How to Use Observability Tools to Set SLOs for Kubernetes Applications

This blog post explores how to use observability tools to set and maintain Service Level Objectives (SLOs) for Kubernetes applications. Understanding the difference between SLOs, SLIs, and SLAs is crucial. The best observability tools for Kubernetes include Prometheus, Grafana, and Jaeger. These tools help you collect metrics, visualize data, and trace requests to set SLOs and troubleshoot performance issues. The key steps to using observability tools effectively involve observing your service's behavior, setting thresholds and error budgets for SLOs, and updating SLOs as your system evolves. By following these steps, you can ensure your Kubernetes applications meet performance and availability targets.

When you deploy a service to your Kubernetes cluster, how can you be sure it’s working as expected? This blog post explores how to use observability tools to set up Service Level Objectives (SLOs) to ensure your Kubernetes applications meet performance and availability targets.

Understanding SLA, SLO and SLI

Effective DevOps and SRE teams rely on Service Level Objectives (SLOs) to maintain the health of their services. An SLO is a measurable target based on Service Level Indicators (SLIs), which are quantifiable metrics that reflect a service’s essential elements. For instance, a common SLI for an endpoint might be its error rate per second.

Service Level Agreements (SLAs) differ from SLOs in that they are guarantees made to service users. SLAs include consequences for missing SLOs, such as credits for cloud provider outages. While SLOs are internal targets and can be adjusted, SLAs are more rigid and visible to external users.

Choosing the Best Observability Tools

Several options exist for observability tools within the Kubernetes ecosystem. Here, we’ll explore some of the most popular choices:

Prometheus: A widely used metrics collection and IT alerting tool, Prometheus is a core component of many Kubernetes monitoring setups. It allows you to define rules that collect data from targets corresponding to your SLIs at regular intervals.

Grafana: A visualization tool that integrates seamlessly with Prometheus, Grafana excels at creating informative dashboards. These dashboards display metrics and graphs, allowing you to monitor your SLOs and SLIs for trends and anomalies.

Jaeger: A distributed tracing platform that adheres to the OpenTracing API, Jaeger is valuable for understanding how requests travel through your system and how long each component takes to respond. This information is crucial for setting SLOs, troubleshooting performance issues, and identifying the root cause of incidents.

Using Observability Tools Effectively

The following steps outline how to leverage observability tools to set and maintain SLOs for your Kubernetes applications:

Observe Your Service: Before defining SLOs, establish a baseline by observing your service’s behavior under load. You can do this in a staging environment, but real-world usage often reveals unforeseen patterns. Aim to observe your service SLIs over a period of several days.
Choose Thresholds and Ranges: Once you have a baseline understanding of your service’s behavior, select appropriate thresholds and ranges for your SLIs. For example, if you observe an error rate between 0.1% and 0.3%, you might set an SLO of 0.5%, accounting for some volatility.
Set Error Budgets: No service is perfect, and SLO violations will occur occasionally due to bugs, misconfigurations, or dependency issues. Rather than treating every violation as an immediate crisis, implement error budgets. An error budget defines the acceptable error rate; for instance, 0.01% might allow one out of every 10,000 requests to violate the SLO without requiring corrective action. Regularly review error rates against your budget. If errors exceed the budget, developers should focus on reducing them before resuming new feature development.
Update SLOs as Needed: SLOs are not static. As your system matures and dependencies change, revisit your SLOs to ensure they remain appropriate. Consult with stakeholders to confirm your SLOs aren’t overly strict. If a service can tolerate more lenient limits, you might loosen SLOs or enlarge error budgets to save resources.

Conclusion

SLOs are fundamental for Kubernetes operations. By using observability tools like Prometheus, Grafana, and Jaeger, you can establish SLOs based on relevant SLIs, monitor your service’s health, and ensure it meets user expectations. Remember, effective observability is key to maintaining a reliable and efficient Kubernetes environment.

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Squadcast is a cloud-based software designed around Site Reliability Engineering (SRE) practices with best-of-breed Incident Management & On-call Scheduling capabilities.