InfoQ Homepage Articles
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Designing Continuous Authorization for Sensitive Cloud Systems
Most cloud systems make one authorization decision at login. Everything after runs on trust established at authentication time. For systems handling regulated data, that gap is where breaches happen. This article presents a continuous authorization architecture covering risk-tiered evaluation, behavioral baselines, privacy-preserving audit trails, and a phased and incremental rollout.
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Governing AI in the Cloud: a Practical Guide for Architects
In this article, the author outlines a practical approach to AI governance in the cloud, covering discovery of shadow AI, data classification at creation, IAM-based enforcement, policy-as-code, and operational controls. The article shows how organizations can embed governance into delivery pipelines, balancing security, compliance, and developer productivity without relying on manual processes.
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Artificial Intelligence-Driven Phishing: How Phishing Technique Is Evolving and Implemented
In this article, the author examines how AI is transforming phishing from a manual, targeted activity into an automated and scalable attack model. The article breaks down each stage of the phishing lifecycle, showing how AI improves reconnaissance, profiling, content generation, delivery, and interaction, while outlining layered defenses that combine controls, processes, and user awareness.
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The Technology Adoption Curve, Twenty Years On
Today, June 8th, InfoQ celebrates 20 years. This is not a comprehensive history, but a deliberately selective look at the technologies and practices InfoQ identified early, where they sit on the adoption curve in 2026, and how that curve may evolve over the next five to ten years.
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Article Series: Securing the AI Stack: from Model to Production
This series provides your roadmap for the machine age, exploring how to move from vulnerable prototypes to resilient systems through layered defense, robust MLOps, and integrated governance.
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Architectural Change Cases: a Practical Tool for Evolutionary Architectures
Architectural change cases extend architecture decision record (ADR) thinking by evaluating how decisions may evolve over time. Change cases expose hidden assumptions and help teams estimate the reversibility and cost of change.
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Two Misconfigurations That Caused Spark OOM Failures on Kubernetes
After migrating Spark pipelines to Azure Kubernetes Service, two infrastructure settings interacted destructively: spark.kubernetes.local.dirs.tmpfs=true backed shuffle spill with RAM instead of disk, and a hard podAffinity rule forced all executors onto one node. Together, they caused repeated OOM kills invisible to standard diagnostics.
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Why Vector Search Alone Isn't Enough: Hybrid Retrieval for RAG
In this article, author Aaditya Chauhan discusses the limitations of RAG pipelines based purely on vector search and how an internal omni-search application using Reciprocal Rank Fusion (RRF) that combines BM25 and vector results, can enhance the search solution.
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The AI Productivity Paradox in Test Automation: Moving beyond Structural Validation to Perception and Intent
The AI productivity paradox states that AI scales whatever abstraction it is built on. If that abstraction is structurally brittle, it scales structural brittleness. This article shows that to build a future of reliable, AI-driven test automation, we must stop scaling DOM-centric abstractions and build a new testing paradigm grounded in perception and intent.
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Stragglers, Not Failures: How Adaptive Hedged Requests Reduce p99 Latency by 74 Percent
In fan-out microservice architectures, slow-but-completing requests accumulate across services and drive p99 latency far higher than per-service metrics suggest. This article presents an adaptive hedging mechanism that uses DDSketch for real-time quantile estimation, windowed rotation to handle distribution drift, and a token-bucket budget to prevent load amplification.
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Architecting Cloud-Native Kafka: from Tiered Storage towards a Diskless Future
This article explores Kafka's transition toward a cloud-native architecture, examining how tiered storage, FinOps telemetry, elastic consumer scaling, virtual clusters, and Share Groups reshape the operational and economic model of event streaming platforms. It also analyzes emerging diskless-storage proposals and their architectural trade-offs.
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The Schema Proliferation Problem in Kafka and Flink Pipelines: How to Solve It
Schema proliferation builds slowly and gets expensive fast. One schema per event type feels right until there are ten tables, union queries spanning all of them, and a single field rename touching every schema. Discriminator-based schema consolidation collapses that to two tables, turning multi-table unions into a single query, while new variants are additive and don't break existing consumers.