SLOs and Error Budgeting
Dynamically create, measure, and iterate SLOs, such as latency SLOs, with flexibility and accuracy, so you can confidently ensure performance requirements are met and that you’re optimally balancing risk and innovation.
Wrong SLOs — and the error budgets they inform — can cost millions of dollars and waste significant resources. At Circonus, we use OpenHistogram for computing SLOs because it ensures the greatest accuracy and flexibility. Histograms are a data structure for representing large quantities of samples (such as the latencies of all API requests). OpenHistogram is a vendor-neutral log-linear histogram technology that allows you to efficiently store an unlimited volume of high frequency data for years at low cost.
“We use Circonus’ histograms extensively to surface issues before users notice them. We also have alerting set up such that if we start to burn error budget in latency for a particular service too quickly, we alert the team. The histograms enable us to identify these issues and make adjustments right away.”
Create & Measure SLOs with Accuracy
- Avoid high error rates associated with averaging precalculated percentiles. OpenHistogram stores the complete distribution of data rather than storing a handful of quantiles. This ensures the most accuracy when analyzing your SLOs to measure latencies and compliance with KPIs.
- Gain new insights into your SLOs with inverse percentiles.
- OpenHisotgram’s approach to binning guarantees worst-case errors are below 5%, significantly better than the hundreds of percent seen by poor binning approaches.
Dynamically create SLOs and error-budgets by calculating percentiles on the fly
- Dynamically calculate percentiles on the fly, after metric ingestion, so you can redefine SLOs as needed at any time.
- Enable various teams to set their own SLOs rather than be forced to share the same pre-calculated aggregations that only a subset of the team can use.
- Optimize your error budgets. Keep testing and measuring your SLOs by leveraging highly granular historical data, so you can identify your minimum thresholds and set SLOs that let you take more risks.
Inform your latency SLOs with powerful visualizations and analytics
- Surface issues before users notice them. Alert on real-time SLO compliance issues, or if you are burning through your error budgets too quickly.
- Add histograms together for quick analysis of historical latency data. Identify changes in service performance, or compare latencies from one software release to another.
- Visualize real-time latency data to assess probability distributions, find disruptions and concentrations, discover extreme system loads or drop-offs, and more.
- Leverage the Circonus Analytics Query Language (CAQL) to create customized and powerful queries against metric data stored as OpenHistogram. Use CAQL to power Circonus or Grafana-based dashboards.
“Using Circonus’ histograms, it’s a huge benefit to be able to go back and sort of redraw the graph at the appropriate SLA to prove to our partners what our delivery time is. We’re able to do this because we are recording the latency of every operation at all times.”
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