Argo聽vs聽Kubernetes

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Argo

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Kubernetes

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Argo vs Kubernetes: What are the differences?

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); Kubernetes: Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops. 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.

Argo and Kubernetes can be primarily classified 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, Kubernetes provides the following key features:

  • Lightweight, simple and accessible
  • Built for a multi-cloud world, public, private or hybrid
  • Highly modular, designed so that all of its components are easily swappable

Argo and Kubernetes are both open source tools. Kubernetes with 55K GitHub stars and 19.1K forks on GitHub appears to be more popular than Argo with 3.25K GitHub stars and 455 GitHub forks.

Advice on Argo and Kubernetes

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?

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Replies (1)
Mortie Torabi
Recommends
Docker Swarm

If you just want the basic orchestration between a set of defined hosts, go with Docker Swarm. If you want more advanced orchestration + flexibility in terms of resource management and load balancing go with Kubernetes. In both cases, you can make it even more complex while making the whole architecture more understandable and replicable by using Terraform.

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Decisions about Argo and Kubernetes
Michael Roberts

We develop rapidly with docker-compose orchestrated services, however, for production - we utilise the very best ideas that Kubernetes has to offer: SCALE! We can scale when needed, setting a maximum and minimum level of nodes for each application layer - scaling only when the load balancer needs it. This allowed us to reduce our devops costs by 40% whilst also maintaining an SLA of 99.87%.

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Simon Reymann
Senior Fullstack Developer at QUANTUSflow Software GmbH | 28 upvotes 路 3M views

Our whole DevOps stack consists of the following tools:

  • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
  • Respectively Git as revision control system
  • SourceTree as Git GUI
  • Visual Studio Code as IDE
  • CircleCI for continuous integration (automatize development process)
  • Prettier / TSLint / ESLint as code linter
  • SonarQube as quality gate
  • Docker as container management (incl. Docker Compose for multi-container application management)
  • VirtualBox for operating system simulation tests
  • Kubernetes as cluster management for docker containers
  • Heroku for deploying in test environments
  • nginx as web server (preferably used as facade server in production environment)
  • SSLMate (using OpenSSL) for certificate management
  • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
  • PostgreSQL as preferred database system
  • Redis 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.
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Pros of Argo
Pros of Kubernetes
    Be the first to leave a pro
    • 155
      Leading docker container management solution
    • 124
      Simple and powerful
    • 99
      Open source
    • 74
      Backed by google
    • 56
      The right abstractions
    • 24
      Scale services
    • 18
      Replication controller
    • 9
      Permission managment
    • 7
      Simple
    • 7
      Supports autoscaling
    • 6
      Cheap
    • 4
      Self-healing
    • 4
      Reliable
    • 4
      No cloud platform lock-in
    • 3
      Open, powerful, stable
    • 3
      Scalable
    • 3
      Quick cloud setup
    • 3
      Promotes modern/good infrascture practice
    • 2
      Backed by Red Hat
    • 2
      Runs on azure
    • 2
      Cloud Agnostic
    • 2
      Custom and extensibility
    • 2
      Captain of Container Ship
    • 2
      A self healing environment with rich metadata
    • 1
      Golang
    • 1
      Easy setup
    • 1
      Everything of CaaS
    • 1
      Sfg
    • 1
      Expandable
    • 1
      Gke

    Sign up to add or upvote prosMake informed product decisions

    Cons of Argo
    Cons of Kubernetes
      Be the first to leave a con
      • 13
        Poor workflow for development
      • 11
        Steep learning curve
      • 5
        Orchestrates only infrastructure
      • 2
        High resource requirements for on-prem clusters

      Sign up to add or upvote consMake informed product decisions

      What is Argo?

      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 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.

      Need advice about which tool to choose?Ask the StackShare community!

      Jobs that mention Argo and Kubernetes as a desired skillset
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      What tools integrate with Argo?
      What tools integrate with Kubernetes?

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      What are some alternatives to Argo and Kubernetes?
      Airflow
      Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
      Flux
      Flux is the application architecture that Facebook uses for building client-side web applications. It complements React's composable view components by utilizing a unidirectional data flow. It's more of a pattern rather than a formal framework, and you can start using Flux immediately without a lot of new code.
      Jenkins
      In a nutshell Jenkins CI is the leading open-source continuous integration server. Built with Java, it provides over 300 plugins to support building and testing virtually any project.
      Spinnaker
      Created at Netflix, it has been battle-tested in production by hundreds of teams over millions of deployments. It combines a powerful and flexible pipeline management system with integrations to the major cloud providers.
      Kubeflow
      The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.
      See all alternatives