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Observability & Testing Workshop based on Dima WebApp

Disclaimer

This application has little security built in, so it can be at risk if left running and open to the internet. You are running this at your own risk.

License

This application runs under the Apache 2.0 License which you can read more about here as well.

Welcome to Dima

The Dima application is a web application with basic CRUD functionality around images. The main goal of this repository is to provide a playground for software professionals to practice their debugging and instrumenting of software applications for greater observability. Therefore, the minimal Dima WebApp is meant as a way to exercise an overpowered telemetry stack.

There will always be bugs and issues that can be found. Some are planned, and others are fun coincidences. If you find something not in the known bugs file please create a pull request and we would love to know about it.

Running the stack

Preparing infrastructure

This stack takes a fair bit of RAM to run successfully, therefore we suggest running on a cloud managed kubernetes cluster. For GKE a setup incl. scripts can be found in stack/kubernetes.

Selecting the application to run

The application images are built via the docker-compose file found under stack/compose.

What you are building

Our application is made up of a WebApp to upload, manipulate, view, and delete images as well as extensive telemetry tooling. For a visual representation of our application, check out the architecture diagram or the infrastructure diagram.

NOTE: These images are prone to getting out of date. Pull requests welcome!

Key application credentials

Grafana credentials: grafana/changeme

Kibana credentials: elastic/changeme

Application services

The following application services can be found under stack/application.

Service Description
frontend app for displaying and interacting
imageorchestrator completes all requested manipulations
imageholder image upload and viewing
imagerotator image rotation
imagegrayscale changes image to grayscale
imageresize resizes up or down by multiples
imageflip horizontal and vertical flip options
imagethumbnail minimises images for quick display / preview
trafficgen configurable image uploader / manipulator

Observability tools

The following observability tools are used in this project.

Tool Description
Elastic APM apm / tracing for EFK
Elastic Curator elasticsearch cluster management
Elastic Heartbeat uptime monitoring
Elastic Kibana time series/logs visualizer
fluentd log collector/aggregator
Grafana time series visualizer
Google Cloud Logging Preview: Alternative zu EFK
index-lifecycle-managament log index lifecycle management
Jaeger tracing (in the docker-compose files)
Kiali service mesh UI
Loki log aggregation
Prometheus time series data base

Technical decisions

Log integration

We use fluentd as the log collector, Elasticsearch as the search engine and Kibana as the visualizer UI.

All containers write their logs to stdout, ideally formatted as json. The fluentd service is running as a daemonset and collecting, parsing and sending logs from all nodes to Elasticsearch.

Kibana displays logs from elasticsearch. We create index patterns "logs-" and "events-".

Monitoring integration

We use Prometheus as the metrics collector and Grafana for visualization.

Tracing integration

We use Jaeger and Elastic APM for tracing.