Operations | Monitoring | ITSM | DevOps | Cloud

The best API monitoring tools are Hyperping for HTTP and API checks with on-call and status pages, Checkly for API monitoring as code, Postman Monitors for teams that already keep collections in Postman, Datadog for connecting failed checks to traces and logs, Grafana Cloud for teams using k6, Better Stack for checks inside a broader incident workflow, and UptimeRobot for inexpensive availability checks.

Ask a platform team why their application logs aren't in their observability backend and you'll often get a one-sentence answer: And, that's where the conversation ends. The logs stay in a silo. Or, they don't get collected at all. The team loses the troubleshooting signal, and nobody revisits the decision because the alternative looks like a compliance violation. Application logs in healthcare, aviation, insurance, and retail are full of personal information that should not be stored in plain text.

Learn why modern IT complexity can slow incident response and how observability, AIOps, operational context, and automation can help teams detect, investigate, and resolve issues faster.

Certification against ISO 20000 puts your service desk under audit. That audit runs on what your team wrote down at the time. The standard does not care how your team describes its process. It does not care which ITIL 4 practices you adopted. It cares what your records show, so auditors spend their time in your tickets, approvals, and review minutes. In this blog, you will: You will finish knowing which of your records would survive an audit.

Most log management tools bill you on log ingestion, the volume of data you send them. That works until your log volume doubles, and the invoice doubles with it. The best log management tools let you control what gets indexed and kept, so growth stops being a budget problem. In this blog, you will see: By the end you will know which fits your volume. Log management is the full lifecycle of your log data, from the moment it is collected to the moment it is deleted.

Labels are a powerful way to organize telemetry and define policies across Grafana Cloud, helping to streamline alerting, attribution, access control, and more. But traditionally, custom labels in Synthetic Monitoring have worked a little differently: they only lived on a single sm_check_info metric, and Grafana Cloud prefixed each one with label_.

GenAI has moved well past the pilot stage. According to a Gartner finding, by 2026, more than 80% of enterprises will have used GenAI APIs or deployed GenAI-enabled applications in production. Today, GenAI is becoming an integral part of how infrastructure and application teams work every day. Organizations are depending on LLMs from a diverse range of vendors—OpenAI, Anthropic, Google AI, and DeepSeek—based on the strengths each offer for different use cases.

AIOps explained in plain terms: what it means, how it differs from AI-SRE and MLOps, how it detects problems, and whether a small team needs it. Sejal Pandey works on content and growth at Last9, writing about observability, reliability, and SRE practices.