Operations | Monitoring | ITSM | DevOps | Cloud

An error budget is the acceptable amount of unreliability permitted by your SLO over a defined time window. It is not a target. It is not a stretch goal. It is a hard ceiling that, when breached, should trigger a pre-agreed organizational response — feature freezes, postmortems, or infrastructure investment. The formula is blunt: Error Budget = 1 - SLO Target Error Budget (time) = (1 - SLO Target) × Window Duration For a 30-day window: That last number should make you uncomfortable.

Here are the three records most teams forget to monitor — and what happens when they break.

Every week, thousands of engineers, SREs, and IT leaders type questions about anomaly detection into ChatGPT, Reddit, and Stack Overflow. They are all trying to answer the same underlying question: why do production incidents keep catching us off guard, and how do we stop them?

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.

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?".

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.

There’s a growing ecosystem of AI coding agents: Claude Code, Cursor, Copilot, Codex, Gemini CLI, Windsurf, and others. They’re good at writing code, but they don’t inherently know how to instrument that code for observability, configure monitoring infrastructure, or troubleshoot production systems using real telemetry data. That knowledge lives in documentation, runbooks, and the heads of your senior SREs.

Certificate automation does a lot of work on your behalf. Agents running on your servers, talking to certificate authorities, deploying certs to your infrastructure. At some point someone (your CISO, your auditor, or your own brain at 3am) is going to ask: what exactly happened, and when? Today we’re shipping audit logs. Every action taken in CertKit is now recorded: logins, invitations, certificates added, issued, renewed, revoked, and deployed. Agent registrations, approvals, and config changes.