Operations | Monitoring | ITSM | DevOps | Cloud

SSL Certificate Verification Failed errors are one of the most common and frustrating issues for developers, DevOps engineers, and system administrators. Whether you're building a Python application, running a Docker container, or managing a web server, this guide will help you.

DORA Metrics are widely regarded as the gold standard for measuring the performance of software development teams. The metrics themselves though are generic, high-level pointers – they are not an instruction manual. Adopting the DORA approach is the first step down the path to continuous improvement. The next steps are deciding how the measures should be defined in the context of your own organisations processes and then figuring out how to retrieve (and present) the relevant data.

Andy Jiang is a JavaScript engineer with nearly 10 years of experience. He’s interested in making JavaScript and TypeScript simpler to use. He currently works at Deno as a product marketing manager. Outside of work, Andy likes cooking, writing, and playing tennis. Observability is essential for modern applications. Metrics, logs, and traces allow you to troubleshoot production issues, monitor performance, and understand usage patterns.

As Government agencies modernize IT operations, many are adopting hybrid cloud and multi-tenant environments to drive agility and resilience. But as environments scale, so does complexity, especially when aligning with overlapping frameworks like FedRAMP, NIST, and CMMC. Today’s cybersecurity landscape—rising threats, shrinking budgets, and expanding compliance demands—requires more than manual oversight.

There’s a question I hear quite often in my conversations about network management: "Aren't all network monitoring tools basically the same?" Honestly, I understand why so many people feel this way. For as long as I remember, the primary role of these tools has been to tell you when something is already broken. Your team gets an alert—a switch is down, an application is slow, a circuit is saturated—and the fire-fighting process begins.

In today's sprawling enterprise environments, keeping the network running smoothly isn’t just a technical hurdle—it’s a logistical marathon. Enterprise IT environments are in constant motion. New employees come on board. Contractors rotate in and out. Departments roll out new tools. Corporate offices expand, consolidate, or close. And users demand flawless connectivity from wherever they are.

Our CLI team has been cooking up some awesome new AI functionality that we think you will love. The latest release includes several new commands such as changelog, commit, pr, and a command to check the remaining tokens on your subscription. They are all nested under a new top level command, gk ai.

Natural language copilots are one of the most exciting developments in AI for network operations. They allow engineers and operators to query complex environments in plain language rather than memorizing obscure CLI commands or digging through multiple dashboards. But here’s the truth: a copilot is only as good as the AI behind it. Without a purpose-built network LLM, a copilot can’t deliver the accuracy, context, and speed that real-world IT operations demand.

AI adoption isn’t just accelerating, it’s compounding. From GPT-5 to Claude to Llama and beyond, engineering teams are integrating diverse LLMs across products, experiments, and services. And finance teams are now grappling with a new kind of cloud complexity: token-based economics and volatile inference costs, often spread across multi-model, multi-cloud, and multi-region architectures. The modern FinOps stack needs to keep up. CloudZero was built for this moment.

When a service slows down, metrics will tell you that it’s happening but logs tell you why. For MySQL, slow queries can be a silent performance killer, gradually chewing through resources until users start complaining. By enabling MySQL’s slow query log and forwarding it to Loki (via Promtail), you can visualize query-level details right alongside your metrics on Grafana dashboards. This makes it easy to correlate what is slow (metrics) with what is causing the slowdown (logs).