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By Mridhula Venkat
Discover 8 critical questions engineering leaders must ask to measure and improve developer productivity. Learn how to assess team velocity, identify bottlenecks, and leverage DORA metrics for data-driven decisions that enhance engineering performance and developer experience. Why does developer productivity feel like it's declining even as your team grows? You hire more engineers, yet features ship slower. Sprint velocity looks healthy on paper, but deployment frequency tells a different story.
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By Kelsey Rosen
Cloud cost optimization often fails not because the tools are broken, but because organizations use outdated approaches. This article explores why traditional cost optimization strategies fall short and reveals how modern FinOps practices and governance frameworks drive sustainable cloud savings. Your cloud cost optimization strategy just flagged a $47,000 anomaly in last month's Kubernetes spend. Finance wants answers. Engineering claims everything is running normally.
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By Mrinalini Sugosh
This comprehensive guide walks you through installing Terraform with a focus on security hardening and scalable infrastructure automation. You'll learn installation steps across platforms, configuration best practices, and how to set up Terraform for production-ready IaC deployments that grow with your organization's needs.
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By Kelsey Rosen
Engineers often ignore cloud costs due to lack of visibility, misaligned incentives, and disconnected workflows. This guide explores the root causes and provides actionable strategies to embed cost awareness into engineering culture, including automation, real-time feedback, and FinOps best practices that make cost optimization a natural part of the development process.
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By Aaron Newcomb
Engineering teams often deploy code much faster than they can safely release new features to users. This gap can create risks if releases skip testing, approvals, or gradual rollouts. Feature flags help by separating deployment from release, so you can ship code continuously and control which features users see through configuration.
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By Lena Sano
Incorporating robust security measures into feature flag management is critical to protecting sensitive data and maintaining compliance. Harness FME security features, like remote evaluations in Thin SDKs and governed AI flag cleanup, let you practice security by design and standardize solid security practices across your teams.
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By Eric Minick
A DevOps toolchain that scales is the smallest unified stack with central governance and golden paths, not the longest list. 71% of teams say context-switching drains productivity; 73% of leaders report barely any teams have golden paths (Harness). AI coding speed stresses the after-code stages where DevOps toolchain sprawl creates the biggest governance gaps. Unified platforms keep governance, verification, and rollback consistent as AI raises code volume entering the pipeline.
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By Rashmi Hegde
Here is a story platform engineering teams know by heart: developers find a shiny new tool, start building at a breakneck pace, and before you know it, the organization is drowning in a massive wave of unmanaged components. Right now, that exact story is playing out with generative AI.
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By Akshit Madan
Teams building agents have converged on something that looks a lot like the software development lifecycle, but reshaped around a system whose output isn't deterministic: prototype an agent against a framework, evaluate it against a dataset of expected behavior, deploy it somewhere real, observe how it behaves against live traffic, and feed what you learn back into the next prototype. Call it the agent development lifecycle (Agent DLC).
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By Sunil Gattupalle
AI agents fail differently from the software we spent the last two decades learning to monitor. We hear some version of the same story from teams shipping agents to production: an agent starts producing wrong answers. Not obviously broken: confident, well-formatted, plausible wrong. The logs are clean, latency looks healthy, and error rates sit at zero. Nothing flags a problem. A user eventually does.
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By Harness
AI agent quality should not depend on manual checks. But for many teams shipping AI in production, agent failures are silent. The agent doesn't crash - it just gives confidently wrong answers, and your monitoring sees nothing wrong. Without automated guardrails, plausible-sounding wrong responses, hallucinations, and quality regressions reach customers before anyone notices.
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By Harness
In this video, we explore two major improvements to the Harness Resilience Testing documentation designed to help you build and manage chaos experiments more efficiently. What's new: ChaosHub Integration AI Prompt Library for Harness MCP These updates make it significantly easier to discover chaos experiments and leverage AI throughout your chaos engineering workflow. If you're using Harness Resilience Testing, this walkthrough will help you get started quickly and make the most of the new documentation experience.
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By Harness
Harness Agent DLC: Ship AI Agents to Production Safely Building an AI agent is easy. Getting one into production safely is where teams get stuck. Harness Agent DLC extends the software delivery lifecycle to AI agents, giving teams a clear path to evaluate, deploy, secure, observe, and optimize agents in production. Learn more: Because agents dynamically choose their own tools, APIs, and actions, their behavior can change every time they run. Harness Agent DLC gives engineering teams the controls needed to move beyond experiments and operate agents safely at scale.
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By Harness
Microsoft patched 570 security vulnerabilities this Patch Tuesday — but every patch is also a public disclosure. The second those fixes drop, attackers know exactly where 570 weaknesses live. The only question that matters: can you find and patch them across your entire environment before someone exploits them? The speed of discovery is only increasing. Are you ready for the velocity of this new world? Let us know in the comments.
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By Harness
While AI coding assistants help developers write code faster than ever, the traditional manual workflows for delivery, security, governance, and production readiness often create a bottleneck. In this demo, see how Cursor and Harness bridge this gap by turning AI-generated code into a safe, governed, and production-ready software delivery lifecycle right from your IDE.
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By Harness
You're already using AI without even thinking about it. That's the realization that kicks off this ShipTalk moment: Apple Maps quietly using on-device machine learning to learn your routes and driving habits — complete trust, zero thought. Which raises the real question: why aren't we there yet with AI in software delivery? The answer comes down to one word: guardrails. Consumer AI earned invisible trust. Shipping software hasn't — not until the guardrails catch up.
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By Harness
In this Harness University Tidbit, learn how to use a custom plugin step in a CD stage. You'll walk through using a plugin to update a task on a self-hosted ITSM service inside your private Kubernetes cluster.
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By Harness
The U.S. just barred foreign nationals from accessing two advanced AI models — Fable and Mythos — citing national security. Around the same time, the Five Eyes intelligence alliance warned that AI-enabled cyberattacks are "months, not years" away. In Season 5 of ShipTalk, host Adam and co-host Martin dig into whether that warning is already overdue — and what it means for the people actually defending software.
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By Harness
Today, we're launching Autonomous Worker Agents, AI agents that run as governed pipeline steps inside Harness. They inherit OPA policies, RBAC, audit trails, and scoped credentials from the first run. And because they live inside your Harness pipelines, they reason using the Harness Knowledge Graph: your services, deployments, incidents, and policies.
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By Harness
Engineering teams are burning through AI budgets with nothing to show for it — $100M across 10,000 engineers and no cost per run, no cost per outcome, just a number that keeps climbing. When it runs dry, your infrastructure upgrade gets cut. Harness ties every AI token to the outcome it created: cost per run, cost per resolved ticket, and anomaly detection before the invoice hits. One customer went from a $28,000 black box bill to $0.60 per ticket.
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By Harness
AI for Development Isn't New. AI for Delivery Is! AI coding assistants have transformed how teams create software. But innovation only delivers business value when code moves quickly and safely from commit to production and into customers' hands. In AI-Native Software Delivery, Harness Field CTO Nick Durkin and DevOps veterans Eric Minick and Chinmay Gaikwad present a practical guide to applying AI across the entire software delivery lifecycle.
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By Harness
Organizations everywhere are racing to modernize DevOps and elevate the developer experience, but how close are they to actually delivering?We surveyed over 650 engineering leaders to find out. The result is The State of Software Engineering Excellence 2025, a report that uncovers the hidden challenges, gaps, and opportunities shaping today's software teams.
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By Harness
This comprehensive whitepaper shows you how modern software delivery platforms solve these challenges.
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By Harness
Modern systems are more complex-and more fragile-than ever before. Whether it's scaling challenges, dependency failures, or unpredictable outages, reliability is no longer optional. It's a competitive edge. This eBook provides a practical blueprint for successfully adopting Chaos Engineering, with strategies proven to work across engineering, SRE, and QA teams. Learn how to overcome internal blockers, align ownership, and embed resilience testing directly into your software delivery lifecycle.
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By Harness
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.
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Harness delivers intelligent AI automation, so your team ships code faster, safer, and smarter.
Don't let your pipeline become the bottleneck as developers and AI coding agents generate more code. Harness AI intelligently automates, safeguards, and accelerates software delivery at any scale.
- AI for DevOps & Automation: Unleash developer productivity with AI that understands your DevOps ecosystem. Harness combines the industry's fastest, most secure CI/CD with developer self-service to automate pipelines, infrastructure, and the entire path from code to production.
- AI for Testing & Resilience: Release software confidently using AI-powered predictive analytics and testing. Make every change fast, safe, and resilient, so your teams can focus on shipping quality code instead of chasing bugs and triaging outages.
- AI for Security & Compliance: Make secure software your new default. From application and API discovery to AI-powered threat prevention, Harness uses contextual insights and agentic workflows to detect and mitigate risks from build to post-deployment.
AI for Everything After Code.