Operations | Monitoring | ITSM | DevOps | Cloud

Recent industry research shows that AI is accelerating code creation, but having mixed results downstream. They also show that better platforms and pipelines yield better outcomes for teams adopting AI for coding. Every engineering leader I talk to is asking the same questions about AI coding assistants: How much faster can we ship? How much more productive can my developers be? On the surface, the answers look pretty good.

As enterprises scale, Infrastructure as Code (IaC) alone isn’t enough to manage the growing complexity of modern infrastructure. Infrastructure as Code Management (IaCM) elevates IaC into a strategic, governed, and automated framework, providing centralized control, compliance, and collaboration at scale. Platforms like Harness IaCM make this transformation practical, turning infrastructure chaos into consistent, secure, and efficient operations.

This technical deep-dive reveals how Harness engineers discovered and fixed a critical Go memory leak where reassigning context variables in worker loops created invisible chains that prevented garbage collection across thousands of goroutines, ultimately consuming gigabytes of memory in their CI/CD delegate service.

Most cloud waste isn’t technical, it’s organizational. Harness brings finance and engineering together with FinOps practices that connect spend to outcomes, not blame. The result: 30%+ savings and alignment that scales. In too many cloud organizations, finance and engineering operate like two planets in orbit. Finance speaks in forecasts, budgets, billing codes. Engineering speaks in uptime, latency, error rates. The result?

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.

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 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.

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 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.

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.