Operations | Monitoring | ITSM | DevOps | Cloud

AI, Platforms, and the Future of Value Delivery: A Conversation with ServiceNow

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.

Automated Release Management: From CABs to Continuous Delivery | Harness Blog

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.

AI Asked Our General Counsel Anything. She Didn't Hold Back.

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.

The AI Productivity Paradox: We're Measuring the Gains and Missing the Costs | Harness Blog

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.

Disaster Recovery Testing: A Practical Step-by-Step Guide for 2026 | Harness Blog

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.

SLI, SLO, SLA: What They Mean for Load Testing

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.

Introducing Harness Release Orchestration: Enterprise Release Management, Reimagined | Harness Blog

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.