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  1. Stackups
  2. Application & Data
  3. Container Registry
  4. Container Tools
  5. Argo vs Tutum

Argo vs Tutum

OverviewComparisonAlternatives

Overview

Tutum
Tutum
Stacks61
Followers74
Votes235
Argo
Argo
Stacks761
Followers470
Votes6

Argo vs Tutum: What are the differences?

  1. Deployment of Applications: Argo allows for more complex application deployments by supporting Kubernetes native features like Custom Resource Definitions (CRDs) and controllers, while Tutum is more focused on simplifying container deployments and management.

  2. Community Support: Argo benefits from a larger community and developer ecosystem due to its open-source nature, while Tutum is a hosted platform with more limited community support.

  3. Scalability: Argo provides better scalability options for larger applications and infrastructure setups, with features like dynamic provisioning and scaling based on Kubernetes resources, whereas Tutum may have limitations in handling large-scale deployments.

  4. Cost Structure: Argo's cost is primarily based on infrastructure and resource usage, making it more cost-efficient for larger deployments, while Tutum may have a fixed pricing model or additional charges for certain features or usage levels.

  5. Integration Capabilities: Argo offers more integrations with other tools and services in the Kubernetes ecosystem, allowing for a more flexible and extensible deployment pipeline, whereas Tutum may have fewer integrations and customization options.

  6. User Interface: Argo provides a more comprehensive and customizable user interface for managing applications and deployments, with options for creating custom dashboards and workflows, while Tutum may have a simpler interface tailored for basic container management tasks.

In Summary, Argo and Tutum differ in terms of application deployment complexity, community support, scalability, cost structure, integration capabilities, and user interface design.

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Detailed Comparison

Tutum
Tutum
Argo
Argo

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.

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).

Deploy from Docker Hub; Free private Docker registry; CLI Tool; Private Links; Dynamic Links; RESTful API; Edit & Redeploy; Jumpstarts & Quickstarts; Webhooks; Bring your own node; Data volumes; Amazon Web Services; Digital Ocean; Microsoft Azure;
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
61
Stacks
761
Followers
74
Followers
470
Votes
235
Votes
6
Pros & Cons
Pros
  • 35
    Awesome user interface
  • 28
    Free private docker registry
  • 24
    Its super easy
  • 24
    Docker public index integration
  • 21
    Friendly support
Pros
  • 3
    Open Source
  • 2
    Autosinchronize the changes to deploy
  • 1
    Online service, no need to install anything
Integrations
Docker
Docker
MongoDB
MongoDB
MariaDB
MariaDB
MySQL
MySQL
DigitalOcean
DigitalOcean
Memcached
Memcached
RabbitMQ
RabbitMQ
PostgreSQL
PostgreSQL
Riak
Riak
WordPress
WordPress
Kubernetes
Kubernetes
Docker
Docker

What are some alternatives to Tutum, 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.

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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