Spotlight

Autoscaling Kafka Consumers on Kubernetes using Confluent and KEDA

Son Ng.

This tutorial teaches how to autoscale Kafka consumers on Kubernetes using KEDA and consumer lag as the scaling metric with Confluent Platform.

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Tools and utilities

  • Chainloop: SDLC Evidence Store

    Chainloop is an evidence store and policy engine for Software Supply Chain attestations, SBOMs, VEX, SARIF, and QA reports, with contract-based workflows, Rego policy evaluation, and third-party integrations such as Dependency-Track and Guac.

  • Docker Time Machine: image evolution

    Docker Time Machine is a CLI tool written in Go that tracks Docker image evolution through git history by walking through commits, building images, and recording metrics like size, layer count, and build time.

  • Kubey: Web-based Kubernetes Dashboard

    Kubey is a web-based Kubernetes dashboard that provides team visibility across multiple clusters, with cross-cluster deployment comparison, real-time monitoring, and web access.

  • KubePolaris: cluster management platform

    KubePolaris is an enterprise Kubernetes multi-cluster management platform built with React and Go, providing workload management, monitoring integration, RBAC access control, and GitOps capabilities through an intuitive web interface.

  • cookiecluster: EKS Terraform CLI

    cookiecluster is a CLI tool written in Rust that generates EKS cluster definitions in Terraform through an interactive configuration process.

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Migrating to Karpenter: Fun Stories
Migrating to Karpenter: Fun Stories

Running multiple Kubernetes clusters on AWS with the cluster autoscaler? Every four months, you face the same grind: upgrading Kubernetes versions, recreating auto scaling groups, and hoping instance type changes stick.

Adhi Sutandi, DevOps Engineer at Beekeeper by LumApps, shares how his team migrated from the cluster autoscaler to Karpenter across eight EKS clusters — and the hard lessons they learned along the way.

In this episode:

  • Why AWS auto scaling groups are immutable and how that creates upgrade bottlenecks at scale
  • How the latest AMI tag accidentally turned less critical clusters into chaos engineering environments, dropping SLOs before anyone realized Karpenter was the cause
  • Why pre-stop sleep hooks solved pod restartability problems that Quarkus's built-in graceful shutdown couldn't
  • The case for pod disruption budgets over Karpenter annotations when protecting critical workloads during node rotations
  • How Karpenter's implicit 10% disruption budget caught the team off guard — and the explicit configuration that fixed it

Learn from production

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Matching jobs

    • Account Executive - Enterprise with Tigera

    • Salary: $200K to $220K a year

    • Location: based in the office (and remote from home) in Vancouver, CA

    • Tech stack: Kubernetes, Azure, AWS, GCP, OpenShift, Python, Shell, SQL, GraphQL, Javascript

    • Data Engineer with Altana

    • Salary: $175K to $205K a year

    • Location: based in the office (and remote from home) in Brooklyn, NY; Washington, DC, USA

    • Tech stack: Kubernetes, AWS, Azure, Docker, SQL, Python, GraphQL, PostgreSQL, Spark, OpenSearch

    • Data Engineer with T-Rex Solutions

    • Salary: $190K to $225K a year

    • Location: based in the office in Ft. Meade, MD, USA

    • Tech stack: Kubernetes, Docker, Java, Groovy, Shell, Python, Terraform, Ansible

    • Data Engineer with Zinnia

    • Salary: $88.2K to $302.5K a year

    • Location: fully remote

    • Tech stack: Kubernetes, GCP, Python, SQL, Airflow, Terraform, ARM templates, Cloudformation, Pulumi, CDK

    • DevOps Engineer with 6sense

    • Salary: $27K to $344K a year

    • Location: fully remote

    • Tech stack: Kubernetes, AWS, SQL, Python, Java, PostgreSQL, Hadoop, Pulumi, Terraform, Cloudformation

Discover more Kubernetes jobs on Kube Careers →

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