tl;dr Enrich your Slack alerts with contextual observability data, helping on-call engineer investigate faster.
PlayBooks are executable notebooks designed to Automate Preliminary Investigations in Production for engineers. Watch demo video.
Using PlayBooks, a user can configure the steps as data queries or actions within their observability stack. Here are the integrations we currently support:
- Run bash commands on a remote server;
- Fetch logs from AWS Cloudwatch and Azure Log Analytics;
- Fetch metrics from any PromQL compatible db, AWS Cloudwatch, Datadog and New Relic;
- Query PostgreSQL, ClickHouse or any other JDBC compatible databases;
- Write a custom API call;
- Query events from EKS / GKE;
- Add an iFrame
- Define a playbook with your enrichment logic
- Configure the playbook to auto-trigger basis a Slack alert received in a channel
- Receive automated investigation summary in the Slack thread for the same alert
- The sandbox has a sample Playbook created. Check out how it works.
- You can also check out the #demo-alerts channel in community Slack workspace to see how automated replies are received for alerts.
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Enrichment library: The tool currently supports fetching 50+ types of enrichment data from metric sources (Datadog, New Relic, Grafana+Prometheus, Cloudwatch Metrics), Logs & Events (Cloudwatch Logs, EKS) and Databases (PostgreSQL DB, Clickhouse DB)
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Past Executions: See the historical runs of a playbook and go back to an investigation from a specific point in time.
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Continuous monitoring: Setup continuous monitoring cron for specific use-cases (e.g. post deployment, peak hours, post bug-fix). Read docs for list of allowed configurations.
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Interpretation Layer: Configure ML modules which can analyse & interpret data from your investigation playbooks.
- Templates: Common investigation & troubleshooting logics which can be used out of the box.
- Conditionals: Create decision trees in your playbooks basis evaluation of a playbook step.
- More integrations: Find something missing? Request here.
docker-compose -f deploy.docker-compose.yaml up -d
Access the portal at localhost (on port 80)
cd helm
helm install playbooks .
Run the following command to get the portal endpoint
kubectl get svc web -o custom-columns="EXTERNAL-IP:.status.loadBalancer.ingress[*].hostname"
OR
git clone git@github.com:DrDroidLab/PlayBooks.git
docker-compose -f playbooks.docker-compose.yaml up -d
Step 2: Follow this Step-by-Step guide to do your first alert enrichment.
Asks questions in the Slack Community or write to us at founders [at] drdroid [dot] io
Read our contribution guidelines
Read our roadmap here