Managing HTTP Request-Response Cycles in Ballerina
Learn how to manage HTTP request-response cycles in Ballerina, balancing automatic serialization with the manual control of the http:Caller object for custom status codes.
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Parallel Execution in Ballerina: Using Workers for CPU-Intensive Tasks
Learn how to use Ballerina workers to offload CPU-intensive tasks from the main event loop, utilizing futures for asynchronous results and locks for thread safety.
ballerinaReducing API Boilerplate with Ballerina's Native Service Constructs
Stop paying the 'boilerplate tax.' Learn how Ballerina's native 'service' keyword and network-aware types eliminate manual routing and DTO mapping in API development.
Resource contention when multiple Ballerina workers access synchronized shared state
Resource contention when multiple Ballerina workers access synchronized shared state The worker keyword creates separate execution contexts, each with its own event loop, but shared resources require synchronization across workers. Scheduling Uncertainty When several workers attempt to lock the same synchronized resource, the runtime scheduler must decide ho
Worker exhaustion during blocking I/O calls in Swan Lake runtime
Concurrency Model Constraints Ballerina's Swan Lake architecture employs a worker-based concurrency model where requests are managed via lightweight strands. While this design aims to reduce OS-level thread switching overhead, the interaction between the event loop and blocking I/O operations can impact service availability. Resource Contention When a servic