Learn Kubernetes Weekly issue 174 · 11 Mar 2026

AI Cut Debugging 75%, 60% Less Pods Doubled Traffic, Scaling Django to 1M Users, Kubernetes Bad Practices, PKI & Kubelet Credential Abuse

This newsletter is brought to you by LearnKube — master Kubernetes with hands-on training designed for engineers who want to learn the smart way.

Articles

  1. How We Cut Build Debugging Time by 75% with a DevEx AI Assistant

    medium.com

    This article describes how the team at Next Insurance built an AI-powered microservice that watches build failures via Jenkins, analyzes logs automatically and posts clear, helpful feedback to Slack.

  2. We Cut Our Kubernetes Pods by 60% and Doubled Traffic Capacity

    medium.com

    This case study shows how reducing JVM MaxRAMPercentage, cutting the Hikari connection pool from 50 to 20, and implementing aggressive HPA scale-up (0s stabilization, 4 pods/min) doubled traffic capacity while cutting baseline pods from 26 to 10.

  3. Scaling Django SaaS to 1M Users: Async ORM, Caching, and Horizontal Pods

    medium.com

    This article covers scaling a Django SaaS from a single EC2 instance to 1M users using async ORM, Redis caching layers, and Kubernetes horizontal pod autoscaling for sub-200ms response times.

  4. Hidden Kubernetes Bad Practices Learned the Hard Way During Incidents

    hackernoon.com

    This article shares hidden Kubernetes bad practices discovered through production incidents covering troubleshooting challenges, configuration mistakes, and operational lessons learned by a Site Reliability Engineer.

  5. Kubernetes PKI & Kubelet Credential Abuse: From Popping a Pod to Owning the Cluster

    medium.com

    This article demonstrates how to exploit Kubernetes PKI and kubelet credentials after gaining node access to escalate from pod compromise to full cluster control.

  6. A Non-MDM MDM: Certificate-Based Wi-Fi Without Device Management

    sudhikan.medium.com

    This article solves automated certificate distribution for EAP-TLS WiFi authentication using nginx-proxy on Kubernetes with step-ca, avoiding traditional MDM by hosting mobileconfig files at an HTTPS endpoint with mTLS authentication.

Articles worth checking out:

Tutorials

  1. Making and scaling a game server in Kubernetes using agones

    noe-t.dev

    This tutorial builds a rock-paper-scissors game server in Go integrated with Agones SDK, deploys it as a Fleet on Kubernetes, creates a matchmaking service using Watermill Pub/Sub with GameServerAllocation, and sets up autoscaling with FleetAutoscaler.

  2. PostgreSQL migration with CloudNativePG Logical Replication on Kubernetes — Zero-Downtime

    kndoni.medium.com

    This tutorial teaches how to migrate PostgreSQL databases to CloudNativePG on Kubernetes using logical replication without downtime.

  3. Gateway API setup on GKE with NGINX Gateway Fabric

    medium.com

    This tutorial shows how to deploy NGINX Gateway Fabric on GKE using Terraform to create separate internal and external traffic paths with Network Load Balancers and automated TLS certificate management.

Migrating Kubernetes Off Big Cloud

Managed Kubernetes on a major cloud provider can cost hundreds or even thousands of dollars a month — and much of that spending hides behind defaults, minimum resource ratios, and auxiliary services you didn't ask for.

Fernando Duran, founder of SadServers, shares how his GKE Autopilot proof of concept ran close to $1,000/month on a fraction of the CPU of the actual workload and how he cut that to roughly $30/month by moving to Hetzner with Edka as a managed control plane.

In this interview:

  • Why Kubernetes hasn't delivered on its original promise of cost savings through bin packing — and what it actually provides instead
  • A real cost comparison: $1,000/month on GKE vs. $30/month on Hetzner with Edka for the same nominal capacity
  • What you need to bring with you (observability, logging, dashboards) when leaving a fully managed cloud provider

The decision comes down to how tightly coupled you are to cloud-specific services and whether your team can spare the cycles to manage the gaps.

Migrating Kubernetes Off Big Cloud

Kubernetes jobs

    • Support Engineer with MongoDB

    • Salary: $90K to $176K a year

    • Location: remote from

    • Tech stack: Kubernetes, AWS, GCP, Azure, EKS, GKE, AKS, Kubernetes, Git, LDAP

    • Support Engineer with MongoDB

    • Salary: $90K to $176K a year

    • Location: remote from

    • Tech stack: Kubernetes, AWS, GCP, Azure, EKS, AKS, GKE, Kubernetes, Git, LDAP

    • Support Engineer with MongoDB

    • Salary: $90K to $176K a year

    • Location: remote from

    • Tech stack: Kubernetes, AWS, GCP, Azure, EKS, AKS, GKE, Kubernetes, AWS EC2, Git

    • Software Engineer with MongoDB

    • Salary: $126K to $248K a year

    • Location: based in the office (and remote from home) in New York City, NY, USA

    • Tech stack: Kubernetes, AWS, GCP, Azure, EKS, GKE, AKS, Kubernetes, AWS EC2, On call

    • Software Engineer with xAI

    • Salary: $180K to $440K a year

    • Location: fully remote

    • Tech stack: Kubernetes, Kubernetes, AWS S3, NumPy, pandas, PySpark, Triton Inference Server, Python, Rust

Discover more Kubernetes jobs on Kube Careers →

Code & tools

  1. Wozz: Kubernetes Cost Tool

    github.com/WozzHQ

    Wozz helps engineering teams reduce Kubernetes spend through two approaches:

    • Analyzes pull requests for resource changes and comments with cost impact before merge.
    • Scans running clusters to identify over-provisioned pods and wasted resources.
  2. Over-Engineered GitOps Homelab

    github.com/theepicsaxguy

    This repo is a GitOps-driven homelab blueprint where all infrastructure and apps are declaratively managed with tools like Talos, OpenTofu, ArgoCD, Cilium, Longhorn, Authentik, cert-manager, and more.

  3. k8sql: Kubernetes SQL query

    github.com/ndenev

    k8sql is a tool written in Rust that queries Kubernetes clusters using SQL syntax, exposing resources as database tables and kubectl contexts as databases with a query planner that optimizes API calls by pushing filters server-side.

  4. Sgl-project/rbg: AI inference orchestrator

    github.com/sgl-project

    RoleBasedGroup is a Kubernetes API written in Go for orchestrating distributed stateful AI inference workloads with multi role collaboration and built in service discovery, treating inference services as role based groups rather than isolated workloads.

  5. k8s-d2: Kubernetes visualization

    github.com/vieitesss

    k8s-d2 generates D2 diagram files from Kubernetes cluster topology, visualizing namespaces, workloads, services, and their relationships with customizable grid layouts and filtering options.

Other interesting projects:

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Until next time!

— Gulcan

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