# Platform Engineering Blog The global home for Platform Engineers. Join the #1 platform engineering community. Learn from leading DevOps and cloud native experts. Connect with fellow platform practitioners. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Infrastructure identity for platform engineers DevFeed: [Infrastructure identity for platform engineers]() Original publisher: [Read original article]() Author: Sam Barlien Published: 2026-09-08T12:20:22Z Content type: tutorial Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [internal developer platform](), [Zero Trust](), [IAM](), [AI Agent]() Tags: [iam](), [identity](), [internal-developer-platform](), [platform-engineering](), [zero-trust]() ### AI overview A guide for platform engineers on adopting infrastructure identity: assigning cryptographic identities and short-lived, just-in-time access to people, machines, workloads, and AI agents. It argues that this approach can replace static secrets and network-based trust in an internal developer platform. ### Source excerpt Discover how platform engineers can eliminate static secrets and embed Zero Trust into their IDP using short-lived, cryptographic infrastructure identities. ## How platform engineering 2.0 mitigates AI security and compliance risks DevFeed: [How platform engineering 2.0 mitigates AI security and compliance risks]() Original publisher: [Read original article]() Author: Steven Vaughan-Nichols Published: 2026-09-04T16:46:09Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [Security](), [Securing AI](), [Responsibility & Safety]() Tags: [ai-agents](), [compliance](), [infrastructure](), [large-language-models-llms](), [platform-engineering](), [policy](), [secure-by-default](), [security]() ### AI overview The article explains how Platform Engineering 2.0 evolves existing Kubernetes, pipeline, internal developer platform, and process foundations to support production use of LLMs and AI agents. It emphasizes platform-level isolation, governance, policy-as-code, guardrails, and continuous compliance to mitigate AI security, regulatory, and operational risks. ### Source excerpt Discover how the shift from Platform Engineering 1.0 to 2.0 addresses critical AI security and compliance challenges. Learn how native model governance and workload isolation establish a scalable, secure foundation for integrating AI agents and LLMs into production workflows. ## What is platform engineering? DevFeed: [What is platform engineering?]() Original publisher: [Read original article]() Author: Luca Galante Published: 2026-09-03T16:27:44Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [internal developer platform](), [AI Bots](), [Artificial Intelligence](), [cloud-infrastructure]() Tags: [agents](), [ai](), [ai-agents](), [developer-platform](), [engineering](), [idp](), [infrastructure](), [internal-developer-platform](), [platform](), [platform-engineering](), [software-development](), [workflows]() ### AI overview Platform engineering is presented as the discipline of building internal platforms that provide self-service paths for software teams and increasingly AI agents. The article explains how Internal Developer Platforms standardize and automate engineering work, and how Agentic Development Platforms add infrastructure and path specifications for collaboration between engineers and AI agents. ### Source excerpt Platform engineering is the method and discipline of designing and building platforms that enable self-service capabilities for teams, and increasingly AI agents, to automate the recurring aspects of knowledge work. ## 9 things to consider before choosing an IaC platform in 2026 DevFeed: [9 things to consider before choosing an IaC platform in 2026]() Original publisher: [Read original article]() Author: Jonah Kowall Published: 2026-08-26T14:33:56Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Infrastructure as code](), [Architecture & Design](), [Provisioning](), [Cloud](), [Terraform]() Tags: [2026](), [ci](), [cloud](), [evaluation](), [iac](), [infrastructure](), [infrastructure-as-code](), [opentofu](), [policy](), [terraform](), [workflows]() ### AI overview This 2026 article presents nine considerations for evaluating an infrastructure as code platform. It emphasizes that mature IaC now involves coordinating changes, managing access, enforcing policies, reviewing infrastructure changes, and keeping environments synchronized--not only provisioning cloud resources. It recommends assessing whether a platform is necessary, examining its execution layer and scalability, testing it under concurrent workloads and failures, and ensuring that engineers beyond the platform builder can use it effectively. ### Source excerpt IaC platform evaluation in 2026: nine things to test, from execution and dependency handling to policy enforcement, support quality and AI workflows. ## What is a Minimum Viable Platform (MVP)? DevFeed: [What is a Minimum Viable Platform (MVP)?]() Original publisher: [Read original article]() Author: Luca Galante Published: 2026-08-21T14:37:28Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [internal developer platform](), [Developer Platform](), [Shared Responsibility Model]() Tags: [engineering](), [evaluation](), [gartner](), [idp](), [internal-developer-platform](), [organizational](), [platform](), [platform-engineering](), [shared-responsibility](), [speed]() ### AI overview This article explains why platform engineering initiatives often fail despite widespread adoption of internal developer platforms. It argues that culture, process, and delivery speed matter more than tooling choices, and recommends starting with a Minimum Viable Platform to build stakeholder support and deliver value quickly. ### Source excerpt Unlock success in platform engineering: Avoid common pitfalls, embrace MVP approach, and win stakeholder support for a transformative platform initiative. ## Platform Engineering Must Adapt to AI-Driven Coding and Agentic Workloads DevFeed: [Platform Engineering Must Adapt to AI-Driven Coding and Agentic Workloads]() Original publisher: [Read original article]() Author: Pankaj Gupta Published: 2026-08-14T06:43:34Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [ai-coding](), [Artificial Intelligence](), [Model Context Protocol](), [Security](), [GPU]() Tags: [agentic](), [agents](), [ai](), [ai-coding](), [model-context-protocol](), [permissions](), [platform-engineering](), [security](), [tooling]() ### AI overview The article argues that platform engineering must evolve as AI-generated code and agentic workloads change delivery, infrastructure, identity, permissions, and security requirements. It highlights parallel builds, automated policy checks, scalable review tooling, GPU and TPU allocation, MCP gateways, and guardrails as platform needs. ### Source excerpt Platform engineering has hit near-universal adoption, but five forces are pushing platforms past their limits. Here is each one and what your platform must do. ## Platforms are sitting on buried knowledge. Your agents are forcing you to dig it up DevFeed: [Platforms are sitting on buried knowledge. Your agents are forcing you to dig it up]() Original publisher: [Read original article]() Author: Mallory Haigh Published: 2026-07-28T10:29:36Z Content type: opinion Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [Artificial Intelligence]() Tags: [agentic](), [agents](), [ai](), [evaluation](), [platform-engineering](), [policy](), [security]() ### AI overview The article argues that trust in AI agents is primarily a platform engineering problem rather than a problem solved by improving agents alone. Platform teams must expose organizational knowledge through evaluation infrastructure, explicit definitions of done, and policy-as-code so agents can produce work that matches security, quality, and production expectations. ### Source excerpt The trust problem with AI agents is actually a platform engineering problem. Here's why platform teams are the only ones who can solve it. ## From pilot to production: The platform team's playbook for scaling AI coding agents in regulated industries DevFeed: [From pilot to production: The platform team's playbook for scaling AI coding agents in regulated industries]() Original publisher: [Read original article]() Author: Eric Paulsen Published: 2026-07-24T11:13:47Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [AI-assisted coding](), [ai-governance](), [observability](), [shadow AI](), [Deployment](), [coding]() Tags: [ai-adoption](), [ai-coding-agents](), [ai-governance](), [developers](), [financial-services](), [government](), [observability](), [shadow-ai]() ### AI overview This article presents a platform-team playbook for scaling AI coding agents from pilots to governed production in regulated industries. It emphasizes governance, observability, production infrastructure, and controls that provide visibility into agent actions, model usage, data access, token consumption, and costs. ### Source excerpt Scaling AI coding agents in regulated industries requires more than just successful pilots; it demands robust governance and production-ready infrastructure. Discover how platform teams can bridge the gap between experimentation and compliance by implementing observability, structured context engineering, and ephemeral workspace patterns to ensure safe, scalable AI adoption. ## Why putting a pane of glass on a pile of sh\*t doesn't solve your problem DevFeed: [Why putting a pane of glass on a pile of sh\*t doesn't solve your problem]() Original publisher: [Read original article]() Author: Lee Ditiangkin Published: 2026-07-23T08:16:12Z Content type: opinion Language: en Sources: [Platform Engineering Blog]() Topics: [DevOps](), [configuration](), [migration](), [Orchestration](), [Kubernetes](), [Terraform](), [Cloud](), [dashboards]() Tags: [cloud](), [configuration](), [dashboards](), [devops](), [migration](), [opinion](), [orchestration](), [terraform]() ### AI overview This opinion article argues that adding a visual "single pane of glass" does not fix underlying platform problems. It advocates addressing difficult issues such as legacy migration, configuration management, collaboration between cloud operations and developers, and infrastructure orchestration to improve maintainability and developer self-service. ### Source excerpt There's been this rumour going around lately, according to which the first step to successful platform transformations is visualizing what you have. "Putting a single pane of glass on top of everything". I believe this is plain nonsense. In this short opinion piece I want to articulate a long-lived conviction of mine: Put a pane of glass on a pile of sh*t and all your developers can see is a pile of sh*t. But let's briefly rewind: you're tasked with somehow "building a platform". ## What does a platform product manager do? DevFeed: [What does a platform product manager do?]() Original publisher: [Read original article]() Author: Mallory Haigh Published: 2026-07-23T08:14:05Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [internal developer platform](), [Product Management](), [Developer experience]() Tags: [architecture](), [developer-experience](), [developer-platform](), [developers](), [engineering](), [internal-developer-platform](), [management](), [organizational](), [platform](), [platform-engineering](), [platforms](), [product](), [product-management](), [product-strategy](), [strategy](), [technical](), [user-research]() ### AI overview This guide explains the role of a Platform Product Manager (PPM) in driving strategy for an Internal Developer Platform. PPMs connect technical platform capabilities with developer needs through user research, feedback loops, roadmaps, stakeholder management, and outcome metrics. The article distinguishes product thinking from project management and describes how continuous prioritization and clear platform boundaries support adoption. ### Source excerpt Platform Product Managers drive internal developer platform strategy, bridging technical capabilities and developer needs through research, roadmaps, and stakeholder management. ## Golden cage syndrome: Why 80% of Internal Developer Platforms fail DevFeed: [Golden cage syndrome: Why 80% of Internal Developer Platforms fail]() Original publisher: [Read original article]() Author: Vladimir Mikhalev Published: 2026-07-23T08:09:23Z Content type: opinion Language: en Sources: [Platform Engineering Blog]() Topics: [internal developer platform](), [Platform Engineering](), [Developer Platform](), [Backstage](), [Kubernetes](), [Terraform]() Tags: [backstage](), [cognitive-load](), [complexity](), [developer-platform](), [internal-developer-platform](), [kubernetes](), [platform-engineering](), [policy](), [terraform]() ### AI overview This opinion argues that internal developer platforms often fail when they prioritize governance and control over developer autonomy and ease of use. It describes a "golden cage" pattern in which rigid, opaque abstractions drive developers toward native tools and workarounds. The article highlights platform adoption, developer friction, cognitive load, and the need to treat a platform as a product. ### Source excerpt Learn the three fatal mistakes of building and IDP and how to succeed with a Platform as a Product (PaaP) mindset ## Why platform engineering will eat the world DevFeed: [Why platform engineering will eat the world]() Original publisher: [Read original article]() Author: Kaspar von Grünberg Published: 2026-07-23T08:08:12Z Content type: opinion Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [internal developer platform](), [Developer Platform](), [software-development](), [Software Engineering](), [Developer experience](), [site-reliability-engineering](), [SRE](), [observability](), [Security]() Tags: [developer-experience](), [developer-platform](), [development](), [engineering](), [internal-developer-platform](), [operations](), [platform](), [platform-engineering](), [security](), [software](), [software-development](), [sre]() ### AI overview The article argues that platform engineering is becoming the dominant model for large-scale software development. It describes platforms as structured digital production lines that reduce time to market, consolidate functions such as operations, databases, security, observability, and SRE, and support greater speed, scale, and security. ### Source excerpt Platform engineering is transforming software development, streamlining operations, and redefining roles. Embrace the shift or risk becoming obsolete. ## Metrics that matter: Measuring platform success and maturity DevFeed: [Metrics that matter: Measuring platform success and maturity]() Original publisher: [Read original article]() Author: Mallory Haigh Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [data]() Tags: [engineering](), [infrastructure](), [measurement](), [metrics](), [platform](), [platform-engineering]() ### AI overview This article argues that platform teams need structured success metrics to demonstrate value, secure funding, and guide improvement. It presents measurement across technical, adoption, and business dimensions, aligned with platform engineering maturity stages, and explains why traditional individual-output metrics fail to capture platform benefits such as reduced deployment friction, knowledge sharing, and error prevention. ### Source excerpt Frameworks to measure platform success and maturity using DORA, SPACE, and MVP metrics--linking technical outcomes to ROI, adoption, and funding ## The CI/CD moment for data analytics DevFeed: [The CI/CD moment for data analytics]() Original publisher: [Read original article]() Author: Gaurav Nanda Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [data analytics](), [DataOps](), [real-time](), [data-engineering](), [CI/CD](), [Kafka](), [apache-flink]() Tags: [ai](), [analytics](), [apache-flink](), [architectures](), [bridging](), [cost](), [data-analytics](), [data-engineering](), [engineering](), [event](), [fraud](), [google](), [insights](), [kafka](), [latency](), [real-time](), [scale](), [streaming](), [systems](), [tools]() ### AI overview The article argues that data analytics is approaching a CI/CD-like transition toward continuous analytics. It describes how multi-step pipelines introduce latency, operational risk, and maintenance burden, and explains why real-time insight is becoming a baseline platform capability for applications such as personalization, fraud detection, reliability, and AI-driven features. ### Source excerpt How converging OLTP and OLAP architectures are driving 'Continuous Analytics', the CI/CD moment for data to deliver real-time, unified insights and operational simplicity. ## Five product management principles for internal developer platforms DevFeed: [Five product management principles for internal developer platforms]() Original publisher: [Read original article]() Author: Mallory Haigh Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [internal developer platform](), [Product Management](), [Platform Engineering](), [Developer Platform](), [Software Engineering](), [Netflix]() Tags: [automation](), [business-value](), [cognitive-load](), [compliance](), [developer](), [developer-platform](), [developers](), [engineering](), [infrastructure](), [internal-developer-platform](), [management](), [platform-engineering](), [platforms](), [software-engineering](), [tooling]() ### AI overview The article presents five product management principles for internal developer platforms. It argues that platform teams should treat developers as customers, measure developer outcomes and adoption, reduce cognitive load through golden paths, and continuously evolve platforms to deliver business value. ### Source excerpt Discover five product management principles crucial for driving adoption and business value in internal developer platforms, focusing on developer needs ## How to win executive buy-in for your Internal Developer Platform DevFeed: [How to win executive buy-in for your Internal Developer Platform]() Original publisher: [Read original article]() Author: Mallory Haigh Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [internal developer platform](), [Platform Engineering](), [Developer Platform]() Tags: [article](), [business](), [cognitive-load](), [developer-platform](), [executive](), [idp](), [internal-developer-platform](), [leadership](), [platform](), [platform-engineering]() ### AI overview This article presents tactical frameworks for winning sustained executive sponsorship for an Internal Developer Platform. It explains how to translate technical platform benefits into business outcomes such as faster time to market, lower operational costs, reduced security risk, and improved talent retention, while addressing executive objections, modeling ROI, building cross-functional support, and driving adoption. ### Source excerpt Tactical frameworks to secure executive sponsorship for an IDP: translate benefits into business outcomes, model ROI, handle objections, and drive adoption. ## GitOps tooling 101 DevFeed: [GitOps tooling 101]() Original publisher: [Read original article]() Author: Artem Lajko Published: 2026-07-23T05:40:01Z Content type: tutorial Language: en Sources: [Platform Engineering Blog]() Topics: [GitOps](), [Tooling](), [Platform Engineering](), [Git](), [Kubernetes](), [CI/CD]() Tags: [git](), [guide](), [how-to](), [infrastructure](), [kubernetes](), [learn](), [platform-engineering](), [tooling](), [tools]() ### AI overview A guide to selecting GitOps tools, comparing Argo CD, Flux CD, and Sveltos. It explains GitOps principles and how tool capabilities align with operational topology, team capabilities, and platform engineering goals. ### Source excerpt Choosing the right GitOps tool is complex. This guide cuts through the noise, comparing Argo CD, Flux CD, and Sveltos. Learn the four GitOps principles, how to match tool strengths to your operational topology, and the crucial 80% of discipline needed for successful adoption ## The continuous validation framework for data pipelines. DevFeed: [The continuous validation framework for data pipelines.]() Original publisher: [Read original article]() Author: Niruta Talwekar Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [data](), [DataOps](), [Data Quality](), [data observability](), [CI/CD](), [data-processing](), [DevOps](), [Platform Engineering]() Tags: [ci-cd](), [data](), [data-quality](), [devops](), [platform-engineering](), [provenance](), [software-testing](), [streaming]() ### AI overview The article introduces the Continuous Validation Framework (CVF), an end-to-end methodology for validating data pipelines through architectural isolation, configuration-driven data quality management, and continuous automation based on lineage-driven impact analysis. It reports production results including a 50% reduction in incidents and an 80% improvement in detecting data quality issues. ### Source excerpt A framework for automated, end-to-end data pipeline validation using isolation, declarative quality checks, and lineage-driven impact analysis. ## Accelerate teams with platform engineering and policy-as-code DevFeed: [Accelerate teams with platform engineering and policy-as-code]() Original publisher: [Read original article]() Author: Rafael Ferreira Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [DevOps](), [Security](), [Code](), [Deployment](), [opa](), [JSON](), [rego](), [YAML](), [Git]() Tags: [best-practices](), [deployment](), [developer](), [devops](), [engineering](), [git](), [json](), [kyverno](), [platform](), [platform-engineering](), [policy](), [rego](), [security]() ### AI overview This article explains how platform engineering uses internal platforms, golden paths, automation, and self-service to reduce developer cognitive load while improving security, compliance, cost control, and delivery speed. It also presents Policy-as-Code as a way to encode rules in versioned, testable definitions and validate them continuously before deployment, with tools such as OPA and Kyverno providing immediate feedback and audit trails. ### Source excerpt Move from DevOps to platform engineering. Learn golden paths, platform thinking, and why demand is rising for skilled platform engineers ## The 4 levels of agentic software development DevFeed: [The 4 levels of agentic software development]() Original publisher: [Read original article]() Author: Kaspar von Grünberg Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [AI Development](), [code productivity](), [software-development](), [cloud-infrastructure]() Tags: [agentic](), [ai](), [autonomous](), [development](), [platform](), [productivity](), [software-development]() ### AI overview The article presents four levels of agentic software development in the enterprise, defined by how much work humans must initiate and approve. It argues that productivity gains depend less on procuring advanced models than on restructuring the software production platform so agents can reliably access code, execute work in suitable environments, and participate in validation workflows. As organizations advance through the levels, humans shift from execution to review, orchestration, and system design. ### Source excerpt Discover the four levels of agentic software development. Learn how evolving your platform from human-in-the-loop to autonomous systems drives up to 30% throughput gains ## 10 Platform engineering predictions for 2026 DevFeed: [10 Platform engineering predictions for 2026]() Original publisher: [Read original article]() Author: Luca Galante Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [Artificial Intelligence](), [Security](), [Architecture & Design](), [Vibe coding](), [Kubernetes](), [Terraform]() Tags: [2026](), [agentic](), [agentic-ai](), [ai](), [ai-agents](), [architecture](), [code](), [code-generation](), [coding](), [finops](), [iam](), [infrastructure](), [kubernetes](), [models](), [platform](), [platform-engineering](), [predictions](), [security](), [terraform](), [vulnerabilities]() ### AI overview The article presents ten predictions for platform engineering in 2026, focusing on the convergence of AI, security-by-design, developer experience, observability, and FinOps. It argues that platform teams will increasingly govern autonomous AI agents, secure AI-generated infrastructure code, and use AI-driven optimization to re-architect systems for cost and latency targets. ### Source excerpt Explore the 10 platform engineering predictions for 2026. See how AI, FinOps, and new security models will fundamentally redefine the platform team's role and architecture. ## Five key recommendations for platform teams in 2026 DevFeed: [Five key recommendations for platform teams in 2026]() Original publisher: [Read original article]() Author: Sam Barlien Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [Artificial Intelligence](), [AI Platforms/Deployment]() Tags: [2026](), [ai](), [complexity](), [engineering](), [leadership](), [organizational](), [platform-engineering](), [platforms]() ### AI overview The article presents five recommendations for platform teams in 2026, based on reported execution gaps in measuring success, developer adoption, proving return on investment, integrating AI, and managing multiple platforms. It emphasizes disciplined execution and treating platform engineering as a product with dedicated leadership. ### Source excerpt Five actionable recommendations for platform teams in 2026 to maximize ROI, drive adoption, integrate AI, and build effective, scalable platform strategies ## Call for Proposals (CfP) open: Speak at PlatformCon 2026! DevFeed: [Call for Proposals (CfP) open: Speak at PlatformCon 2026!]() Original publisher: [Read original article]() Author: Luca Galante Published: 2026-07-23T05:40:01Z Content type: news Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [GitOps](), [Infrastructure as code](), [Kubernetes](), [Tooling](), [Security]() Tags: [2026](), [conference](), [event](), [iac](), [kubernetes](), [platform-engineering](), [security]() ### AI overview PlatformCon 2026 has opened its Call for Proposals for virtual pre-recorded talks and live workshops focused on platform engineering. The event seeks practical experiences, architectural insights, platform tooling, and real-world technology combinations. ### Source excerpt The PlatformCon 2026 Call for Proposals (CfP) is open! Submit your talk or workshop proposal to share your platform engineering insights. ## Alpha features in Kubernetes 1.36 DevFeed: [Alpha features in Kubernetes 1.36]() Original publisher: [Read original article]() Author: Nigel Douglas Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Kubernetes](), [AI Platform](), [Hardware](), [Scalability](), [Security](), [API](), [cpu](), [real-time]() Tags: [ai-ml](), [api](), [cpu](), [hardware](), [kubernetes](), [real-time](), [scalability](), [security]() ### AI overview An overview of selected Alpha-stage features planned for Kubernetes 1.36, focusing on five Dynamic Resource Allocation enhancements for AI/ML workloads. The article explains improved hardware discovery, real-time resource availability, list-typed device attributes, group-aware resource claims, and native resource requests. ### Source excerpt Explore the top 10 new Alpha features in Kubernetes 1.36. Learn about 5 DRA advancements for AI/ML workloads, workload-aware scheduling, new security policies, and major scalability gains [Next page]()