Original, implementation-focused research for engineering, finance and technology leaders making decisions about FinOps, AWS, Azure, Google Cloud, Kubernetes, platform engineering, security, migration and reliability.
Understand why Cloud Run costs continue during quiet periods, then review minimum instances, billing settings and concurrency against production requirements.
Read the guide7 focused cloud engineering collections
Query scans, idle containers and network transfer: investigate the workload before changing its configuration.
Allocation, anomaly response, commitments, AI economics and the operating model behind durable savings.
Explore FinOps consultingWorkload allocation, requests, autoscaling, node provisioning and provider-specific cost decisions.
Internal developer platforms, golden paths, CI/CD and delivery measures grounded in developer workflows.
Explore platform engineering consultingIdentity, secure builds, SBOMs, provenance, policy as code and release controls designed around risk.
Explore DevSecOps consultingSLOs, observability, incident learning, RTO, RPO and recovery exercises across cloud platforms.
Landing zones, migration strategy, cutover, architecture assurance and provider-specific foundations.
29 practical guides and field notes
Investigate Google Cloud data transfer charges by SKU and traffic path, then evaluate cross-region traffic, Cloud NAT and caching without sacrificing resilience.
Find expensive BigQuery jobs, reduce unnecessary data scans, and choose cost controls that fit on-demand or capacity billing without disrupting reporting.
Build a cloud cost anomaly management process across AWS, Azure and Google Cloud with useful thresholds, accountable routing, investigation evidence and measurable response.
A practical FinOps for AI framework for allocating GPU and model spend, measuring cost per outcome, controlling experiments and optimizing production inference.
Compare native cloud tools, FinOps platforms, internal automation, consulting and managed FinOps services by capability, ownership, cost and operating maturity.
Reduce Amazon EKS cost through pod allocation, resource rightsizing, Karpenter NodePools, consolidation, Spot diversification, Graviton and commitment-aware capacity design.
Design a practical DevSecOps delivery system with threat-based controls, workload identity, dependency governance, SBOMs, build provenance and policy as code.
Design a cloud disaster recovery strategy for AWS, Azure or Google Cloud using business impact, RTO and RPO targets, tested recovery paths and explicit cost tradeoffs.
Decide what to build, buy and integrate for an internal developer platform using workflow research, a thinnest viable platform, golden paths and adoption evidence.
How to build a durable Azure FinOps practice across cost data, workload ownership, rightsizing, Reservations, Savings Plans and unit economics.
How to design an Azure landing zone that balances subscription autonomy with governance across identity, policy, networking, operations and FinOps.
An Azure migration framework for portfolio assessment, workload decisions, landing zone readiness, migration waves, data cutover and source retirement.
How to design a secure Azure delivery system using trusted artifacts, infrastructure as code, federated identity, safe deployment, AKS and DORA metrics.
How to build a Google Cloud FinOps practice using billing exports, ownership, rightsizing, GKE, BigQuery, CUDs and business unit economics.
How to design a Google Cloud landing zone across resource hierarchy, IAM, Organization Policy, Shared VPC, security, operations and FinOps.
A Google Cloud migration framework for continuous discovery, workload decisions, foundation readiness, migration waves, data cutover and source retirement.
How to design secure Google Cloud delivery and SRE using pipeline identity, Cloud Deploy, GKE, canaries, SLOs, error budgets and DORA metrics.
Build a practical FinOps operating model for allocation, forecasting, anomaly response, commitment management and cloud unit economics at scale.
Optimize Kubernetes cost across EKS, AKS and GKE through allocation, pod rightsizing, autoscaling, node efficiency and reliability controls.
Run an evidence-based AWS Well-Architected Review, prioritize findings by business risk and turn recommendations into a funded improvement plan.
Plan a secure cloud migration with portfolio discovery, the 7 Rs, landing zones, dependency-based waves, tested cutovers and operating readiness.
Design a DevOps and SRE operating model that connects service ownership, secure CI/CD, SLOs, incident learning, platforms and DORA metrics.
Reduce AWS costs with a structured plan for billing data, ownership, EC2, storage, databases, networking, commitments and financial guardrails.
Compare AWS Savings Plans and Reserved Instances by flexibility, discount scope, capacity, risk and workload fit before building a commitment portfolio.
Compare a DevOps consultant, permanent hire and hybrid model by urgency, ownership, capability, continuity, cost, risk and knowledge transfer.
Build a credible DevOps career through systems fundamentals, cloud, infrastructure as code, CI/CD, containers, observability and portfolio evidence.
Reduce cloud cost through risk-classified changes, SLO evidence, staged validation, rollback planning and verified savings across AWS, Azure and GCP.
Define credible SLIs, SLO targets, error budgets and burn-rate alerts that connect customer experience with engineering and product decisions.
Design internal developer platform golden paths with product research, self-service workflows, secure defaults, extension points and adoption metrics.