Learn Kubernetes Weekly issue 136 · 18 Jun 2025

Native macOS Workloads with Kubernetes, Pods breaking bad, FacetController: Infrastructure Changes at Lyft, Managing Stateful Workloads

This issue is brought to you by Learnk8s — get started on your Kubernetes journey through comprehensive online, in-person or remote training.

This Thursday, I'm going live with Andrew to discuss one of the most persistent challenges in Kubernetes: resource management.

We will explore how algorithms can make more effective resource decisions than manual configuration!

Articles

  1. How We Integrated Native macOS Workloads with Kubernetes

    medium.com

    Agoda built macOS-vz-Kubelet, a virtual kubelet running directly on macOS, to manage Apple Silicon VMs via Apple’s Virtualization Framework.

    It turns Mac Minis into schedulable Kubernetes nodes with OCI-backed VM images and hybrid Pod support.

  2. Why our pods were breaking bad (and how we fixed them)

    kshitij-nawandar.medium.com

    Razorpay's UPI service pods were silently degrading over time.

    They used Go's pprof profiling to find that a global variable kept growing.

    The code fix reduced CPU usage from 5 cores to ~150m, memory from 700 MiB to 50 MiB, and API latency by half.

  3. FacetController: How We Made Infrastructure Changes at Lyft Simple

    eng.lyft.com

    Learn how Lyft developed FacetController, a CRD that simplifies infrastructure changes by creating a unified abstraction for microservice deployments.

    This enables rapid, safe updates across thousands of services without manual intervention.

  4. Operational Considerations for Managing Stateful Workloads

    dev.to

    This article provides a playbook for managing database workloads in Kubernetes, focusing on strategies for isolation, dynamic credential management, high availability, disaster recovery, and observability.

  5. Can configuration languages (Config DSLs) solve configuration complexity?

    itnext.io

    Can config DSLs solve config complexity?

    This article reviews various config languages (HCL, Jsonnet, etc.). It concludes that they offer some benefits but are ultimately micro-optimizations that don't solve the core IaC challenges.

  6. GKE Cost Cutting — Three Key Lookout Points to View Your Potential Savings

    medium.com

    Optimize GKE expenses by analyzing cluster costs, identifying at-risk workloads, and rightsizing resources using Google's built-in tools to reduce infrastructure spending by up to 50%.

Articles worth checking out:

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Tutorials

  1. Track privilege escalations with eBPF

    parseable.com

    This guide shows how to detect Kubernetes runtime threats (e.g. sudo misuse, suspicious file access) using Falco + eBPF, forward logs with Fluent Bit, and route them to Parseable log streams like falcowarn or falconotice.

  2. \Why every platform engineer should care about Kubernetes operators

    pulumi.com

    This tutorial explains how kubernetes operators extend controllers with CRDs to automate complex app lifecycles.

    They manage deployments, upgrades, backups, and recovery, embedding domain-specific logic for self-managing systems.

  3. Optimizing Kubernetes Resource Allocation with Robusta-KRR

    medium.com

    This article demonstrates how Robusta KRR analyzes pod CPU and memory usage, then recommends optimized resource requests and limits.

    Learn how to reduce overprovisioning and lower costs using automated metrics-based tuning in Kubernetes.

  4. Demystifying Swap in Kubernetes: A Handbook for DevOps Engineers

    medium.com

    Kubernetes 1.28+ allows controlled swap via LimitedSwap for Burstable pods, avoiding OOMs during memory spikes.

    This guide shows how to set up swap files, enable Kubelet config flags, and test behavior.

  5. Argo Rollouts  —  Canary Deployment with Istio

    medium.chuklee.com

    This article demonstrates how Argo Rollouts leverages Istio’s traffic routing—via VirtualService and DestinationRule—to enable advanced canary strategies: by percentage, HTTP header, and request mirroring.

Beyond Kubernetes: Serverless Execution Models for Variable Workloads

Marc Campora, a systems consultant with experience in high-throughput platforms, shares his analysis of a real customer deployment with 500+ microservices. He breaks down the cost implications, technical constraints, and operational trade-offs between Kubernetes containers and AWS Lambda functions based on actual production data and migration assessments.

You will learn:

  • Cost analysis frameworks for comparing Lambda vs Kubernetes across different traffic patterns, including specific examples of 3x savings potential and the 80/20 rule for service utilization
  • Migration complexity factors when moving existing microservices to Lambda, including cold start issues, runtime model changes, and why it's often a complete rewrite rather than a simple port
  • Decision criteria for choosing between platforms based on traffic consistency, computational requirements, and operational overhead tolerance
Beyond Kubernetes: Serverless Execution Models for Variable Workloads

Kubernetes jobs

    • Software Engineer with Hootsuite

    • Salary: CA$98.4K to CA$137.8K a year

    • Location: remote from Canada

    • Tech stack: Kubernetes, Docker, Go, Javascript, Scala, PHP, Typescript, Redis, MySQL, Kafka

    • Data Engineer with Chartbeat

    • Salary: $128K to $147K a year

    • Location: remote from the United States

    • Tech stack: Kubernetes, Python, PostgreSQL, Snowflake, Kafka

    • Software Engineer with NVIDIA

    • Salary: $148K to $276K a year

    • Location: remote from the United States

    • Tech stack: Kubernetes, Shell, Python, Ansible, Puppet

    • Solution Architect with NVIDIA

    • Salary: $148K to $235.75K a year

    • Location: based in the office (and remote from home) in Santa Clara, CA / NC / TX / CO / WA, USA

    • Tech stack: Kubernetes, Data center, Docker, C++, C

    • Platform Engineer with Handshake

    • Salary: $180K to $220K a year

    • Location: remote from the United States

    • Tech stack: Kubernetes, AWS, GCP, ArgoCD, Java, Elastic Search, Terraform, Datadog, OTEL, Istio

Discover more Kubernetes jobs on Kube Careers →

Code & tools

  1. kpatch: Live Kernel Patching

    github.com/dynup

    kpatch enables runtime kernel function patching by injecting precompiled replacement functions directly into the live kernel.

    It's built on the CONFIG_LIVEPATCH infrastructure and uses ftrace to reroute function calls at runtime.

  2. Kubernetes Security Cheatsheet Diagram: A Visual Map of On-Prem Cluster Security Controls

    kubesec-diagram.github.io

    This diagram maps core Kubernetes security concepts—from RBAC, PodSecurity, and audit logging to container isolation—helping teams visualize enforcement points.

    Built by Telenor for on-prem clusters, it’s ideal for threat modelling or reviews.

  3. Kubernetes-WithOut-Kubelet

    github.com/kubernetes-sigs

    KWOK (Kubernetes-WithOut-Kubelet) is a toolkit that enables setting up a cluster of thousands of nodes in seconds.

    Under the scene, all Nodes are simulated to behave like real ones, so the overall approach employs a pretty low resource footprint.

  4. kubernetes/git-sync

    github.com/kubernetes

    git-sync is a simple command that pulls a git repository into a local directory.

    It is a perfect "sidecar" container in Kubernetes - it can periodically pull files down from a repository so that an application can consume them.

  5. Talos Linux

    talos.dev

    Talos is a modern Linux distribution for running Kubernetes: secure, immutable, and minimal.

    Talos is fully open-source & production-ready.

    All system management is done via an API - no shell or interactive console exists.

Other interesting projects:

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Until next time!

— Dan

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