In this video, we’ll show how Causely leverages OpenTelemetry. (For more on how and why we use OpenTelemetry in our causal AI platform, read the blog from Endre Sara.)
Distributed tracing gives you a bird’s eye view of transactions across your microservices. Far beyond what logs and metrics can offer, it helps you trace the path of a request across service boundaries. Setting up distributed tracing has never been easier. In addition to OpenTelemetry and other existing tracing tools such as Tempo and Jaeger, with open source tools like Grafana Beyla and Keyval Odigos, you can enable distributed tracing in your system without a single line of change.
These tools allow the instrumented applications to start sending traces immediately. But, with potentially hundreds of spans in each trace and millions of traces generated per minute, you can easily become over overwhelmed. Even with a bird’s eye view, you might feel like you’re flying blind.
That’s where Causely comes in. Causely efficiently consumes and analyzes tracing data, automatically constructs a cause and effect relationship, and pinpoints the root cause.
Interested in seeing how Causely makes it faster and easier to use tracing data in your environment so you can understand the root cause of challenging problems?
Comment here or contact us. We hope to hear from you!
Related resources
- Read the blog: Eating Our Own Dog Food: Causely’s Journey with OpenTelemetry & Causal AI
- Watch the video: Causely for Asynchronous Communication
- Read the blog: Moving Beyond Traditional RCA in DevOps