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Do you want cloud-native Java applications that can start up in milliseconds, without compromising on throughput, memory, development-production parity, or Java language features? The Open Liberty 22.0.0.11-beta brings you InstantOn, an exciting new feature that provides incredibly fast startup times for MicroProfile and Jakarta EE applications.
Open Liberty 22.0.0.12-beta release previews MicroProfile 6 features: MicroProfile JSON Web Token (JWT) 2.1, which includes simple JWT validation, and MicroProfile Metrics 5.0, which provides user-defined metric registry scopes.
Liberty Tools for Eclipse provides a new experience for developing cloud-native Java microservices on Open Liberty. This early release provides assistance when using MicroProfile APIs, editing your Liberty server.xml configuration in Maven and Gradle projects, a Liberty Dashboard for organizing your projects, and Liberty dev mode (automatically deploying code changes to your running app, without having to restart the server), all from within your Eclipse IDE.
For MicroProfile 4.1 applications that require additional startup time on their first initialization, you can define startup probes which are used to check the startup status of the application before the Liveness probe takes over. MicroProfile Health 3.1 introduces a new health check called Startup. You can create your own health check procedures to verify that your microservices have fully initialized using the @Startup annotation. And you can configure the Kubernetes Startup probe with the REST endpoint /health/started.
To learn how to develop cloud-native Java applications and microservices with MicroProfile 5.0 and Jakarta EE 9.1, you can try out our updated Open Liberty guides. You can run our guides in a hosted environment with enhanced interfaces, without having to worry about local setup and prerequisites. We recently updated 31 of our guides for compatibility with MicroProfile 5 and Jakarta EE 9.
OpenTelemetry is a collection of APIs, SDKs, tools you can use to instrument, generate, capture and export telemetry data. An example of telemetry data are metrics and logs which can then be analyzed to evaluate your application’s performance and behaviour. In the era of cloud-native applications, it is pretty common to combine polyglot architectures. This leads to a major challenge: how to power observability in a standard way?
