In this comprehensive tutorial, we explore the crucial aspect of observability in Ballerina programs, drawing parallels between walking in the dark without visibility and running a production system without observability. The video focuses on two key components of observability: tracing and metrics.
The speaker walks you through a Ballerina service, demonstrating how to enable observability by adding a config file with specific entries. The discussion covers the three fundamental aspects of observability: logs, tracing, and metrics, with a particular emphasis on the latter two.
Tracing is illustrated using Jaeger, showcasing the service's flow and interactions with external endpoints. The tutorial provides insights into how tracing helps identify issues and monitor the sequence of events in your Ballerina programs.
Metrics are explored using Grafana, where the speaker explains the process of setting up a data source and importing a pre-configured dashboard. The video demonstrates how metrics provide real-time information about request errors, throughput, response time, and more. A live example further emphasizes the power of metrics by intentionally causing errors in a supporting service and observing the impact on the dashboards.
The tutorial encourages viewers to experiment with observability on their own by providing a link to the repository containing the sample Ballerina service. The speaker assures that the process is straightforward and guides viewers through the steps of running the service, sending requests, and exploring the generated dashboards.
Whether you're new to observability or looking to enhance your Ballerina programs' monitoring capabilities, this video equips you with the knowledge and tools needed to implement logs, tracing, and metrics effectively. Don't let your production system operate in the dark-enable observability with Ballerina!
Github repo: github.com/shafreenAnfar/social-media-demo-observability
Негізгі бет Observe Ballerina Programs
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