Systems | Development | Analytics | API | Testing

Announcing Codemagic Patch: an open-source CodePush rebuild for React Native

Having maintained a CodePush fork for 18 months and served billions of updates, we decided it was time for an overhaul. We’re big fans of CodePush, and it was a great benefit to the React Native community. But, it was written in 2015 and had some weaknesses. The biggest of these was architectural, with limitations in how update checks and release metadata could scale. The result, Codemagic Patch, is now public and available to self-host.

Introducing the Skills Marketplace: AI analyses on your data, with expert judgment built in

Every team we talk to has a running list of questions they wish they could get fast, reliable answers to. What changed in our performance last month and why. Which clients are showing the early signs of churn. Which channels are actually pulling weight and which ones are quietly burning budget. The pull toward AI for this kind of work is obvious. The answers should be a question away.

Tideways 2026.2 Release

Understanding complex request traces is one of the hardest parts of performance analysis. In this Release, we focused on making this significantly easier in Tideways. The Timeline has been redesigned to provide a clearer view of how requests are executed, with new layout modes, improved navigation, and a more consistent span model. These changes help you follow execution order, understand dependencies, and identify performance bottlenecks faster, even in complex applications.

Apache Kafka 4.3.0 Release Announcement

We are proud to announce the release of Apache Kafka 4.3. This release contains many new features and improvements. This blog post will highlight some of the more prominent ones. For a full list of changes, be sure to check the release notes. With 25 KIPs and over 600 commits since 4.2.0, this release introduces many new features, improvements and bug fixes to all the components. See the Upgrading to 4.3 section in the documentation for the list of notable changes and detailed upgrade steps.

Integrate.io Delivers Cloud-Native SharePoint Integration: Write Directly to SharePoint from Your Data Pipeline | March 2026

We're excited to announce a new cloud-native capability that deepens Integrate.io's integration with the Microsoft 365 ecosystem. SharePoint is now available as a write destination in the package designer. This release enables data teams to push transformed, pipeline-processed data directly into SharePoint Online libraries and lists through a fully cloud-native, API-first connection.

ClearML Enterprise v3.29: Fine-grained Control for Enterprise AI Teams

ClearML Enterprise v3.29 builds on the governance and infrastructure foundations introduced in recent releases. This update focuses on giving administrators and AI teams more granular control over resource allocation, gateway access, and pipeline management while delivering a meaningful set of UI quality improvements across the platform.

DreamFactory 7.5.0 Release: GitHub-Connected AI Agents, a Platform-Wide Security Hardening Pass, and a Smoother MCP Authoring Experience

DreamFactory 7.5.0 is focused on two audiences that have been growing fastest in our user base: teams wiring LLM agents to production databases through MCP, and security and platform teams hardening those deployments for real-world traffic.

Introducing Katalon True Platform: AI Agents for the Full Testing Lifecycle

Software testing has a fragmentation problem. Most teams run test generation in one tool, execution in another, defect tracking in a third, and pull together release decisions from whatever they can stitch together at the last minute. Every handoff between tools is a gap where context gets lost, work gets duplicated, and quality suffers. Katalon True Platform closes those gaps.

Govern the Full AI Data Path with Kong AI Gateway 3.14

The shift from single-model AI features to multi-agent pipelines is no longer a future concern — it's running in production today. MCP has become the de facto protocol for tool-calling, agent-to-agent (A2A) communication patterns are proliferating, and enterprise teams are wiring together complex AI workflows that span multiple providers, services, and agents. Every hop in that data path is an opportunity for something to go wrong. The challenge is governance.