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Per-Tenant Performance Regression Detection

1 post · Feb 2026

What this trail covers

Atlassian is enhancing its performance monitoring capabilities with a new system for detecting and mitigating performance regressions at the per-tenant, per-endpoint level. This system aims to catch issues that are often missed by aggregated metrics, especially in complex, multi-tenant products like Jira Cloud. It leverages detailed metrics, statistical process control, and AI-powered root cause analysis to quickly identify and resolve performance degradations, ensuring a better experience for all users. The system has been integrated with Rovo Dev CLI for automated root cause analysis, successfully identifying and mitigating multiple production regressions by correlating performance metrics with feature flag evaluations and source code changes.

All Atlassian trails
  1. How we catch and mitigate performance regressions at scale in Jira CloudThis post details the implementation of a per-tenant, per-endpoint performance regression detection system for Jira Cloud. It explains the challenges of performance variation across tenants and the limitations of aggregated monitoring. The system uses statistical process control (SPC) to detect regressions by comparing current performance to historical baselines for each tenant and endpoint. It integrates with Rovo Dev CLI to automate root cause analysis by correlating performance data with feature flag evaluations and source code changes, as demonstrated by a real-world regression involving synchronous network calls to the Tenant Context Service.