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By Chinmay Gaikwad
Continuous integration (CI) costs can escalate quickly as engineering teams scale. While most organizations focus on cloud bills, the true cost of CI includes slow build times, developer wait time, inefficient test execution, and overprovisioned infrastructure. CI cost optimization is the practice of reducing the total cost of CI pipelines by improving build efficiency, minimizing compute usage, and eliminating unnecessary work without slowing down development.
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By Shibam Dhar
Three weeks into a platform modernization project, this question landed in my inbox: "Why does our deployment pipeline take 40 minutes instead of four?" This is artifact repository sprawl in practice, and it does more than slow pipelines. It fragments your security posture, your compliance evidence, and your ability to answer basic questions like "what's actually running in production right now?".
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By Roshan Piyush
Shai-Hulud is back - this time being lighter, faster and more automated than before. This new wave, termed as Mini Shai-Hulud, has affected a number of packages from tanstack, uipath, opensearch-project and mistralai among others over the past few weeks, with the latest series of major compromises coming on 19th May, 2026 on major organizations openclaw-cn and antv. Check an extensive list of affected packages here.
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By Dewan Ahmed
Engineers have been shipping pieces of "the graph" for years. Service maps. Dependency graphs. Knowledge graphs. RDF triples. The newest entrant is the context graph, and the reason it shows up now is specific: software is increasingly executed by agents, and agents need a model of how work actually happens, not just an index of what exists.
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By Dewan Ahmed
When you're architecting an enterprise Java application, one decision quietly shapes everything downstream: runtime footprint, deployment pipelines, and how your platform team handles incidents at 3 a.m. For two decades, that decision was framed as Java SE vs Java EE. In 2026, that framing has quietly inverted.
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By Dewan Ahmed
The thing with Change Advisory Boards is that the intent was always good. Get smart people in a room, look at the evidence, and make sure nothing catastrophic goes out the door. In theory, that's hard to argue with. It doesn't scale in practice. Things happen between meetings. Teams rush to hit the window. The CAB meeting may not catch every risky deployment, but at least everyone can feel good about the process before the incident happens. Automated release management asks a different question entirely.
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By Trevor Stuart
For the past year, I've been hearing a version of the same thing from engineering leaders: AI tools are working, productivity is up, the business case is there. And yet, something about the picture still feels incomplete. So we decided to go find out how widespread that feeling actually is. We surveyed 700 engineers and managers across five countries, and published the results in the State of Engineering Excellence 2026.
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By Pritesh Kiri
Effective disaster recovery testing follows a clear three-phase lifecycle: plan, execute, and review. Most DR programs fail not because of missing tools, but because of untested runbooks and unclear ownership. Platforms like Harness Resilience Testing bring chaos, load, and DR testing into one pipeline so teams can catch risks before they become incidents. Most organizations don't fail at disaster recovery because they lack technology.
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By Vishal Vishwaroop
The first quarter of 2026 introduces AI-powered continuous verification that eliminates configuration overhead, expanded deployment platform support including Azure Container Apps and enhanced Windows capabilities, and GitOps workflow improvements that align with how teams actually ship software.
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By Vishal Vishwaroop
Enterprise releases spanning multiple services, teams, and environments demand more than spreadsheets and manual coordination. Harness Release Orchestration provides a unified framework for modeling, automating, and tracking complex releases with complete visibility from planning through production deployment.
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By Harness
See how to configure Harness so that OPA policies are evaluated in your infrastructure.
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By Harness
This example hows how to use Harness CI/CD to build a Cobol application and deploy it to a mainframe running z/OS. We leverage IBM DBB and Wazi Deploy in this example.
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By Harness
How do enterprises turn AI from experimental potential into real-world software delivery value — without slowing down, breaking security, or sacrificing reliability? At {unscripted} 2025, Amit Zavery — President, Chief Product Officer, and COO of ServiceNow — joined Harness CEO and Founder Jyoti Bansal for a candid fireside chat on the future of AI in the enterprise, the role of platforms in unlocking developer productivity, and why"AI-native" only works when speed, security, and reliability move together.
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By Harness
What happens when AI interviews a tech leader? You get unexpectedly honest answers. Harness General Counsel Hanna Steinbach sat down with ChatGPT — and skipped the corporate script. From the realities of parenting while leading a legal team at a high-growth startup, to the daily habits that keep her grounded, this is the kind of candid leadership perspective you rarely see. Oh, and she's definitely the person sprinting to the gate right as boarding starts.
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By Harness
Most engineers can recite these three terms. Fewer know how they actually connect during a load test. If your team is running performance tests without mapping results to SLOs, you're collecting data without a pass/fail signal. This short gives you the mental model to turn load test output into something your SLA can actually depend on.
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By Harness
Having backups doesn't mean you have disaster recovery. And that gap could kill your business. Backups are just data snapshots stored safely for restoration when files get corrupted or deleted. Disaster recovery is your complete operational playbook for bringing back servers, applications, networks, and entire infrastructure after catastrophic failures. You can restore every byte of data from backup and still watch your business stay offline for hours or days because you lack the recovery procedures, failover systems, and tested runbooks to actually get operations running again.
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By Harness
April was a big month at Harness. AI is changing how code gets written — and the rest of the SDLC is catching up. In this update, Dewan Ahmed walks through Harness product releases across three themes: AI in the developer workflow, security and governance for AI assets, and self-service maturity for developers and platform teams. What's covered (with timestamps): Found this useful? Subscribe for monthly product updates, and drop a comment telling us which release you want a deep dive on next.
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By Harness
Want to start chaos engineering? Don't randomly break stuff and hope for the best. Real chaos engineering starts with defining your system's steady state metrics like latency, throughput, and error rates. Then you form a clear hypothesis about what should happen when failures occur. Next, you inject controlled failures, starting small with single pod kills or network drops, not production meltdowns. Finally, you limit the blast radius by running experiments in safe environments first.
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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.