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Jira Configuration Optimization Tools

2 posts · Jul 2025 – May 2026

What this trail covers

Jira Cloud is introducing optimization tools to combat configuration bloat. These tools help customers understand, identify, and remediate unused or redundant configuration entities like custom fields, work types, screens, and workflows. The system includes reporting, bulk remediation with safety mechanisms, and audit logs. It leverages a pre-computation framework for asynchronous scanning and a tiered state management system for storing usage data. The goal is to improve Jira performance at sca

All Atlassian trails
  1. Optimisation Tools for Jira: Reducing Configuration Bloat and Enhancing PerformanceThis post details the design and implementation of Jira's optimization tools for configuration entities like fields and work types. It covers the high-level overview, architecture (reporting and remediation phases), pre-computation framework for asynchronous scanning, tiered state management for storing usage data (Memcache & Polymorphic Persistence), and recoverability mechanisms. The post highlights the smart, prioritized refresh strategy for usage data and the impact of these tools on configuration health, performance, and admin experience.
  2. Building an enterprise-grade Jira bulk operations Forge appThis post details the development of a Forge app to address limitations in Jira Cloud's native bulk move and bulk edit capabilities. The app provides an extensible solution for customers to tailor bulk operations, preventing accidental changes that violate custom workflows and governance rules. Key technical aspects include a single-page UI with state management, acting as a proxy for Jira API requests with in-memory caching for large datasets, performance optimizations like debouncing and lazy loading, and the use of Atlassian Design System tokens. Backend logic is minimal, invoked via Forge functions for sensitive operations like temporary privilege elevation. The app uses basic authorization for certain backend operations due to limitations with the Forge Jira authentication API, requiring credentials to be stored in environment variables and egress permissions to be restricted. The extensibility is achieved through colocated functions and customer-configurable settings, though a code-based API approach requires manual re-integration on app updates. Handling large-scale data involves client-side caching, debounced input, and retry handling for eventual consistency issues.