InfoQ Homepage Architecture & Design Content on InfoQ
-
/articles/ai-agent-cli/en/smallimage/ai-agent-cli-thumbnail-1754471958152.jpg)
Keep the Terminal Relevant: Patterns for AI Agent Driven CLIs
Well-designed CLIs are crucial in the agentic AI era—serving both human users and autonomous agents with precision and reliability. Treat CLI output formats as stable API contracts and prioritize adoption of the MCP protocol for agent integration from day one.
-
/articles/backend-finops-cost-efficiency/en/smallimage/thumbnail-backend-finops-cost-efficiency-1754301935666.jpg)
Backend FinOps: Engineering Cost-Efficient Microservices in the Cloud
Backend FinOps integrates financial discipline into microservices, crucial for cutting cloud costs. Challenges such as resource fragmentation and cold starts underscore the need for intelligent design, effective language choice, robust tagging, and automation. Implementing FinOps via IaC, CI/CD checks, and dynamic autoscaling (e.g., Karpenter) ensures sustained efficiency.
-
/articles/guide-curating-technical-conference-track/en/smallimage/thumbnail-logo-image-A-First-Timers-Guide-to-Curating-a-Technical-Conference-Track-1753687916291.jpg)
A First-Timer’s Guide to Curating a Technical Conference Track
One first-time track host shares the process, constraints, and takeaways from building a track from scratch at QCon London 2025.
-
/articles/jakarta-ee-11-overview/en/smallimage/jakarta-ee-11-overview-thumbnail-1753179997354.jpg)
Jakarta EE 11 Overview: Virtual Threads, Records, and the Future of Persistence
Jakarta EE 11 delivers enhancements that include support for Java 17 and 21, integration with Java records and virtual threads, and the introduction of the Jakarta Data specification for unified SQL and NoSQL persistence. This release simplifies enterprise Java and establishes the groundwork for Jakarta EE 12, which will advance capabilities in data management.
-
/articles/green-microservices/en/smallimage/green-microservices-thumbnail-1753175502128.jpg)
Understanding and Mitigating High Energy Consumption in Microservices
Microservices often consume more energy than monoliths due to distributed overhead. Architects can make design decisions that improve sustainability. This article covers several techniques, such as defining clear service boundaries, optimizing service granularity, using energy-efficient deployment regions, and consolidating workloads.
-
/articles/spring-ai-1-0/en/smallimage/spring-ai-1-0-thumbnail-1753091174091.jpg)
Spring AI 1.0 Delivers Easy AI Systems and Services
AI is here to stay, and it represents a unique and wonderful opportunity for Java and Spring developers. For most people, “AI engineering” simply means calling an LLM-based service over HTTP. In this article, we’ll examine the new Spring AI 1.0 project and explore how it can be used to integrate AI more effectively.
-
/articles/architecting-mvp-AI/en/smallimage/architecting-mvp-AI-thumbnail-1752567203613.jpg)
Architecting the MVP in the Age of AI
AI enhances software architecture by informing decisions, suggesting alternatives, and streamlining documentation. While it can’t replace human judgment, it accelerates MVP development and supports experimentation, trade-off analysis, and technical debt management when provided with sufficient context.
-
/articles/optimizing-search-systems/en/smallimage/optimizing-search-systems-thumbnail-1752139120744.jpg)
Optimizing Search Systems: Balancing Speed, Relevance, and Scalability
Innovative software engineer focused on optimizing search performance in dynamic environments. This article highlights key strategies from our QCon San Francisco 2024 presentation, addressing challenges faced by platforms like Uber Eats in data indexing and retrieval. Our advancements ensure swift, relevant user experiences amidst ever-growing datasets.
-
/articles/agentic-ai-architecture-framework/en/smallimage/agentic-ai-architecture-framework-thumbnail-1752043295919.jpg)
Agentic AI Architecture Framework for Enterprises
To deploy agentic AI responsibly and effectively in the enterprise, organizations must progress through a three-tier architecture, Foundation tier, Workflow tier, and Autonomous tier where trust, governance, and transparency precede autonomy.
-
/articles/cloud-prem-architecture-challenges/en/smallimage/cloud-prem-architecture-challenges-thumbnail-1750753890389.jpg)
Engineering Principles for Building a Successful Cloud-Prem Solution
Discover how Cloud-Prem solutions combine cloud efficiency with on-premise control, meeting data sovereignty and compliance demands while optimizing operational costs and enhancing customer security.
-
/articles/apache-kafka-stretch-cluster-failures/en/smallimage/apache-kafka-stretch-cluster-failures-thumbnail-1750152098922.jpg)
Analyzing Apache Kafka Stretch Clusters: WAN Disruptions, Failure Scenarios, and DR Strategies
Proficient in analyzing the dynamics of Apache Kafka Stretch Clusters, I assess WAN disruptions and devise effective Disaster Recovery (DR) strategies. With deep expertise, I ensure high availability and data integrity across multi-region deployments. My insights optimize operational resilience, safeguarding vital services against service level agreement violations.
-
/articles/decentralized-architecture-advice-process/en/smallimage/decentralized-architecture-advice-process-thumbnail-1750145111292.jpg)
Decentralized Architecture Needs More Than Autonomy
Architectural success in decentralized systems depends more on how decisions are made than on system design alone. Replacing control with trust requires visible, structured practices—such as ADRs and advice forums—to build confidence and clarity.