Operations | Monitoring | ITSM | DevOps | Cloud

When AI agents operate across a multi-module platform like Harness (from CI/CD to DevSecOps to FinOps), the number one goal is to give you answers that are correct, consistent, and grounded in real data. Getting there requires a deliberate architectural choice: when a question can be answered from structured platform data, the agent should use a schema-driven Knowledge Graph rather than raw API calls via MCP. The principle is simple: if the data is modeled, retrieval should be deterministic.

Infrastructure as Code (IaC) solves the provisioning problem. It doesn't solve the governance problem. You can version your Terraform configuration, run it in a pipeline, review every pull request — and still deploy an S3 bucket with public access, a VM with no encryption, or a resource that exceeds your cost budget. Nothing in the standard IaC workflow checks for those things. The reviewer has to know what to look for. And they won't catch it every time. Policy as Code changes that.

You could have the most detailed metrics displayed on your dashboard, but if no one gets notified when things break, you’re just collecting data. Alerts help turn this passive monitoring into an active response. It’s like they tell you, “Hey, your error rate just spiked!” or “Your memory usage is through the roof,” even before your users start filing support tickets, or worse, give up on your tool entirely.

In Grafana Cloud we use a simple yet generous formula that lets you query up to 100x your monthly ingested log volume in gigabytes for free. This works for the vast majority of our customers, but if you aren’t careful and strategic with your usage, you could find yourself with an overage bill.

Autonomous IT becomes real when teams move from insight to governed action. Most IT teams still operate on an alert-first, human-coordinated model. When something breaks, alerts fire across multiple tools, engineers get pulled in, and the first part of the response goes to figuring out who owns the problem, which signals matter, and how far the impact has spread. Containment comes after that. That sequence made sense in slower, more isolated environments.

The most expensive hour in software engineering is the hour spent trying to figure out why a bug exists in production that doesn’t exist anywhere else. For many teams, the first 70% of a debugging cycle isn't spent fixing code; it is spent on "plumbing." This is the time lost to reproducing the issue, wrestling with environment drift, and sanitizing datasets just to get to a starting line.

Organizations frequently debate ITAM vs CMDB because both disciplines describe the same environment from different angles. A CMDB gives operational context – how services, applications, and infrastructure relate – so teams can restore service fast and manage risk. ITAM focuses on financial accountability, control, and governance across the asset management lifecycle, from request to retirement. In practice, the strongest ITSM operating models connect both.

The market for enterprise service desk automation platforms has matured, but the way most enterprises evaluate them hasn’t. A lot of teams still start in the same place. They pull a shortlist from a review site, they compare pricing tiers, and sit through a few polished demos. Then, somewhere down the line, they realize they still haven’t answered the real questions that matter for their organization. What happens when the environment gets complicated and messy?

CertKit is officially out of beta. We started building CertKit a year ago, and since then over 600 people signed up, issued certificates, and deployed to their infrastructure. Several are running it as their production certificate management platform right now. We built a lot during the beta. Some of it we planned: SSO, team management, alerting. Other things, users had to beat into us. The Keystore came from enterprise security requirements to keep private keys in house.