Strategic and technical analysis on Platform Engineering, Cloud and AI.
Launching an IDP is not enough. Failures often come from complexity, non-consumable standards, and governance bolted on too late.
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Reflecting on the major trends of 2025 and how they've shaped the future of software delivery and infrastructure.
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How Serverless is changing the role of Platform Engineering from managing clusters to managing high-level service contracts.
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Why the technical excellence of a platform is not enough, and how a dedicated Product Manager can drive adoption and business value.
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How to move from manual spreadsheets to automated, continuous compliance checks that satisfy both regulators and developers.
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How distributed tracing, profiling, and eBPF are changing how we understand complex cloud-native systems.
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Why data teams need their own 'Internal Developer Platform' to manage pipelines, datasets, and governance at scale.
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Why you should treat your Terraform or Pulumi code like application code and how to implement a testing strategy for your infrastructure.
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Why intentionally injecting failures into your systems is the best way to prevent major production outages.
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Why organizations need a dedicated entry point for AI services to manage costs, security, and performance.
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Exploring the benefits and complexities of using multiple cloud providers and how to decide if it's right for your organization.
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Why Kyverno is becoming the go-to choice for policy-as-code in Kubernetes, without the need to learn a new language.
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How to move from anecdotal 'frustration' to measurable DevEx metrics that drive platform engineering priorities.
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Why thinking about leaving the cloud is a vital part of risk management, and how to build portability without sacrificing innovation.
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How to move from manual firefighting to automated remediation using event-driven patterns and runbooks-as-code.
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How having a detailed inventory of your software components can accelerate vulnerability response and improve compliance.
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How to manage API contracts, versions, and quality standards across hundreds of microservices.
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Comparing the industry-standard Terraform with the Kubernetes-native newcomer, Crossplane. Which one should you choose?
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Why the Internal Developer Platform deserves the same reliability standards as your production applications.
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Why hardcoding secrets is a recipe for disaster and how to use modern vaults and dynamic secrets to secure your applications.
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Why a well-architected landing zone is essential for security, compliance, and multi-team cloud adoption.
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How to integrate security checks early in the development lifecycle to reduce remediation costs and friction.
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How to use the four key metrics from the DevOps Research and Assessment group to track and improve your engineering velocity.
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How to implement Retrieval-Augmented Generation without leaking sensitive business information.
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How to design a self-service model that gives developers autonomy without compromising on security or cost.
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Why infrastructure drift happens and how to use automation to ensure your code always matches reality.
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How Backstage.io helps organizations centralize service catalogs, documentation, and scaffolding in one place.
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Why securing your build pipeline and dependencies is just as important as securing your production code.
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A practical guide to defining Service Level Indicators and Objectives that align engineering efforts with user experience.
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Why environmental sustainability is becoming a key metric for IT organizations and how to start your GreenOps journey.
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Moving from simple reporting to operational cost control through architectural choices and automation.
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How OPA and Gatekeeper enable automated governance by turning rules into code within your Kubernetes clusters.
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How to safely share clusters between teams using Namespaces, Vcluster, and Network Policies.
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Why internal platforms fail without product management, and how to shift from projects to products.
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Why Infrastructure as Code and GitOps are the technical foundations for secure, traceable, and repeatable delivery at scale.
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How to move from AI experiments to industrialized, governed, and auditable models in regulated financial environments.
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In critical environments, observability isn't just about dashboards—it's about understanding risk, resilience, and traceability.
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What leaders should prepare for: IDPs as products, policy-driven governance, AI-enabled operations, and measurable engineering economics.
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A platform team is not a support team. It is a product team with engineering excellence, clear ownership, and measurable outcomes.
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FinOps is most effective when implemented through the platform: standardization, visibility, and guardrails that scale with delivery.
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Golden Paths provide paved roads to production: secure-by-default workflows that reduce cognitive load and accelerate delivery.
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The most effective security strategy is to embed guardrails into platform workflows—so secure delivery becomes the default behavior.
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A Cloud Operating Model turns cloud adoption into repeatable execution—balancing autonomy, security, reliability, and cost control.
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AI changes platforms: better developer experience, faster operations, and new governance needs—if you integrate it with discipline.
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An IDP is a product with users, adoption, and outcomes. Treating it as such is the difference between success and shelfware.
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Security cannot be bolted on after delivery. A DevSecOps platform makes secure-by-default workflows scalable and auditable.
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Why Platform Engineering has become a core capability for modern IT organizations—and how it changes speed, reliability, and governance.
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