Strategic and technical analysis on Platform Engineering, Cloud and AI.
Putting LLMs in production is more than an API call. Without dedicated observability (cost, quality, security), incidents become invisible. Here are the signals that matter.
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A platform contract makes the platform’s promises explicit: interfaces, guardrails, and versioning. It’s the foundation for adoption and for industrializing golden paths.
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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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