# internal developer platform An internal developer platform is a centralized set of tools, services, and workflows that helps developers build, deploy, and operate software while managing environments, deployments, resources, and configurations. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Building an Internal Developer Platform with Artificial Intelligence DevFeed: [Building an Internal Developer Platform with Artificial Intelligence]() Original publisher: [Read original article]() Author: Ben Linders Published: 2026-09-17T11:11:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [internal developer platform](), [AI Development](), [AI search](), [agent observability](), [OpenTelemetry](), [telemetry]() Tags: [agent](), [agents](), [artificial-intelligence](), [culture-methods](), [developer-experience](), [developer-platform](), [distributed-tracing](), [guardrails](), [internal-developer-platform](), [logging](), [logs](), [metrics](), [news](), [opentelemetry](), [platform-artificial-intelligence](), [platform-engineering](), [prometheus](), [traces]() ### AI overview This news article covers a KubeCon presentation about using AI agents as an internal developer platform. It discusses semantic search across sources such as Git, Slack, Jira, repositories, pull requests, and wiki pages; guardrails for controlling actions; and logs, metrics, and traces for understanding agent behavior. The speakers also describe OpenTelemetry conventions for GenAI and related observability tools. ### Source excerpt Agents are becoming the new developer platform, using semantic search with data from tools like Git, Slack, and Jira for context. Things to consider are setting guardrails to block or allow things, and using logs, metrics, and traces to understand agent behavior. By Ben Linders ## 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. ## 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. ## Why AI coding agents need context graphs DevFeed: [Why AI coding agents need context graphs]() Original publisher: [Read original article]() Author: Talia Kohan Published: 2026-08-25T16:00:00Z Content type: article Language: en Sources: [Postman Blog]() Topics: [AI-assisted coding](), [Graphs](), [coding](), [API](), [internal developer platform](), [context window](), [long-context]() Tags: [ai-coding-agents](), [api-governance](), [apis](), [context-window](), [developer](), [developer-platform](), [engineering](), [general](), [graphs](), [knowledge-graphs]() ### AI overview The article argues that AI coding agents struggle in real codebases primarily because they lack access to a knowledge graph connecting code, APIs, services, ownership, dependencies, policies, and related organizational context. It describes service catalogs, API registries, ownership maps, dependency graphs, and internal developer platforms as different forms of the same underlying structure. It also argues that simply increasing the context window does not solve retrieval and context-quality problems. ### Source excerpt AI coding agents don't fail from small context windows. They fail without a knowledge graph of your code, APIs, and vendors. The post Why AI coding agents need context graphs appeared first on Postman Blog. ## Internal Developer Platform Golden Paths Guide DevFeed: [Internal Developer Platform Golden Paths Guide]() Original publisher: [Read original article]() Author: Rashmi Hegde Published: 2026-08-25T00:00:00Z Content type: tutorial Language: en Sources: [Harness Blog]() Topics: [internal developer platform](), [Platform Engineering](), [Developer Platform](), [Template]() Tags: [catalog](), [guide](), [internal-developer-platform](), [platform-engineering](), [productivity](), [self-service](), [visibility](), [workflows]() ### AI overview This guide explains how platform engineers can evolve an internal developer platform from a basic service catalog into maintained golden paths. It describes opinionated workflows, self-service capabilities, and embedded operational practices intended to improve developer adoption, speed, and reliability. ### Source excerpt Transform your service catalog into golden paths that developers love. Build an IDP that boosts productivity. Learn more. | Blog ## 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. ## 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. ## 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. ## New reference architecture for an AI/ML Internal Developer Platform on GCP DevFeed: [New reference architecture for an AI/ML Internal Developer Platform on GCP]() Original publisher: [Read original article]() Author: Luca Galante Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [internal developer platform](), [Artificial Intelligence](), [Machine learning](), [Architecture & Design](), [Data Management](), [cloud-infrastructure](), [GPU](), [Inference](), [Monitoring](), [observability](), [Security]() Tags: [ai](), [ai-ml](), [architecture](), [data](), [gcp](), [gpu](), [inference](), [infrastructure](), [internal-developer-platform](), [monitoring](), [observability](), [security](), [technical]() ### AI overview The article presents a six-plane reference architecture for an AI/ML internal developer platform on GCP. It addresses the distinct needs of data-intensive and compute-heterogeneous workloads, including data management, dynamic CPU/GPU/TPU provisioning, model lifecycle management, security, and observability. ### Source excerpt Bridge the gap between AI pilots and production. Explore the new six-plane reference architecture for an AI/ML Internal Developer Platform (IDP) on GCP, designed to handle data-intensive and complex ML workloads. ## Why enterprises fail at platform engineering: Project vs Product mindset DevFeed: [Why enterprises fail at platform engineering: Project vs Product mindset]() Original publisher: [Read original article]() Author: Sam Barlien Published: 2026-07-23T05:40:01Z Content type: opinion Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [internal developer platform](), [DevOps](), [Developer Platform]() Tags: [cognitive-load](), [devops](), [engineering](), [idp](), [internal-developer-platform](), [leadership](), [organizational](), [platform-engineering](), [scale](), [workflows]() ### AI overview The article argues that enterprises succeed with platform engineering when they treat the Internal Developer Platform as a continuously evolving internal product rather than a finite engineering project. A product-led approach investigates developers' problems, supports adoption, aligns stakeholders, secures ongoing investment, and uses a Platform Product Manager to connect user needs, technical priorities, and business goals. ### Source excerpt Discover why enterprises struggle with platform engineering and how shifting from a project mindset to a product-led approach drives adoption, alignment, and real developer value ## Privilege separation and the validation loop: The two controls that make AI agents safe in regulated industries DevFeed: [Privilege separation and the validation loop: The two controls that make AI agents safe in regulated industries]() Original publisher: [Read original article]() Author: Eric Paulsen Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Security](), [Architecture & Design](), [Developer Platform](), [internal developer platform](), [iac-security](), [prompt injection](), [CI/CD](), [IAM](), [Kubernetes](), [YAML]() Tags: [ai](), [ai-agents](), [ci-cd](), [compliance](), [developer-platform](), [governance](), [iam](), [infrastructure-as-code](), [internal-developer-platform](), [kubernetes](), [prompt-injection](), [security]() ### AI overview The article argues that regulated organizations can deploy useful AI agents safely by combining privilege separation with validation loops into one governance system. It assigns platform teams responsibility for the execution environment, including internal developer platforms, CI/CD pipelines, and policy enforcement, while highlighting risks such as hallucinations, excessive IAM permissions, and prompt injection. ### Source excerpt How platform teams can safely deploy AI agents in regulated industries. Unifying privilege separation and the validation loop creates a single governance system that satisfies security and compliance ## The empathy gap: Why your platform needs UX, not just APIs DevFeed: [The empathy gap: Why your platform needs UX, not just APIs]() Original publisher: [Read original article]() Author: Tatiana Mikhaleva Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [User experience (UX)](), [Platform Engineering](), [internal developer platform](), [Developer Platform](), [dashboards](), [Backstage](), [Kubernetes](), [Terraform](), [dora metrics]() Tags: [backstage](), [developer-platform](), [dora-metrics](), [idp](), [kubernetes](), [logs](), [metrics](), [onboarding](), [platform-engineering](), [product-design](), [terraform](), [ux]() ### AI overview The article argues that Internal Developer Platforms should be designed as products with strong UX, not exposed as collections of APIs. It describes how cognitive friction, unclear errors, outdated documentation, and tool switching reduce developer adoption and productivity. It recommends visual engineering practices such as pipeline graphs, actionable failure messages, and service status dashboards, while questioning an exclusive focus on DORA metrics. ### Source excerpt Discover "the empathy gap" in platform engineering. Learn why relying only on APIs and DORA metrics leads to low Internal Developer Platform (IDP) adoption, and how treating your platform as a product with great UX can reduce cognitive friction and bring developers joy ## Creating a shared platform vision: How platform leaders align teams DevFeed: [Creating a shared platform vision: How platform leaders align teams]() 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](), [internal developer platform](), [internal developer portal]() Tags: [developer-platform](), [idp](), [internal-developer-platform](), [leadership](), [organizational](), [platform](), [platform-engineering](), [strategy]() ### AI overview This article presents a framework for creating a shared vision for an internal developer platform. It explains that platform initiatives often fail because executives, developers, security, and operations teams have different expectations, incentives, and measures of success. Platform leaders must build stakeholder alignment, communicate shared value, and use deliberate strategy to support genuine adoption. ### Source excerpt Framework for aligning executives, developers, and ops on an internal developer platform vision using shared language, metrics, and product-minded roadmaps ## The platform engineering certification path: From Practitioner to Architect DevFeed: [The platform engineering certification path: From Practitioner to Architect]() Original publisher: [Read original article]() Author: Karolina Semiuk Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [internal developer platform](), [DevOps]() Tags: [and-best-practices](), [concepts](), [engineering](), [platform-engineering](), [practitioner](), [validation]() ### AI overview The article presents a vendor-neutral platform engineering certification path progressing from foundational concepts toward architect-level expertise. It explains that senior engineers and platform teams seek validation, shared language, and best practices, and distinguishes platform engineering competencies from tool-specific DevOps training. ### Source excerpt Explore the platform engineering certification path, from foundational concepts to architect-level expertise, designed for senior engineers and entire teams. ## How to set up an Internal Developer Platform: An implementation guide DevFeed: [How to set up an Internal Developer Platform: An implementation guide]() Original publisher: [Read original article]() Author: Mallory Haigh Published: 2026-07-23T05:40:01Z Content type: tutorial Language: en Sources: [Platform Engineering Blog]() Topics: [internal developer platform](), [internal developer portal](), [Automation](), [Back end](), [Orchestration](), [Backstage](), [Front end](), [Infrastructure as code]() Tags: [automation](), [backend](), [backstage](), [building](), [developer](), [developer-portal](), [infrastructure-as-code](), [internal-developer-platform](), [orchestration]() ### AI overview A practical eight-week guide to building an Internal Developer Platform using a four-phase, MVP-first approach. It covers choosing an initial team, implementing developer self-service, demonstrating value, and avoiding common adoption failures. ### Source excerpt A practical 8-week guide to building your Internal Developer Platform (IDP) MVP. Discover the 4-phase framework for developer self-service, how to pick your first team, and expert tips to ensure successful platform adoption. ## Platform engineering makes a difference. Here's how to prove it DevFeed: [Platform engineering makes a difference. Here's how to prove it]() Original publisher: [Read original article]() Author: Liz Coolman Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [internal developer platform](), [AI Engineering](), [Developer Platform](), [configuration](), [Security](), [telemetry]() Tags: [ai](), [ai-engineering](), [ai-impact](), [cognitive-load](), [configuration](), [developer-platform](), [encryption](), [engineering](), [idp](), [infrastructure](), [least-privilege](), [metrics](), [performance](), [platform](), [platform-engineering](), [platforms](), [security](), [software](), [speed](), [tooling]() ### AI overview This article explains how platform engineering teams can prove the value of an internal developer platform (IDP) to executives. It describes how IDPs reduce developer friction and cognitive load through standardized golden paths, configuration, and tooling; provide guardrails for security, encryption, and least-privilege access; and help organizations manage the effects of AI on engineering work. It recommends measuring velocity indicators such as cycle time and lead time to change, along with AI adoption, impact, and other metrics, to quantify platform performance and guide improvements. ### Source excerpt Learn how to prove the value of platform engineering to executives. This article outlines the essential metrics--from velocity and AI impact to developer sentiment--needed to quantify the success of your Internal Developer Platform (IDP) and keep pace with evolving AI capabilities. ## Runtime security monitoring and threat detection: Protecting production without slowing developers DevFeed: [Runtime security monitoring and threat detection: Protecting production without slowing developers]() Original publisher: [Read original article]() Author: Ajay Chankramath Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [threat detection](), [Platform Engineering](), [Monitoring](), [Security](), [Containers](), [internal developer platform](), [eBPF](), [Network](), [Processes]() Tags: [blog-post](), [containers](), [developer](), [ebpf](), [firewalls](), [internal-developer-platform](), [monitoring](), [network](), [platform](), [platform-engineering](), [processes](), [security](), [threat-detection]() ### AI overview This article explains how runtime security monitoring protects production workloads from threats that static scans may miss, including privilege escalation, container escapes, unexpected processes, sensitive file access, and suspicious network connections. It presents kernel-level monitoring, including eBPF, as a way to provide continuous protection while embedding security policies into the platform and minimizing developer friction. ### Source excerpt Runtime security monitoring detects zero-days, container escapes, and privilege escalations in production. Discover how eBPF enables 'invisible, always-on' protection for platform engineers ## AI-powered platforms vs platforms for AI: A platform engineer's guide DevFeed: [AI-powered platforms vs platforms for AI: A platform engineer's guide]() 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](), [internal developer platform](), [Artificial Intelligence](), [Architecture & Design]() Tags: [ai](), [architecture](), [article](), [developer-platform](), [infrastructure](), [internal-developer-platform](), [platform-engineering](), [platforms]() ### AI overview This article distinguishes AI-powered platforms from platforms for AI. AI-powered platforms add artificial intelligence to existing developer workflows and internal developer platforms, while platforms for AI are purpose-built for training models, managing large datasets, orchestrating GPU resources, and serving AI applications. The distinction affects architecture, skills, operational models, infrastructure choices, and platform complexity. ### Source excerpt Understand how AI-powered platforms differ from platforms for AI, why the distinction matters, and how each impacts architecture, teams, and infrastructure decisions. ## New reference architectures for IDPs on AWS, GCP, and Azure: Version 2.0 now available DevFeed: [New reference architectures for IDPs on AWS, GCP, and Azure: Version 2.0 now available]() Original publisher: [Read original article]() Author: Luca Galante Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [internal developer platform](), [Platform Engineering](), [Architecture & Design](), [Cloud](), [Amazon Web Services](), [Artificial Intelligence](), [Security]() Tags: [ai](), [architecture](), [aws](), [azure](), [cloud](), [code](), [configuration](), [gcp](), [identity-control](), [idp](), [internal-developer-platform](), [platform-engineering](), [policy](), [secrets-management](), [security](), [workflows]() ### AI overview Version 2.0 of cloud-agnostic internal developer platform reference architectures for AWS, GCP, and Azure reflects real-world platform implementations and enterprise operating patterns. The update emphasizes multi-platform support, dedicated AI integration, embedded security, and code-first declarative and GitOps workflows. ### Source excerpt Explore version 2.0 of cloud-agnostic IDP reference architectures for AWS, GCP, and Azure, featuring multi-platform support, AI integration, and embedded security for modern enterprise platform teams. ## How We Use Our Own Developer Portal DevFeed: [How We Use Our Own Developer Portal]() Original publisher: [Read original article]() Author: Mor Paz Published: 2026-07-22T11:37:29Z Content type: article Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [internal developer portal](), [Developer experience](), [dogfooding](), [internal developer platform](), [Deployment](), [code productivity](), [observability](), [Microservices](), [dashboards]() Tags: [dashboards](), [deployment](), [developer-experience](), [developer-portal](), [dogfooding](), [internal-developer-platform](), [internal-developer-portal](), [microservices](), [observability](), [productivity]() ### AI overview This article explains how Port uses its own internal developer portal as a form of dogfooding to improve developer experience and productivity. It describes the portal's software catalog and several use cases, with particular focus on deployment tracking and environment locks. ### Source excerpt How we use our internal developer portal for a better developer experience and productivity - specifically for deployment tracking and environment locks ## Managing Databases on Kubernetes Requires Platform Engineering and Automation DevFeed: [Managing Databases on Kubernetes Requires Platform Engineering and Automation]() Original publisher: [Read original article]() Author: Oliver Wolf Published: 2026-07-21T15:00:00Z Content type: opinion Language: en Sources: [Kubernetes Overview, News and Trends | The New Stack]() Topics: [Kubernetes](), [Databases](), [Platform Engineering](), [internal developer platform](), [Provisioning](), [opensearch](), [Redis]() Tags: [anynines](), [automation](), [backups](), [databases](), [devops](), [internal-developer-platform](), [kubernetes](), [monitoring](), [opensearch](), [platform-engineering](), [post](), [provisioning](), [redis](), [sponsor-anynines](), [sponsored-post]() ### AI overview The article argues that application teams should not be expected to manage the full operational burden of databases and data services on Kubernetes. It recommends internal developer platforms and Kubernetes-native automation so developers can request services while centralized systems handle provisioning, backups, patching, monitoring, recovery, and governance. ### Source excerpt The DevOps movement, set in motion nearly 20 years ago, broke down the traditional divide between software developers and IT The post Kubernetes made deploying easy. Nobody warned you about the databases. appeared first on The New Stack. [Next page]()