Operations | Monitoring | ITSM | DevOps | Cloud

Single Sign-On is now generally available in Oh Dear, on every plan. Your team signs in with the credentials they already have, and you manage access from one place: your identity provider.

Argo Rollouts exposes Prometheus metrics on port 8090 — but the docs lie about which labels exist. Here's how to scrape them into Last9, build a canary dashboard, and use Last9 as an automated AnalysisTemplate gate, including the auth and base64 gotchas. Prathamesh works as an evangelist at Last9, runs SRE stories - where SRE and DevOps folks share their stories, and maintains o11y.wiki - a glossary of all terms related to observability.

Part of what makes Cloud Provider Observability in Grafana Cloud really useful is that it gives you prebuilt dashboards and drill-downs for AWS, Azure, and Google Cloud. Out of the box you get service overviews, instance-level views, and quick links to explore your data. However, you might already have dashboards you trust, want a view tailored to your team’s workflow, or need to change which panels show up when you drill into a single instance.

One early spring morning in 1535, the residents of Stockholm awoke to a most curious sight. Six suns lit up the sky, connected by bright halos, as immortalized in Vädersolstavlan, seen here. Today, we recognize these atmospheric effects as a parhelion (also referred to as ‘sun dogs’)—an illusion caused by light refracting off crystalline formations in the atmosphere.

Every team running Apache ActiveMQ in production eventually hits the same conversation: throughput is lower than expected, latency is inconsistent, or producers are getting blocked without an obvious reason. The broker logs show flow control events. Queue depth is climbing.

Service Leadership, a leading company that works to measure IT and managed service provider (MSP) performance, defines the five levels of operational maturity for solution providers. Often referred to simply as operational maturity levels (OMLs), OMLs help managed service providers (MSPs) measure how consistently, intentionally, and effectively they run their businesses.

For those of us using tools like Claude Code, Codex, or Gemini, we already know they’re powerful. They can write code, refactor functions, open PRs, even run commands. For a lot of developers, they’re already part of the daily workflow. But once you zoom out beyond the individual developer, the biggest problem isn’t productivity. It’s control. AI coding tools are powerful, but they introduce a new, unpredictable cost layer that most teams don’t fully understand.

It's 2:47 AM. PagerDuty fires. You open a Slack alert and see: p99 latency spike on checkout-service. You SSH into the host, check dashboards in four tabs, grep logs for the last 20 minutes, and eventually find a slow query introduced in a deploy six hours ago. It took 34 minutes. You resolved it, w Prathamesh works as an evangelist at Last9, runs SRE stories - where SRE and DevOps folks share their stories, and maintains o11y.wiki - a glossary of all terms related to observability.

> Standard OTel.NET instrumentation captures headers, status codes, and timing — not request or response bodies. Here's how to add body capture to your traces while keeping PHI out of your observability backend. Prathamesh works as an evangelist at Last9, runs SRE stories - where SRE and DevOps folks share their stories, and maintains o11y.wiki - a glossary of all terms related to observability.