Operations | Monitoring | ITSM | DevOps | Cloud

The AI Velocity Paradox

AI-powered coding alone isn’t enough. True software delivery velocity requires end-to-end automation and intelligent governance across the entire lifecycle. Harness enables organizations to escape the AI Velocity Paradox by unifying speed, safety, and resilience, turning rapid development into a sustainable competitive advantage. The widespread adoption of AI coding assistants is transforming software engineering.

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.

{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.

AI-Powered Chaos Engineering with Harness MCP Server and Cursor

The Harness MCP Server integration with Cursor transforms chaos engineering from a complex, specialized discipline into an accessible, conversational workflow that any developer can leverage directly within their AI-powered IDE. By combining natural language prompts with comprehensive resilience testing tools, teams can discover, execute, and analyze chaos experiments without vendor-specific expertise, democratizing system reliability across DevOps, QA, and SRE functions.

Harness GitOps: Scaling Argo CD with Enterprise-Grade Control

Harness GitOps extends Argo CD by preserving its reconciliation loop while adding governance, audit, and RBAC through the GitOps Agent’s secure connection to Harness SaaS. Teams can choose Harness-managed or bring-your-own Argo CD and scale to multi-cluster fleets with unified dashboards, promotion pipelines, and true rollback, while Git stays the single source of truth.

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 Named a Leader in the 2025 Gartner Magic Quadrant for DevOps Platforms For the Second Consecutive Year

Harness has been recognized as a Leader in the 2025 Gartner Magic Quadrant for DevOps Platforms for the second consecutive year. To us, this recognition acknowledges our solutions and capabilities that we offer. . Harness continues to support the full software delivery lifecycle and remains focused on expanding capabilities and improving adoption across industries.

{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. We’ve moved beyond just AI-powered analysis to AI-powered setup.

Measuring the Impact of AI Development Tools

You're adopting AI code generation tools to enhance your engineering team's output, but how do you quantify the real return on investment? Without precise measurement, you're navigating in the dark, unable to identify true productivity gains or pinpoint areas for optimization. Justifying these critical AI investments becomes difficult.