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| Дата | Залучення підписників | Згадування | Канали | |
| 01 серпня | +1 |
Дописи каналу
Repost from N/a
Three Kubernetes tools are standing out right now.
Shani Adadi Kazaz says Kro, Argo CD, and ACK each solve a different operational layer: delivery, cloud resource management, and higher-level orchestration.
The takeaway is that platform teams get leverage by combining the right abstractions, not by adding more raw cluster complexity.
Watch the full interview: https://ku.bz/kThBjp3Lj
| 2 |  Okteto is a development platform that creates production-like Kubernetes environments with live code sync, allowing developers to code directly in clusters without local setup or Docker builds.
More: https://ku.bz/zvHF54_1x | 170 |
| 3 |  John Howard, Senior Software Engineer at Solo.io, provides clear recommendations for teams looking to implement mTLS in Kubernetes environments.
He strongly advises against DIY approaches for most organizations, noting he's rarely seen successful implementations at scale. Instead, he recommends service mesh solutions, with Ambient Mesh as the optimal choice for teams specifically focused on mTLS implementation. John outlines a clear hierarchy of options: Ambient Mesh first, traditional sidecar mesh second, and DIY as a last resort. He explains that Ambient Mesh was specifically designed for straightforward mTLS deployment across Kubernetes environments.
Watch the full episode: https://kube.fmhttps://ku.bz/sk-ZF1PG9 | 185 |
| 4 |  OpenTelemetry profiling gives teams visibility from the kernel to the application layer, which is why it stands out to Mauricio Salatino.
Mauricio Salatino also points to llm-d as a project worth watching as more large language model workloads move onto Kubernetes and developers start building practical examples around them.
Watch the full interview: https://ku.bz/QXKc1tBFY | 227 |
| 5 |  This article explains how to design an AI agent for SRE operations that reads alerts, logs, Kubernetes data, runbooks, deployments, and observability signals to diagnose incidents and propose safe actions.
More: https://ku.bz/2S6-kCZ2y | 225 |
| 6 | KubeGUI is a desktop application that provides a graphical interface for managing Kubernetes clusters with resource visualization and management capabilities.
More: https://ku.bz/R_RzJwSVH | 263 |
| 7 |  This week on Learn Kubernetes Weekly 194:
🤖 We're a 3-Person Tech Team Running Production Kubernetes — So We Built an AI SRE
💸 The GPU Bill Was $40,000. Nobody Knew Why.
🔓 Copy Fail in Kubernetes: PSS Restricted and RuntimeDefault Did Not Block AF_ALG
📦 How We Set Up One Private Container Registry for 6 AKS Clusters Across 3 Regions and What Broke Along the Way
⚙️ GitOps with Terraform Using tofu-controller: Grafana and Hashicorp Vault as Code
Read it now: https://kube.today/issues/194
⭐️ This issue is brought to you by Isovalent — enterprise-grade Kubernetes networking and security, built by the creators of Cilium and eBPF https://ku.bz/d6xF7GMzh | 701 |
| 8 |  This article explains why ONNX Runtime can keep gigabytes of memory after inference.
It shows how allocator behavior, session reuse, and runtime tuning affect memory usage, latency, and containerized workloads.
More: https://ku.bz/cfqxFhv93 | 286 |
| 9 | Kubernetes abstracts away Linux primitives — but understanding them makes you better at your job.
Mauro Morales explains why knowing cgroups, namespaces, and how Linux processes work gives you a real advantage. You can architect systems deliberately instead of guessing, debug problems below the Kubernetes layer, and use that knowledge as a safety net when the abstractions don't give you answers.
You don't need to be an expert. But fluency in the layer beneath pays off.
Watch the full interview: https://ku.bz/8cpgjFfjn
This interview is a reaction to Eric Jalal's episode https://ku.bz/-jCTfgqRC | 279 |
| 10 | Federico Iezzi, Customer Engineer at Google Cloud, explains how his team achieved 1 million output tokens per second using Qwen 3.5 27B, vLLM, GKE Autopilot, and NVIDIA B200 GPUs.
You will learn:
- Why memory bandwidth limits decode performance
- How Federico chose between tensor and data parallelism
- What changed after enabling multi-token prediction and reducing the KV cache footprint with FP8 quantization
Watch (or listen to) it here: https://ku.bz/1xD9Md0mb
🌟 This episode is brought to you by LearnKube. Download the free book, The Technical Guide to Kubernetes Rightsizing, to understand what Prometheus and Grafana cannot tell you about safely reducing requests and limits: https://learnkube.com/kubernetes-rightsizing
With @Birthmarkb | 166 |
| 11 | Grafana Beyla is an open source eBPF-based tool that auto-instruments HTTP/gRPC apps to collect essential traces and RED metrics and exports them in OpenTelemetry or Prometheus formats.
More: https://ku.bz/61N3-25F4 | 330 |
| 12 | "Kubernetes 2.0. Let's go."
Nicholas Eberts on where Kubernetes is heading: AI/ML workloads are pushing the platform to adapt in ways it hasn't had to historically. Expect major movement in the scheduler — look at DRA (Dynamic Resource Allocation) and how it handles disparate hardware classes within deployments.
These changes are shaping what Kubernetes 2.0 will look like. The question is how far it can keep evolving with the industry.
Watch the full interview: https://ku.bz/jlDL5XzCd | 294 |
| 13 | This tutorial explains how to sign and verify Docker images in Amazon ECR using Cosign and AWS KMS.
It also shows how trusted image enforcement can fit into EKS and Kyverno-based supply chain security.
More: https://ku.bz/NG8185Rvq | 351 |
| 14 |  This case study shows how a 3-person team built a Claude-based AI SRE that triages SigNoz alerts, checks Kubernetes, GitLab, logs, traces, and Slack, then ignores noise, escalates, or runs safe fixes.
More: https://ku.bz/X_PPQ-4lR | 904 |
| 15 | Custom compute classes and in-place pod resize change how teams manage Kubernetes workloads.
Roman Arcea explains how both features reduce manual tuning and make cluster operations easier to control.
Watch the full interview: https://ku.bz/sFvFF3Kvs | 356 |
| 16 | This case study explains how one private container registry was shared across six AKS clusters in three regions.
It covers ACR geo-replication, image pull reliability, network access, permissions, and operational breakages.
More: https://ku.bz/CjrRY3Jp8 | 255 |
| 17 | Stephan Schwarz, DevOps Engineer at iits-consulting, explains the difference between load testing and observability when diagnosing performance issues in production Kubernetes environments. He addresses a common challenge: what to do when requests are slow in production and you can't run disruptive load tests to identify the root cause.
Stephan introduces OpenTelemetry tracing as the solution for distributed systems running in Kubernetes.
This approach enables teams to investigate specific customer requests that are performing poorly while other requests work normally, providing granular visibility into distributed application performance without impacting production workloads. The discussion highlights how observability complements traditional performance testing by addressing real-time production debugging scenarios.
Watch the full episode: https://ku.bz/yY-FnmGfH | 314 |
| 18 |  "I just want Kubernetes to disappear."
Zain Malik from ExoStellar shares his vision for the next decade: a world where Kubernetes becomes so automated and self-reliant that developers don't even know they're running on it.
The goal isn't to learn Kubernetes—it's to move to the next layer where everyone can reliably build applications without thinking about the underlying platform.
Watch the full interview: https://ku.bz/rwttMCncv | 294 |
| 19 |  Fulling automatically sets up a complete development environment with Next.js, PostgreSQL, and Claude Code so you can build full-stack apps through natural language conversation.
More: https://ku.bz/NWz4hg2d6 | 319 |
| 20 |  This tutorial shows how to deploy a 5-agent ADK system on Amazon EKS and test Agent-to-Agent workflows with Gemini CLI.
More: https://ku.bz/NwN8mpHb7 | 353 |
