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The latest News and Information on DevOps, CI/CD, Automation and related technologies.

Streamline Software Delivery Right From Your IDE with Amazon Kiro and Harness

The integration of Amazon Kiro and Harness’s MCP server enables developers to manage, troubleshoot, and optimize CI/CD pipelines directly from their IDE using natural language, dramatically reducing manual effort and accelerating software delivery from code generation to production.

Harness Acquires Qwiet AI to Power Its Application Security for the AI Era

Harness acquires Qwiet AI to power application security in the AI era, embedding reachability analysis to cut noise and prioritize real risks. By Sanjay Nagaraj, SVP Global Engineering, Harness; Co-founder and CTO, Traceable by Harness Today, I am excited to share that Harness has acquired Qwiet AI (formerly ShiftLeft), a leader in agentic AI-powered vulnerability detection and reachability analysis.

Top 11 Java APM Tools: A Comprehensive Comparison

Are your Java applications running at their optimal performance, or is there room for improvement to make them faster and more efficient? With so many services depending on Java, keeping applications responsive and reliable is a core part of modern software engineering. This blog walks you through the leading Java Application Performance Monitoring (APM) tools, with a clear comparison to help you choose the right option for your needs.

The evolution of Integration technology through AI

Join us in this exciting podcast episode where integration pioneer Tom shares his 25+ year journey in tech, from message-oriented middleware in 1998 to leading AI projects at Microsoft. Tom dives into how AI is revolutionizing integration as the "backbone" of modern systems - think generative AI agents automating home damage inspections in minutes, reducing manufacturing downtime, and transforming financial trading.

{Unscripted} Autonomous Code Maintenance

Nothing drains developer productivity like codebase maintenance. The endless cycle of dependency upgrades, bug fixes, refactoring, and paying down technical debt is tedious, error-prone work that pulls engineers away from building new features. Harness Autonomous Code Maintenance (ACM) turns these manual chores into automated, intent-driven workflows. Developers can now state their intent in plain English, with prompts like, "Upgrade the front end from React 15.6 to 16.4". From there, the Harness AI agent drives the workflow.

{unscripted} AI for DevOps and DBDevOps

Many software engineers are experts in application code but not in the nuances of creating a production-ready delivery pipeline. Architect Mode acts as a seasoned DevOps expert, engaging the user in a conversation to design a pipeline that incorporates organizational best practices for security, quality, and compliance from the very beginning. It’s like having a personal DevOps architect as a partner.

{unscripted} IDP Knowledge Agent

We're making Internal Developer Platforms (IDPs) more accessible with a natural language assistant. Developers can ask questions like, "What are the failing checks for my service's scorecard?" or "Who is the owner of a service?" to find metadata instantly. The agent also bridges the gap to action by suggesting and executing self-service workflows, like creating a new repo or onboarding a new engineer. It can even assist in generating new workflows, turning complex processes into simple conversational tasks.

{unscripted} AI Verification and Rollback

Our first AI/ML capability, Continuous Verification, made Harness the first Continuous Delivery tool to understand observability telemetry and trigger rollbacks when deployments caused trouble. We knew we could do more to eliminate the friction involved in its setup. Deploying with confidence shouldn't require a coordination meeting between DevOps, SREs, and developers just to configure the right health checks. That’s why we’re introducing the next generation: AI Verification and Rollback.

{unscripted} AI in Chaos Engineering

Harness AI enhances your chaos engineering capabilities by leveraging artificial intelligence to automate and optimize reliability testing and analysis. One of the challenges of scaling up the Chaos Engineering practice within the organization is skilling up the users to create or run chaos experiments and to come up with solutions to mitigate the risks that are identified during the chaos experiment execution. The Chaos Engineering module comes with an AI Agent called "AI Reliability Agent" that helps in these aspects.