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  5. Argo vs minikube

Argo vs minikube

OverviewComparisonAlternatives

Overview

minikube
minikube
Stacks110
Followers262
Votes3
GitHub Stars31.1K
Forks5.1K
Argo
Argo
Stacks761
Followers470
Votes6

Argo vs minikube: What are the differences?

What is Argo? Container-native workflows for Kubernetes. Argo is an open source container-native workflow engine for getting work done on Kubernetes. Argo is implemented as a Kubernetes CRD (Custom Resource Definition).

What is minikube? Local Kubernetes engine. 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.

Argo and minikube can be categorized as "Container" tools.

Some of the features offered by Argo are:

  • DAG or Steps based declaration of workflows
  • Artifact support (S3, Artifactory, HTTP, Git, raw)
  • Step level input & outputs (artifacts/parameters)

On the other hand, minikube provides the following key features:

  • Local Kubernetes
  • LoadBalancer
  • Multi-cluster

Argo and minikube are both open source tools. It seems that minikube with 15.2K GitHub stars and 2.39K forks on GitHub has more adoption than Argo with 3.47K GitHub stars and 497 GitHub forks.

Kalibrr, CommonBond, and Fivestars are some of the popular companies that use minikube, whereas Argo is used by Intuit, Solvvy, and Buzzvil. minikube has a broader approval, being mentioned in 3 company stacks & 5 developers stacks; compared to Argo, which is listed in 5 company stacks and 3 developer stacks.

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Detailed Comparison

minikube
minikube
Argo
Argo

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.

Argo is an open source container-native workflow engine for getting work done on Kubernetes. Argo is implemented as a Kubernetes CRD (Custom Resource Definition).

Local Kubernetes; LoadBalancer; Multi-cluster
DAG or Steps based declaration of workflows;Artifact support (S3, Artifactory, HTTP, Git, raw);Step level input & outputs (artifacts/parameters);Loops;Parameterization;Conditionals;Timeouts (step & workflow level);Retry (step & workflow level);Resubmit (memoized);Suspend & Resume;Cancellation;K8s resource orchestration;Exit Hooks (notifications, cleanup);Garbage collection of completed workflow;Scheduling (affinity/tolerations/node selectors);Volumes (ephemeral/existing);Parallelism limits;Daemoned steps;DinD (docker-in-docker);Script steps
Statistics
GitHub Stars
31.1K
GitHub Stars
-
GitHub Forks
5.1K
GitHub Forks
-
Stacks
110
Stacks
761
Followers
262
Followers
470
Votes
3
Votes
6
Pros & Cons
Pros
  • 1
    Let's me test k8s config locally
  • 1
    Easy setup
  • 1
    Can use same yaml config I'll use for prod deployment
Pros
  • 3
    Open Source
  • 2
    Autosinchronize the changes to deploy
  • 1
    Online service, no need to install anything
Integrations
Windows
Windows
Linux
Linux
macOS
macOS
Kubernetes
Kubernetes
Docker
Docker

What are some alternatives to minikube, Argo?

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.

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.

k3s

k3s

Certified Kubernetes distribution designed for production workloads in unattended, resource-constrained, remote locations or inside IoT appliances. Supports something as small as a Raspberry Pi or as large as an AWS a1.4xlarge 32GiB server.

Flocker

Flocker

Flocker is a data volume manager and multi-host Docker cluster management tool. With it you can control your data using the same tools you use for your stateless applications. This means that you can run your databases, queues and key-value stores in Docker and move them around as easily as the rest of your app.

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