Technology

Jenkins vs Codemagic: Why Mobile Teams Are Making the Switch

Mar 3, 2026 By Codemagic In Codemagic

If you’re a mobile developer running builds on Jenkins, you already know the drill: a flaky agent goes down on a Friday afternoon, your Xcode version is three months behind, and the DevOps engineer who set the whole thing up left six months ago. The builds ship eventually - but at what cost? Jenkins is a powerful, battle-tested automation server. For teams building web backends or managing complex polyglot pipelines, it earns its place.

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Simplified Kafka Cluster Migration: Strimzi to AWS Express Brokers with Lenses

Mar 3, 2026 By LensesIO In Lenses

Migrating Kafka clusters doesn't have to be a complex or high-risk operation. In this technical walkthrough, we demonstrate how Lenses K2K managed through Lenses 6 simplifies the migration of mission-critical banking applications from Strimzi to AWS Express Brokers with minimal downtime and zero data loss.

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The MCP Hub: Your Registry for All MCP Servers

Mar 3, 2026 By WSO2 In WSO2

Learn how to manage and scale your AI agents using the new MCP (Model Context Protocol) Gateway and MCP Hub in WSO2 API Manager 4.6.0. What’s covered: Whether you are using CrewAI, AutoGen, or LangChain, the WSO2 MCP Gateway allows secure connectivity to your MCP endpoints.

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Tricentis AI Workspace: The new control plane for autonomous quality engineering

Mar 3, 2026 By Luke Mahon In Tricentis

AI is reshaping how software gets built, tested, and delivered. For quality engineering teams, AI agents promise extraordinary acceleration by automating analysis, executing tests, generating assets, and orchestrating tasks across the SDLC. But when enterprises begin experimenting at scale, new challenges appear. Where are these agents running? What exactly are they doing? Who approves their decisions? How do we govern them safely?

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Queues for Apache Kafka Is Here: Your Guide to Getting Started in Confluent

Mar 3, 2026 By Jonathan Lacefield In Confluent

Queues for Kafka is now in General Availability (GA) on Confluent Cloud and is coming soon to Confluent Platform, coinciding with the Apache Kafka 4.2 release. This milestone brings production-ready queue semantics and elastic consumer scaling natively to Kafka through KIP-932, enabling organizations to consolidate their messaging infrastructures while gaining elastic consumer scaling and per-message processing controls. Get started.

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Agentic Payments: Redefining the Future of Payments for Enterprises

Mar 3, 2026 By Nikunj Patel In Zymr

‍ Enterprise payment systems are at a breaking point: rising volumes, tighter margins, and ever-more sophisticated fraud are pushing traditional automation to its limits. The AI-enabled payments market was valued at $38.36 billion in 2024 and is projected to grow over the next decade. As firms seek smarter, real-time decisioning and risk control, highlighting how indispensable AI has become in payment stacks today. -

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7 things engineering teams get wrong about AI-powered QA

Mar 3, 2026 By Fred Stevens-Smith In Rainforest

We’ve all been there. When engineering teams evaluate AI-powered QA tools, the same questions come up again and again. Some are rooted in genuine technical curiosity. Others stem from experiences with earlier-generation tools that earned a healthy dose of skepticism. After hundreds of these conversations, I’ve identified the seven most common misconceptions. Contents Toggle.

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How to Calculate Measurable Returns from AI Spend?

Mar 3, 2026 By Radhakanth Kodukula In Antino

AI isn’t just some side project anymore. These days, it’s a real budget line for big companies, something boards talk about all the time. Global investment in AI is about to break $300 billion a year. McKinsey says AI could add up to $4.4 trillion to the economy every year. That’s huge. But even with all this promise, a lot of businesses still have trouble figuring out if their AI projects are actually paying off. That’s the spot most CXOs are stuck in now.

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How ClearML Helps Optimize Resource Allocation Across AI Workloads

Mar 3, 2026 By ClearML In ClearML

Author: Adam Wolf Efficient resource allocation is a foundational requirement for scaling AI workloads, particularly as organizations move from isolated experiments to shared infrastructure supporting multiple teams, models, and environments. GPUs, CPUs, and high-performance storage are costly and finite, and without coordination, utilization often degrades as usage grows.

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Stop Cloud Complexity: Cloudera's Anywhere Cloud for Unified Data & AI

Mar 2, 2026 By Cloudera, Inc. In Cloudera

Today’s enterprises face immense pressure: scaling fast, staying compliant, and unlocking AI-driven insights—all while fighting siloed data and growing cloud complexity. There is a better way forward, and it starts with Cloudera Anywhere Cloud. Cloudera is the only data and AI platform that delivers the cloud experience anywhere—public clouds, data centers, and the edge—bringing unified security, governance, and control to data wherever it resides. Access 100% of your data for AI-driven insights and future-proof—not just modernize–your enterprise data strategy.

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