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  1. Stackups
  2. Application & Data
  3. Infrastructure as a Service
  4. Cluster Management
  5. kops vs minikube

kops vs minikube

OverviewComparisonAlternatives

Overview

kops
kops
Stacks94
Followers77
Votes0
GitHub Stars16.5K
Forks4.7K
minikube
minikube
Stacks110
Followers262
Votes3
GitHub Stars31.1K
Forks5.1K

kops vs minikube: What are the differences?

Introduction:

Kops and Minikube are two popular tools used in the development and deployment of Kubernetes clusters. While both tools serve similar purposes, they have certain differences that make them suitable for specific use cases.

Key differences between kops and minikube:

  1. Cluster creation and management: Kops is primarily used for creating and managing production-ready, highly available Kubernetes clusters on cloud infrastructure providers such as AWS, GCP, and Azure. It automates the process of deploying and operating clusters at scale. On the other hand, Minikube is designed for local development and testing purposes. It allows developers to run a single-node Kubernetes cluster locally on their machines, simulating the behavior of a full-scale cluster.

  2. Scalability and resource consumption: Kops enables the creation of large-scale Kubernetes cluster deployments, supporting multiple availability zones and distributed systems. It allows users to create high-availability clusters suitable for production environments. In contrast, Minikube is limited in scalability as it runs on a single node on a local machine. It is optimized for minimal resource consumption and is more suitable for individual developers or small teams.

  3. Networking and cluster setup: Kops provides options for configuring advanced networking features such as networking plugins, network policies, and load balancers during cluster creation. It supports integration with various cloud networking solutions. On the other hand, Minikube simplifies the setup process by providing an easy-to-use command-line interface. It sets up a default networking configuration suited for local development, allowing developers to focus on application development rather than network setup.

  4. Persistent storage: Kops provides features for persistent storage management, allowing users to define and manage storage volumes for their applications running on Kubernetes clusters. It supports integration with cloud-specific storage solutions. In contrast, Minikube does not offer built-in persistent storage management. It is designed to use host machine storage and does not provide advanced storage options out-of-the-box.

  5. Supported operating systems: Kops can be used on various operating systems, including Linux, macOS, and Windows. It provides flexibility in terms of platform choice. On the other hand, Minikube is primarily designed for macOS and Linux platforms. While it can be used on Windows, certain features and functionalities may not be fully supported.

  6. Deployment environments: Kops is primarily used for deploying Kubernetes clusters on public cloud providers. It leverages the infrastructure-as-code approach, allowing users to define the cluster configuration in files that can be version-controlled. Minikube, on the other hand, is focused on local development and testing environments. It provides a lightweight and portable solution for running Kubernetes on a single machine.

In summary, kops is focused on the creation and management of production-grade, highly available Kubernetes clusters on cloud platforms, while Minikube is optimized for local development and testing of Kubernetes applications on individual machines.

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Detailed Comparison

kops
kops
minikube
minikube

It helps you create, destroy, upgrade and maintain production-grade, highly available, Kubernetes clusters from the command line. AWS (Amazon Web Services) is currently officially supported, with GCE in beta support , and VMware vSphere in alpha, and other platforms planned.

It implements a local Kubernetes cluster on macOS, Linux, and Windows. Its goal is to be the tool for local Kubernetes application development and to support all Kubernetes features that fit.

-
Local Kubernetes; LoadBalancer; Multi-cluster
Statistics
GitHub Stars
16.5K
GitHub Stars
31.1K
GitHub Forks
4.7K
GitHub Forks
5.1K
Stacks
94
Stacks
110
Followers
77
Followers
262
Votes
0
Votes
3
Pros & Cons
No community feedback yet
Pros
  • 1
    Let's me test k8s config locally
  • 1
    Easy setup
  • 1
    Can use same yaml config I'll use for prod deployment
Integrations
No integrations available
Windows
Windows
Linux
Linux
macOS
macOS

What are some alternatives to kops, minikube?

Kubernetes

Kubernetes

Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions.

Rancher

Rancher

Rancher is an open source container management platform that includes full distributions of Kubernetes, Apache Mesos and Docker Swarm, and makes it simple to operate container clusters on any cloud or infrastructure platform.

Docker Compose

Docker Compose

With Compose, you define a multi-container application in a single file, then spin your application up in a single command which does everything that needs to be done to get it running.

Docker Swarm

Docker Swarm

Swarm serves the standard Docker API, so any tool which already communicates with a Docker daemon can use Swarm to transparently scale to multiple hosts: Dokku, Compose, Krane, Deis, DockerUI, Shipyard, Drone, Jenkins... and, of course, the Docker client itself.

Tutum

Tutum

Tutum lets developers easily manage and run lightweight, portable, self-sufficient containers from any application. AWS-like control, Heroku-like ease. The same container that a developer builds and tests on a laptop can run at scale in Tutum.

Portainer

Portainer

It is a universal container management tool. It works with Kubernetes, Docker, Docker Swarm and Azure ACI. It allows you to manage containers without needing to know platform-specific code.

Codefresh

Codefresh

Automate and parallelize testing. Codefresh allows teams to spin up on-demand compositions to run unit and integration tests as part of the continuous integration process. Jenkins integration allows more complex pipelines.

Nomad

Nomad

Nomad is a cluster manager, designed for both long lived services and short lived batch processing workloads. Developers use a declarative job specification to submit work, and Nomad ensures constraints are satisfied and resource utilization is optimized by efficient task packing. Nomad supports all major operating systems and virtualized, containerized, or standalone applications.

Apache Mesos

Apache Mesos

Apache Mesos is a cluster manager that simplifies the complexity of running applications on a shared pool of servers.

CAST.AI

CAST.AI

It is an AI-driven cloud optimization platform for Kubernetes. Instantly cut your cloud bill, prevent downtime, and 10X the power of DevOps.

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