InfoQ Homepage Development Content on InfoQ
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/articles/evolutionary-architecture-change-locality/en/smallimage/evolutionary-architecture-change-locality-thumbnail-1785239081753.jpg)
Enabling Evolutionary Architecture through the Preservation of Change Locality
Why do simple features suddenly require cross-team negotiations? In this article, explore how boundary drift quietly destroys change locality and increases cognitive load across teams. Learn practical sociotechnical strategies - redistributing mechanics, exposing essential policy, and rehearsing exception paths - to restore domain boundaries and enable a truly evolutionary software architecture.
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/articles/virtual-threads-after-jdk24/en/smallimage/virtual-threads-after-jdk24-thumbnail-1785232507934.jpg)
Virtual Threads after JDK 24: What Changed for Production Java
JDK 24 removed the monitor-related carrier-thread pinning that stalled Netflix and similar teams on Java 21. What has replaced it on JDK 25 LTS is downstream-resource saturation: the bottleneck moved and now demands explicit bounding in application code. This article maps the failure modes that surface after virtual-thread adoption and gives a practical sequence backed by a public benchmark.
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/articles/securing-mcp-production-gateway/en/smallimage/securing-mcp-production-gateway-thumbnail-1784884301110.jpg)
Securing MCP in Production: Defense-in-Depth beyond the Gateway
This article presents a defense-in-depth approach for securing Model Context Protocol (MCP) deployments in production. It outlines four architectural control layers: safe execution, management infrastructure, outbound trust, and semantic integrity, arguing that production security requires enforcement beyond the gateway at the earliest trustworthy control points.
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/articles/evolutionary-architecture-pattern/en/smallimage/evolutionary-architecture-pattern-thumbnail-1784798616611.jpg)
An Evolutionary Architecture Pattern for Managing AI’s Pace of Change
Traditional API gateways assume deterministic services and simple schemas - assumptions agentic AI breaks. Discover why enterprise engineering leaders are adopting AI Gateways as an evolutionary architecture seam. Centralize guardrails, model routing, agent identity, action policy, and semantic audit within a single control plane to prevent costly incidents while keeping core platforms stable.
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/articles/self-building-agent-langchain4j/en/smallimage/the-self-building-agent-a-langChain4j-experiment-thumb-1784637877074.jpg)
The Self-Building Agent: a LangChain4j Experiment
The article discusses an experiment where a code assistant had to design an agentic system using LangChain4j documentation. The assistant created a coding framework capable of writing, testing, and debugging code autonomously. Results showed that two architectural patterns—supervisor and workflow—offered different trade-offs between flexibility and execution speed during debugging tasks.
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/articles/ai-speed-context-store-architecture/en/smallimage/ai-speed-context-store-architecture-thumbnail-1783673492911.jpg)
Comprehension at AI Speed: Building a Context Store for Evolutionary Architecture
AI makes the first 80% of development feel fast, but hides architectural complexity until it's too late. To prevent system instability, engineering leaders must shift from raw throughput to systemic comprehension. By unifying spec-anchored SDD, TDD, and automated fitness functions into a repo-bound "Context Store," teams can ensure AI agents and human reviewers evolve code safely.
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/articles/aws-multi-region-signing/en/smallimage/aws-multi-region-signing-thumbnail-1783602485181.jpg)
Removing a Hidden Round Trip from a Multi-Region AWS API
When a series of regional outages forced a rethink of a multi-region AWS API, the team discovered that an obstacle to global failover was hiding in plain sight: a pre-flight discovery call baked into every client session years earlier as the only available option. This article describes what it took to remove it, and what the rollout actually cost.
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/articles/multi-region-latency-cost-tradeoffs/en/smallimage/multi-region-latency-cost-tradeoffs-thumbnail-1783416229477.jpg)
Trade-Offs in Multi-Region Architectures: Latency vs. Cost
Adding cloud regions changes latency and cost in ways simple math can't capture. This article presents a framework from multiple launches: decompose your latency budget before committing to infrastructure, choose deployment patterns by consistency and traffic profile, and optimize before expanding. A phased approach cut latency 35% through routing alone, before a new region brought it under 60ms.
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/articles/android-beat-aligned-mobile-audio-streaming/en/smallimage/android-beat-aligned-mobile-audio-streaming-thumbnail-1783408153943.jpg)
Beat-Aligned Mobile Audio Streaming with Virtual Chunks and Native Playback
In this article, I describe the challenges and the design of a React Native real-time mobile beat-aligned playback system for iOS and Android. The system combines personalization with low-latency, and seamless navigation and was the result of careful analysis and experimentation to address strict mobile and network constraints as well as meet user expectations.
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/articles/tradeoffs-event-driven-design/en/smallimage/tradeoffs-event-driven-design-thumbnail-1782458803116.jpg)
Scaling Java-Based Real-Time Systems: the Hidden Tradeoffs of Event-Driven Design
Event-driven architecture promises scalability, but in Java-based real-time systems the tradeoffs only surface in production. Drawing on a Java/Kafka contact center platform handling 80k BHCC across 10k agents, this article details where the design breaks down—state management, partition limits, deduplication, JVM tuning, cascading consumer failures—and the Redis-backed patterns that fixed each.
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/articles/security-ai-threat-evolution/en/smallimage/security-ai-threat-evolution-thumbnail-1782202845102.jpg)
Virtual panel: Security in the Machine Age: Expert Insights on AI Threat Evolution
This virtual panel brings together AI security experts to examine the evolution of AI-driven threats, from prompt injection and data poisoning to agent abuse and AI-powered social engineering. The discussion explores emerging attack patterns, incident response challenges, and the changes security teams must make as AI systems become more autonomous and integrated into critical workflows.
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/articles/rdla-offline-first-reactive-android-data-layer/en/smallimage/rdla-offline-first-reactive-android-data-layer-thumbnail-1781776366032.jpg)
Beyond CLEAN and MVP: Architecting an Offline-First Reactive Data Layer in Android
With the Reactive Data Layer Architecture (RDLA), you establish a clear boundary between public data APIs and private, framework-specific data-source implementations. Your presentation layer operates in a purely reactive manner, observing data changes rather than procedurally querying them. RDLA also simplifies testing by encouraging you to program to interfaces and use clean seeding patterns.