Boost observability with Fluent Bit and OpenTelemetry! Collect, process, and export logs and metrics easily for smarter monitoring.

I’m a big fan of tasting menus. In the culinary world they let us sample a variety of dishes in small portions, helping us understand and appreciate different flavors and options. Inspired by this concept and a talk I gave earlier this year, I have crafted a “tasting menu” of OpenTelemetry Collector configurations in Grafana Cloud.

It’s very popular to push logs, in a formatted way, to the console output of an application (sometimes referred to as stdout). Although using a push-based approach like OTLP over gRPC/HTTP is preferred and has more benefits, there are many legacy systems that still use this approach. These systems typically use a JSON output for their logs. So, how do we get these JSON logs into a backend analysis system like Honeycomb that primarily accepts OTLP data?

Migrating from other vendors becomes a lot easier with OpenTelemetry and Grafana Alloy, our distribution of the OpenTelemetry Collector. But when you come from platforms that use different temporalities, such as Datadog or Dynatrace, you face a challenge integrating with a Prometheus-like ecosystem such as Grafana Cloud: Your metrics still mean the same as before, but they just don’t look right.

Yuri Shkuro· Follow Published in JaegerTracing · 6 min read· 1 day ago -- Listen Share Jaeger, the popular open-source distributed tracing platform, has had a successful 9 year history as being one of the first graduated projects in the Cloud Native Computing Foundation (CNCF). After over 60 releases, Jaeger is celebrating a major milestone with the release of Jaeger v2.

Serverless or event-driven applications can comprise many different distributed components, including serverless compute services such as AWS Lambda and AWS Fargate for Amazon ECS, as well as managed data streams, data stores, workflow orchestration tools, queues, and more. Having full end-to-end visibility into requests as they propagate across all of these parts of your application is crucial to monitoring performance, locating affected up- or downstream services, and troubleshooting issues.

In the world of security, being able to use system telemetry of Windows hosts opens new possibilities for monitoring, troubleshooting, and securing IT environments. Recognizing this, Elastic has introduced new capabilities focused on Event Tracing for Windows (ETW) — a powerful Windows-native mechanism for capturing a vast array of system and application events. With these new additions, Elastic users can capture, analyze, and visualize Windows telemetry using the Elastic Search AI Platform.

Recently, I have seen a trend of enterprises moving toward OpenTelemetry (OTel) for application tracing. Tail sampling, in particular, has emerged as a preferred approach to gain actionable insights while balancing data volume and cost. OpenTelemetry offers developers and practitioners the ability to instrument their code with open-source tools, moving away from vendor-provided tools for application instrumentation.

Maximize your observability with tracing tools to track requests, identify bottlenecks, and optimize system performance across services.

OpenTelemetry and OpenTracing are two closely connected open-source projects that enhance observability in modern distributed systems. They are designed to instrument application code for generating telemetry data. OpenTelemetry is a comprehensive, vendor-neutral framework that helps capture various types of telemetry data, while OpenTracing focuses specifically on tracing and provides a way to instrument applications for that purpose.