Thursday, October 29, 2020
Modern applications are increasingly becoming more of a distributed computing problem. With the availability of feature rich cloud services, our solutions are increasingly relying on these in implementing functionality. Also, the application itself is adopting more of a disaggregated architecture in favor of extensibility, scalability, re-usability, and deployment flexibility. This is how microservices architectures are becoming popular everyday. But there is no free lunch; with the benefits, there are new challenges that are introduced. Compared to monoliths, with microservices we need to handle the complexities that come with networked architectures, such as communication latency, unreliable connections, protocols, data formats, and transactions. So while we come up with many new techniques to tackle these problems, it’s vital for us to have a proper observability functionality to verify the behavior. The Ballerina programming, which is designed from ground-up to work with networked applications, takes in a unique approach by having built-in observability functionality in language constructs. It exploits the language awareness for network operations, such as service types, remote function invocations, communication resiliency mechanisms, to automatically observe the operations done by the users. Basically the Ballerina platform takes care of the majority observability situations automatically, so the developer can only focus on the core business logic, and not sprinkle your code with lots of observability code. In this session, we will look at these features on how these built-in functionality will be used for metrics generation and distributed tracing using the Ballerina platform.
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