InfoQ Homepage Articles
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The Hard-Stop Rule: from 3 HCM Monoliths to 120 Domain Microservices
A payroll and HR software team rebuilt three monoliths into over 120 smaller services over five years, with no dedicated migration budget. Every new feature was built as its own service instead of changing the old ones. The article covers the pull-based migration, the tools that made this possible, how costs were kept down, and the problems the team ran into along the way.
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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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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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Multi-Agent AI for Production Security Operations: an A2A and MCP Architecture in a 5G Core
The bottleneck in a mature SOC is rarely analyst triage; rather, it is the detection-engineering team's ability to keep the rule base aligned with a threat landscape that evolves faster than rules can be written. Learn how multi-agent system for production security operations has reduced mean times to detect and to respond by 40% and compressed the human work required by 12x.
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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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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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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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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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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.
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/articles/understanding-ml-model-poisoning/en/smallimage/thumbnail-understanding-ml-model-poisoning-1781597719188.jpg)
Understanding ML Model Poisoning: How it Happens and How to Detect it
In this article, the author explores data poisoning as a threat to machine learning systems, covering techniques such as label flipping, backdoors, clean-label poisoning, and gradient manipulation. The article reviews real-world incidents, discusses the challenges of detecting poisoned data, and presents practical defenses, tools, and operational practices for securing ML training pipelines.