Reduce memory-heavy dependencies. Third party libraries are often very resource-hungry. Opt for lightweight lambda-friendly frameworks such as  Micronaut or Quarkus. - Source: dev.to / 2 months ago

The innovations didn't stop there. We also use compilation to a native image via GraalVM, which enabled us to switch to the latest Java versions. Also, we use DI based on Micronaut, and overall, we try to keep up with new industry trends. - Source: dev.to / 3 months ago

This allows Java to have such goodies as reflection, dynamic proxies, ServiceLoader, and DI frameworks like Spring, Micronaut, or Quarkus. - Source: dev.to / 4 months ago

Micronaut is a modern, JVM-based, full-stack framework designed for building modular, highly testable microservices and serverless applications. After working with Micronaut for over two years, I decided to transition to Quarkus. - Source: dev.to / 8 months ago

In this application, we will create products and retrieve them by their ID and use Amazon DynamoDB as a NoSQL database for the persistence layer. We use Amazon API Gateway which makes it easy for developers to create, publish, maintain, monitor and secure APIs and AWS Lambda to execute code without the need to provision or manage servers. We also use AWS SAM, which provides a short syntax optimised for defining... - Source: dev.to / about 1 year ago

Durable execution — the pattern implemented by Temporal, Inngest, Rivet Actors, and now Cloudflare Workflows — treats waiting as a continuation rather than a loop:. - Source: dev.to / 1 day ago

Two specific moves stand out in Duncan's account. The first is durable execution, via Temporal — Mercury replaced fragile cron-and-database state machines with workflow code whose failure semantics are platform-handled (replay, retry, timeout, cancellation). Mercury open-sourced its hs-temporal-sdk, which wraps Temporal's official Rust Core SDK via FFI and provides a Haskell-native API. The dovetail with Haskell's... - Source: dev.to / 29 days ago

We picked Temporal as the first reference engine on purpose. Temporal has the strictest execution model we know of – a V8 sandbox, determinism constraints, replay-driven recovery. If our port contract holds up against that, easier engines – an in-memory test double, a BullMQ queue, or JSON-first platforms like Inngest or Restate – plug in through the same two interfaces. We're shipping Temporal first; the rest is... - Source: dev.to / about 2 months ago

The trick is to find whatever metadata channel the queue already gives you and use that and thankfully, almost every mature queue has one (probably because of this scenario). SQS has message attributes, Temporal has context propagators built into the SDK, and Hatchet (which we use to run our workflows) has a metadata field called additionalMetadata. - Source: dev.to / 3 months ago

A typical production stack for teams using Claude or Gemini as the reasoning layer includes an LLM provider API, an orchestration layer (n8n, Temporal, or a custom Python service), application infrastructure (a server running the orchestration code), and a data layer (a database for storing results). Each boundary introduces a failure point. When the LLM provider changes its rate limits, as OpenAI did repeatedly... - Source: dev.to / 3 months ago