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DevMate: Accelerating React Native Development at Atlassian
DevMate is Atlassian’s in-house CLI tool that slashes React Native build times and automates environment setup—making development faster, smoother, and more consistent for our teams.
1 Billion Build Minutes Later: How we reinvented CI/CD at Atlassian
From pipeline chaos to 1K+ builds per day
Improving Coding Agent Experience
Atlassian is enhancing coding agents by using machine learning to identify well-scoped Jira work items and provide relevant code context, making AI-powered development faster, smarter, and more reliable for software teams.
Comment ranker – An ML-based classifier to improve LLM code review quality using Atlassian’s proprietary data
Atlassian’s ML-based comment ranker filters LLM code review comments, boosting quality and efficiency with proprietary data.
Atlassian’s AI Gateway: Best in Class Model Garden
LLMs represent a rapidly advancing area of technology, with various foundation model providers competing to build the leading solution. Like any technology, the differing models often have a spectrum of their own strengths and weaknesses. Atlassian currently partners with an array of leading proprietary model providers and open-source technologies, incorporating models from OpenAI, Anthropic, Google, […]
Unraveling Rovo search relevance
Discover how Rovo search delivers fast, relevant results across Atlassian and 50+ SaaS applications. This blog unpacks the technology behind Rovo’s search relevance, smart answers, and personalization, revealing how advanced ranking, AI, and user signals power seamless knowledge discovery for modern teams.
The AI Technologies Behind Speech Editing at Loom
Speech editing at Loom lets users update parts of their video instantly, without re-recording. Powered by advanced AI, this technology enables seamless, high-quality edits—like swapping names or company details in your own voice—making video creation faster, more flexible, and highly personalized.
How Atlassian continuously improves Rovo Search quality
Exploring the latest updates and inner workings of Atlassian’s AI-powered enterprise search solution.
Atlassian’s Inference Engine, our self-hosted AI inference service
Powering Enterprise-scale AI As Atlassian’s AI capabilities continue to scale rapidly across multiple products, a pressing challenge emerged: how do we deliver world-class AI-powered solutions to millions of users without compromising on latency, flexibility, and operational control? The answer: Atlassian’s Inference Engine, our custom-built, self-hosted AI inference platform that now powers production LLMs, search models, […]
Atlassian research: AI adoption is rising, but friction persists
Atlassian’s 2025 State of DevEx Survey reveals a paradox: AI is saving developers time, but they’re still losing time to organizational inefficiencies
Migrating the Jira Database Platform to AWS Aurora
Discover how Atlassian migrated four million Jira databases to AWS Aurora—at scale and with minimal user impact. Learn about the technical challenges, strategies, and outcomes that enabled this ambitious transformation in reliability, performance, and cost efficiency
How We Achieved 75% Faster Builds by Removing Barrel Files
Removing JavaScript barrel files from our Jira frontend codebase led to a 75% reduction in build times, with significantly faster TypeScript highlighting and unit testing. This large-scale automated change also improved CI efficiency and made code navigation much clearer for developers.
Enhancing resiliency in opensearch clusters: An in-depth technical exploration of Admission Control
Admission control in OpenSearch helps keep clusters stable by limiting incoming requests when nodes are under heavy load. Atlassian saw improved search reliability after enabling this feature, especially during traffic spikes.
Producing Software Bill of Materials a.k.a SBOMs for Atlassian
Atlassian’s SBOM platform generates detailed software inventories for compliance and security, using tools like Syft and cdxgen.