# Containers Containers are isolated processes that package an application's required files for portable execution. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Kubernetes Architecture: Control Plane, Scheduler, and Kubelet DevFeed: [Kubernetes Architecture: Control Plane, Scheduler, and Kubelet]() Original publisher: [Read original article]() Author: Nimesha Jinarajadasa Published: 2026-09-17T06:25:02Z Content type: tutorial Language: en Sources: [Kubernetes - KodeKloud Blog | DevOps, Cloud, Kubernetes, AI Tutorials & More]() Topics: [Kubernetes](), [control-plane](), [api server](), [Containers](), [etcd](), [kubectl]() Tags: [api](), [api-server](), [containers](), [control-plane](), [controllers](), [etcd](), [kubectl](), [kubernetes](), [kubernetes-architecture](), [kubernetes-networking](), [node](), [scheduler]() ### AI overview A beginner-friendly tutorial explaining how Kubernetes maintains the desired state of containerized applications. It covers the control plane, API server, etcd, controllers, scheduler, and kubelet. ### Source excerpt Learn how Kubernetes works, from the control plane and scheduler to kubelet, pods, and Services, with simple answers to interview questions. ## Secure Compute and Static IP builds start 64% faster DevFeed: [Secure Compute and Static IP builds start 64% faster]() Original publisher: [Read original article]() Author: Karim Hasebou Published: 2026-09-16T17:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Deployment](), [Containers](), [Network Configuration]() Tags: [automatically](), [build](), [compute](), [containers](), [faster](), [ip](), [network-configuration](), [static]() ### AI overview Vercel reports that builds using Secure Compute or Static IPs now start 64% faster on average, improving from 6.7 seconds to 2.4 seconds. The change uses prewarmed build containers with network configuration attached at build start and requires no configuration changes. ### Source excerpt Builds using Secure Compute or Static IPs now start 64% faster, with the average time from deployment creation to build start dropping from 6.7 seconds to 2.4 seconds. Previously, each build waited for a new build container to boot with its network configuration. These builds now use prewarmed build containers, with your network configuration attached when the build starts. The improvement is applied automatically to builds using Secure Compute or Static IPs, with no configuration changes required. Learn more about Secure Compute and Static IPs. Read more ## Constraining AI agents with Red Hat AI: Containment, identity, and governance DevFeed: [Constraining AI agents with Red Hat AI: Containment, identity, and governance]() Original publisher: [Read original article]() Author: Grace Ableidinger Published: 2026-09-16T13:01:59Z Content type: tutorial Language: en Sources: [Red Hat](), [Red Hat Developer]() Topics: [Artificial Intelligence](), [Security](), [Zero Trust](), [Containers](), [Kubernetes](), [Architecture & Design]() Tags: [ai](), [ai-agents](), [containers](), [deployment](), [kubernetes](), [prompt-injection](), [security](), [trust]() ### AI overview This tutorial explains how to secure AI agents running on Red Hat OpenShift using containment, verifiable identity, and governance. It covers namespace isolation, quotas, sandboxing, workload identity, and admission control, with OpenClaw used in the demo. ### Source excerpt When an agent process runs on your laptop, it typically inherits anything your user has access to. Often this includes the full network stack, the file system, and the credentials sitting in memory. When integrating with GitHub, Slack, or a cloud provider, you could be one faulty permission or well-crafted prompt injection away from a security incident. The post Constraining AI agents with Red Hat AI: Containment, identity, and governance appeared first on Red Hat Developer. ## Seven Reliability Tests for Home Lab Services DevFeed: [Seven Reliability Tests for Home Lab Services]() Original publisher: [Read original article]() Author: Brandon Lee Published: 2026-09-13T12:34:15Z Content type: tutorial Language: en Sources: [Virtualization Howto]() Topics: [Homelab](), [Self-hosted](), [Containers](), [Network](), [Proxmox]() Tags: [home-lab](), [home-server](), [network](), [proxmox](), [self-hosted](), [server]() ### AI overview The article presents seven reliability tests for home lab services, including disconnecting Internet access and stopping one container in a redundant setup. It explains how these tests can reveal dependencies on external resources and weaknesses in DNS and service design. ### Source excerpt When it comes to putting a new service into the home lab that is something I will feel like I can rely on and trust, it has to be able... The post I Don't Trust a Home Lab Service Until It Passes These 7 Tests appeared first on Virtualization Howto. ## CrowdStrike Named Strongest Overall Leader in 2026 Frost Radar™: Cloud Workload Protection Platforms DevFeed: [CrowdStrike Named Strongest Overall Leader in 2026 Frost Radar™: Cloud Workload Protection Platforms]() Original publisher: [Read original article]() Author: Brett Shaw Published: 2026-09-12T11:17:51.295154Z Content type: article Language: en Sources: [Blog]() Topics: [workload protection](), [Security & compliance, Cloud security](), [Security](), [telemetry](), [Containers](), [Kubernetes](), [SOC]() Tags: [2026](), [cloud](), [cloud-application-security](), [cloud-security](), [containers](), [growth](), [innovation](), [kubernetes](), [real-time](), [security](), [soc](), [telemetry](), [workload-protection]() ### AI overview CrowdStrike says Frost & Sullivan named it the strongest overall leader in the 2026 Frost Radar for Cloud Workload Protection Platforms. The article highlights Falcon Cloud Security's focus on connecting risk, adversary intelligence, and real-time protection across containers, Kubernetes, identities, cloud control planes, endpoints, and SOC operations. ### Source excerpt Falcon Cloud Security earned the highest scores in both Innovation and Growth by connecting risk, adversary intelligence, and real-time protection to stop attacks. ## Red Hat edge platforms: Choosing the right one for your use case DevFeed: [Red Hat edge platforms: Choosing the right one for your use case]() Original publisher: [Read original article]() Author: Daniel Froehlich Published: 2026-09-11T13:01:48Z Content type: article Language: en Sources: [Red Hat](), [Red Hat Developer]() Topics: [Edge](), [Containers](), [Kubernetes](), [Architecture & Design](), [Hardware](), [Availability](), [Microservice]() Tags: [containers](), [deployment](), [edge](), [edge-computing](), [hardware](), [high-availability](), [kubernetes](), [management-tools](), [microservices](), [red-hat](), [virtual-machines]() ### AI overview This article introduces a series about choosing Red Hat edge platforms for specific deployment needs. It compares Red Hat Enterprise Linux and Red Hat OpenShift across workload types, platform sizes, hardware requirements, Kubernetes use cases, availability, storage, and management needs. ### Source excerpt Choosing the right platform for an edge deployment is one of the most consequential decisions an organization makes--and one of the most confusing. The options range from a single-board computer running a handful of containers to a full Kubernetes cluster with high availability, software-defined storage, and centralized management. Pick too small, and you hit a wall when requirements grow. The post Red Hat edge platforms: Choosing the right one for your use case appeared first on Red Hat Developer. ## Kubernetes v1.37: Scheduler Preemption for In-Place Pod Resize (Alpha) DevFeed: [Kubernetes v1.37: Scheduler Preemption for In-Place Pod Resize (Alpha)]() Original publisher: [Read original article]() Author: Natasha Sarkar Published: 2026-09-10T18:30:00Z Content type: article Language: en Sources: [Kubernetes Blog]() Topics: [Kubernetes](), [Containers]() Tags: [containers](), [cpu](), [feature](), [kubernetes](), [memory](), [node](), [resource](), [scale]() ### AI overview Kubernetes v1.37 adds an alpha scheduler-preemption feature for in-place Pod resizes. It can preempt lower-priority workloads to make capacity available for valid, higher-priority resize requests that are deferred on full nodes. ### Source excerpt In Kubernetes, resource allocation has historically been a static decision made during a Pod's initial scheduling and placement. With the graduation of the core in-Place Pod resize feature to General Availability in v1.35, application developers and cluster operators gained the powerful ability to dynamically adjust CPU and memory allocations of running containers without incurring disruptive restarts or application downtime. However, in-place resizing introduced a unique resource scheduling gap: if a running Pod requested a resource scale-up that exceeded the host node's allocatable headroom, the Kubelet was forced to mark the request as Deferred. The Pod would remain parked in this state indefinitely, waiting for resources on the node to naturally free up. To bridge this scheduling gap, Kubernetes v1.37 introduces scheduler preemption for in-place Pod resize (Alpha), behind the InPlacePodVerticalScalingSchedulerPreemption feature gate. This feature allows the Kubernetes scheduler to actively free up capacity on a fully-utilized node by preempting lower-priority workloads, enabling the pending in-place resizes of critical, higher-priority applications to succeed. The "deferred" resize challenge To understand why this preemption mechanism is needed, it is helpful to look at how Kubernetes handles running Pod resizing. When a user or controller (such as the Vertical Pod Autoscaler) updates the resource requests of an active container, the Kubelet evaluates whether the underlying node has enough spare allocatable capacity to fulfill the increase. If the node's resources are fully utilized and cannot satisfy the new limits, the Kubelet sets the container's resizeStatus (reported in the Pod's status.containerStatuses[]) to Deferred. Unlike an Infeasible resize request (which is immediately rejected because it exceeds physical machine boundaries, namespace limit ranges, or admission quotas) a Deferred status indicates that the request is valid but is temporarily unable t ## Simplify and support your TorchServe workloads using Ray Serve Deep Learning Containers DevFeed: [Simplify and support your TorchServe workloads using Ray Serve Deep Learning Containers]() Original publisher: [Read original article]() Author: Ananth Raghavendra Published: 2026-09-09T15:51:29Z Content type: tutorial Language: en Sources: [Artificial Intelligence]() Topics: [Inference](), [model-deployment](), [Amazon Elastic Kubernetes Service](), [Containers](), [vlm](), [GPU](), [PyTorch]() Tags: [amazon-eks](), [containers](), [gpu](), [inference](), [intermediate-200](), [pytorch](), [technical-how-to](), [vulnerabilities]() ### AI overview The article introduces AWS Ray Serve Deep Learning Containers as a maintained, pre-tested inference option for teams moving from unmaintained TorchServe workloads. It demonstrates deploying a vision-language model on Amazon EKS using a single GPU node. ### Source excerpt TorchServe is no longer maintained, leaving teams to own the entire GPU inference stack. The AWS Ray Serve Deep Learning Container is a supported, pre-tested container with the framework, GPU drivers, and serving layer already assembled. This post walks through deploying a vision-language model on Amazon EKS using the Ray Serve DLC on a single GPU node. ## Introducing worker topologies for self-hosted Appwrite DevFeed: [Introducing worker topologies for self-hosted Appwrite]() Original publisher: [Read original article]() Author: Atharva Deosthale Published: 2026-09-07T00:00:00Z Content type: release Language: en Sources: [Appwrite Blog]() Topics: [Appwrite](), [Self-hosted](), [Containers](), [Coroutines](), [Docker Compose]() Tags: [announcements](), [compose](), [container](), [containers](), [coroutines](), [self-hosted]() ### AI overview Appwrite introduces two worker topologies for self-hosted instances. The combined topology is now the default and runs background work in two containers, while the separate topology preserves one container per queue and scheduler for installations needing independent scaling or resource controls. ### Source excerpt Self-hosted Appwrite now runs all background workers in a single container by default. Learn how the combined topology works and when to scale out with separate workers. ## Appwrite 2.0 is now available for self-hosting DevFeed: [Appwrite 2.0 is now available for self-hosting]() Original publisher: [Read original article]() Author: Atharva Deosthale Published: 2026-09-07T00:00:00Z Content type: release Language: en Sources: [Appwrite Blog]() Topics: [Appwrite](), [Self-hosted](), [PostgreSQL](), [Containers]() Tags: [containers](), [postgresql](), [products](), [self-hosting](), [upgrade]() ### AI overview Appwrite 2.0 is available for self-hosting. It introduces a rebuilt Console, PostgreSQL as the default database for new installations, a coroutine-based server engine, and a combined worker topology that reduces the default instance from 33 to 16 containers. Existing installations retain their current database when upgraded. ### Source excerpt Appwrite 2.0 brings a rebuilt Console, PostgreSQL as the default database, and a combined worker topology that runs your instance on 16 containers instead of 33. ## 7 Simple Home Lab HA Projects for This Weekend DevFeed: [7 Simple Home Lab HA Projects for This Weekend]() Original publisher: [Read original article]() Author: Brandon Lee Published: 2026-09-05T12:22:03Z Content type: tutorial Language: en Sources: [Virtualization Howto]() Topics: [Homelab](), [Availability](), [Pi-hole](), [Docker](), [Containers]() Tags: [availability](), [containers](), [dns](), [docker](), [high-availability](), [home-lab](), [home-server](), [server](), [servers]() ### AI overview This article presents seven simple high-availability projects for a home lab. Its detailed example recommends running two DNS servers, separating them across Docker hosts, configuring primary and secondary DNS addresses, and synchronizing the DNS platforms. ### Source excerpt A lot of times we think about high availability being some complicated or complex thing that we just think in the home lab it isn't worth doing. However, HA doesn't... The post 7 Simple Home Lab HA Projects for This Weekend appeared first on Virtualization Howto. ## Kubernetes v1.37: KubeletInUserNamespace (aka Rootless mode) Graduates to Beta DevFeed: [Kubernetes v1.37: KubeletInUserNamespace (aka Rootless mode) Graduates to Beta]() Original publisher: [Read original article]() Author: Akihiro Suda Published: 2026-09-04T18:30:00Z Content type: release Language: en Sources: [Kubernetes Blog]() Topics: [Kubernetes](), [Vulnerabilities](), [Containers]() Tags: [containers](), [feature](), [kubernetes](), [linux](), [production](), [v1](), [vulnerabilities]() ### AI overview Kubernetes v1.37 promotes KubeletInUserNamespace, or rootless mode, to beta. It lets Kubernetes node components run as a non-root host user in a Linux user namespace, reducing the impact of container-breakout vulnerabilities while complementing conventional hardening such as seccomp. ### Source excerpt Kubernetes v1.37 promotes the KubeletInUserNamespace feature gate to beta. With this feature enabled, all of the node components (kubelet, CRI and OCI runtimes, CNI plugins, and kube-proxy) can run as a non-root user on the host, using a Linux user namespace. This technique is also known as rootless mode. The work started as an experiment in 2018, and was merged into Kubernetes v1.22 (2021) as an alpha feature (Kubernetes Enhancement Proposal KEP-2033). This feature should not be confused with user namespaces for pods (hostUsers: false with the UserNamespacesSupport feature gate, GA since v1.36), which puts pods in user namespaces but still runs the node components as root. These two features do not conflict. Moreover, they can be combined to nest Kubernetes inside Kubernetes without resorting to the full privileged: true. Why run the node components in a user namespace? Because the node components have historically had container-breakout vulnerabilities that could compromise full root privileges on the host. Examples of such vulnerabilities include: CVE-2022-0811 ("cr8escape"): CRI-O could be tricked into setting arbitrary sysctls, such as kernel.core_pattern, resulting in arbitrary code execution as root on the host CVE-2023-27561: runc could be tricked into bypassing the masked paths of a container via a volume mount race, exposing the host's procfs files (a regression of CVE-2019-19921) CVE-2024-10220: the kubelet could be made to execute arbitrary commands as root via gitRepo volumes (gitRepo volumes had a similar vulnerability, CVE-2018-11235, back in 2018 too) CVE-2025-31133: runc could be tricked into bind-mounting attacker-controlled paths and writing to the host's procfs files, such as /proc/sysrq-trigger and /proc/sys/kernel/core_pattern CVE-2026-53488: containerd could be tricked into executing arbitrary commands on the host, via crafted labels in a container image By running the node components in a user namespace, the potential damage is confined to th ## Rootless Podman: Preserving Source IPs DevFeed: [Rootless Podman: Preserving Source IPs]() Original publisher: [Read original article]() Author: Jan Rodak Published: 2026-09-04T14:25:02Z Content type: article Language: en Sources: [blog.podman.io]() Topics: [podman](), [Containers](), [Networks](), [Access Control](), [Logging]() Tags: [blog](), [bridge](), [container](), [containers](), [ipv4](), [ipv6](), [logging](), [networks](), [podman](), [port](), [rate-limiting](), [routing](), [tips-and-tricks]() ### AI overview This article explains how Pesto, a companion tool from the passt project, addresses Rootless Podman's inability to preserve incoming client source IPs on bridge networks. Pesto updates pasta's forwarding table so traffic reaches containers without source-address rewriting, while retaining existing port-mapping capabilities. The article also documents configuration steps, traffic flow, supported networking features, and limitations when switching from the current forwarder. ### Source excerpt Rootless Podman has a long-standing limitation reported since 2020: containers on bridge networks can't see the real source IP of incoming connections. The `rootlessport` userspace proxy rewrites the source to the container's own subnet address, breaking IP-based access control, logging, and rate limiting. Pesto, a new companion tool from the passt project solves this. Pesto [...] ## BGP-Free Core with SR-MPLS DevFeed: [BGP-Free Core with SR-MPLS]() Original publisher: [Read original article]() Published: 2026-09-03T05:30:00Z Content type: article Language: en Sources: [ipSpace.net blog]() Topics: [SR-MPLS](), [BGP](), [networking](), [Network](), [Routing (disambiguation)](), [Containers](), [Linux](), [GitHub]() Tags: [bgp](), [containers](), [edge](), [examples](), [github](), [is-is](), [linux](), [mpls](), [netlab](), [network](), [router](), [routing](), [sr-mpls]() ### AI overview This article demonstrates how to build a BGP-free transport core with SR-MPLS using netlab. It describes a lab topology with IS-IS, BGP, Linux container hosts, and PE routers, then shows how SR-MPLS labels provide end-to-end connectivity without BGP routes on the core router. ### Source excerpt The beauty of SR-MPLS is that it's a drop-in replacement for the traditional (LDP- or RSVP-based) MPLS control plane. For example, you could replace LDP with SR-MPLS in a network using MPLS to implement a BGP-free transport core, and it just keeps working. This scenario was the first "fun" scenario in the ITNOG10 Segment Routing workshop. The core network uses the same topology as in the previous examples; I added two hosts and BGP routing. Simplest possible network using a BGP-free core Read more ... ## Networking Aspects of Running VMs in Containers DevFeed: [Networking Aspects of Running VMs in Containers]() Original publisher: [Read original article]() Published: 2026-09-02T05:44:00Z Content type: article Language: en Sources: [ipSpace.net blog]() Topics: [Containers](), [virtualization](), [networking](), [Linux](), [Orchestration]() Tags: [bridge](), [containers](), [docker](), [ethernet](), [linux](), [netlab](), [networking](), [podman](), [qemu](), [virtual-machines](), [virtualization]() ### AI overview The article explains how vrnetlab and a containerlab fork package virtual machines, especially network devices, as containers so container orchestration can provision network topologies. It focuses on connecting QEMU virtual network interfaces, Linux tap interfaces, bridges, and container veth pairs, including why data-plane and management interfaces require different handling. ### Source excerpt The vrnetlab project and its containerlab fork implement a wonderful idea: let's package virtual machines (primarily network devices that cannot be containerized) as containers to use reliable orchestration tools like containerlab to provision network topologies. That approach might have a few drawbacks (depending on how the container images are built), but the obvious elephant in the room is: how do you make the virtual network plumbing work? Read more ... ## Automate proxy injection for Amazon EKS on AWS Fargate using Kyverno DevFeed: [Automate proxy injection for Amazon EKS on AWS Fargate using Kyverno]() Original publisher: [Read original article]() Author: Himanshu Bansal Published: 2026-09-01T15:59:57Z Content type: tutorial Language: en Sources: [Containers]() Topics: [Amazon EKS](), [Kubernetes](), [Containers](), [Amazon EC2]() Tags: [advanced-300](), [amazon-eks](), [amazon-elastic-kubernetes-service](), [aws-fargate](), [compliance](), [containers](), [how-to](), [kubernetes](), [policy]() ### AI overview This tutorial shows how to use a Kyverno mutating admission policy to inject corporate HTTP/HTTPS proxy environment variables into Amazon EKS pods running on AWS Fargate. It targets labeled namespaces, avoids per-application manifest changes, and covers validation and proxy bypasses for Fluent Bit and AWS endpoints. ### Source excerpt Learn how to use a Kyverno mutating admission policy to automatically inject corporate proxy environment variables into Amazon EKS on AWS Fargate pods at admission time, delivering consistent egress compliance without modifying application deployment manifests. ## Meet editorial-guide-ramalama: An AI Assistant That Checks Your Fedora CommBlog and Magazine Articles Against Editorial Guidelines DevFeed: [Meet editorial-guide-ramalama: An AI Assistant That Checks Your Fedora CommBlog and Magazine Articles Against Editorial Guidelines]() Original publisher: [Read original article]() Author: Ananya Nalavathu Published: 2026-08-25T12:47:18Z Content type: article Language: en Sources: [Fedora Community Blog]() Topics: [Fedora](), [Retrieval Augmented Generation (RAG)](), [Artificial Intelligence](), [Local AI](), [Containers](), [Open Source](), [Tooling](), [On-device AI]() Tags: [ai](), [articles](), [blog](), [fedora-project-community](), [inference](), [local](), [mentored-projects](), [oci](), [open-source](), [rag](), [tool]() ### AI overview The article introduces editorial-guide-ramalama, a Retrieval-Augmented Generation assistant built for Fedora contributors. It checks drafts against Fedora's editorial guidelines and published articles, cites specific guidelines when it identifies problems, and suggests actionable fixes. The tool uses RamaLama to run open models locally as OCI containers, with built-in ingestion, chunking, and retrieval, avoiding API keys and external services. ### Source excerpt By Ananya Nalavathu and Francois Gonothi Toure Introduction Open source communities run on contribution, and contribution runs on documentation, storytelling, and knowledge sharing. At the Fedora Project, that means the Fedora Community Blog and Fedora Magazine, two publications that give contributors a voice and give the community a way to stay informed, inspired, and connected. [...] The post Meet editorial-guide-ramalama: An AI Assistant That Checks Your Fedora CommBlog and Magazine Articles Against Editorial Guidelines appeared first on Fedora Community Blog. ## From dotnet run to Foundry Hosted Agent in 3 lines of C# DevFeed: [From dotnet run to Foundry Hosted Agent in 3 lines of C#]() Original publisher: [Read original article]() Author: Bruno Capuano Published: 2026-08-24T19:00:00Z Content type: tutorial Language: en Sources: [.NET Blog]() Topics: [hosted-agents](), [Microsoft Agent Framework](), [Azure](), [C#](), [.NET](), [NuGet](), [Entra ID](), [Containers](), [telemetry]() Tags: [agent](), [agents](), [ai](), [azd](), [azure](), [blog](), [c-sharp](), [csharp](), [dotnet](), [entra-id](), [framework](), [hosted-agents](), [hosting](), [infrastructure](), [microsoft](), [microsoft-agent-framework](), [microsoft-foundry](), [net](), [nuget](), [observability](), [post](), [production]() ### AI overview This tutorial shows how to deploy a Microsoft Agent Framework console agent as a Foundry Hosted Agent using one NuGet package, three lines of C#, and two commands. Foundry provides managed Azure infrastructure, scaling, identity, session state, observability, and lifecycle management. ### Source excerpt You built an agent with Microsoft Agent Framework and it works great on your machine. Now what? Turns out deploying it to production takes 1 NuGet package, 3 lines of C#, and 2 commands. Let's do it. The post From dotnet run to Foundry Hosted Agent in 3 lines of C# appeared first on .NET Blog. ## Arista cEOS Does Not Apply ACLs to Control-Plane Traffic DevFeed: [Arista cEOS Does Not Apply ACLs to Control-Plane Traffic]() Original publisher: [Read original article]() Published: 2026-08-24T05:20:00Z Content type: opinion Language: en Sources: [ipSpace.net blog]() Topics: [Network](), [BGP](), [Containers](), [Finite-state machine](), [configuration]() Tags: [bgp](), [containers](), [netlab](), [network](), [release](), [security](), [testing]() ### AI overview The article reports that Arista cEOS containers do not apply inbound ACLs to control-plane traffic or to traffic sent to the container's own IP addresses. This behavior differs from Arista vEOS virtual machines and can cause BGP connectivity tests using ACLs to produce unexpected results. ### Source excerpt When someone starts singing the Use Digital Twins to Test Your Network hymn (or, more recently, tells you how AI agents can do that to validate their ideas), ask them about these minor details. If they persist, point them (not that it would help) to this long list of gotchas. That list just got longer: Arista cEOS container does not apply inbound ACLs to control-plane traffic (Arista vEOS VM does). Read more ... ## How Kubernetes Actually Works DevFeed: [How Kubernetes Actually Works]() Original publisher: [Read original article]() Author: Nikki Siapno Published: 2026-08-21T12:52:09Z Content type: tutorial Language: en Sources: [Level Up Coding System Design Newsletter]() Topics: [Kubernetes](), [Containers](), [Deployment](), [API](), [Replication]() Tags: [api](), [components](), [containers](), [deployment](), [health](), [kubernetes](), [reconciliation](), [replication]() ### AI overview A tutorial explaining Kubernetes as a platform that continuously reconciles desired and actual cluster state. It covers Pods, scheduling, container health monitoring, failure recovery, and the roles of the control plane and worker nodes. ### Source excerpt The mental model that makes Kubernetes click. ## Podman 6.1.0: Volume Renaming, Machine Restarts, and a Long List of Bug Fixes DevFeed: [Podman 6.1.0: Volume Renaming, Machine Restarts, and a Long List of Bug Fixes]() Original publisher: [Read original article]() Author: Mohan Boddu Published: 2026-08-17T19:51:34Z Content type: release Language: en Sources: [blog.podman.io]() Topics: [podman](), [podman machine](), [API](), [Containers](), [macOS](), [Windows](), [Windows Subsystem for Linux](), [Docker]() Tags: [announcement](), [api](), [articles](), [blog](), [bug-fixes](), [buildah](), [containers](), [docker](), [macos](), [new-feature](), [podman](), [podman-desktop](), [podman-machine](), [release](), [releases](), [update](), [volume](), [windows](), [wsl]() ### AI overview Podman 6.1.0 adds volume renaming, a dedicated podman machine restart command, idempotent network removal, retry options for manifest pushes, improved Kubernetes healthcheck mapping, WSL port-forwarding support, IPv6 forwarding fixes, and free-memory reporting. It also improves Docker-compatible API behavior and includes numerous bug fixes and dependency updates. ### Source excerpt Podman 6.1.0 is here, and while it's not a flashy release, it's the kind of update that quietly makes day-to-day container work smoother. This release focuses on rounding out long-requested quality-of-life commands, tightening up podman machine reliability across Windows, macOS, and WSL, and squashing a healthy batch of bugs in Quadlet, healthchecks, and the API [...] ## WorkOS Applied AI Showcase July 28 2026 - Moving to an AI-native Organization DevFeed: [WorkOS Applied AI Showcase July 28 2026 - Moving to an AI-native Organization]() Original publisher: [Read original article]() Author: WorkOS Published: 2026-08-14T13:36:57Z Content type: article Language: en Sources: [WorkOS Blog]() Topics: [Artificial Intelligence](), [Low-Code / Internal Tools](), [AI-assisted coding](), [Containers](), [MCP](), [Command-line interface](), [incident](), [Security](), [datadog](), [Pull Request](), [Slack](), [GitHub]() Tags: [agent](), [agents](), [ai](), [applied-ai](), [cli](), [coding](), [coding-agents](), [containers](), [datadog](), [demo](), [event](), [github](), [incident](), [internal-tools](), [mcp](), [organization](), [pull-request](), [slack](), [talks](), [team]() ### AI overview WorkOS's Applied AI Showcase in New York presented five internal tools--Horizon, Blog Bot, the CLI, Wallaby, and Atlas--through live demos and talks. The article explains how the Applied AI team helps non-engineering functions build AI-powered workflows and systems. ### Source excerpt WorkOS is becoming an AI-native organization. The Applied AI Showcase in NYC on July 28th 2026 showed exactly how with live demos and talks from the Applied AI team. ## How we migrated the database behind every Vercel build DevFeed: [How we migrated the database behind every Vercel build]() Original publisher: [Read original article]() Author: Andrew Healey Published: 2026-08-11T22:00:00Z Content type: article Language: en Sources: [Vercel News]() Topics: [migration](), [Redis](), [Vercel](), [Containers](), [Deployment](), [Database](), [Cache]() Tags: [cache](), [containers](), [database](), [deployment](), [latency](), [migration](), [production](), [redis](), [vercel]() ### AI overview Vercel describes migrating the database behind its build warm pool from Redis to DynamoDB. The migration moved important billing mappings and other pool state to durable storage while running live under production traffic, in phased rollouts with feature flags and rollback plans. ### Source excerpt Every build on Vercel starts in the build warm pool, which is a set of standby containers that let builds begin without waiting for new compute. The pool runs on state that tracks which containers are ready, the tokens each one uses to authenticate, and the mapping that ties every running build back to the deployment that gets billed for it. When we built the pool, we put all of that in Redis, which was fast and made sense at the time. Over the years, though, that state turned into a liability. Tokens and container statuses can be rebuilt if they get lost, but the billing mappings can't, and all of it was sitting in a store that we ran as an ephemeral cache. That state needed to live somewhere durable, which is why we decided to migrate it to DynamoDB. The problem is that the pool never stops. Containers are coming up, polling, picking up work, and expiring around the clock, which meant we couldn't pause the world, copy the data, and restart. The migration had to happen live, under production traffic, in phases, each one behind a flag with a rollback ready if we needed it. Durable state in an ephemeral store Redis was a good home for it at first. It was fast, familiar, and efficient for the access patterns the pool started with. But over time the state became more important than the store holding it. If Redis became unavailable or lost data, the pool could no longer reliably authenticate containers, track which of them were ready, or resolve the work in flight. Lose a token and the pool rebuilds it within about ten minutes. Lose a mapping and the build is never billed, because nothing else records which deployment it belonged to. We wanted it in durable storage and landed on DynamoDB. On-demand scaling fits bursty deployment traffic, TTL is native, and there are no connections to manage at high concurrency. But what it did not promise was Redis's latency. What Redis made cheap Inside Redis, the pool's state looked like this: Tokens lived in a set so we could check m ## Containing Locally Running AI Agents with Layered Security Controls DevFeed: [Containing Locally Running AI Agents with Layered Security Controls]() Original publisher: [Read original article]() Author: Spencer Reeves Published: 2026-08-10T18:00:00Z Content type: tutorial Language: en Sources: [Apartment 304]() Topics: [Artificial Intelligence](), [Security](), [Containers](), [virtualization](), [macOS](), [npm]() Tags: [agent](), [ai-agents](), [apartment-304](), [apple](), [credentials](), [custom-software-solutions](), [devops](), [devops-engineer](), [macos](), [networking](), [npm](), [open-source](), [sandboxing](), [security](), [software-architecture](), [software-development](), [software-engineer]() ### AI overview This article presents a layered security approach for running AI agents locally. It focuses on sandboxing the agent, restricting internet access, and protecting secrets and environment files, with container isolation as the foundation. ### Source excerpt Running an agent locally gives it a foothold on your machine -- here's how we keep it contained. [Next page]()