Incident response and management (IRM) doesn’t happen in a vacuum. Your ability to respond to issues in a timely manner depends greatly on how well your on-call engineers can use their IRM tooling and observability tools together to understand what changed and why.

Hey, I just deployed — and this is crazy. But the server’s down, so call me, maybe? Making your services available at all times is the gold standard of modern software operations. The easiest way to reach this would be to just write bug-free software, but even if you reach this completely unattainable goal — stuff happens! Modern software rarely exists in a vacuum and often depends on a multitude of external services and libraries.

OpenAI’s ChatGPT has an extraordinary ability to process natural language, reason about a user’s prompts, and generate human-like conversation in response. However, as the saying goes, “a picture is worth a thousand words” — and perhaps an even more significant achievement is ChatGPT’s ability to understand and answer questions about images.

Last November, Dimitris and Giordano Ricci wrote a blog post about CI/CD observability that looked into ways to extract traces and metrics in order to get a better understanding of possible issues inside a CI/CD system. That post focused on getting data from a continuous integration (CI) system, and it really resonated with the community.

There is a Polish proverb: “Co za dużo to niezdrowo,” which more or less translates to “Enough is as good as a feast.” (Or, translated verbatim: “Too much of something can be unhealthy.”) Sometimes this is true for data as well. At Grafana Labs, we’re always introducing products and features that help you make sense of that abundance of data, either by efficient visualizations, adaptive observability, or apps dedicated to specific workflows and use cases.

Monitoring your identity provider’s logs is critical to identify potential security threats. These logs are vital for a security team, who may store them in a specialized tool like Grafana Loki for enhanced accessibility and analysis. The ability to pinpoint specific patterns within these logs is key — and by crafting these patterns into Loki queries, you can conduct focused searches across logs.

These days, everything can be tracked: transportation, deliveries, food orders. . . For consumers, knowing the location of a package or courier is a bonus, but for companies in the business of shipping, delivering, and third-party logistics, it’s a necessity. And so is having the right observability system to ensure everything gets where it needs to go. After all, errors, downtime, or anything that causes delays will end up delivering unhappy customers and lost revenue.

Integrating monitoring and logging into your application stack is crucial for maintaining performance, enhancing security, and streamlining troubleshooting. Grafana Cloud offers a robust solution for monitoring your applications by collecting metrics and logs using an agent, such as Grafana Agent, but there are many environments where this isn’t feasible.

Grafana Beyla, an open source eBPF auto-instrumentation tool, has been able to produce OpenTelemetry trace spans since we introduced the project. However, the traces produced by the initial versions of Grafana Beyla were single span OpenTelemetry traces, which means the trace context information was limited to a single service view. Beyla was able to ingest TraceID information passed to the instrumented service, but was unable to propagate it upstream to other services.

We are consistently releasing helpful updates and fun features in Grafana Cloud, our fully managed observability platform powered by the open source Grafana LGTM Stack (Loki for logs, Grafana for visualization, Tempo for traces, and Mimir for metrics). In case you missed it, here’s a roundup of the latest and greatest upgrades for Grafana Cloud this month. If you’re not a Grafana Cloud user, what are we waiting for?