Ultimate Guide to Rightsizing for Variable Workloads
Monitor vCPU, memory and I/O, use automation and tagging to rightsize cloud workloads and cut costs by 30–50% while maintaining performance.
Read moreBlog posts in the Cloud Optimization category
Monitor vCPU, memory and I/O, use automation and tagging to rightsize cloud workloads and cut costs by 30–50% while maintaining performance.
Read moreUse impact analysis to map dependencies, focus testing, and cut post-release defects and rework—improving speed, reliability and reducing downtime costs.
Read moreCompare Kubernetes cost allocation and chargeback: visibility vs internal billing, when to use each, tagging best practices and implementation tips.
Read morePractical steps to lower CDN egress: aggressive caching, Brotli/WebP compression, multi‑CDN routing, regional optimisation and moving static assets to CDN storage.
Read moreHow Spot Instances can cut cloud bills by up to 90% — ideal for stateless, fault‑tolerant workloads; learn interruption risks, pricing differences and best practices.
Read moreCut big data cloud costs by rightsizing, auto-scaling, Spot instances, containerisation and FinOps — save up to 70% without hurting performance.
Read moreCentralise telemetry, adopt OpenTelemetry, automate CI/CD with GitOps, and apply AI for anomaly detection to secure and optimise multi‑cloud observability.
Read moreConnect legacy on‑prem systems to private cloud APIs using gateways, containerisation and phased migration, with security, tools and deployment steps.
Read moreCompare backup, pilot light, warm and hot standby DR patterns, costs, RTO/RPO trade-offs and practical tips for automation, testing and network optimisation.
Read moreCompare seven leading cloud patch compliance tools, their coverage, reporting, automation and best use cases for AWS, Azure, GCP and hybrid environments.
Read morePractical guidance to optimise AWS RDS: choose the right instance and storage, tune engine parameters, speed up queries, use RDS features and monitor key metrics.
Read moreAI-powered forecasting for multi-cloud billing using time-series models, anomaly detection and reinforcement learning to cut variance, speed analysis and improve ROI.
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