Topic: General Level: All
In this post, we shall catch up on the multi-faceted technological updates that happened over the past week,
Dealing with checked exceptions in functional interfaces via lambdas in Java Streams shatters the intent of a simplified functional pipeline making it verbose. By extracting the exception handling block to a class, Lombok annotation SneakyThrow, Apache Commons Lang Failable stream API, and Varv functional library with Streams offers alternatives for handlezing the try/catch scenario embracing code pipe flow, thereby optimizing lambdas in the Streams.
When we package and ship our application to the clients, making it evident on the dependencies (both stated and transitive) used in the application aids clients in making informed decisions, adhering to any defined standards, and guarding their system against vulnerabilities making them aware of what they are signing up for. With this, the SBOM (Software Bill Of Materials) addresses comprehensive dependencies used that can be generated via SPDX and CycloneDX Maven and Gradle plugins are part of the SDLC build process.
How the Virtual threads vary from the traditional threads, in terms of REST HTTP calls, database connections, queues, and file operations with the aid of Project Loom. Implications of blocking and non-blocking operations, asynchronous calls on Virtual Threads that run on the platform threads.
Concurrency on the data state reads and writes can be achieved by sharing/exclusive lock via Spring Data JPA entity locking mechanism. With LockModeType set to PESSIMISTIC_READ and PESSIMISTIC_WRITE data lock can be established during fetching a single row (via any of the inbuilt JPA methods or custom-defined methods) and for multi-row entity lock on the JPA implementation we can annotate the method with @Lock followed by locking type
Evaluate Virtual threads for default priority, daemon setup, thread local, inherited thread local, and other JVM thread features.
Scaling the AWS Lambda for asynchronously consuming AWS Kinesis events by introducing new execution instances inducted cold starts that increased with the application memory size. Dagger2 eliminates part of the cold start problems via static compilation of dependencies. GraalVM Native Image and Micronaut serverless framework to the rescue.
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