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  1. Stackups
  2. Application & Data
  3. Container Registry
  4. Helm Charts
  5. Argo vs Helm

Argo vs Helm

OverviewComparisonAlternatives

Overview

Helm
Helm
Stacks1.4K
Followers911
Votes18
Argo
Argo
Stacks763
Followers470
Votes6

Argo vs Helm: What are the differences?

Key Differences between Argo and Helm

  1. Installation Process: Argo and Helm have different installation processes. Argo is installed as a Kubernetes controller, which means it requires persistent storage and runs as a long-running process within the Kubernetes cluster. On the other hand, Helm is installed as a command-line tool that interacts with the Kubernetes API server to deploy and manage applications.

  2. Application Packaging and Deployment: Argo and Helm differ in their approach to application packaging and deployment. Argo uses a template-based approach where application manifests are defined as Kubernetes YAML files. It provides more flexibility in defining complex deployment workflows and allows versioning of application manifests. Helm, on the other hand, uses charts to package and deploy applications. Charts are collections of files that describe a set of Kubernetes resources. Helm provides a simpler way to package and deploy applications but may not be as flexible as Argo for complex deployment scenarios.

  3. Workflow Orchestration: Argo and Helm have different capabilities when it comes to workflow orchestration. Argo is specifically designed for workflow orchestration and provides features like DAG (Directed Acyclic Graph) execution, parameter passing between steps, and synchronization primitives. Helm, on the other hand, focuses more on application deployment and does not provide native workflow orchestration capabilities. However, Helm can be integrated with other tools or frameworks to achieve workflow orchestration.

  4. Application Lifecycle Management: Argo and Helm have different approaches to application lifecycle management. Argo provides advanced features like automatic rollbacks, canary deployments, and rollout history tracking. It allows for more granular control over application updates and rollbacks. Helm, on the other hand, provides basic rollback features but does not have the same level of granularity as Argo for managing application updates and rollbacks.

  5. Community Support and Adoption: Argo and Helm have different levels of community support and adoption. Argo is relatively newer compared to Helm and has a smaller community. However, it is gaining popularity for its workflow orchestration capabilities and is actively developed and maintained. Helm, on the other hand, has a larger and more mature community with a wide range of charts available for various applications. It is widely adopted and has been around for a longer time.

  6. Tool Ecosystem: Argo and Helm have different tool ecosystems. Argo provides a set of tools that complement its workflow orchestration capabilities, such as Argo CD for continuous deployment and Argo Events for event-driven automation. Helm, on the other hand, is integrated with Kubernetes core tooling and has a vast ecosystem of Helm charts contributed by the community. It can be easily integrated with other Kubernetes tools and frameworks.

In summary, Argo and Helm have different installation processes, application packaging and deployment approaches, workflow orchestration capabilities, application lifecycle management features, levels of community support and adoption, and tool ecosystems. Choosing between Argo and Helm depends on the specific requirements and preferences of the application deployment and management process.

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Detailed Comparison

Helm
Helm
Argo
Argo

Helm is the best way to find, share, and use software built 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).

-
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
1.4K
Stacks
763
Followers
911
Followers
470
Votes
18
Votes
6
Pros & Cons
Pros
  • 8
    Infrastructure as code
  • 6
    Open source
  • 2
    Easy setup
  • 1
    Testa­bil­i­ty and re­pro­ducibil­i­ty
  • 1
    Support
Pros
  • 3
    Open Source
  • 2
    Autosinchronize the changes to deploy
  • 1
    Online service, no need to install anything
Integrations
Docker
Docker
Kubernetes
Kubernetes
Kubernetes
Kubernetes
Docker
Docker

What are some alternatives to Helm, 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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