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* Causely Integration Tile * Update causely/README.md Co-authored-by: Esther Kim <esthercodes2019@gmail.com> * Update causely/README.md Co-authored-by: Esther Kim <esthercodes2019@gmail.com> * Update CHANGELOG.md --------- Co-authored-by: Esther Kim <esthercodes2019@gmail.com> Co-authored-by: James Eichelbaum <133711517+james-eichelbaum@users.noreply.github.com>
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# CHANGELOG - Causely | ||
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## 1.0.0 / 2024-08-07 | ||
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***Added***: | ||
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* Initial Release |
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# Causely - Assure Continuous Application Reliability using Causal AI | ||
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## Overview | ||
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The [Causal AI platform][1] automatically captures, represents and analyzes causality. It enables self-managed, resilient applications by bridging observability with automated orchestration. | ||
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Instead of flood of alerts, Causely tells you exactly what you need to know about all active and emerging application failures. With Causely, understand why a failure happened, what the root cause was, and how to fix it. | ||
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Use Causely to: | ||
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- **Assure continuous application reliability**: Guarantee that KPIs, SLAs, SLOs, and SLIs are consistently met to maintain application reliability and performance. | ||
- **Improve operational efficiency**: Reduce labor, data, and tooling costs by focusing on faster Mean Time to Repair (MTTR) and implementing efficient operational processes. | ||
- **Accelerate the delivery of features and innovations**: Enhance the speed and reliability of shipping new services and features to market, ensuring a competitive edge and meeting customer demands promptly. | ||
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Causely integrates with Datadog to provide automated root cause analysis for Datadog Watchdog events. Causely uses the Datadog API key to fetch the configured monitors and use the triggered Watchdog events as input to the Causal AI reasoning platform and identifies the root cause of the anomalies and alerts. Causely sends back the remediated root cause as events to Datadog which can be viewed in the Causely Datadog dashboard. | ||
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## Setup | ||
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Causely uses the [Datadog API key][2] to fetch the configured monitors and use the triggered Watchdog events as input to the Causal AI reasoning platform. Causely analyzes the events and identifies the root cause of the anomalies and alerts. To learn how to configure the Causely integration for Datadog, see the [Causely documentation][4]. | ||
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## Data Collected | ||
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### Events | ||
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Causely identified and remediated root causes display in your Causely dashboard. | ||
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## Support | ||
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Need help? Contact [Causely support](mailto:support@causely.io). | ||
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## Further reading | ||
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Additional helpful documentation, links, and articles: | ||
- [Request a demo][5] to experience automated root cause analysis with Causely first-hand | ||
- [Read the blog][6]: DevOps may have cheated death, but do we all need to work for the king of the underworld? | ||
- [Watch the video][7]: Causely for asynchronous communication | ||
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[1]: https://www.causely.io | ||
[2]: https://app.datadoghq.com/organization-settings/api-keys | ||
[3]: https://docs.datadoghq.com/monitors/ | ||
[4]: https://github.com/Causely/documentation/blob/main/install_agents.md | ||
[5]: https://www.causely.io/demo/ | ||
[6]: https://www.causely.io/blog/devops-may-have-cheated-death-but-do-we-all-need-to-work-for-the-king-of-the-underworld/ | ||
[7]: https://www.causely.io/video/causely-for-asynchronous-communication/ |
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{ | ||
"title": "Causely Overview", | ||
"description": "This dashboard shows a timeline of recent Causely remediation actions.", | ||
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} |
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{ | ||
"manifest_version": "2.0.0", | ||
"app_uuid": "0ac3b5eb-46d2-4091-a001-e95dc5782609", | ||
"app_id": "causely", | ||
"display_on_public_website": true, | ||
"tile": { | ||
"overview": "README.md#Overview", | ||
"configuration": "README.md#Setup", | ||
"support": "README.md#Support", | ||
"changelog": "CHANGELOG.md", | ||
"description": "Causal AI platform automatically captures, represents and analyzes causality.", | ||
"title": "Causely", | ||
"media": [ | ||
{ | ||
"media_type": "image", | ||
"caption": "Kubernetes Service Congested Causality", | ||
"image_url": "images/Service_Congested_Causality.png" | ||
}, | ||
{ | ||
"media_type": "image", | ||
"caption": "Application DB Connection Noisy Neighbor Causality", | ||
"image_url": "images/DB_Connections_Causality.png" | ||
}, | ||
{ | ||
"media_type": "image", | ||
"caption": "Causelhy Remediated Root Causes", | ||
"image_url": "images/Causely_Remediated_RootCauses.png" | ||
} | ||
], | ||
"classifier_tags": [ | ||
"Category::Containers", | ||
"Category::Kubernetes", | ||
"Category::Incidents", | ||
"Offering::Integration", | ||
"Queried Data Type::Metrics", | ||
"Queried Data Type::Events", | ||
"Submitted Data Type::Events", | ||
"Supported OS::Linux", | ||
"Supported OS::Windows", | ||
"Supported OS::macOS" | ||
] | ||
}, | ||
"assets": { | ||
"dashboards": { | ||
"causely": "assets/dashboards/causely_dashboard.json" | ||
}, | ||
"integration": { | ||
"auto_install": true, | ||
"source_type_name": "Causely", | ||
"source_type_id": 18684278, | ||
"configuration": {}, | ||
"events": { | ||
"creates_events": true | ||
}, | ||
"service_checks": { | ||
"metadata_path": "assets/service_checks.json" | ||
} | ||
} | ||
}, | ||
"author": { | ||
"name": "Causely", | ||
"homepage": "https://portal.causely.app", | ||
"sales_email": "early-access@causely.io", | ||
"support_email": "support@causely.io" | ||
} | ||
} |