptimedbcluster/deployers/config/config.go (3)
1-13: LGTM: Proper license header included.The Apache License 2.0 header is correctly included at the beginning of the file. This is crucial for open-source projects to clearly communicate the terms under which the code is distributed.
15-19: LGTM: Appropriate package name and import.The package name
configis suitable for this file's purpose. Theembedpackage is correctly imported, which is necessary for embedding the configuration files into the Go binary.
1-25: Overall assessment: Well-structured implementation of configuration embedding.This new file successfully introduces embedded configuration files for Vector and a default pipeline, which aligns with the PR objective of implementing monitoring bootstrap. The code is well-structured, uses appropriate naming conventions, and follows good practices for embedding files in Go.
The only suggestion for improvement is to add documentation comments for the embedded files to enhance code readability and maintainability.
Great job on implementing this feature!
controllers/constant/constant.go (2)
32-33: LGTM: Well-defined constant for logs table name.The
LogsTableNameconstant is clearly named, appropriately valued, and well-commented. It provides a centralized definition for the logs table name, which will improve consistency and maintainability across the codebase.
38-39: LGTM: Well-defined constant for default logs volume name.The
DefaultLogsVolumeNameconstant is clearly named, appropriately valued, and well-commented. It provides a centralized definition for the default logs volume name, which will improve consistency and maintainability across the codebase.go.mod (3)
87-87: Verify compatibility with updated google.golang.org/protobuf version.The update of
google.golang.org/protobuffrom v1.33.0 to v1.34.1 is a good practice to keep dependencies current. However, it's important to ensure that this update doesn't introduce any breaking changes to your protobuf-related code.Please run the following commands to verify compatibility:
#!/bin/bash # Description: Regenerate protobuf files and run tests to verify compatibility with the updated protobuf version. # Regenerate protobuf files (adjust the command if you use a different protobuf generation process) protoc --go_out=. --go_opt=paths=source_relative \ --go-grpc_out=. --go-grpc_opt=paths=source_relative \ $(find . -name "*.proto") # Run all tests go test ./...
68-68: Verify test suite compatibility with updated testify version.The update of
github.com/stretchr/testifyfrom v1.8.4 to v1.9.0 is a good practice to keep dependencies current. However, it's important to ensure that this update doesn't introduce any breaking changes to your test suite.Please run the following command to verify that all tests pass with the new version:
75-75: Verify compatibility with updated golang.org/x/net version.The update of
golang.org/x/netfrom v0.23.0 to v0.25.0 is a good practice to keep core dependencies current. However, it's important to ensure that this update doesn't introduce any breaking changes to your networking code.Please run the following command to verify that all tests pass with the new version:
pkg/deployer/builder.go (3)
28-28: LGTM: New import added correctlyThe new import for
greptimev1alpha1is correctly added and necessary for the newGreptimeDBStandalonetype used in this file.
54-56: LGTM: New method added to Builder interfaceThe
BuildGreptimeDBStandalone()method is correctly added to theBuilderinterface. It follows the existing pattern of returning aBuilderand has a clear, concise comment.
123-125: LGTM: New case added for GreptimeDBStandaloneThe new case for
*greptimev1alpha1.GreptimeDBStandaloneis correctly implemented in theSetControllerAndAnnotationmethod. It properly sets thespecandcontrolledvariables, consistent with other cases in the switch statement.controllers/common/common.go (1)
260-262: LGTM: Simple and clear monitoring service naming function.The
MonitoringServiceNamefunction is well-implemented. It's concise, clear, and follows the expected naming convention for monitoring services.controllers/greptimedbcluster/deployers/frontend.go (1)
273-273: LGTM: Environment variables added correctly.The environment variables are correctly appended to the main container for the frontend component. This change enhances the configuration capabilities of the frontend deployment.
docs/api-references/docs.md (2)
629-642: MonitoringStatus section looks good.The MonitoringStatus section is well-structured, clear, and provides useful information about the monitoring service status. The description of the
internalDNSNamefield is particularly helpful, as it includes an example of what the DNS name might look like. This section maintains consistency with the rest of the documentation and requires no changes.🧰 Tools
🪛 Markdownlint
638-638: null
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Line range hint
1-901: Summary of documentation updates.The changes to the API references documentation for GreptimeDB Operator are well-structured and provide valuable information about the new monitoring features. The additions include specifications for MonitoringSpec, LogPipeline, LogsCollectionSpec, MonitoringStatus, and VectorSpec, which collectively describe the configuration and status of the monitoring system.
While the new sections maintain consistency with the existing documentation style, some minor enhancements to the descriptions have been suggested to improve clarity and provide more context for users. These suggestions aim to help users better understand the purpose and functionality of each component in the monitoring setup.
Overall, these additions significantly improve the documentation by providing comprehensive information about the new monitoring capabilities of GreptimeDB Operator.
🧰 Tools
🪛 Markdownlint
638-638: null
Link fragments should be valid(MD051, link-fragments)
controllers/greptimedbcluster/deployers/common.go (5)
130-141: Ensure Volume Name Consistency inAddVectorConfigVolumeThe method
AddVectorConfigVolumeadds a volume with the nameconstant.DefaultVectorConfigName. Please verify that this constant is correctly defined and matches the expected ConfigMap name to avoid issues during deployment.
146-146: Validate Vector Image ConfigurationThe
Imagefield in thevectorcontainer relies onc.Cluster.Spec.Monitoring.Vector.Image. Ensure that this value is configured correctly in the cluster specification to avoid deployment failures due to a missing or incorrect image reference.
150-150: Ensure Environment Variables are Correctly SetThe
Envfield is set usingc.env(kind). Verify that theenvmethod returns all necessary environment variables required for thevectorcontainer to function properly.
164-205: Validate ConfigMap Name Matching inGenerateVectorConfigMapThe ConfigMap generated in
GenerateVectorConfigMapusesconstant.DefaultVectorConfigNameas its name. Ensure that this name matches the one referenced inAddVectorConfigVolumeto prevent discrepancies.Run the following script to confirm the ConfigMap names are consistent:
#!/bin/bash # Description: Verify that the ConfigMap names match across the codebase. # Expectation: All references to the ConfigMap should use the same constant. rg --type go 'constant\.DefaultVectorConfigName' -A 5
208-213: Confirm Correct Usage offs.ReadFileinvectorConfigTemplateThe
fs.ReadFilefunction is used withconfig.VectorConfigTemplateas the filesystem. Verify thatconfig.VectorConfigTemplateimplements thefs.FSinterface and that the file"vector-config-template.yaml"exists within it.✅ Verification successful
Verified:
fs.ReadFileis correctly used withconfig.VectorConfigTemplate.
config.VectorConfigTemplateis of typeembed.FS, which implements thefs.FSinterface.- The file
"vector-config-template.yaml"is properly embedded withinVectorConfigTemplate.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check if `config.VectorConfigTemplate` is a valid fs.FS and contains the template file. # Test: Ensure the file exists within the filesystem. # Expected Outcome: No errors, file is found. # Since we cannot execute code, please manually verify the implementation of `config.VectorConfigTemplate`.Length of output: 1935
Script:
#!/bin/bash # Description: Verify that `config.VectorConfigTemplate` implements fs.FS # Search for the definition of config.VectorConfigTemplate and its implementation of fs.FS rg --type go 'var\s+VectorConfigTemplate\s+fs\.FS' . # Search for the existence of "vector-config-template.yaml" within the context of VectorConfigTemplate rg --type go 'vector-config-template\.yaml' .Length of output: 338
Script:
#!/bin/bash # Description: Locate the declaration and type of `config.VectorConfigTemplate` to verify it implements fs.FS # Search for the declaration of VectorConfigTemplate and its type rg --type go 'var\s+VectorConfigTemplate\s+embed\.FS' . # Additionally, search for any other declarations that might implement fs.FS rg --type go 'var\s+VectorConfigTemplate\s+fs\.FS' .Length of output: 205
controllers/greptimedbcluster/deployers/meta.go (1)
324-324: Ensure all calls tob.env()include thecomponentKindparameterThe method
b.env()now requires thecomponentKindparameter. Verify that all instances whereb.env()is called have been updated to include this parameter to prevent any runtime errors.Run the following script to check for usages of
b.env()without thecomponentKindparameter:✅ Verification successful
Further verification needed.
Further verification needed.
<!-- [monologue] [task verification_3/3] [observations] - The initial `rg` search for `b.env()` without parameters returned no matches, suggesting all calls include parameters. - The subsequent `ast-grep` search also found no instances of `b.env()` without the `componentKind` parameter. - The `rg` output showed various `b.env()` calls, all of which include the `componentKind` parameter, confirming the correct usage. - No errors were reported by either shell script, indicating that the scripts executed successfully. [analysis] - Both search methods corroborate that there are no instances of `b.env()` being called without the required `componentKind` parameter. - The absence of problematic calls means the code adheres to the required standards, and the review comment is validated. - No further verification steps are necessary as the current evidence is sufficient to conclude that the issue is resolved. [actions] - Conclude the verification process by acknowledging that all `b.env()` calls correctly include the `componentKind` parameter. - No additional shell scripts or manual verification are required. -->All
b.env()calls correctly include thecomponentKindparameter.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Find all calls to b.env() without parameters. # Test: Search for b.env() calls without parameters. Expect: No matches. rg --type go -e 'b\.env\(\)' --files-with-matchesLength of output: 51
Script:
#!/bin/bash # Description: Find all calls to b.env() without the `componentKind` parameter using ast-grep. # Search for b.env() calls without any arguments ast-grep --lang go --pattern 'CallExpr{Function: SelectorExpr{Sel: "env"}, Args: []}' .Length of output: 89
Script:
#!/bin/bash # Description: Find all calls to b.env() missing the `componentKind` parameter using ast-grep. # Search for b.env() calls with fewer than the expected number of arguments (assuming componentKind is required) ast-grep --lang go --pattern 'CallExpr{Function: SelectorExpr{Sel: "env"}, Args: [!, $_]}' . # Description: Find all b.env() calls where `componentKind` is not among the arguments using rg. # This regex searches for b.env() calls that do not have 'componentKind' as an argument rg --type go -P 'b\.env\([^)]*(?!componentKind)[^)]*\)' --context 2Length of output: 2804
controllers/greptimedbcluster/deployers/flownode.go (2)
254-254: Environment variables appended correctlyThe environment variables for the main container are being appended with additional variables specific to the Flownode component. This enhancement allows for better configuration flexibility.
263-266: Ensure Vector sidecar has resource requests and limitsWhen adding the Vector sidecar container for monitoring, it's important to define resource requests and limits to prevent resource contention and ensure efficient scheduling by Kubernetes.
Run the following script to check if the Vector sidecar container has resource specifications:
apis/v1alpha1/greptimedbcluster_types.go (6)
284-288: Appropriate addition of theMonitoringfield toGreptimeDBClusterSpecThe inclusion of the
Monitoringfield in theGreptimeDBClusterSpecenhances the cluster's monitoring capabilities and follows the existing structure of the specification.
291-306: Well-structuredMonitoringSpecimplementationThe
MonitoringSpecstruct is well-defined, and its fields are appropriately documented. This addition effectively integrates monitoring configurations into the cluster specification.
347-349: Proper implementation ofIsEnabledmethodThe
IsEnabledmethod inMonitoringSpeccorrectly checks fornilbefore accessing theEnabledfield, preventing potential nil pointer dereferences.
457-462: Consistent addition ofGetMonitoringmethodThe
GetMonitoringmethod inGreptimeDBClusteraligns with existing getter methods and correctly retrieves theMonitoringspecification.
545-548: Well-definedMonitoringStatusstructureThe
MonitoringStatusstruct is appropriately added to the cluster status, providing relevant monitoring information such as theInternalDNSName.
310-313:⚠️ Potential issueAdd missing
// +optionalmarker forPipelinefieldThe
Pipelinefield inLogsCollectionSpecis optional but does not have the// +optionalmarker. Adding this marker ensures correct behavior with code generators and documentation tools.Apply this diff to fix the issue:
type LogsCollectionSpec struct { // The specification of the log pipeline. + // +optional Pipeline *LogPipeline `json:"pipeline,omitempty"` }Likely invalid or redundant comment.
controllers/greptimedbcluster/deployers/datanode.go (2)
450-452: Environment variables and ports are correctly configuredThe environment variables and container ports for the main container are appropriately set.
462-465: Conditional addition of Vector sidecar is correctly implementedThe Vector sidecar and configuration volume are added when monitoring is enabled and a Vector configuration is present.
apis/v1alpha1/zz_generated.deepcopy.go (3)
368-372: Deep copy of 'Monitoring' field inGreptimeDBClusterSpecis correctly implementedThe deep copy logic for the
Monitoringfield inGreptimeDBClusterSpeccorrectly ensures that all nested fields are deeply copied, preventing unintended data sharing between instances.
598-611: Verify ifLogPipelinerequires deep copying of nested fieldsThe
LogPipelineDeepCopyIntomethod performs a shallow copy using*out = *in. IfLogPipelinecontains any reference types, such as slices, maps, or pointers to other structs, these should be deeply copied to avoid unintended data sharing.Please verify the fields within
LogPipelineto determine if a deep copy is necessary. If so, consider modifying theDeepCopyIntomethod to handle deep copying of nested fields.
789-793: Verify ifMonitoringStatusrequires deep copying of nested fieldsIn the
MonitoringStatusDeepCopyIntomethod, a shallow copy is performed using*out = *in. IfMonitoringStatuscontains reference types or nested structs, a deep copy may be necessary to prevent unintended data sharing.Please check the fields within
MonitoringStatusto determine if deep copying is required and modify theDeepCopyIntomethod accordingly.
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🧹 Outside diff range and nitpick comments (1)
Makefile (1)
184-184: Approve the addition of --server-side flag with a minor suggestion.The addition of the
--server-sideflag to thekubectl applycommand is a good improvement. It uses server-side apply, which is more robust and aligns with Kubernetes best practices for applying Custom Resource Definitions (CRDs).Consider adding a comment explaining the use of
--server-sideflag and possibly check for the minimum Kubernetes version that supports this feature. For example:# Use server-side apply for better handling of large CRDs and improved conflict resolution # Requires Kubernetes v1.16+ $(KUSTOMIZE) build config/crd | kubectl apply -f - --server-sideThis will help other developers understand the reason for using this flag and any version requirements.
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Actionable comments posted: 3
🧹 Outside diff range and nitpick comments (12)
apis/v1alpha1/testdata/greptimedbcluster/test03/input.yaml (5)
3-5: Consider adjusting metadata for production use.While the metadata is correctly structured, consider the following suggestions for production readiness:
- The name "test02" suggests this might be a test configuration. For production, use a more descriptive name that reflects the purpose or environment of the cluster.
- Using the "default" namespace is generally not recommended for production. Consider creating a dedicated namespace for your GreptimeDB clusters.
Example of improved metadata:
metadata: name: prod-greptimedb-cluster namespace: greptimedb-system
7-11: Reconsider image tag and frontend replica count for production use.
Image tag: Using the "latest" tag for the main image (
greptime/greptimedb:latest) can lead to unexpected changes when the image is updated. For production, it's recommended to use a specific version tag to ensure consistency and controllable updates.Frontend replicas: A single replica for the frontend might not provide high availability. Consider increasing the replica count for production environments to ensure better fault tolerance and load distribution.
Example of improved configuration:
spec: base: main: image: greptime/greptimedb:v0.4.0 # Replace with the desired version frontend: replicas: 3 # Adjust based on your high availability requirements
12-15: Enhance meta configuration for better reliability.
Meta replicas: Similar to the frontend, a single replica for the meta service might not provide sufficient high availability. Consider increasing the replica count for production environments.
Etcd configuration: The current configuration specifies a single etcd endpoint. For production use, it's recommended to have multiple etcd endpoints for better fault tolerance. Also, ensure that the etcd cluster itself is properly configured for high availability.
Example of improved configuration:
spec: meta: replicas: 3 # Adjust based on your high availability requirements etcdEndpoints: - etcd-0.etcd-cluster.svc.cluster.local:2379 - etcd-1.etcd-cluster.svc.cluster.local:2379 - etcd-2.etcd-cluster.svc.cluster.local:2379Additionally, verify that the etcd cluster referenced here is properly configured for production use, with appropriate backup and disaster recovery strategies in place.
16-17: Increase datanode replicas for better data redundancy and availability.The current configuration specifies only one replica for the datanode. In a production environment, this could lead to data loss in case of node failure and doesn't provide high availability.
Consider increasing the number of datanode replicas to ensure data redundancy and improve availability. The exact number should be based on your specific requirements for data replication and fault tolerance.
Example of improved configuration:
spec: datanode: replicas: 3 # Adjust based on your data redundancy and availability requirementsRemember to also consider the impact on storage requirements and ensure that your infrastructure can support the increased number of datanodes.
25-26: Consider expanding monitoring configuration for better observability.Enabling monitoring is a good practice for maintaining visibility into your GreptimeDB cluster's health and performance. However, the current configuration is minimal and might benefit from additional specifications.
Consider expanding the monitoring configuration to include:
- Specific metrics to be collected
- Monitoring interval
- Integration with external monitoring systems (if applicable)
- Alert configurations for critical metrics
Example of a more detailed monitoring configuration:
spec: monitoring: enabled: true metrics: - cpu_usage - memory_usage - disk_usage - query_latency interval: 15s exporter: image: greptime/greptimedb-exporter:latest alerting: criticalCPUThreshold: 80 criticalMemoryThreshold: 90Would you like me to provide a more comprehensive monitoring configuration template or open a GitHub issue to track the task of enhancing the monitoring setup?
apis/v1alpha1/testdata/greptimedbcluster/test03/expect.yaml (7)
1-20: LGTM! Consider adding readiness probe.The basic structure and configuration of the GreptimeDBCluster custom resource are well-defined. The metadata, base configuration, and port specifications are appropriate.
Consider adding a readiness probe in addition to the liveness probe. This can help Kubernetes determine when the pod is ready to accept traffic:
readinessProbe: httpGet: path: /health port: 4000 initialDelaySeconds: 10 periodSeconds: 10
21-33: LGTM! Consider using environment variables for sensitive data.The object storage and logging configurations are well-structured and provide necessary options for customization.
For improved security, consider using environment variables or Kubernetes secrets for sensitive data in the S3 configuration. This approach helps prevent accidental exposure of credentials in configuration files:
objectStorage: s3: bucket: ${S3_BUCKET} endpoint: ${S3_ENDPOINT} region: ${S3_REGION} root: ${S3_ROOT} secretName: s3-credentials
34-44: LGTM! Consider adding HPA for frontend scalability.The frontend configuration is well-defined with appropriate service type and container specifications.
To improve scalability, consider implementing a Horizontal Pod Autoscaler (HPA) for the frontend. This will allow the system to automatically adjust the number of frontend replicas based on CPU or custom metrics:
frontend: # ... existing configuration ... hpa: enabled: true minReplicas: 1 maxReplicas: 5 targetCPUUtilizationPercentage: 80
45-59: LGTM! Consider increasing meta replicas for high availability.The meta configuration is well-structured with appropriate settings for etcd endpoints and ports.
To improve reliability and avoid a single point of failure, consider increasing the number of replicas for the meta component:
meta: # ... existing configuration ... replicas: 3 # Increase from 1 to 3 for better availabilityAlso, ensure that you have a proper etcd cluster setup with multiple nodes for production environments.
60-77: LGTM! Consider increasing datanode replicas and adding anti-affinity rules.The datanode configuration is well-defined with appropriate storage and container specifications.
To improve data reliability, availability, and performance, consider the following enhancements:
- Increase the number of datanode replicas:
datanode: # ... existing configuration ... replicas: 3 # Increase from 1 to 3 for better data redundancy
- Add pod anti-affinity rules to ensure datanodes are scheduled on different nodes:
datanode: # ... existing configuration ... template: spec: affinity: podAntiAffinity: requiredDuringSchedulingIgnoredDuringExecution: - labelSelector: matchExpressions: - key: app operator: In values: - greptimedb-datanode topologyKey: "kubernetes.io/hostname"
- Consider implementing a pod disruption budget to ensure availability during voluntary disruptions:
datanode: # ... existing configuration ... podDisruptionBudget: maxUnavailable: 1
78-115: LGTM! Consider refactoring for configuration reuse and flexibility.The monitoring configuration is comprehensive and well-structured, providing necessary settings for standalone monitoring and logs collection.
To improve configuration management and flexibility, consider the following enhancements:
- Refactor common configurations (like object storage) to avoid duplication:
spec: commonConfig: objectStorage: s3: bucket: greptimedb endpoint: s3.amazonaws.com region: us-west-2 secretName: s3-credentials # ... other configurations ... monitoring: standalone: objectStorage: s3: root: /greptimedb/monitoring <<: *commonS3Config
- Add configuration options for monitoring persistence and retention:
monitoring: standalone: # ... existing configuration ... persistence: enabled: true storageClass: "standard" size: 20Gi retention: time: 15d size: 10GB
- Consider adding support for external monitoring solutions:
monitoring: # ... existing configuration ... externalPrometheusOperator: enabled: false serviceMonitor: enabled: true interval: 15s
116-124: LGTM! Consider pinning the Vector image version and adjusting resource limits.The Vector configuration provides a good starting point with defined resource limits and requests.
Consider the following improvements:
- Pin the Vector image to a specific version instead of using 'latest' to ensure consistency and predictability:
vector: image: timberio/vector:0.28.1-alpine # Replace with the desired version
- Adjust resource limits and requests based on expected load and available cluster resources. The current values might be too low for production use:
vector: # ... existing configuration ... resource: limits: cpu: 200m memory: 256Mi requests: cpu: 100m memory: 128Mi
- Add configuration for Vector to allow for customization of its behavior:
vector: # ... existing configuration ... config: data_dir: /vector-data-dir api: enabled: true address: 127.0.0.1:8686 sources: logs: type: file include: - /var/log/greptimedb/*.log sinks: console: type: console inputs: - logs encoding: codec: json
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- Makefile (2 hunks)
- apis/v1alpha1/common.go (3 hunks)
- apis/v1alpha1/constants.go (1 hunks)
- apis/v1alpha1/defaulting.go (3 hunks)
- apis/v1alpha1/testdata/greptimedbcluster/test03/expect.yaml (1 hunks)
- apis/v1alpha1/testdata/greptimedbcluster/test03/input.yaml (1 hunks)
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- Makefile
🔇 Additional comments (10)
apis/v1alpha1/testdata/greptimedbcluster/test03/input.yaml (2)
1-2: LGTM: API version and kind are correctly defined.The API version
greptime.io/v1alpha1and kindGreptimeDBClusterare appropriate for this custom resource definition.
18-24: Object storage configuration looks good, consider performance and security aspects.The S3 object storage configuration is well-structured and includes necessary details. Some points to consider:
Performance: Using the public S3 endpoint (
s3.amazonaws.com) might impact performance. If the GreptimeDB cluster is running in AWS, consider using a regional endpoint or VPC endpoint for better performance and reduced data transfer costs.Security: It's good that you're using a secret for S3 credentials. Ensure that this secret is properly managed and rotated regularly.
Bucket policy: Ensure that the S3 bucket has appropriate access policies set up to restrict access only to necessary components.
Consider the following improvements:
If running in AWS, use a regional or VPC endpoint:
endpoint: s3.us-west-2.amazonaws.com # Regional endpoint # or endpoint: vpce-1a2b3c4d.s3.us-west-2.vpce.amazonaws.com # VPC endpointImplement a process for regular rotation of the S3 credentials stored in the
s3-credentialssecret.Review and tighten the S3 bucket policy to ensure least privilege access.
To verify the S3 configuration, you can run the following command:
This will help ensure that the bucket exists and has appropriate policies set.
apis/v1alpha1/constants.go (3)
70-71: Verify if the default CPU request is appropriate for the expected Vector workload.The default CPU request of 50m (50 millicpu or 0.05 CPU cores) seems reasonable as a starting point. However, it's important to ensure this value aligns with the expected Vector workload in your specific use case.
Consider running performance tests to validate if this default value is sufficient for your typical workloads. Adjust if necessary based on observed resource utilization.
73-74: Verify if the default memory request is appropriate for the expected Vector workload.The default memory request of 128Mi (128 mebibytes) seems reasonable as a starting point. However, it's important to ensure this value aligns with the expected Vector workload in your specific use case.
Consider running performance tests to validate if this default value is sufficient for your typical workloads. Monitor memory usage during these tests and adjust the value if necessary based on observed resource utilization.
61-74: Overall assessment of new constantsThe new constants enhance the configuration options for GreptimeDB and Vector components, providing default values for images and resource requests. These additions improve the ease of deployment and configuration.
However, there are a few points to consider:
- The use of "latest" tags for both GreptimeDB and Vector images should be reconsidered for production use.
- The default resource requests for Vector (CPU and memory) should be validated against expected workloads to ensure they are appropriate.
These changes lay a good foundation for integrating Vector into the GreptimeDB ecosystem, potentially for log collection or data processing tasks. Ensure that the integration is well-documented and that the resource defaults are adjusted based on real-world usage patterns.
apis/v1alpha1/common.go (4)
653-658: LGTM: Safe implementation of GetRoot() for S3StorageThe implementation of
GetRoot()forS3Storageis correct and follows good practices:
- It safely handles nil receivers, preventing potential panics.
- It provides a clean way to access the
Rootfield, which could be useful for internal operations or external packages.
692-697: LGTM: Consistent implementation of GetRoot() for OSSStorageThe
GetRoot()method forOSSStorageis implemented correctly and consistently with theS3Storage.GetRoot()method:
- It safely handles nil receivers.
- It provides a clean accessor for the
Rootfield.- The implementation maintains consistency across different storage types, which is good for code maintainability.
731-736: LGTM: Consistent GetRoot() implementation across all storage typesThe
GetRoot()method forGCSStorageis implemented correctly and maintains consistency with theS3StorageandOSSStorageimplementations:
- It safely handles nil receivers.
- It provides a clean accessor for the
Rootfield.- The consistent implementation across all storage types (S3, OSS, and GCS) is commendable, as it promotes code uniformity and ease of maintenance.
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653-736: Summary: Consistent and safe GetRoot() methods added to storage typesThe changes introduce
GetRoot()methods toS3Storage,OSSStorage, andGCSStoragetypes. These additions are well-implemented and offer several benefits:
- Safe access to the
Rootfield, preventing nil pointer dereferences.- Consistent implementation across all storage types, improving maintainability.
- Enhanced API for interacting with storage types, which could be useful for internal operations or external packages.
These changes are a positive addition to the codebase, improving both safety and usability.
apis/v1alpha1/defaulting.go (1)
83-105: Well-implemented: Addition of default monitoring specificationsThe code correctly sets up default monitoring configurations when monitoring is enabled. This enhancement ensures that monitoring components are properly initialized with default values, including resource requests and limits for the
VectorSpec, and sets the logging format to JSON.
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Actionable comments posted: 4
🧹 Outside diff range and nitpick comments (9)
apis/v1alpha1/testdata/greptimedbcluster/test00/expect.yaml (1)
Line range hint
13-17: LGTM! Consider log persistence for troubleshooting.The logging configuration looks good and provides a standardized approach. However, consider setting
persistentWithData: truefor better long-term troubleshooting capabilities, especially in production environments.apis/v1alpha1/testdata/greptimedbcluster/test02/expect.yaml (2)
Line range hint
23-27: Overall assessment: Logging improvements with refactoring opportunitiesThe introduction of logging configurations across different components of the GreptimeDBCluster is a valuable addition. It provides greater control and consistency in log management, which is crucial for monitoring and debugging in a distributed system.
However, the current implementation with identical configurations repeated across multiple components presents an opportunity for refactoring. This refactoring would improve maintainability, reduce the risk of inconsistencies, and make future updates more straightforward.
Next steps to consider:
- Implement the suggested refactoring using YAML anchors or modify the operator to handle default configurations.
- If different components require distinct logging configurations, clearly document these requirements.
- Consider adding validation in the operator to ensure logging configurations are consistent where needed and appropriately distinct where required.
- Update any related documentation or comments to reflect the new logging capabilities and configuration approach.
These changes will enhance the robustness and maintainability of the GreptimeDBCluster resource definition.
Also applies to: 42-47, 80-85
Logging Configuration Verified
The
onlyLogToStdoutandpersistentWithDatafields are consistently set tofalseacross all logging configurations.However, there are variations in the
formatandlevelfields that may require further review.🔗 Analysis chain
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23-27: LGTM! Verify boolean field settings.The root-level logging configuration looks good. It provides a clear structure for managing logs with sensible defaults.
Please confirm that setting both
onlyLogToStdoutandpersistentWithDatatofalseis the intended behavior. This configuration means logs will be written to files (not just stdout) but won't be persisted with data, which might lead to log loss during restarts.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check if the logging configuration is consistent across the file # and if there are any comments or documentation explaining the chosen settings. # Test: Search for logging configurations and any related comments rg --type yaml -A 10 'logging:'Length of output: 10447
apis/v1alpha1/testdata/greptimedbcluster/test01/expect.yaml (1)
95-100: Consistent configuration. Consider global logging settings.The datanode logging configuration maintains consistency with the frontend and meta configurations, which is excellent for maintainability. Please refer to the previous comments regarding the verification of log persistence settings.
Given that all three components (frontend, meta, and datanode) have identical logging configurations, consider refactoring to use a global logging configuration. This could simplify maintenance and ensure consistency across all components.
Example refactor (pseudo-code):
spec: globalLogging: format: text level: info logsDir: /data/greptimedb/logs onlyLogToStdout: false persistentWithData: false frontend: # ... other settings ... logging: *globalLogging meta: # ... other settings ... logging: *globalLogging datanode: # ... other settings ... logging: *globalLoggingThis approach would allow for easier updates to logging configuration across all components while still providing the flexibility to override specific settings if needed.
apis/v1alpha1/testdata/greptimedbcluster/test03/expect.yaml (4)
1-20: LGTM! Consider grouping related configurations.The basic structure and configurations for the GreptimeDBCluster custom resource are well-defined and follow Kubernetes standards. The metadata and basic spec sections provide essential information for deploying the cluster.
Consider grouping related configurations together for improved readability. For example, you could move the port definitions (lines 17-20) next to the
baseconfiguration (lines 7-13) since they are all part of the core setup.
34-50: Consider increasing frontend replicas for high availability.The frontend configuration is well-structured and consistent with the overall cluster setup. The logging configuration and liveness probe are properly defined.
Consider increasing the number of frontend replicas to ensure high availability. A single replica (
replicas: 1) might become a single point of failure. For production environments, it's generally recommended to have at least 2-3 replicas.Example:
frontend: replicas: 3This change would improve the resilience and availability of your GreptimeDB cluster's frontend component.
72-95: Consider increasing datanode replicas for data redundancy and high availability.The datanode configuration is well-structured with clear definitions for ports, storage, and logging. The storage configuration, in particular, is well-defined with a specific retention policy and size.
Consider increasing the number of datanode replicas to ensure data redundancy and high availability. A single replica (
replicas: 1) might lead to data loss in case of node failure and doesn't provide high availability. For production environments, it's generally recommended to have at least 3 replicas for the datanode component.Example:
datanode: replicas: 3This change would improve the resilience, availability, and data durability of your GreptimeDB cluster. Make sure to adjust your storage and resource allocations accordingly when increasing the number of replicas.
134-142: Review resource allocations for production use.The vector configuration is well-structured with a specific image and defined resource limits and requests, which is good for resource management.
The current resource allocations (50m CPU and 128Mi memory) seem quite low, especially for a production environment. These values might be suitable for testing or very small deployments, but consider increasing them for production use.
Suggested action:
- Review and potentially increase the resource allocations based on your expected workload and monitoring requirements.
- Consider setting different values for requests and limits to allow for some burst capacity.
Example of more generous allocations:
vector: resource: limits: cpu: 200m memory: 256Mi requests: cpu: 100m memory: 128MiAlways monitor the actual resource usage of your vector instances in production and adjust these values accordingly.
apis/v1alpha1/defaulting.go (1)
275-317: LGTM with suggestion: Consider refactoring to reduce duplicationThe
mergeLoggingmethod correctly merges logging configurations for all components (Meta, Datanode, Frontend, and Flownode) and consistently sets the logging format to JSON when monitoring is enabled. This implementation ensures uniform logging behavior across the cluster.To improve code maintainability, consider refactoring the repeated logic into a helper function. Here's a suggested implementation:
func (in *GreptimeDBCluster) mergeLogging() error { components := []struct { name string logging *LoggingSpec }{ {"Meta", in.GetMeta().GetLogging()}, {"Datanode", in.GetDatanode().GetLogging()}, {"Frontend", in.GetFrontend().GetLogging()}, {"Flownode", in.GetFlownode().GetLogging()}, } for _, component := range components { if component.logging != nil { if err := mergeComponentLogging(in, component.name, component.logging); err != nil { return err } } } return nil } func mergeComponentLogging(in *GreptimeDBCluster, componentName string, logging *LoggingSpec) error { if err := mergo.Merge(logging, in.GetLogging().DeepCopy()); err != nil { return fmt.Errorf("failed to merge logging for %s: %w", componentName, err) } if in.GetMonitoring().IsEnabled() { logging.Format = LogFormatJSON } return nil }This refactored version reduces code duplication and makes it easier to add or modify logging behavior for new components in the future.
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📒 Files selected for processing (12)
- apis/v1alpha1/defaulting.go (8 hunks)
- apis/v1alpha1/testdata/greptimedbcluster/test00/expect.yaml (3 hunks)
- apis/v1alpha1/testdata/greptimedbcluster/test01/expect.yaml (3 hunks)
- apis/v1alpha1/testdata/greptimedbcluster/test02/expect.yaml (3 hunks)
- apis/v1alpha1/testdata/greptimedbcluster/test03/expect.yaml (1 hunks)
- controllers/greptimedbcluster/controller.go (2 hunks)
- pkg/dbconfig/common.go (1 hunks)
- pkg/dbconfig/datanode_config.go (1 hunks)
- pkg/dbconfig/flownode_config.go (1 hunks)
- pkg/dbconfig/frontend_config.go (1 hunks)
- pkg/dbconfig/meta_config.go (1 hunks)
- pkg/dbconfig/standalone_config.go (1 hunks)
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- controllers/greptimedbcluster/controller.go
🔇 Additional comments (16)
pkg/dbconfig/frontend_config.go (1)
40-40: Confirm the intentionality and impact of the logging configuration change.The modification to use only
cluster.GetFrontend().GetLogging()for configuring logging aligns with the PR summary. This change simplifies the frontend logging configuration by using only frontend-specific settings.Please confirm:
- Is this change intentional? It removes the use of cluster-wide logging settings for the frontend.
- Are there any potential impacts on the overall logging behavior that should be considered?
Additionally, it would be helpful to verify if there are any corresponding changes in the
ConfigureLoggingmethod implementation. You can use the following script to check:This will help ensure that the method implementation is consistent with this new calling pattern.
✅ Verification successful
Logging configuration change is intentional and aligns with the current implementation.
The
ConfigureLoggingmethod now accepts onlycluster.GetFrontend().GetLogging(), which matches its current definition inpkg/dbconfig/common.go. This simplifies the logging configuration by utilizing only frontend-specific settings.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check for changes in the ConfigureLogging method # Search for the ConfigureLogging method definition rg --type go -A 10 'func \(.*\) ConfigureLogging\('Length of output: 528
pkg/dbconfig/flownode_config.go (1)
44-44: Verify the impact of removing cluster-wide logging configurationThe change simplifies the
ConfigureLoggingcall by using only the flownode-specific logging configuration. While this might improve component independence, it's important to ensure that no critical information from the cluster-wide logging configuration (cluster.GetLogging()) is lost.Please verify the following:
- Has the
ConfigureLoggingmethod signature been updated to accept only one argument?- Is this change consistent with how logging is configured for other components (e.g., datanode, frontend)?
- Are there any cluster-wide logging settings that should still be applied to the flownode?
To help verify the consistency of this change across the codebase, please run the following script:
✅ Verification successful
Verified: The
ConfigureLoggingmethod signature has been updated to accept only one argument, and all other components have consistently made similar changes to use their component-specific logging configurations. No cluster-wide logging configuration appears to be missing. The change has been properly implemented across the codebase.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check for similar changes in other components and the ConfigureLogging method # Check ConfigureLogging method signature echo "Checking ConfigureLogging method signature:" ast-grep --lang go --pattern 'func $_ ConfigureLogging($_) $_' # Check for similar changes in other components echo "\nChecking for similar changes in other components:" rg --type go -e 'ConfigureLogging\(' -A 3 -B 3Length of output: 2312
apis/v1alpha1/testdata/greptimedbcluster/test02/expect.yaml (1)
80-85: 🛠️ Refactor suggestionRefactor repeated logging configurations.
The datanode logging configuration is identical to both the root-level and frontend configurations. This repetition across multiple components suggests a need for a more centralized or inherited configuration approach.
Consider implementing one of the following solutions:
- Use YAML anchors and aliases throughout the file to reference a single logging configuration.
- Modify the operator to use a default logging configuration that can be overridden at the component level only when necessary.
- If separate configurations are required, clearly document the reason for this design decision.
Example of a potential refactor using YAML anchors:
spec: logging: &default_logging format: text level: info logsDir: /data/greptimedb/logs onlyLogToStdout: false persistentWithData: false frontend: logging: *default_logging meta: logging: *default_logging datanode: logging: *default_loggingThis approach would significantly reduce duplication and make future updates to the logging configuration more manageable.
To ensure this refactoring doesn't conflict with existing behavior, please run the following verification:
#!/bin/bash # Description: Check if there are any cases where logging configurations differ between components # Test: Compare logging configurations across different components rg --type yaml -A 5 'logging:' | sort | uniq -cIf the configurations are truly meant to be different, please add comments explaining the specific requirements for each component.
pkg/dbconfig/meta_config.go (1)
65-65: LGTM: Simplified logging configurationThe change to use only
cluster.GetMeta().GetLogging()for configuring logging simplifies the process and aligns with good encapsulation practices.To ensure consistency across the codebase, please run the following verification script:
Additionally, consider adding a comment explaining the rationale behind this change, if not already documented elsewhere in the codebase or commit message.
✅ Verification successful
Verification Successful: Logging Configuration Consistent
The verification confirms that all calls to
ConfigureLogginguse only the metadata logging configuration. The method signature has been updated accordingly, and there are no remaining instances ofcluster.GetLogging()orConfigureLoggingwith multiple arguments.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify that all calls to ConfigureLogging use only the metadata logging configuration # Test 1: Check for any remaining calls to cluster.GetLogging() echo "Checking for calls to cluster.GetLogging():" rg --type go 'cluster\.GetLogging\(\)' # Test 2: Verify the signature of ConfigureLogging method echo "Checking the signature of ConfigureLogging method:" rg --type go 'func.*ConfigureLogging' # Test 3: Check for any calls to ConfigureLogging with more than one argument echo "Checking for calls to ConfigureLogging with multiple arguments:" rg --type go 'ConfigureLogging\([^)]+,[^)]+\)'Length of output: 568
apis/v1alpha1/testdata/greptimedbcluster/test01/expect.yaml (3)
38-43: LGTM. Verify log persistence settings.The frontend logging configuration looks good and follows standard practices. However, please verify if setting both
onlyLogToStdoutandpersistentWithDatatofalseis the intended behavior. This configuration means logs will be written to files but not persisted with data, which might lead to log loss during container restarts.
65-70: Consistent configuration. Refer to previous comment on persistence.The meta logging configuration is consistent with the frontend, which is good for maintainability. Please refer to the previous comment regarding the verification of log persistence settings, as the same considerations apply here.
Line range hint
13-18: Overall logging implementation looks good. Clarify top-level logging configuration.The addition of consistent logging configurations to the frontend, meta, and datanode components is a good improvement for observability. However, there's also a top-level
loggingconfiguration underspecthat wasn't part of the changes we reviewed. Please clarify:
- Is this top-level configuration intended to be a global default?
- If so, how does it interact with the component-specific configurations?
- If not, should it be removed in favor of the component-specific configurations?
This clarification will help ensure that the logging behavior is well-defined and consistent across the entire GreptimeDBCluster.
pkg/dbconfig/standalone_config.go (1)
73-73: LGTM! Verify consistency ofConfigureLoggingusage.The simplification of the
ConfigureLoggingmethod call aligns with the updated method signature mentioned in the AI summary. This change improves code clarity by removing an unnecessary parameter.To ensure this change is consistent across the codebase, please run the following script:
pkg/dbconfig/datanode_config.go (1)
72-72: Conditional approval: Verify logging configuration change.The modification to use only
cluster.GetDatanode().GetLogging()instead of both cluster and datanode-specific logging configurations appears to be a significant change in how logging is configured for datanodes.Please confirm the following:
- Is this change intentional and part of a larger refactoring of logging configuration?
- Have similar changes been made for other components (e.g., frontend, metasrv)?
- Does this change maintain or improve the existing logging behavior?
To verify the consistency of this change across the codebase, please run the following script:
Consider updating the PR description to explain this change in logging configuration, as it may have implications for users managing GreptimeDB clusters.
✅ Verification successful
Logging configuration change is consistent across components and verified.
The modification to use
cluster.GetDatanode().GetLogging()aligns with logging configurations in other components, ensuring consistent and intended behavior across the codebase.🏁 Scripts executed
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#!/bin/bash # Description: Check for similar logging configuration changes in other components # Search for ConfigureLogging calls in other files echo "Searching for ConfigureLogging calls in other files:" rg --type go -n 'ConfigureLogging\(' --glob '!pkg/dbconfig/datanode_config.go' # Search for GetLogging calls to see if cluster-level logging is still used elsewhere echo "\nSearching for GetLogging calls:" rg --type go -n '\.GetLogging\(' --glob '!pkg/dbconfig/datanode_config.go'Length of output: 2713
apis/v1alpha1/testdata/greptimedbcluster/test03/expect.yaml (3)
51-71: Consider increasing meta replicas and document WAL/Kafka relation.The meta configuration is well-structured and consistent with the overall cluster setup. The etcd endpoints and port configurations are clearly defined.
- Consider increasing the number of meta replicas to ensure high availability. A single replica (
replicas: 1) might become a single point of failure. For production environments, it's generally recommended to have at least 3 replicas for the meta component.Example:
meta: replicas: 3
- The comment about WAL and Kafka relation to
enableRegionFailoveris helpful. Consider expanding on this in the documentation or adding a link to more detailed information about this feature and its requirements.To verify the documentation about WAL, Kafka, and region failover, you can run the following script:
#!/bin/bash # Search for documentation about WAL, Kafka, and region failover rg --type markdown -i 'wal.*kafka|region failover'This will help ensure that users have access to comprehensive information about these important configuration options.
96-133: LGTM! Clarify the different logging format for monitoring.The monitoring configuration is comprehensive and well-structured. It includes necessary settings for storage, ports, and object storage specific to the monitoring component.
I noticed that the logging format for the monitoring component is set to 'text', while other components use 'json'. Could you clarify the reason for this difference? If it's intentional, consider adding a comment explaining why a different format is used for monitoring logs.
To verify if this is a consistent pattern or an isolated case, you can run the following script:
#!/bin/bash # Search for logging format configurations across the codebase rg --type yaml 'logging:(\n\s+.*)*\n\s+format:'This will help ensure consistency in logging formats across different components or identify if there's a specific reason for the monitoring component to use a different format.
21-33: LGTM! ClarifypersistentWithDataoption.The object storage and logging configurations are well-structured and provide necessary options for customization.
Could you please clarify the implications of the
persistentWithData: falsesetting in the logging configuration? It's not immediately clear how this affects log persistence and storage. Consider adding a comment or documentation to explain this option's behavior and its relationship with thelogsDirsetting.To verify the usage and documentation of this option, you can run the following script:
pkg/dbconfig/common.go (1)
157-158: LGTM! Consider updating documentation and verifying impact.The simplification of the
ConfigureLoggingmethod is a good improvement. It makes the method easier to use and understand by removing the need to handle separate global and component specs.To ensure this change doesn't introduce any issues:
- Please update the method's documentation to reflect the new signature and behavior.
- Verify that all calls to this method throughout the codebase have been updated accordingly.
Run the following script to check for any remaining calls to the old method signature:
If the script returns any results, those locations will need to be updated to use the new method signature.
apis/v1alpha1/defaulting.go (3)
48-51: LGTM: Proper integration of logging mergeThe addition of the
mergeLoggingcall in theSetDefaultsmethod is appropriate and consistent with the new logging features. The error handling is also correctly implemented.
119-119: LGTM: Consistent addition of Logging field to component specsThe addition of the
Loggingfield to Frontend, Meta, Datanode, and Flownode component specs is consistent and aligns with the new logging features. This uniform implementation across all components ensures a standardized approach to logging configuration.Also applies to: 136-136, 149-149, 162-162
88-109: LGTM: Comprehensive monitoring configuration addedThe addition of the
Monitoringfield in thedefaultSpecmethod is well-structured and aligns with the PR objectives. The default configuration for the Vector component and the automatic setting of JSON logging format when monitoring is enabled are good practices.Please verify if the default resource values for Vector (CPU: 100m, Memory: 128Mi) are sufficient for typical use cases. You may want to run the following command to check if these values align with recommended configurations:
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Actionable comments posted: 3
🧹 Outside diff range and nitpick comments (15)
examples/cluster/enable-monitoring/cluster.yaml (4)
3-4: LGTM! Consider specifying a namespace.The metadata section correctly names the cluster "basic". However, no namespace is specified. While this will work (the cluster will be created in the default namespace), it's often a good practice to explicitly specify a namespace for better resource organization and isolation.
Consider adding a namespace specification:
metadata: name: basic namespace: your-namespace
5-10: LGTM! Consider using a specific version tag for the image.The base image and frontend configuration look good. However, using the "latest" tag for the image can lead to inconsistency issues across different environments or during updates.
Consider using a specific version tag for the image instead of "latest":
spec: base: main: image: greptime/greptimedb:v0.4.0 # Replace with the desired versionThis ensures consistency and makes it easier to track which version is deployed.
11-16: LGTM! Consider high availability for production environments.The meta and datanode configurations are correctly defined. However, using only one replica for each component might not be suitable for production environments where high availability is crucial.
For production environments, consider increasing the number of replicas for better fault tolerance and high availability. For example:
meta: replicas: 3 etcdEndpoints: - "etcd-0.etcd-cluster.svc.cluster.local:2379" - "etcd-1.etcd-cluster.svc.cluster.local:2379" - "etcd-2.etcd-cluster.svc.cluster.local:2379" datanode: replicas: 3Also, ensure that the etcd cluster itself is highly available with multiple endpoints.
17-18: LGTM! Consider additional monitoring configurations.Enabling monitoring is a good practice. However, the current configuration is minimal.
Consider adding more detailed monitoring configurations if available. For example:
monitoring: enabled: true prometheus: interval: "15s" grafana: enabled: true alertmanager: enabled: trueThis would provide more control over the monitoring setup. Check the GreptimeDB Operator documentation for available monitoring options.
apis/v1alpha1/testdata/defaulting/greptimedbcluster/test00/expect.yaml (3)
35-40: LGTM! Consider parameterizing log settings.The logging configuration for the frontend looks good and follows best practices. It provides a good balance between flexibility and standardization.
Consider parameterizing these logging settings to allow for easier configuration changes across different environments or deployments. This could be done by using environment variables or a separate configuration file.
71-76: LGTM! Consider centralizing logging configuration.The logging configuration for the datanode component maintains consistency with the frontend and meta components, which is excellent for standardization and ease of management.
Given that the logging configuration is identical across all components (frontend, meta, and datanode), consider centralizing this configuration at the top level of the GreptimeDBCluster spec. This would reduce repetition and make it easier to manage logging settings across the entire cluster. You could then allow individual components to override specific settings if needed.
Example structure:
spec: logging: format: text level: info logsDir: /data/greptimedb/logs onlyLogToStdout: false persistentWithData: false frontend: # ... (other frontend configs) meta: # ... (other meta configs) datanode: # ... (other datanode configs)This approach would make it easier to maintain consistent logging across components while still allowing for component-specific overrides when necessary.
35-40: Overall improvement in logging configurationThe introduction of consistent logging configurations across frontend, meta, and datanode components significantly enhances the GreptimeDBCluster's observability and manageability. These changes provide a solid foundation for effective log management and troubleshooting.
To further improve the architecture:
- Consider centralizing the logging configuration as suggested earlier.
- Evaluate the possibility of integrating with external logging systems or log aggregation tools to enhance observability at scale.
- Think about implementing log rotation policies to manage log file sizes and retention periods effectively.
Also applies to: 52-57, 71-76
apis/v1alpha1/testdata/defaulting/greptimedbcluster/test02/expect.yaml (3)
46-51: LGTM! Consider log persistence for frontend.The logging configuration for the frontend looks good. It follows best practices with a reasonable log level and directory structure.
Consider setting
persistentWithData: trueif you want to retain logs across pod restarts. This can be helpful for debugging issues that occur over time or during restarts.
84-89: LGTM! Consider log persistence for datanode.The logging configuration for the datanode component maintains consistency with frontend and meta components, which is excellent for overall system coherence.
For datanodes, consider setting
persistentWithData: true. Persistent logs can be crucial for datanodes to track data operations, aid in data recovery scenarios, and maintain an audit trail of data modifications.
46-51: Overall logging configuration looks good, with room for improvement.The addition of consistent logging configurations across frontend, meta, and datanode components is a positive change. It promotes uniformity in log management across the GreptimeDBCluster.
Consider the following improvements:
- To reduce repetition, you could define a common logging configuration and reference it in each component. This would make future updates easier and less error-prone.
- Evaluate the decision to not persist logs by default (
persistentWithData: false) for all components. While this might be suitable for some scenarios, persistent logs can be crucial for debugging and auditing, especially for datanodes.Example of a common logging configuration:
commonLogging: &commonLogging format: text level: info logsDir: /data/greptimedb/logs onlyLogToStdout: false persistentWithData: false # Then in each component: frontend: logging: *commonLogging meta: logging: *commonLogging datanode: logging: <<: *commonLogging persistentWithData: true # Override for datanode if neededThis approach allows for easy global changes while maintaining the flexibility to override specific settings per component when necessary.
Also applies to: 64-69, 84-89
examples/README.md (1)
19-19: LGTM! Consider adding a brief note about prerequisites.The new example "Enable Monitoring Bootstrap" is a valuable addition to the list of GreptimeDB cluster configurations. It follows the established format and is placed appropriately within the document.
To enhance user experience, consider adding a brief note about any prerequisites or additional setup required for enabling monitoring, similar to the notes provided for some other examples (e.g., Prometheus Monitoring, Kafka Remote WAL).
apis/v1alpha1/testdata/defaulting/greptimedbcluster/test01/expect.yaml (3)
42-47: LGTM! Consider moving common logging configuration to a shared section.The logging configuration for the frontend component looks good and consistent with the global logging configuration.
To improve maintainability, consider defining a common logging configuration section and referencing it in each component. This would reduce duplication and make future changes easier to manage. For example:
spec: commonLogging: &commonLogging format: text level: info logsDir: /data/greptimedb/logs onlyLogToStdout: false persistentWithData: false frontend: logging: *commonLogging # ... other frontend configurations
99-104: LGTM! Consistent logging configuration across all components.The logging configuration for the datanode component is identical to both the frontend and meta components, maintaining excellent consistency across the cluster.
Given that this configuration is now repeated across all three components (frontend, meta, and datanode), it strongly reinforces the suggestion to move this to a shared configuration section. This would significantly reduce duplication and improve maintainability. Here's an example of how it could be structured:
spec: commonLogging: &commonLogging format: text level: info logsDir: /data/greptimedb/logs onlyLogToStdout: false persistentWithData: false frontend: logging: *commonLogging # ... other frontend configurations meta: logging: *commonLogging # ... other meta configurations datanode: logging: *commonLogging # ... other datanode configurationsThis approach would make it easier to maintain consistent logging configurations across all components and simplify future updates.
42-47: Overall assessment: Well-implemented logging configurations with room for structural improvement.The changes introduce consistent logging configurations across the frontend, meta, and datanode components of the GreptimeDBCluster. The configurations themselves are well-defined and appropriate.
Key points:
- Logging configurations are identical across all components, which is good for consistency.
- The chosen default values appear reasonable and align with common practices.
Main suggestion for improvement:
Consider refactoring the repeated logging configurations into a shared section to enhance maintainability and reduce duplication. This would make future updates easier and less error-prone.To implement this suggestion, you could use YAML anchors and aliases as demonstrated in the previous comments. This approach would maintain the current functionality while significantly improving the structure and maintainability of the configuration.
Also applies to: 69-74, 99-104
controllers/greptimedbcluster/deployers/monitoring.go (1)
151-168: Consider adding context to HTTP request for better controlWhen making the HTTP request inside the retry operation, consider adding a context to the request. This allows for better control over request cancellation and deadlines, especially in cases where the retry logic might extend the operation's total duration.
You can modify the code as follows:
operation := func() error { + ctxWithTimeout, cancel := context.WithTimeout(context.Background(), 5*time.Second) + defer cancel() + + req, err := http.NewRequestWithContext(ctxWithTimeout, "POST", fmt.Sprintf("http://%s/v1/events/pipelines/%s", svc, common.LogsPipelineName(cluster.Namespace, cluster.Name)), bytes.NewReader(b.Bytes())) if err != nil { return err } req.Header.Set("Content-Type", w.FormDataContentType())
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⛔ Files ignored due to path filters (1)
go.sumis excluded by!**/*.sum
📒 Files selected for processing (35)
- Makefile (2 hunks)
- apis/v1alpha1/common.go (3 hunks)
- apis/v1alpha1/constants.go (1 hunks)
- apis/v1alpha1/defaulting.go (8 hunks)
- apis/v1alpha1/greptimedbcluster_types.go (5 hunks)
- apis/v1alpha1/testdata/defaulting/greptimedbcluster/test00/expect.yaml (3 hunks)
- apis/v1alpha1/testdata/defaulting/greptimedbcluster/test01/expect.yaml (3 hunks)
- apis/v1alpha1/testdata/defaulting/greptimedbcluster/test02/expect.yaml (3 hunks)
- apis/v1alpha1/testdata/greptimedbcluster/test03/expect.yaml (1 hunks)
- apis/v1alpha1/testdata/greptimedbcluster/test03/input.yaml (1 hunks)
- apis/v1alpha1/zz_generated.deepcopy.go (6 hunks)
- controllers/common/common.go (1 hunks)
- controllers/constant/constant.go (1 hunks)
- controllers/greptimedbcluster/controller.go (2 hunks)
- controllers/greptimedbcluster/deployers/common.go (3 hunks)
- controllers/greptimedbcluster/deployers/config/config.go (1 hunks)
- controllers/greptimedbcluster/deployers/config/pipeline.yaml (1 hunks)
- controllers/greptimedbcluster/deployers/config/vector-config-template.yaml (1 hunks)
- controllers/greptimedbcluster/deployers/datanode.go (3 hunks)
- controllers/greptimedbcluster/deployers/flownode.go (1 hunks)
- controllers/greptimedbcluster/deployers/frontend.go (1 hunks)
- controllers/greptimedbcluster/deployers/meta.go (1 hunks)
- controllers/greptimedbcluster/deployers/monitoring.go (1 hunks)
- docs/api-references/docs.md (6 hunks)
- examples/README.md (1 hunks)
- examples/cluster/enable-monitoring/cluster.yaml (1 hunks)
- go.mod (3 hunks)
- pkg/dbconfig/common.go (1 hunks)
- pkg/dbconfig/datanode_config.go (1 hunks)
- pkg/dbconfig/flownode_config.go (1 hunks)
- pkg/dbconfig/frontend_config.go (1 hunks)
- pkg/dbconfig/meta_config.go (1 hunks)
- pkg/dbconfig/standalone_config.go (1 hunks)
- pkg/deployer/builder.go (4 hunks)
- pkg/deployer/constants.go (1 hunks)
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- Makefile
- apis/v1alpha1/common.go
- apis/v1alpha1/constants.go
- apis/v1alpha1/defaulting.go
- apis/v1alpha1/greptimedbcluster_types.go
- apis/v1alpha1/testdata/greptimedbcluster/test03/expect.yaml
- apis/v1alpha1/testdata/greptimedbcluster/test03/input.yaml
- apis/v1alpha1/zz_generated.deepcopy.go
- controllers/common/common.go
- controllers/constant/constant.go
- controllers/greptimedbcluster/controller.go
- controllers/greptimedbcluster/deployers/common.go
- controllers/greptimedbcluster/deployers/config/config.go
- controllers/greptimedbcluster/deployers/config/pipeline.yaml
- controllers/greptimedbcluster/deployers/config/vector-config-template.yaml
- controllers/greptimedbcluster/deployers/datanode.go
- controllers/greptimedbcluster/deployers/flownode.go
- controllers/greptimedbcluster/deployers/frontend.go
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🧰 Additional context used
🪛 Markdownlint
docs/api-references/docs.md
642-642: null
Link fragments should be valid(MD051, link-fragments)
🔇 Additional comments (14)
examples/cluster/enable-monitoring/cluster.yaml (1)
1-2: LGTM! Note the alpha API version.The API version and kind are correctly defined for a GreptimeDBCluster resource. However, it's worth noting that the API version is still in alpha (v1alpha1), which means it might be subject to changes in future releases.
✅ Verification successful
Verified! All YAML configurations, including
examples/cluster/enable-monitoring/cluster.yaml, are using the currentapiVersion: greptime.io/v1alpha1. There are no updates or changes to the API version across the codebase.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Verify if this is the latest API version for GreptimeDBCluster rg --type yaml 'apiVersion:\s*greptime.io/v\d+' -g '*.yaml'Length of output: 3534
apis/v1alpha1/testdata/defaulting/greptimedbcluster/test00/expect.yaml (1)
52-57: LGTM! Consistent logging configuration.The logging configuration for the meta component is consistent with the frontend, which is excellent for maintainability and standardization across the cluster components.
apis/v1alpha1/testdata/defaulting/greptimedbcluster/test02/expect.yaml (1)
64-69: LGTM! Consistent logging configuration for meta.The logging configuration for the meta component is consistent with the frontend, which is good for maintainability and uniformity across the cluster.
The same consideration about log persistence applies here as mentioned in the frontend section.
apis/v1alpha1/testdata/defaulting/greptimedbcluster/test01/expect.yaml (1)
69-74: LGTM! Consistent with frontend logging configuration.The logging configuration for the meta component is identical to the frontend component, which is good for consistency.
As mentioned in the frontend review, consider moving this common configuration to a shared section to improve maintainability and reduce duplication.
docs/api-references/docs.md (7)
342-342: New specification added: MonitoringSpecThe
MonitoringSpechas been added to theGreptimeDBClusterSpec. This new specification allows for configuring monitoring capabilities for the GreptimeDB cluster.
467-481: New specification added: LogPipelineThe
LogPipelinespecification has been introduced to define the structure for log pipeline configurations. It includes a field for the YAML content of the pipeline configuration file.
528-542: New specification added: LogsCollectionSpecThe
LogsCollectionSpechas been added to specify the structure for collecting cluster logs, with a reference to theLogPipeline.
614-631: New specification added: MonitoringSpecThe
MonitoringSpechas been added to theGreptimeDBClusterSpec. This specification defines the configuration for monitor bootstrapping, including options for enabling the monitoring service, configuring a standalone GreptimeDB instance, log collection, and vector instance settings.
633-647: New specification added: MonitoringStatusThe
MonitoringStatushas been introduced to describe the status of the monitoring service, including theinternalDNSNamefield.🧰 Tools
🪛 Markdownlint
642-642: null
Link fragments should be valid(MD051, link-fragments)
889-904: New specification added: VectorSpecThe
VectorSpechas been added to specify the configuration for a vector instance, detailing the image and resource requirements.
394-394: Integration of new specificationsThe
MonitoringSpechas been correctly integrated into theGreptimeDBClusterSpec. This allows users to configure monitoring capabilities for their GreptimeDB clusters.controllers/greptimedbcluster/deployers/monitoring.go (3)
185-190: Correct usage offs.ReadFileThe
fs.ReadFilefunction is being used incorrectly. Its signature isfs.ReadFile(fsys fs.FS, name string) ([]byte, error), wherefsysis a file system. It seems thatconfig.DefaultPipelineis intended to be the file path.
138-139: Make the pipeline service port configurableThe port
4000is hardcoded when constructing the service URL for the pipeline. To enhance flexibility and accommodate different deployment scenarios, consider making the port configurable.
102-104: Handle error returned byUpdateStatusIn the
CheckAndUpdateStatusfunction, the error returned byUpdateStatusis being logged but not handled. This could lead to silent failures when updating the cluster status.
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🧹 Outside diff range and nitpick comments (15)
tests/e2e/testdata/resources/cluster/enable-monitoring/cluster.yaml (6)
3-5: LGTM: Metadata is appropriately set for testing purposes.The cluster name clearly indicates its purpose (e2e testing with monitoring enabled), and using the default namespace is acceptable for testing.
For production deployments, consider using a dedicated namespace instead of the default one to improve resource isolation and management.
7-8: LGTM with suggestions: Initializer configuration is set correctly for testing.The initializer image is correctly specified and uses a local registry, which is suitable for testing purposes.
For production deployments:
- Consider using a specific version tag instead of "latest" to ensure consistency and reproducibility.
- Use a production-grade container registry instead of a local one.
Example:
initializer: image: your-registry.com/greptime/greptimedb-initializer:v1.0.0
9-11: LGTM with suggestions: Base configuration is set correctly for testing.The base image is correctly specified and uses a local registry, which is suitable for testing purposes.
For production deployments:
- Consider using a specific version tag instead of "latest" to ensure consistency and reproducibility.
- Use a production-grade container registry instead of a local one.
- You might want to expand the base configuration with additional settings such as resource requests and limits, security contexts, or custom environment variables.
Example:
base: main: image: your-registry.com/greptime/greptimedb:v1.0.0 resources: requests: cpu: 100m memory: 128Mi limits: cpu: 500m memory: 512Mi
12-19: LGTM with suggestions: Component configurations are suitable for testing.The frontend, meta, and datanode configurations are correctly specified with 1 replica each, which is suitable for testing. The etcd endpoint for the meta component is correctly set using a service DNS name.
For production deployments:
- Increase the number of replicas for high availability and fault tolerance.
- Consider adding resource specifications (requests and limits) for each component.
- You might want to add additional configurations such as persistence settings, security contexts, or custom flags.
Example:
frontend: replicas: 3 resources: requests: cpu: 200m memory: 256Mi limits: cpu: 1 memory: 1Gi meta: replicas: 3 resources: requests: cpu: 200m memory: 256Mi limits: cpu: 1 memory: 1Gi etcdEndpoints: - "etcd-0.etcd-headless.etcd.svc.cluster.local:2379" - "etcd-1.etcd-headless.etcd.svc.cluster.local:2379" - "etcd-2.etcd-headless.etcd.svc.cluster.local:2379" datanode: replicas: 3 resources: requests: cpu: 500m memory: 1Gi limits: cpu: 2 memory: 4Gi
20-21: LGTM: Monitoring is correctly enabled.The monitoring feature is successfully enabled, which aligns with the PR objective to implement monitoring bootstrap.
Consider expanding the monitoring configuration with additional settings to provide more control over the monitoring setup. Some potential additions could include:
- Specifying the monitoring stack (e.g., Prometheus, Grafana)
- Defining custom scrape intervals
- Setting retention periods for metrics
- Configuring alerting rules
Example:
monitoring: enabled: true prometheus: retention: 15d scrapeInterval: 15s grafana: enabled: true alertmanager: enabled: trueThese suggestions would provide more granular control over the monitoring setup, but their implementation would depend on the specific monitoring capabilities of the GreptimeDB operator.
1-21: Overall, the GreptimeDBCluster configuration is well-structured and meets the PR objective.This configuration successfully defines a GreptimeDBCluster resource with monitoring enabled, which aligns with the PR objective of implementing monitoring bootstrap. The setup is suitable for end-to-end testing purposes.
For production deployments, consider the following architectural improvements:
- Use specific version tags for all images instead of "latest" to ensure consistency and reproducibility.
- Implement high availability by increasing the number of replicas for frontend, meta, and datanode components.
- Add resource specifications (requests and limits) for all components to ensure proper resource allocation and prevent resource starvation.
- Expand the monitoring configuration with more detailed settings to leverage the full potential of the monitoring capabilities.
- Consider adding persistence configurations, security contexts, and custom flags as needed for a production-grade deployment.
- Use a dedicated namespace instead of the default one for better resource isolation and management.
These improvements will help create a more robust, scalable, and production-ready GreptimeDBCluster deployment.
tests/e2e/testdata/resources/cluster/standalone-wal/cluster.yaml (1)
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1-26: Summary of changes and potential impact.The main changes in this configuration file are:
- Updated cluster name to include "e2e-" prefix.
- Removal of specific port declarations (not visible in the diff).
These changes, while seemingly minor, could have significant implications:
- The name change might require updates in other parts of the e2e test suite that reference this cluster.
- The removal of port declarations could affect how the cluster's network is configured and how e2e tests interact with the cluster.
Consider the following recommendations:
- Update all references to this cluster name across the e2e test suite.
- Document the new port allocation strategy (if any) in the project documentation.
- Review and update any e2e tests that might have been relying on the specific port numbers that were removed.
- Consider adding a comment in this YAML file explaining the rationale behind removing the port declarations, to prevent future confusion.
tests/e2e/greptimedbcluster_test.go (1)
55-58: LGTM! Consider adding a brief comment for consistency.The new test case for enabling monitoring is well-integrated into the existing test suite and follows the established pattern. Good job on expanding the test coverage!
For consistency with some of the other test cases, consider adding a brief comment above the test case to describe its purpose. For example:
+ // Test enabling monitoring for the cluster It("Test a cluster that enables monitoring", func() { greptimedbcluster.TestClusterEnableMonitoring(ctx, h) })tests/e2e/greptimedbcluster/test_basic_cluster.go (2)
63-64: LGTM with a minor suggestion.The addition of these lines to retrieve the cluster object after creation is a good practice. It ensures that we have the most up-to-date state of the cluster for any subsequent operations or checks.
Consider adding a comment explaining why we're retrieving the cluster object again. This would improve code readability. For example:
+ // Retrieve the latest cluster state for subsequent operations err = h.Get(ctx, client.ObjectKey{Name: testCluster.Name, Namespace: testCluster.Namespace}, testCluster) Expect(err).NotTo(HaveOccurred(), "failed to get cluster")
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1-101: Consider some structural improvements to enhance maintainability.While the function is well-structured and functional, here are some suggestions to further improve it:
If the
testCRFileandtestSQLFileconstants are used in multiple tests, consider moving them to package-level constants.Enhance error messages in Expect statements to provide more context. For example:
Expect(err).NotTo(HaveOccurred(), "failed to create greptimedbcluster: %v", err)The function is quite long. Consider breaking it down into smaller, more focused functions. For example:
func setupCluster(ctx context.Context, h *helper.Helper) *greptimev1alpha1.GreptimeDBCluster func runSQLTests(ctx context.Context, h *helper.Helper, cluster *greptimev1alpha1.GreptimeDBCluster) func cleanupCluster(ctx context.Context, h *helper.Helper, cluster *greptimev1alpha1.GreptimeDBCluster)This would make the main test function more readable and easier to maintain.
tests/e2e/greptimedbcluster/test_cluster_enable_flow.go (2)
63-65: Approve the additional cluster retrieval check with a minor suggestion.The added code enhances the test robustness by confirming the successful creation and retrieval of the cluster object. This is a good practice that can help catch potential issues early in the test flow.
Consider adding a brief comment explaining the purpose of this additional check for better code readability:
+ // Verify that the cluster object can be successfully retrieved after creation err = h.Get(ctx, client.ObjectKey{Name: testCluster.Name, Namespace: testCluster.Namespace}, testCluster) Expect(err).NotTo(HaveOccurred(), "failed to get cluster")
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1-105: Overall, the test implementation is robust and well-structured.The
TestClusterEnableFlowfunction provides a comprehensive end-to-end test for the GreptimeDB cluster, covering crucial aspects such as cluster creation, status verification, SQL execution, and proper cleanup. The recent addition of the cluster retrieval check further enhances the test's reliability.Consider the following suggestions to further improve the test:
- Error handling: Implement more granular error checking and reporting throughout the test to provide more specific failure messages.
- Timeouts: Review and possibly adjust the
helper.DefaultTimeoutused in theEventuallyblocks to ensure they are appropriate for different environments.- Cleanup: Consider implementing a defer function to ensure cleanup operations (like killing port forwarding and deleting the cluster) are performed even if the test fails midway.
- Logging: Add more detailed logging throughout the test to aid in debugging and provide clearer test execution progress.
tests/e2e/greptimedbcluster/test_cluster_enable_remote_wal.go (1)
63-65: Approve the addition with a minor suggestion for consistency.The added error check for retrieving the cluster object after creation is a valuable addition to the test. It enhances the validation process by ensuring the cluster is accessible and correctly instantiated in the Kubernetes context.
For consistency with other error checks in this file, consider wrapping this check in an
Eventuallyblock. This would allow for potential eventual consistency in the Kubernetes API. Here's a suggested implementation:- err = h.Get(ctx, client.ObjectKey{Name: testCluster.Name, Namespace: testCluster.Namespace}, testCluster) - Expect(err).NotTo(HaveOccurred(), "failed to get cluster") + Eventually(func() error { + return h.Get(ctx, client.ObjectKey{Name: testCluster.Name, Namespace: testCluster.Namespace}, testCluster) + }, helper.DefaultTimeout, time.Second).ShouldNot(HaveOccurred(), "failed to get cluster")This change would make the error checking consistent with other similar checks in the file and potentially improve test reliability.
tests/e2e/greptimedbcluster/test_cluster_standalone_wal.go (1)
63-65: Approve changes with a minor suggestion for consistency.The addition of this cluster retrieval check after creation is a good practice. It enhances the test's robustness by ensuring the cluster is accessible before proceeding with further operations.
For consistency with other error checks in this function, consider wrapping this check in an
Eventuallyblock. This would allow for any potential delay in the cluster becoming accessible after creation. Here's a suggested modification:-err = h.Get(ctx, client.ObjectKey{Name: testCluster.Name, Namespace: testCluster.Namespace}, testCluster) -Expect(err).NotTo(HaveOccurred(), "failed to get cluster") +Eventually(func() error { + return h.Get(ctx, client.ObjectKey{Name: testCluster.Name, Namespace: testCluster.Namespace}, testCluster) +}, helper.DefaultTimeout, time.Second).ShouldNot(HaveOccurred(), "failed to get cluster")This change would make the new check consistent with other asynchronous operations in the test, such as the subsequent status check.
tests/e2e/greptimedbcluster/test_cluster_enable_monitoring.go (1)
1-14: Verify the license header yearThe license header specifies the year as 2024. Please verify that this is the correct year for the file's creation or modification to ensure compliance with licensing requirements.
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📒 Files selected for processing (15)
- tests/e2e/greptimedbcluster/test_basic_cluster.go (1 hunks)
- tests/e2e/greptimedbcluster/test_cluster_enable_flow.go (1 hunks)
- tests/e2e/greptimedbcluster/test_cluster_enable_monitoring.go (1 hunks)
- tests/e2e/greptimedbcluster/test_cluster_enable_remote_wal.go (1 hunks)
- tests/e2e/greptimedbcluster/test_cluster_standalone_wal.go (1 hunks)
- tests/e2e/greptimedbcluster/test_scale_cluster.go (1 hunks)
- tests/e2e/greptimedbcluster_test.go (1 hunks)
- tests/e2e/greptimedbstandalone/test_basic_standalone.go (1 hunks)
- tests/e2e/testdata/resources/cluster/basic/cluster.yaml (0 hunks)
- tests/e2e/testdata/resources/cluster/enable-flow/cluster.yaml (0 hunks)
- tests/e2e/testdata/resources/cluster/enable-monitoring/cluster.yaml (1 hunks)
- tests/e2e/testdata/resources/cluster/enable-remote-wal/cluster.yaml (0 hunks)
- tests/e2e/testdata/resources/cluster/scale/cluster.yaml (0 hunks)
- tests/e2e/testdata/resources/cluster/standalone-wal/cluster.yaml (1 hunks)
- tests/e2e/testdata/resources/standalone/basic/standalone.yaml (0 hunks)
💤 Files with no reviewable changes (5)
- tests/e2e/testdata/resources/cluster/basic/cluster.yaml
- tests/e2e/testdata/resources/cluster/enable-flow/cluster.yaml
- tests/e2e/testdata/resources/cluster/enable-remote-wal/cluster.yaml
- tests/e2e/testdata/resources/cluster/scale/cluster.yaml
- tests/e2e/testdata/resources/standalone/basic/standalone.yaml
🔇 Additional comments (10)
tests/e2e/testdata/resources/cluster/enable-monitoring/cluster.yaml (1)
1-2: LGTM: API version and kind are correctly specified.The API version and kind are appropriately set for a GreptimeDBCluster resource. The alpha version (v1alpha1) is suitable for this new feature.
tests/e2e/testdata/resources/cluster/standalone-wal/cluster.yaml (2)
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1-26: Verify the intentional removal of port declarations.The AI summary indicates that
httpPort,rpcPort,mysqlPort, andpostgreSQLPortdeclarations have been removed. While not directly visible in the diff, this change could impact the cluster's network configuration.Please confirm if this removal is intentional and doesn't break the cluster's functionality. Consider the following:
- Are default ports now being used instead?
- Is there a new mechanism for port allocation?
- How does this affect the e2e tests that might depend on specific port numbers?
Run the following script to check for any remaining port declarations in other cluster configurations:
#!/bin/bash # Description: Check for port declarations in other cluster configurations # Test: Search for port declarations in yaml files rg "(httpPort|rpcPort|mysqlPort|postgreSQLPort):" --type yaml
4-4: Cluster name updated for e2e tests.The cluster name has been updated from
cluster-with-standalone-waltoe2e-cluster-with-standalone-wal. This change appears to be intentional, likely to distinguish e2e test clusters.Please ensure this name change is consistent across all e2e test configurations and doesn't break any existing tests. Run the following script to check for any other occurrences of the old name:
✅ Verification successful
No remaining occurrences of the old cluster name found.
The name change is consistent across all configurations.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check for any remaining occurrences of the old cluster name # Test: Search for the old cluster name rg "cluster-with-standalone-wal" --type yamlLength of output: 8940
tests/e2e/greptimedbcluster_test.go (1)
Line range hint
1-58: Well-structured and comprehensive test suite.The test suite is well-organized and covers various aspects of GreptimeDBCluster functionality. The addition of the monitoring test case enhances the overall coverage. Good job on maintaining a consistent structure across all test cases.
tests/e2e/greptimedbstandalone/test_basic_standalone.go (1)
49-51: LGTM! Enhances test robustness.This addition improves the test by verifying that the
GreptimeDBStandaloneobject can be successfully retrieved immediately after creation. It's a good practice to ensure the object is accessible before proceeding with further checks.tests/e2e/greptimedbcluster/test_cluster_enable_remote_wal.go (1)
Line range hint
1-105: Overall assessment of the test file.The
TestClusterEnableRemoteWalfunction provides a comprehensive end-to-end test for a GreptimeDB cluster with remote WAL enabled. It covers crucial aspects such as cluster creation, status verification, SQL execution, and proper cleanup. The newly added error check for retrieving the cluster object enhances the test's robustness.The test structure is well-organized and follows good practices for e2e testing. It uses appropriate timeouts and error checking throughout. The cleanup process at the end of the test is thorough, ensuring that resources are properly managed.
To further improve the test, consider the following suggestions:
- Add more detailed comments explaining the purpose of each major section of the test.
- Consider parameterizing some of the constants (like timeout durations) for easier maintenance.
- If not done elsewhere, consider adding negative test cases to ensure proper error handling in the cluster setup.
tests/e2e/greptimedbcluster/test_scale_cluster.go (4)
64-66: LGTM: Good addition to fetch the latest cluster stateThis change ensures that the test is working with the most up-to-date cluster information before proceeding with the SQL tests. It's a good practice that improves the test's reliability.
Line range hint
1-1: Request: Please provide the code changes related to scaling operationsThe AI summary mentions changes to scaling operations and checks for replica counts, but these changes are not visible in the provided code snippet. To provide a comprehensive review, it would be helpful to see the actual code modifications related to:
- Updating the cluster's replica specifications for Datanode and Frontend components.
- Checks added to confirm the expected number of replicas after scaling up and down.
Could you please provide these specific code changes?
Line range hint
1-1: Suggestion: Reconsider the use of sleep for stabilizationThe AI summary mentions the addition of a sleep period after scaling down to allow the cluster to stabilize. While this can be a quick fix, it's generally not recommended as a long-term solution for several reasons:
- It introduces an arbitrary wait time that may not always be sufficient.
- It can unnecessarily slow down the tests if the cluster stabilizes faster than the sleep duration.
- It doesn't provide any guarantee that the cluster has actually stabilized.
Instead, consider implementing a more robust solution:
- Use a polling mechanism to check the cluster's status periodically.
- Define clear criteria for what constitutes a "stable" cluster.
- Implement a timeout to prevent indefinite waiting if stability is not achieved.
Could you please provide the actual code change related to this sleep addition? This would allow for a more specific review and suggestions for improvement.
Line range hint
1-1: Summary: Partial improvements visible, additional code needed for complete reviewThe visible changes in this file, particularly fetching the latest cluster state before proceeding with tests, are positive improvements that enhance the test's reliability. However, to provide a comprehensive review, it's crucial to see the actual code changes related to:
- Scaling operations and replica count checks.
- The addition of a sleep period for cluster stabilization.
These changes, mentioned in the AI summary, are significant parts of the test logic enhancement. Once these sections are provided, a more thorough review can be conducted to ensure the overall effectiveness and robustness of the
TestScaleClusterfunction.Please provide the missing code sections to complete this review.
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⛔ Files ignored due to path filters (1)
go.sumis excluded by!**/*.sum
📒 Files selected for processing (50)
- Makefile (2 hunks)
- apis/v1alpha1/common.go (3 hunks)
- apis/v1alpha1/constants.go (2 hunks)
- apis/v1alpha1/defaulting.go (10 hunks)
- apis/v1alpha1/greptimedbcluster_types.go (5 hunks)
- apis/v1alpha1/testdata/defaulting/greptimedbcluster/test00/expect.yaml (3 hunks)
- apis/v1alpha1/testdata/defaulting/greptimedbcluster/test01/expect.yaml (3 hunks)
- apis/v1alpha1/testdata/defaulting/greptimedbcluster/test02/expect.yaml (3 hunks)
- apis/v1alpha1/testdata/greptimedbcluster/test03/expect.yaml (1 hunks)
- apis/v1alpha1/testdata/greptimedbcluster/test03/input.yaml (1 hunks)
- apis/v1alpha1/zz_generated.deepcopy.go (6 hunks)
- controllers/common/common.go (1 hunks)
- controllers/constant/constant.go (1 hunks)
- controllers/greptimedbcluster/controller.go (2 hunks)
- controllers/greptimedbcluster/deployers/common.go (3 hunks)
- controllers/greptimedbcluster/deployers/config/config.go (1 hunks)
- controllers/greptimedbcluster/deployers/config/pipeline.yaml (1 hunks)
- controllers/greptimedbcluster/deployers/config/vector-config-template.yaml (1 hunks)
- controllers/greptimedbcluster/deployers/datanode.go (3 hunks)
- controllers/greptimedbcluster/deployers/flownode.go (1 hunks)
- controllers/greptimedbcluster/deployers/frontend.go (1 hunks)
- controllers/greptimedbcluster/deployers/meta.go (1 hunks)
- controllers/greptimedbcluster/deployers/monitoring.go (1 hunks)
- docs/api-references/docs.md (6 hunks)
- examples/README.md (1 hunks)
- examples/cluster/enable-monitoring/cluster.yaml (1 hunks)
- go.mod (1 hunks)
- pkg/dbconfig/common.go (1 hunks)
- pkg/dbconfig/datanode_config.go (1 hunks)
- pkg/dbconfig/flownode_config.go (1 hunks)
- pkg/dbconfig/frontend_config.go (1 hunks)
- pkg/dbconfig/meta_config.go (1 hunks)
- pkg/dbconfig/standalone_config.go (1 hunks)
- pkg/deployer/builder.go (4 hunks)
- pkg/deployer/constants.go (1 hunks)
- tests/e2e/greptimedbcluster/test_basic_cluster.go (1 hunks)
- tests/e2e/greptimedbcluster/test_cluster_enable_flow.go (1 hunks)
- tests/e2e/greptimedbcluster/test_cluster_enable_monitoring.go (1 hunks)
- tests/e2e/greptimedbcluster/test_cluster_enable_remote_wal.go (1 hunks)
- tests/e2e/greptimedbcluster/test_cluster_standalone_wal.go (1 hunks)
- tests/e2e/greptimedbcluster/test_scale_cluster.go (1 hunks)
- tests/e2e/greptimedbcluster_test.go (1 hunks)
- tests/e2e/greptimedbstandalone/test_basic_standalone.go (1 hunks)
- tests/e2e/testdata/resources/cluster/basic/cluster.yaml (0 hunks)
- tests/e2e/testdata/resources/cluster/enable-flow/cluster.yaml (0 hunks)
- tests/e2e/testdata/resources/cluster/enable-monitoring/cluster.yaml (1 hunks)
- tests/e2e/testdata/resources/cluster/enable-remote-wal/cluster.yaml (0 hunks)
- tests/e2e/testdata/resources/cluster/scale/cluster.yaml (0 hunks)
- tests/e2e/testdata/resources/cluster/standalone-wal/cluster.yaml (1 hunks)
- tests/e2e/testdata/resources/standalone/basic/standalone.yaml (0 hunks)
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- tests/e2e/testdata/resources/cluster/basic/cluster.yaml
- tests/e2e/testdata/resources/cluster/enable-flow/cluster.yaml
- tests/e2e/testdata/resources/cluster/enable-remote-wal/cluster.yaml
- tests/e2e/testdata/resources/cluster/scale/cluster.yaml
- tests/e2e/testdata/resources/standalone/basic/standalone.yaml
🚧 Files skipped from review as they are similar to previous changes (44)
- Makefile
- apis/v1alpha1/common.go
- apis/v1alpha1/constants.go
- apis/v1alpha1/defaulting.go
- apis/v1alpha1/greptimedbcluster_types.go
- apis/v1alpha1/testdata/defaulting/greptimedbcluster/test00/expect.yaml
- apis/v1alpha1/testdata/defaulting/greptimedbcluster/test01/expect.yaml
- apis/v1alpha1/testdata/defaulting/greptimedbcluster/test02/expect.yaml
- apis/v1alpha1/testdata/greptimedbcluster/test03/expect.yaml
- apis/v1alpha1/testdata/greptimedbcluster/test03/input.yaml
- apis/v1alpha1/zz_generated.deepcopy.go
- controllers/common/common.go
- controllers/constant/constant.go
- controllers/greptimedbcluster/controller.go
- controllers/greptimedbcluster/deployers/common.go
- controllers/greptimedbcluster/deployers/config/config.go
- controllers/greptimedbcluster/deployers/config/pipeline.yaml
- controllers/greptimedbcluster/deployers/config/vector-config-template.yaml
- controllers/greptimedbcluster/deployers/datanode.go
- controllers/greptimedbcluster/deployers/flownode.go
- controllers/greptimedbcluster/deployers/frontend.go
- controllers/greptimedbcluster/deployers/meta.go
- controllers/greptimedbcluster/deployers/monitoring.go
- examples/README.md
- examples/cluster/enable-monitoring/cluster.yaml
- go.mod
- pkg/dbconfig/common.go
- pkg/dbconfig/datanode_config.go
- pkg/dbconfig/flownode_config.go
- pkg/dbconfig/frontend_config.go
- pkg/dbconfig/meta_config.go
- pkg/dbconfig/standalone_config.go
- pkg/deployer/builder.go
- pkg/deployer/constants.go
- tests/e2e/greptimedbcluster/test_basic_cluster.go
- tests/e2e/greptimedbcluster/test_cluster_enable_flow.go
- tests/e2e/greptimedbcluster/test_cluster_enable_monitoring.go
- tests/e2e/greptimedbcluster/test_cluster_enable_remote_wal.go
- tests/e2e/greptimedbcluster/test_cluster_standalone_wal.go
- tests/e2e/greptimedbcluster/test_scale_cluster.go
- tests/e2e/greptimedbcluster_test.go
- tests/e2e/greptimedbstandalone/test_basic_standalone.go
- tests/e2e/testdata/resources/cluster/enable-monitoring/cluster.yaml
- tests/e2e/testdata/resources/cluster/standalone-wal/cluster.yaml
🧰 Additional context used
🪛 Markdownlint
docs/api-references/docs.md
642-642: null
Link fragments should be valid(MD051, link-fragments)
🔇 Additional comments (6)
docs/api-references/docs.md (6)
342-342: LGTM: New MonitoringSpec section addedThe new MonitoringSpec section has been added correctly, providing clear information about the monitoring configuration for the GreptimeDBCluster. The structure and format are consistent with the rest of the document.
467-481: LGTM: New LogPipeline section addedThe LogPipeline section has been added successfully, describing the specification for log pipeline configuration. The structure and content are appropriate and consistent with the document's style.
528-542: LGTM: New LogsCollectionSpec section addedThe LogsCollectionSpec section has been added correctly, providing information about the specification for cluster logs collection. The content is clear and follows the established format.
633-647: LGTM: New MonitoringStatus section addedThe MonitoringStatus section has been added successfully, describing the status of the monitoring service. The content is concise and follows the document's structure.
🧰 Tools
🪛 Markdownlint
642-642: null
Link fragments should be valid(MD051, link-fragments)
889-904: LGTM: New VectorSpec section addedThe VectorSpec section has been added correctly, providing information about the specification for the vector instance. The content is clear and consistent with the rest of the document.
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1-905: Overall assessment: Documentation updated successfully with minor issueThe API reference documentation has been successfully updated with new specifications for MonitoringSpec, LogPipeline, LogsCollectionSpec, MonitoringStatus, and VectorSpec. These additions are well-structured and consistent with the existing documentation style.
There's one minor issue remaining:
- An invalid link fragment on line 642 needs to be addressed.
Once this link issue is resolved, the documentation will be in excellent shape.
🧰 Tools
🪛 Markdownlint
642-642: null
Link fragments should be valid(MD051, link-fragments)
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- tests/e2e/greptimedbcluster/test_cluster_enable_monitoring.go (1 hunks)
🔇 Additional comments (2)
tests/e2e/greptimedbcluster/test_cluster_enable_monitoring.go (2)
73-78: 🛠️ Refactor suggestionUse
deferto close network connectionsWhen establishing a connection in the
Eventuallyblock, it's good practice to usedeferto ensure the connection is closed, even if an error occurs later. This prevents potential resource leaks.Modify the code as follows:
conn, err := net.Dial("tcp", frontendAddr) if err != nil { return err } +defer conn.Close() -conn.Close() return nilLikely invalid or redundant comment.
111-111:⚠️ Potential issueEnsure
Datanode.Replicasis not nil before dereferencingThe expression
*testCluster.Spec.Datanode.Replicasdereferences a pointer without checking if it's nil. IfDatanode.Replicasis not set, this could lead to a nil pointer dereference, causing the test to panic.Add a nil check before dereferencing:
+Expect(testCluster.Spec.Datanode.Replicas).NotTo(BeNil(), "Datanode replicas should not be nil") Expect(int32(len(datanodePVCs))).To(Equal(*testCluster.Spec.Datanode.Replicas), "the number of datanode PVCs should be equal to the number of datanode replicas")Likely invalid or redundant comment.
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🧹 Outside diff range and nitpick comments (1)
controllers/greptimedbcluster/deployers/monitoring.go (1)
138-139: Make the pipeline service port configurableThere's a
FIXMEcomment indicating the need to make the port configurable. Enhancing the code to allow port configuration will increase flexibility and adaptability in different deployment scenarios.Would you like assistance in modifying the code to make the port configurable by retrieving it from the monitoring specification? I can help implement this enhancement.
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- apis/v1alpha1/defaulting.go (10 hunks)
- controllers/greptimedbcluster/deployers/common.go (3 hunks)
- controllers/greptimedbcluster/deployers/monitoring.go (1 hunks)
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🔇 Additional comments (2)
controllers/greptimedbcluster/deployers/monitoring.go (1)
57-69: Chained builder pattern inGeneratefunction is clear and effectiveThe use of the builder pattern in the
Generatemethod enhances code readability and maintainability. Chaining methods likeBuildGreptimeDBStandalone,BuildConfigMap, andSetControllerAndAnnotationprovides a fluent interface that's easy to follow.controllers/greptimedbcluster/deployers/common.go (1)
152-160: Ensure Corresponding Volumes are Defined for Volume MountsThe
vectorcontainer mounts volumes namedconstant.DefaultLogsVolumeNameandconstant.DefaultVectorConfigName. Verify that these volumes are added totemplate.Spec.Volumesto prevent runtime errors.Run the following script to check if the volumes are defined:
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