InfoQ Homepage Cloud Content on InfoQ
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/articles/high-availability-not-resilience-cloud/en/smallimage/high-availability-not-resilience-cloud-thumbnail-1790670587417.jpg)
High Availability is Not Resilience: Why Cloud Systems Fail When it Matters Most
A routine TLS 1.3 upgrade silently broke Route 53 health checks, causing a CDN to stop routing traffic to a healthy region while internal dashboards showed nothing wrong. This article examines why HA and resilience are different problems, how control-plane dependencies create invisible failure modes, and why recovery capability erodes without explicit ownership.
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/articles/modular-edge-computing/en/smallimage/modular-edge-computing-thumbnail-1790163631197.jpg)
Modular Edge Computing at Multi-Tenant SaaS Scale on Cloudflare Workers
At multi-tenant SaaS scale, a monolithic edge worker creates deployment coupling and broad blast radius. The article presents a modular Cloudflare Workers architecture using service bindings, with image optimization as a worked example of per-tenant format negotiation and device-aware sizing. It covers multi-CDN differences, staged releases, configuration, and testing.
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/articles/secure-scalable-facial-verification/en/smallimage/secure-scalable-facial-verification-thumbnail-1789468796366.jpg)
Architecting Secure and Scalable Facial Verification Systems
When three thousand employees verify at once, synchronous API calls collapse. This article presents a four-layer architecture for high-volume face verification: client-side filtering that cut cloud costs 30%, decoupled detection and verification enabling 10x scaling, risk-based dynamic thresholds, and zero-trust privacy with consent gates and automated data purging for GDPR and HIPAA.
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/articles/chaos-engineering-ecs-payments/en/smallimage/chaos-engineering-ecs-payments-thumbnail-1788254676411.jpg)
Implementing Chaos Engineering in Financial Payment Systems: Lessons from Enterprise ECS Deployments
Standard chaos engineering assumes experiments stop cleanly, blast radius is knowable in advance, and production is fair game. Payment systems violate all three. Salim Adedeji describes ECS-specific failure modes from enterprise deployments: a 60-second DNS TTL that produced 93-second failover, retry logic amplifying database load 2.4x, and AZ rebalancing loops that generic tooling misses.
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/articles/gcp-wif-scale/en/smallimage/gcp-wif-scale-thumbnail-1787838950646.jpg)
Eliminating Long-Lived Credentials in GCP with Workload Identity Federation
Long-lived GCP service account keys are secrets that must be managed forever, are hard to rotate, and are easy to leak. Scaling Workload Identity Federation to 120+ production projects shows why it changes how machine identity is approached entirely: keys are secrets to manage, federated identities are trust relationships configured once, gated by attribute conditions.
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/articles/cloud-devops-trends-2026/en/smallimage/infoq-trends-report-small-logo-1785421405039.jpeg)
InfoQ Cloud and DevOps Trends Report - 2026
InfoQ editorial staff and friends of InfoQ are discussing the current trends in the domain of Cloud and DevOps as part of the process of creating our annual 2026 trends report.
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/articles/pull-based-migration/en/smallimage/pull-based-migration-thumbnail-1784812950594.jpg)
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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/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/continuous-authorization-cloud/en/smallimage/continuous-authorization-cloud-thumbnail-1781599988842.jpg)
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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/articles/adoption-curve-twenty/en/smallimage/20-birthday-InfoQ-thumb-image-updated-1780931679034.jpg)
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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/articles/spark-oom-kubernetes-misconfigurations/en/smallimage/spark-oom-kubernetes-misconfigurations-thumbnail-1780044756757.jpg)
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.