Blog
Mert Özen's blog posts on software development, backend, frontend, and DevOps.
Observability in Production: Azure Monitor and Application Insights, Sampling, Cost, PII and Auto-Instrumentation on Kubernetes
In production the cost and risk of telemetry are managed through sampling, volume and personal data: head sampling in the application on top of tail sampling loses most slow traces. With Bookstore we measure both settings, build a per-order budget of spans, logs and series, audit PII in Loki, and look at the new Microsoft OpenTelemetry Distro for Azure Monitor, semantic convention migrations and the Kubernetes Operator.
Querying Application Insights and Log Analytics with KQL: where, summarize, bin, join, percentiles and Alert Queries
When you query Application Insights with KQL you count with sum(itemCount), not count(): with 25 percent sampling, 300 checkouts shrink to 82 rows and none of the 7 failed ones remains. We collect Bookstore's telemetry in the Application Insights schema without an Azure account and try where, summarize, percentile, bin, make-series, join, lookup, parse/extract and alert queries on real data.