Operations | Monitoring | ITSM | DevOps | Cloud

Do you receive 50 million log lines per day and struggle to see what actually matters? Health checks, heartbeat pings, connection pool messages—they all drown out the errors and anomalies you're trying to find. Most teams deal with this by writing filter rules to drop the noisy patterns. But those rules are manual, per-pattern, and brittle. A new deployment changes a log format and the filter misses it. A new service starts logging a chatty startup sequence nobody thought to exclude.

Why ECS containers collapse under service.name = aws_ecs and how to fix it for both EC2 launch type and Fargate, including the resource-vs-log-record pitfall that quietly breaks log filtering. 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.

LocalStack lets you run SQS, Lambda, and S3 locally in Docker — but there's a hidden trap: OpenTelemetry's default AWS propagator doesn't work with free LocalStack. Here's how to set up end-to-end local testing with working trace propagation. 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.

SQS doesn't propagate trace context automatically. You instrument both sides, deploy, and get two disconnected traces. This post shows how to wire them into one waterfall — and the ESM format gotcha that silently breaks it every time. 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.

Health check endpoints generate thousands of identical, useless spans per day. Here are two production-ready approaches to filter them from your Python OTel traces — and the correctness trap most implementations miss. 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.

The OTLPMetricsWriter is a new Icinga 2 feature available since v2.16 that exports check plugin performance data as OpenTelemetry-compliant metrics via the OTLP HTTP protocol. With a single configuration object, it connects Icinga 2 to any OTLP-compatible backend like Prometheus, Grafana Mimir, Datadog, Elasticsearch, VictoriaMetrics, and more.

GCP's load balancer silently rewrites your traceparent header, orphaning spans in any OTLP backend. Here's the custom propagator that fixes it. 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.

Your SLI query shows 100% availability as No Data. Here's why PromQL returns empty results instead of zero — and the label-preserving fix. 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.

Real production data tells the story better than I can. Juraci Paixão Kröhling, a friend and fellow observability practitioner at OllyGarden, recently shared an example from an anonymized production environment: 1,830 occurrences of http.url and 23,984 occurrences of url.full in the same dataset. Both attributes describe the same thing. Both are actively being written to the same backend at the same time.

Are you writing agentic applications, but aren’t sure what the agents are doing? Finding out too late that you've blown the budget with super expensive models? Not sure where the agents are failing, and feeling a loss of control? Could they do better? Observability is the visibility you need to get the job done. Sending telemetry to Honeycomb explains what your agents are actually doing.