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| Fecha | Crecimiento de Suscriptores | Menciones | Canales | |
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| 01 octubre | +3 |
Publicaciones del Canal
Repost from N/a
GitOps resolves real deployment problems, but it also creates new operational work.
Shani Adadi Kazaz explains that a Git repo as the source of truth improves rollbacks and consistency, but teams still need to operate tools like Argo CD or Flux across many clusters.
The key point is that GitOps reduces deployment chaos, not platform responsibility.
Watch the full interview: https://ku.bz/kThBjp3Lj
| 2 | WaaS creates browser-accessible Linux and Windows desktops as Kubernetes resources, with GitOps workflows, secure remote access, quotas, and OIDC and RBAC controls.
More: https://ku.bz/TgntmDfyC | 179 |
| 3 |  This article explains how Kubernetes 1.37 gives controllers shared APIs and a Go library for workload-aware scheduling, including gang scheduling and grouped workloads.
More: https://ku.bz/t7qQCk1Hz | 204 |
| 4 |  Why can a Go service be OOM-killed while its heap looks healthy?
The heap is only part of the container's memory usage. Goroutine stacks, native allocations, and runtime overhead also count toward the container limit.
In this new article from Gulcan, you will learn:
- How CPU quotas affect Go's parallelism and why extra threads can increase throttling.
- How to measure total container memory, including goroutine stacks and native allocations.
- Why a tighter memory budget can increase garbage collection work and reduce throughput.
Read: https://learnkube.com/go-kubernetes-requests-limits
This article is also included in our book on Kubernetes rightsizing: https://learnkube.com/kubernetes-rightsizing | 203 |
| 5 |  Join NeuBird and industry leaders at FLOCK ’26 on October 14 in San Francisco.
Built for SREs, platform engineers, and reliability leaders exploring autonomous ops.
Expect keynotes from former NASA astronaut Mike Massimino and MIT Media Lab’s Ramesh Raskar, hands-on breakouts, and curated seating.
📆 October 14 · SF
Register here: https://na2.hubs.ly/H08984m0 | 293 |
| 6 |  Understudy is a Kubernetes operator that starts a temporary replacement for a single-replica workload before a planned node disruption, helping reduce downtime without running two pods all day.
More: https://ku.bz/kG1TYjcCT | 336 |
| 7 |  This case study shows how an AKS-based GitOps platform gave on-premises clusters workload identity by publishing static OIDC discovery and JWKS files, avoiding API server changes after provisioning.
More: https://ku.bz/TpvjylBlF | 309 |
| 8 | This case study shows how WSC Sports rebuilt their entire deployment model from helm upgrade pipelines to full GitOps using ArgoCD ApplicationSets, covering:
- single-chart monorepo design,
- shadow deployments,
- AppProjects,
- CI code freeze gates.
More: https://ku.bz/k0MjkJlfX | 489 |
| 9 | PigeonEye is a fast native Kubernetes GUI that loads large clusters through the Table API and gives you multi-cluster search, logs, safe edits, debugging tools, and automatic CRD support.
More: https://ku.bz/B0087NZrd | 538 |
| 10 | MariaDB Operator manages MariaDB on Kubernetes with high-availability clusters, backups, point-in-time recovery, TLS, rolling updates, and declarative SQL resources.
More: https://ku.bz/4LmZWWbm- | 582 |
| 11 |  InfraLens uses eBPF to map live TCP and UDP connections across Kubernetes and Linux servers, identify services, and show real-time traffic without changing application code.
More: https://ku.bz/1ZBpgFSz9 | 656 |
| 12 |  Mac Chaffee shares his approach to building internal platforms that expose rather than hide Kubernetes complexity.
He argues against creating additional abstraction layers over the Kubernetes API, explaining how this often leads to reinventing the Kubernetes API in less feature-rich ways.
Using Docker Compose as an example, Mac demonstrates how simplified abstractions still contain the same core concepts (health checks, security contexts) but in condensed, limited formats. Instead of hiding complexity, he advocates for exposing the Kubernetes API directly to developers while building comprehensive guardrails around it.
Watch the full episode: https://ku.bz/9nFPmG85f | 586 |
| 13 | Postgres Operator manages external PostgreSQL databases and users via Kubernetes custom resources, automatically creates credentials, and supports AWS RDS, Azure, and GCP Cloud SQL.
More: https://ku.bz/CqZGlb7zl | 458 |
| 14 | Attune watches real pod usage and adjusts CPU and memory requests without restarting pods, with canary rollouts, safety checks, and automatic rollback.
More: https://ku.bz/bqN9cJ24f | 476 |
| 15 |  Sveltos manages apps and add-ons across multiple Kubernetes clusters from one management cluster using Helm, YAML, Kustomize, Carvel, or Jsonnet, with deployment ordering and drift repair.
More: https://ku.bz/s0f7l2QBf | 517 |
| 16 | Fabián Sellés Rosa, Tech Lead in the Runtime team @ Adevinta, explains the technical challenges that emerge when platform tenants want to integrate with external managed Kafka services.
The core DNS challenge becomes clear: Kafka clients need to connect to external broker infrastructure without knowing the specific connection details. This requires DNS rewriting capabilities, allowing applications to seamlessly access external Kafka services while the platform handles the complexity of routing traffic through private links to the provider's infrastructure.
Watch the full episode: https://ku.bz/NsBZ-FwcJ | 483 |
| 17 |  This week on Learn Kubernetes Weekly 203:
🔥 Building Modelplane on Crossplane
🚪 Kubernetes Gateway API: Why Ingress Is Being Replaced and Which Gateway Controller to Pick
🛡️ From Fragile VMs to Bulletproof GitOps: Modernizing a DevOps Platform on AWS EKS
💾 How a 500 MB Buffer Killed Our Archival Job, and Why Streaming Fixed It
🎮 How GPU MIG + Kueue Can Transform Multi-Tenant AI Workloads on Kubernetes
Read it now: https://kube.today/issues/203
⭐️ This newsletter is brought to you by LearnKube — understand how Kubernetes works, and what to do when it breaks. Live training with 60% hands-on labs.https://ku.bz/hypSbyc-V | 336 |
| 18 | "Most teams don't lack tools. They lack trust."
Only 6% of teams use commercial optimization tools, and just 32% use VPA or HPA — even though both are freely available. Ray Chen argues the problem isn't access to automation, it's confidence in it. At Trumid, automation stays read-only in the cluster: it proposes changes, opens a PR, and lets someone with business context approve. A 10% increase in CPU makes sense after a volume ramp-up. A 50% memory reduction makes sense when a service is being replaced.
Teams adopt automation when they stay in control of the decisions.
Watch the full interview: https://ku.bz/w50VfwtYd | 452 |
| 19 | This tutorial shows how to put dev, QA and staging clusters to sleep overnight with KEDA's cron scaler, including the Argo CD gotchas around CRDs, RoleBindings and replica drift.
More: https://ku.bz/7zK_Wx9G4 | 438 |
| 20 |  This article explains how to design a production-grade MCP server for platform teams, with governance, backend clients, tool definitions and auth as four separate layers, plus the RBAC and deployment work needed before it touches a real cluster.
More: https://ku.bz/6c5t89LYj | 607 |
