SLO Monitoring and Alerting with Prometheus and Sloth
This article was originally published on the Mattermost Engineering Blog.
The Challenge of Reliability
As Site Reliability Engineers, we face the constant challenge of balancing system reliability with feature delivery. At Mattermost, we tackled this challenge by implementing a comprehensive Service Level Objective (SLO) Framework.
Key Components of Our SLO Implementation
Tools We Used
- Sloth: For standardized SLO generation for Prometheus
- Prometheus: Metrics collection and storage
- Alertmanager: Alert routing and notification
- Thanos: Rule evaluation and long-term storage
- Grafana: Visualization and dashboarding
Implementation Strategy
We started with our most critical application - the Mattermost server, focusing on:
- Availability as our primary SLI
- Error rate monitoring
- Integration with our cloud provisioner
- Automated SLO creation for new workspaces
Measuring Success
Our initial focus was on availability through error rate monitoring:
Error Rate = Error Requests / Total Requests
Future Directions
Our SLO journey continues with plans to:
- Define more service-specific SLIs
- Implement cross-service and cross-cluster SLIs
- Expand the framework to internal services
- Foster a culture of shared responsibility
This post summarizes our detailed engineering blog post. For complete technical details, metrics queries, and implementation specifics, please visit the original article.
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