Operations | Monitoring | ITSM | DevOps | Cloud

For years, the Kubernetes sidecar pattern has been a practical way to capture observability data. Running a collector alongside each application pod gave us deep visibility into traffic, including full request and response payloads across supported protocols. However, as cloud-native environments have grown more complex, the limitations of sidecars—such as resource overhead, operational complexity, and scaling challenges—have become more apparent.

Eliminate the “idle tax” to reclaim 40% of your cloud spend and secure CSRD compliance.

AI that understands human insight and connects it to the changes that drive real incidents. At Harness, our story has always been about change — helping teams ship faster, deploy safer, and control the blast radius of every modification to production. Deployments, feature flags, pipelines, and governance are all expressions of how organizations evolve their software. Today, the pace of change is accelerating.

With all we’ve seen from AI in the last several years, it can be easy to forget that it’s still in its very early days. As torrid as its evolution has been thus far, it will only intensify. As SVP of Engineering at a B2B SaaS company, I’ve had a front-row seat for much of this evolution. Here are three ways I see AI heading in 2026.

Anyone who has ever attempted to learn the guitar knows the lure of buying high-end gear. Surely, an expensive guitar and a best-in-class amplifier will hide the fact that you only know a few chords and maybe the lead line to that one song you keep hearing on the radio. What most players find out, however, is that spending thousands of dollars on gear doesn't change the fact that you're not that good yet.

Gartner has predicted that 2026 will see a 10.6% increase in India’s total IT spend from 2025 (2025: USD 159 billion vs 2026: USD 176.3 billion), with data centres, cloud infrastructure, and AI-enabled technologies driving this growth. This isn’t just a budget increase; it’s a fundamental shift in where innovation happens, who owns the infrastructure, and how we translate AI potential into scalable impact.

CIOs rarely struggle to find automation ideas. What they struggle with is getting those ideas funded, then keeping support once the first few workflows go live. We built this guide for IT leaders who need a credible, repeatable way to present IT automation ROI in language that resonates with the C suite. If you are shaping an automation program across service desk, IT operations, and network operations, our Agentic Automation for CIOs & CTO’s hub lays out the strategic lens.

ServiceNow is the system of record for change and approvals in most regulated enterprises. And yet, for many teams, it has become the place where delivery slows to a crawl. Not because ServiceNow is broken. But because the evidence model underneath it is. Developers ship fast through modern CI/CD pipelines, automated tests, and security scans, only to hit a wall when changes reach approval. Tickets bounce back. Evidence is questioned. Screenshots do not tell the full story. CABs hesitate. Releases wait.

In regulated environments, slow change is often blamed on process. Too many approvals. Too much governance. Too much red tape. But in reality, most delays are not caused by regulation itself. They are caused by missing, fragmented, or untrusted evidence. Screenshots pasted into tickets. Proof assembled weeks later. Approvals stalled because no one can confidently say whether a change actually meets policy. When evidence is an afterthought, compliance turns into chaos.

In an era where digital performance defines business success, large enterprises are embracing Event Intelligence Solutions (EIS) to keep services available, resilient, customer-facing operations protected from disruption. According to Gartner, Event Intelligence Solutions use AI and advanced analytics to enhance and automate how organizations respond to signals generated by digital services.