# Giant Swarm Blog Get Kubernetes insight through regularly updated articles, webinars, downloads, and Podcasts all based on the cloud native ecosystem. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## What 143 platform teams told us about keeping infrastructure alive DevFeed: [What 143 platform teams told us about keeping infrastructure alive]() Original publisher: [Read original article]() Author: Oliver Thylmann Published: 2026-09-04T10:15:45Z Content type: opinion Language: en Sources: [Giant Swarm Blog]() Topics: [Platform Engineering](), [Kubernetes](), [cloud-infrastructure](), [Security](), [observability]() Tags: [aws](), [azure](), [bare-metal](), [infrastructure](), [kubernetes](), [observability](), [open-source](), [platform](), [platform-engineering](), [security](), [survey](), [team](), [tech]() ### AI overview Giant Swarm surveyed 143 platform and infrastructure professionals about the ongoing work required to keep production platforms running. The article argues that this platform integration tax is primarily a time cost, with security, reliability, cluster management, and observability consuming engineering capacity. ### Source excerpt The hidden cost of platform engineering isn't building your stack. It's keeping it alive. Giant Swarm surveyed 143 platform teams to find out. ## The post-VMware playbook: what to move first, what to leave for last DevFeed: [The post-VMware playbook: what to move first, what to leave for last]() Original publisher: [Read original article]() Author: manuel@giantswarm.io (Manuel Gawert) Published: 2026-08-18T09:25:47Z Content type: tutorial Language: en Sources: [Giant Swarm Blog]() Topics: [migration](), [Proxmox](), [virtualization](), [Amazon Web Services](), [Azure]() Tags: [cost](), [cost-optimization-in-kubernetes](), [migration](), [open-source](), [platform-engineering](), [proxmox](), [time](), [virtualization]() ### AI overview This article presents a migration playbook for teams evaluating a move away from VMware. It focuses on sequencing workloads, deciding among Proxmox, Azure, and AWS, and accounting for workload fit, risk, time, and cost. It emphasizes making the infrastructure decision before moving workloads because migrations can stall when that decision is unresolved. ### Source excerpt The post-VMware playbook: what to move first, what to leave for last, and what each option costs in risk, time, and money. (Giant Swarm) ## Hiring, tools, overload, automation: one cost wearing four names DevFeed: [Hiring, tools, overload, automation: one cost wearing four names]() Original publisher: [Read original article]() Author: The Team @ Giant Swarm Published: 2026-08-14T14:19:01Z Content type: opinion Language: en Sources: [Giant Swarm Blog]() Topics: [Kubernetes](), [Open Source](), [Tool](), [Automation]() Tags: [automation](), [cost](), [engineering](), [enterprise](), [kubernetes](), [open-source](), [operational](), [platform-engineering](), [teams](), [tools]() ### AI overview The article argues that hiring difficulties, tool overload, operational pressure, and insufficient automation are connected manifestations of a platform integration tax. It describes the cost of assembling and operating production platforms from open-source components, including time, specialist staffing, and enterprise operating expense. ### Source excerpt Four challenges platform teams keep naming turn out to be one cost: the platform integration tax. Giant Swarm's framework for where to start. ## Diagnosing the integration tax: three costs, three fixes DevFeed: [Diagnosing the integration tax: three costs, three fixes]() Original publisher: [Read original article]() Author: The Team @ Giant Swarm Published: 2026-08-13T10:22:19Z Content type: opinion Language: en Sources: [Giant Swarm Blog]() Topics: [Platform Engineering](), [Open Source](), [Architecture & Design]() Tags: [cncf](), [cost](), [evaluation](), [integration](), [maintenance](), [open-source](), [platform-engineering]() ### AI overview This article examines the integration tax of building and operating a production platform from open-source projects. It identifies evaluation paralysis, integration challenges, and ongoing maintenance as distinct costs that can delay delivery and consume team time. ### Source excerpt The hidden costs of building your own platform: endless evaluation, messy integration, and time you don't get back. Giant Swarm helps. ## Pushing container images to China: what we learned the hard way DevFeed: [Pushing container images to China: what we learned the hard way]() Original publisher: [Read original article]() Author: Team Honey Badger Published: 2026-08-06T15:34:42Z Content type: article Language: en Sources: [Giant Swarm Blog]() Topics: [container images](), [ACR](), [Azure](), [Kubernetes](), [AI Infrastructure](), [Inference](), [Cloud]() Tags: [acr](), [ai-infrastructure](), [azure](), [china](), [circleci](), [container](), [container-image-building](), [container-images](), [firewall](), [inference](), [kubernetes]() ### AI overview This article explains why container image pushes to China can be much slower than elsewhere. It attributes the problem to China's separate registry infrastructure and cross-border transfer throttling, and says Giant Swarm cut delivery time to under two minutes with a split push through Singapore. ### Source excerpt Why container pushes to China take 30 minutes, and how Giant Swarm cut it to under 2 with a split push through Singapore. ## The CNCF landscape has 230+ tools. Choosing from it is where platform teams get stuck. DevFeed: [The CNCF landscape has 230+ tools. Choosing from it is where platform teams get stuck.]() Original publisher: [Read original article]() Author: The Team @ Giant Swarm Published: 2026-08-03T14:41:21Z Content type: opinion Language: en Sources: [Giant Swarm Blog]() Topics: [Platform Engineering](), [Tool](), [Kubernetes]() Tags: [cncf](), [complexity](), [open-source](), [platform](), [platform-engineering](), [tools]() ### AI overview The article argues that the CNCF landscape's 230-plus projects create evaluation paralysis for platform teams. It says the landscape shows what exists but not which combinations work for a team's production environment, cloud provider, and size, making selection and integration a significant source of delay. ### Source excerpt The CNCF landscape has 230+ projects. Here's why that's where evaluation paralysis starts, and what it costs. (Giant Swarm) ## Introducing the Giant Swarm Agent Platform: Agents that run where your data lives DevFeed: [Introducing the Giant Swarm Agent Platform: Agents that run where your data lives]() Original publisher: [Read original article]() Author: Henning Lange Published: 2026-07-07T18:33:18Z Content type: release Language: en Sources: [Giant Swarm Blog]() Topics: [AI Agent](), [AI Platform](), [audit trail](), [shadow AI]() Tags: [agents](), [ai](), [ai-agents](), [audit-trail](), [platform](), [product](), [shadow-ai](), [tooling]() ### AI overview Giant Swarm introduces an agent platform designed to run AI agents on events rather than user clicks, with isolated execution, scoped tool access, and logged decisions for unattended production use. ### Source excerpt Your engineers are already running AI agents. Not as an approved rollout, but as something that crept in over the past year, wired into whatever tools got a task done. ## The platform assembly tax: a framework for what platform teams keep describing " Giant Swarm DevFeed: [The platform assembly tax: a framework for what platform teams keep describing " Giant Swarm]() Original publisher: [Read original article]() Author: The Team @ Giant Swarm Published: 2026-06-29T17:02:43Z Content type: opinion Language: en Sources: [Giant Swarm Blog]() Topics: [AI Platform](), [Open Source](), [Framework](), [Automation](), [Kubernetes]() Tags: [automation](), [engineering](), [enterprise](), [kubernetes](), [open-source](), [operational](), [platform](), [platform-engineering](), [teams](), [tools]() ### AI overview The article describes the "platform assembly tax": the cumulative time, money, and senior engineering effort required to select, integrate, and operate open-source platform components reliably in production. It connects this cost to hiring constraints, tool sprawl, operational overload, and limited time for automation, and gives enterprise-scale estimates for assembling and running such platforms. ### Source excerpt Ask a platform team to describe what's getting in the way of their work, and you'll usually hear about four things: hiring the right people, too many tools for the team size, operational overload, and not enough time for automation. Different teams put them in different orders, but the same four answers come back. ## Kubernetes Secrets and ConfigMaps in 2026: the Secret is the last mile " Giant Swarm DevFeed: [Kubernetes Secrets and ConfigMaps in 2026: the Secret is the last mile " Giant Swarm]() Original publisher: [Read original article]() Author: Puja Abbassi Published: 2026-06-29T10:31:16Z Content type: tutorial Language: en Sources: [Giant Swarm Blog]() Topics: [Kubernetes](), [configuration](), [Containers]() Tags: [configuration](), [containers](), [dev](), [kubernetes](), [kubernetes-secrets](), [platform-engineering](), [secrets](), [tech]() ### AI overview This tutorial revisits Kubernetes Secrets and ConfigMaps and explains how their role fits into a longer production pipeline in 2026. It covers their purpose, scope, delivery methods, size and update behavior, including the need to restart workloads after Secret changes. ### Source excerpt Part IV of the Understanding Basic Kubernetes Concepts series, updated from the 2016 original. ## Nine years of predicting cloud native, scored honestly " Giant Swarm DevFeed: [Nine years of predicting cloud native, scored honestly " Giant Swarm]() Original publisher: [Read original article]() Author: Oliver Thylmann Published: 2026-06-29T10:07:32Z Content type: opinion Language: en Sources: [Giant Swarm Blog]() Topics: [Cloud Native Ecosystem](), [Platform Engineering](), [Kubernetes](), [Open Source](), [Artificial Intelligence]() Tags: [ai](), [cloud](), [cloud-native](), [grafana](), [history](), [istio](), [kubernetes](), [microservices](), [open-source](), [platform-engineering](), [tech]() ### AI overview An author reflects on nine years of publishing and scoring annual cloud-native predictions. The article argues that making predictions specific and publicly scoring misses can expose the gap between expectations and reality. It traces a shift from Kubernetes-related technologies to platform engineering and, later, AI in operations. ### Source excerpt I started writing annual predictions in 2017 to find out whether I could read the industry. Nine years in, that's turned out to be one of the least interesting things the exercise has done. What it does instead is harder to say, or harder to predict. Something like: it surfaces the gap between what I think will happen and what I want to be true. Nine years of scoring myself has been nine years of watching that gap.