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Uber developed a context-aware mechanism to prevent retry storms in deep microservice dependency chains. It introduces "error ownership" where services claim errors they originate and unclaim errors they propagate, allowing upstream callers to make informed retry decisions and avoid amplifying load on already struggling services.
Codename One introduced an experimental native Java backend that compiles Java controllers to a tiny native executable via ParparVM. Benchmarks show sub‑millisecond startup, 10‑40 MiB memory, and up to 20 % higher request throughput than a Go fasthttp server.
The article walks through the hidden costs of both monoliths and microservices, showing that the choice isn’t about hype but about concrete trade‑offs like deployment coordination, observability, data consistency, and team structure. It recommends a modular monolith as a pragmatic middle ground when the organization isn’t ready for full service sprawl.
This article differentiates data-driven and event-driven architectures, explaining that data-driven focuses on state for analysis, while event-driven focuses on changes for real-time reactions. It provides clear use cases and trade-offs for each, emphasizing that they often complement each other in complex systems.
This article argues that independent microservice deployments, while seemingly fast, often lead to complex and fragile releases due to environment drift and implicit dependencies. It advocates for "application-level releasing," where a consistent, validated snapshot of interdependent components is promoted together across environments to restore predictability and stability.
API design is shifting from human‑centric, resource‑based REST toward machine‑friendly, capability‑oriented interfaces as AI agents become major consumers. This drives changes in rate limiting, just‑in‑time security, system‑wide reliability, and regulatory compliance.
