Docker gets all the attention, but runc does the heavy lifting underneath. One of our most popular articles explains how containers really run, how OCI fits in, and why understanding the lower layers helps you debug and operate them better. Read it here: https://mkdev.me/posts/the-tool-that-really-runs-your-containers-deep-dive-into-runc-and-oci-specifications

Cloud should make things easier, not leave your team buried in endless service choices, messy configs, and rising costs. We help you find the right path in AWS, GCP, and multi-cloud environments. Check out our Public Cloud Consulting and schedule a call: https://mkdev.me/b/consulting/public-cloud

DevOps Accents is a bi-weekly podcast about DevOps, Cloud, and AI, hosted by Pablo, Leo, and Kirill. Here are some more of our latest highlights — hit play wherever you listen to podcasts! https://www.youtube.com/watch?v=KgJsFjPS9_I

Our Terraform Lightning Course is a rapid and free introduction into Terraform and IaC. You will learn how to use Terraform to manage multi-cloud environments, starting with most basic concepts and going to complex setups closer to the end.

Video: https://www.youtube.com/playlist?list=PLozcbFx8FoPHM7n2DGLa6G8ZwtWFsVZsP
Articles: https://mkdev.me/posts/infrastructure-as-code-and-how-terraform-fits-into-it

#mkdevWeeklyHighlight
One big hidden risk is missing here: chart provider deciding not to do open source anymore, like Bitnami: https://www.prequel.dev/blog-post/the-real-state-of-helm-chart-reliability-2025-hidden-risks-in-100-open-source-charts

Platform engineering only works when it reflects how your teams actually build and operate software. We bring deep hands-on DevOps, cloud, CI/CD, and platform experience to help you build it right. Check out the page and schedule a call: https://mkdev.me/b/consulting/platform-engineering

Replace Docker for Podman for local development of containerized applications! This evergreen tutorial by Kirill teaches you all about basic usage of Podman and provides examples: https://mkdev.me/posts/dockerless-part-3-moving-development-environment-to-containers-with-podman

In the 89th mkdev dispatch Kirill reports back on our own experiences with OpenClaw. Get an mkdev dispatch in your Inbox every other week, subscribe now! https://mkdev.me/posts/openclaw-post-hype-report-89

CI is not enough anymore. Modern teams need pipelines that build, test, deploy, spin up PR environments, and keep security in check without slowing delivery down. See how we approach it and schedule a call: https://mkdev.me/b/consulting/majestic-pipeline

In case you missed it when we released it last year: mkdev has an open source Terraform provider for OpenAI. It lets you provision and manage OpenAI resources with Terraform instead of endless clickops. Worth a look if you work with AI infra: https://mkdev.me/posts/announcing-the-open-source-terraform-provider-for-openai

Helm Lightning Course! A quick introduction to Helm in 5 steps. You will go from zero to a fully functioning Helm Chart by watching our videos: https://www.youtube.com/playlist?list=PLozcbFx8FoPHqL9Gm1IpboF45gekmgYjO
Or by going along with the articles: https://mkdev.me/posts/why-do-you-even-need-helm

One detail about Helm that is easy to miss: charts do not always have to be purely declarative and static.

Using lookup, Helm can inspect the current cluster state during rendering. In the article’s example, that means pulling all namespaces, checking which ones carry a particular label, and then generating CronJobs only for those namespaces.

There is a catch: lookup does not filter by labels for you, so you have to fetch the resources first and then handle the label checks inside the template logic. Slightly clunky, but still surprisingly powerful for lightweight Kubernetes automations.

https://mkdev.me/posts/lookup-kubernetes-resources-inside-helm-charts

A Kubernetes security audit should do more than point at problems. We review your cluster hands-on, work with your team to understand the real setup, and deliver practical recommendations you can actually put into the backlog. Check out the page and schedule a call: https://mkdev.me/b/audits/kubernetes-security-audit

Getting traffic into EKS on Fargate can feel confusing until you see how the pieces connect.

This video walks through how a Kubernetes Ingress can automatically create an AWS Application Load Balancer, route traffic to your service, and expose your app to the outside world.

Watch it here: https://www.youtube.com/watch?v=cRODPz9GXb0

In the 90th mkdev dispatch Leo weights in on Anthropic's CEO recent comments about the state of the future white-collar jobs market. Subscribe for our bi-weekly newsletter all about Cloud, DevOps and AI! https://mkdev.me/posts/was-dario-amodei-right-90

A lot of engineers jump straight into containers and cloud platforms without ever building a clear mental model of virtualization. But the basics still matter.

Why can one physical machine run many isolated systems?
Why does KVM still show up everywhere in Linux infrastructure?
And why do tools like libvirt still matter when you want a sane way to manage VMs?

If you understand host, guest, hypervisor, and where KVM fits, a lot of modern infrastructure starts making more sense. This article does a good job covering those fundamentals through the lens of KVM. Still very relevant in 2026, especially for anyone touching Linux hosts, VM performance, or infra automation: https://mkdev.me/posts/virtualization-basics-and-an-introduction-to-kvm

If your teams use ChatGPT, AI analytics, screening tools, or any AI-powered workflow, AI literacy is now part of doing business responsibly. We offer practical training to help teams understand AI, ask better questions, and avoid costly mistakes. Check out the page and book training: https://mkdev.me/b/consulting/ai-literacy

A useful way to think about the EU AI Act’s literacy requirement:

This is not really about making everyone an AI expert. It’s about making sure people in your company know:

– what AI tools they are using
– where those tools help
– where they can fail
– what should never be pasted into them
– when human judgment still matters

That’s the difference between “we gave everyone access to AI” and “we actually built a company that can use AI safely.”

Read more: https://mkdev.me/posts/the-carrot-and-stick-of-the-eu-ai-act-s-literacy-requirements-benefits-compliance-and-risks

Kubernetes resource management is not about throwing apps into a cluster and hoping the scheduler is smart enough to figure it out. If you don’t set requests and limits correctly, you’re not doing capacity planning — you’re planting time bombs.

This article explains what actually matters: QoS, autoscaling, node capacity, and why Kubernetes is not what many people think it is. Read it here: https://mkdev.me/posts/kubernetes-capacity-and-resource-management-it-s-not-what-you-think-it-is

These case studies highlight the work we’ve done for our clients and how our partnerships progressed from the initial contact to implementation. Check them out: https://mkdev.me/b/cases

One of the most useful cloud cost questions in 2026 is still: “Am I paying for compute, or am I paying for idle time?”

That is especially relevant for background jobs. Lambda is billed by execution duration in 1 ms increments. Fargate is billed per second with a 1-minute minimum. So even when container compute looks attractive on paper, the economics can flip fast for short async tasks that do not run continuously. The result: background processing is often less about raw price and more about matching the billing model to the workload pattern.

This mkdev piece explains the tradeoff really well: https://mkdev.me/posts/processing-background-jobs-on-aws-lambda-vs-ecs-vs-ecs-fargate