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From Zero to Open Source Contributor

Never contributed to open source and feeling intimidated? Same. Before joining Datadog, Alessandro had zero open source experience. Now he's a regular contributor to Apache Iceberg. Here's exactly how he got started. Step 1: Join the Slack community and answer user questions. Step 2: Look for "good first issue" tags in the repo. Step 3: Remember that opening bug reports and doing code reviews count as contributions too.

Building a Code Review system that uses prod data to predict bugs

This post takes a closer look at how Sentry’s AI Code Review actually works. As part of Seer, Sentry’s AI debugger, it uses Sentry context to accurately predict bugs. It runs automatically or on-demand, pointing out issues and suggesting fixes before you ship. We know AI tools can be noisy, so this system focuses on finding real bugs in your actual changes—not spamming you with false positives and unhelpful style tips.

Elastic at AWS re:Invent: Concluding a year of partnership in agentic AI innovation

Highlights of another laudable year of customer-centric collaboration The integration of Elastic’s capabilities, including vector databases and context engineering, with AWS services helps customers build intelligent, scalable, and secure applications faster and with greater flexibility. Our ongoing collaboration has resulted in another year of notable innovation with AWS. This blog highlights our continued collaboration with AWS throughout 2025 to help you capitalize on the power of AI.

Rovo Dev Auto Closing Vulnerabilities | Bitbucket Blitz | Atlassian

Learn how Atlassian uses Rovo Dev to automatically find and fix code vulnerabilities with Rovo Dev and Bitbucket. This capability saves our developers thousands of hours over three months and reduces issue resolution time by half, allowing them to focus on building software and solving problems for our customers. This technology is available to all of our customers. Learn how it works, and start using it yourself.

The Observability Stack is Collapsing: Why Context-First Data is the Only Path to AI-Powered Root Cause Analysis

By Bill Balnave, VP of Customer Success at Mezmo The core promise of modern observability is simple: cut Mean Time To Resolution (MTTR). Yet, despite a boom in tooling and investment over the last four years, the data tells a sobering story: our industry is actually getting worse at finding and resolving issues. Dashboards, once our trusted guide, have become the starting point for a chaotic "dashboard hunt" that rarely leads to the definitive root cause.

Get Kafka-Nated, Bonus Episode: A tale of Kafka Past, Current, and Future

Join us for “A Kristmas Kafka,” an informal technical roundtable with Apache Kafka committers, contributors, and community leaders. We’re gathering the people who build and shape Kafka to explore where the project has been, where it is today, and where it’s heading next. No marketing, no product pitches—just a dense, technical conversation about architecture, innovation, and the future of streaming systems.