Operations | Monitoring | ITSM | DevOps | Cloud

With the advanced containerization that has become the norm in the modern cloud, your infrastructure is likely more distributed, and thus more exposed to networking issues, than ever before. When troubleshooting application performance issues, this can make it difficult to link the symptoms you observe through monitoring the “golden signals” (requests, latency, and errors) on individual endpoints in your application to their underlying root causes.

Grafana Tempo, the recently announced distributed tracing backend, relies on integrations with other data sources for trace discovery. Tempo’s job is to store massive amounts of traces, place them in object storage, and retrieve them by ID. Logs and other data sources allow users to quickly and more powerfully jump directly to traces than ever before. Previously we investigated discovering traces with Loki and exemplars.

Performance monitoring is great because it lets you see whether your application is fast or slow, and which parts need speeding up. For Node developers, those “parts” are most often endpoints handling incoming requests. Since the introduction of our performance monitoring offering in July 2020, Node devs have been able to use the Sentry SDK, @sentry/node, to measure the total time it takes to process each request, but we made some significant improvements since then.

Kubernetes namespaces enable you to organize cluster objects, such as applications, devices and variables. Once you define namespaces, you can use this classification to filter, group and manage objects. You can use the same namespaces in duplicated environments and apply policies to specific clusters segments. Kubernetes namespaces are also important for defining roles and ensuring proper access configuration. If you're monitoring Kubernetes, you should try out MetricFire.