Tracing in Grafana With Tempo and Jaeger. Grafana Tempo: Tempo is an open source, highly scalable distributed tracing backend option. We can easily integrate it with Grafana, Loki, and Prometheus. Compatible with other open tracing protocols like Jaeger, Zipkin, and OpenTelemetry.
Application logs are beneficial for displaying important events if something is not working as expected (failure, error, incorrect config, etc.). Although it is a very crucial element in application design, one should log thriftily. This is because log collection, transformation, and storage are costly.
Unlike logging, which is event triggered and discrete, tracing provides a broader and continuous application view. Tracing helps us understand the path of a process/transaction/entity while traversing the application stack and identifying the bottlenecks at various stages. This helps to optimize the application and increase performance.
In this post, we will see how to introduce tracing in logs and visualize it easily. In this example, we will use Prometheus, Grafana Loki, Jaeger, and Grafana Tempo as data sources for monitoring metrics, logs, and traces respectively in Grafana.
In a microservices architecture, understanding an application behavior can be an intriguing task. This is because the incoming requests may span over multiple services, and each intermittent service may have one or more operations on that request. It thus increases complexity and takes more time while troubleshooting problems.
Distributed tracing helps to get insight into the individual operation and pinpoint the areas of failure caused by poor performance.
OpenTracing comprises an API specification, frameworks, and libraries to enable distributed tracing in any application. OpenTracing APIs are very generic and prevents vendor/product lock-in. Recently, OpenTracing and OpenCensus merged to form OpenTelemetry (acronym OTel). It targets the creation and management of telemetry data such as traces, metrics, and logs through a set of APIs, SDKs, tooling, and integrations. Note: OpenCensus consists of a set of libs for various languages to collect metrics and traces from Applications, visualize them locally and send them remotely for storage and analysis.
In this lesson, we are going to learn how to Log Monitoring and Alerting With Grafana Loki - Let's deploy Grafana Loki to monitor logs in Grafana and create custom metric based on logs and configure alert accordingly.
How to best monitor your external and third party API integrations and hold partners accountable to SLAs
How To Set Up Monitoring Using Prometheus and Grafana. Monitoring our microservices is as important as its development. In this article, we see how you can monitor your microservices using Prometheus and Grafana.
On Wednesday, March 11, 2020, I conducted the webinar titled “Monitoring & Orchestrating Your Microservices Landscape using Workflow Automation”. Not only was I overwhelmed by the number of attendees, but we also got a huge list of interesting questions before and especially during the webinar. Some of them were answered, but a lot of them were not. I want to answer all open questions in this series of seven blog posts. Today I am posting the final two in the series.
Monitoring Spring Boot Applications with Prometheus and Grafana. All three applications are based on Spring Boot, but have very different workloads. We started with looking into Prometheus (and Grafana) and we soon learned that it was really easy to get a monitoring system up and running.