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  5. Argo vs Docker Swarm

Argo vs Docker Swarm

OverviewDecisionsComparisonAlternatives

Overview

Docker Swarm
Docker Swarm
Stacks779
Followers990
Votes282
Argo
Argo
Stacks761
Followers470
Votes6

Argo vs Docker Swarm: What are the differences?

Introduction

Argo and Docker Swarm are both container orchestration platforms that allow users to manage and deploy containers at scale. However, there are several key differences between the two platforms that can influence the choice of which one to use for specific use cases. In this Markdown code, I will present six specific differences between Argo and Docker Swarm.

  1. Architecture: Argo is built on top of Kubernetes, which provides a more robust and scalable architecture for container orchestration. On the other hand, Docker Swarm has a simpler architecture and is easier to set up and manage.

  2. Scaling: Docker Swarm allows for both vertical and horizontal scaling of containers. It automatically distributes containers across multiple hosts, allowing for improved load balancing and scalability. Argo, on the other hand, primarily focuses on horizontal scaling and provides advanced features like pod autoscaling based on CPU and memory usage.

  3. Rolling Updates: Docker Swarm supports rolling updates, which allows for zero-downtime deployments by gradually updating containers in a controlled manner. Argo, on the other hand, does not provide built-in rolling updates functionality. However, it can still achieve similar results by using Kubernetes deployments and rolling update strategies.

  4. Service Discovery: Docker Swarm includes a built-in DNS-based service discovery mechanism, which allows containers to discover and communicate with each other using service names. Argo relies on Kubernetes' service discovery mechanism, which provides similar functionality but requires additional configuration and setup.

  5. Networking: Argo uses the default networking capabilities provided by Kubernetes, including the ability to create and manage virtual networks and load balancers. Docker Swarm, on the other hand, has its own overlay network driver, which simplifies networking configuration and allows for secure and isolated communication between containers.

  6. Community and Ecosystem: Kubernetes, the underlying platform for Argo, has a larger and more active community compared to Docker Swarm. This means that there is a wider range of resources, tools, and third-party integrations available for Kubernetes and Argo. Docker Swarm, on the other hand, has a smaller but still dedicated community and a more focused ecosystem around Docker.

In summary, the key differences between Argo and Docker Swarm include their underlying architecture, scaling capabilities, rolling updates support, service discovery mechanisms, networking options, and the size and activity of their respective communities and ecosystems. These differences should be taken into consideration when choosing the container orchestration platform that best fits a specific use case.

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Advice on Docker Swarm, Argo

Simon
Simon

Senior Fullstack Developer at QUANTUSflow Software GmbH

Apr 27, 2020

DecidedonGitHubGitHubGitHub PagesGitHub PagesMarkdownMarkdown

Our whole DevOps stack consists of the following tools:

  • @{GitHub}|tool:27| (incl. @{GitHub Pages}|tool:683|/@{Markdown}|tool:1147| for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
  • Respectively @{Git}|tool:1046| as revision control system
  • @{SourceTree}|tool:1599| as @{Git}|tool:1046| GUI
  • @{Visual Studio Code}|tool:4202| as IDE
  • @{CircleCI}|tool:190| for continuous integration (automatize development process)
  • @{Prettier}|tool:7035| / @{TSLint}|tool:5561| / @{ESLint}|tool:3337| as code linter
  • @{SonarQube}|tool:2638| as quality gate
  • @{Docker}|tool:586| as container management (incl. @{Docker Compose}|tool:3136| for multi-container application management)
  • @{VirtualBox}|tool:774| for operating system simulation tests
  • @{Kubernetes}|tool:1885| as cluster management for docker containers
  • @{Heroku}|tool:133| for deploying in test environments
  • @{nginx}|tool:1052| as web server (preferably used as facade server in production environment)
  • @{SSLMate}|tool:2752| (using @{OpenSSL}|tool:3091|) for certificate management
  • @{Amazon EC2}|tool:18| (incl. @{Amazon S3}|tool:25|) for deploying in stage (production-like) and production environments
  • @{PostgreSQL}|tool:1028| as preferred database system
  • @{Redis}|tool:1031| as preferred in-memory database/store (great for caching)

The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

  • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
  • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
  • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
  • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
  • Scalability: All-in-one framework for distributed systems.
  • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
12.8M views12.8M
Comments
Pavel
Pavel

Jan 27, 2021

Needs adviceonLinuxLinuxWindowsWindowsDockerDocker

Hello, we have a bunch of local hosts (Linux and Windows) where Docker containers are running with bamboo agents on them. Currently, each container is installed as a system service. Each host is set up manually. I want to improve the system by adding some sort of orchestration software that should install, update and check for consistency in my docker containers. I don't need any clouds, all hosts are local. I'd prefer simple solutions. What orchestration system should I choose?

199k views199k
Comments

Detailed Comparison

Docker Swarm
Docker Swarm
Argo
Argo

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.

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).

-
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
Stacks
779
Stacks
761
Followers
990
Followers
470
Votes
282
Votes
6
Pros & Cons
Pros
  • 55
    Docker friendly
  • 46
    Easy to setup
  • 40
    Standard Docker API
  • 38
    Easy to use
  • 23
    Native
Cons
  • 9
    Low adoption
Pros
  • 3
    Open Source
  • 2
    Autosinchronize the changes to deploy
  • 1
    Online service, no need to install anything
Integrations
Docker
Docker
Kubernetes
Kubernetes
Docker
Docker

What are some alternatives to Docker Swarm, 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.

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.

Kitematic

Kitematic

Simple Docker App management for Mac OS X

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