Argo vs AWS Controllers for Kubernetes

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

Argo

699
469
+ 1
6
AWS Controllers for Kubernetes

4
5
+ 1
0
Add tool

AWS Controllers for Kubernetes vs Argo: What are the differences?

Introduction

Taking a closer look at AWS Controllers for Kubernetes and Argo, it's essential to understand the key differences between these two popular tools in the Kubernetes ecosystem.

  1. Integration Approach: AWS Controllers for Kubernetes provides a deep integration with AWS services, allowing users to define and manage these resources directly within their Kubernetes clusters. On the other hand, Argo focuses more on workflow automation and orchestration within Kubernetes clusters, offering a broader range of functionalities beyond just resource management.

  2. Resource Support: AWS Controllers for Kubernetes is specifically designed to support AWS-specific resources, such as EC2 instances, S3 buckets, and RDS databases, seamlessly integrating them with Kubernetes clusters. In contrast, Argo is more agnostic and supports a wide variety of resources and applications, making it versatile for different use cases beyond just AWS services.

  3. Workflow Automation: Argo excels in providing comprehensive workflow automation capabilities, allowing users to define complex workflows, dependencies, and triggers for their applications running on Kubernetes. AWS Controllers for Kubernetes, while offering resource management, may not have the same level of sophistication in workflow automation as Argo.

  4. Community Support: Argo benefits from a robust and active community of users and contributors, leading to frequent updates, enhancements, and a wide array of resources and tutorials available. While AWS Controllers for Kubernetes also has solid support from AWS, the community backing may not be as extensive as that of Argo.

  5. Custom Resource Definitions (CRDs): AWS Controllers for Kubernetes heavily utilizes custom resource definitions to extend Kubernetes API and manage AWS resources. Argo, on the other hand, focuses more on workflow customizations and automation, utilizing CRDs for defining complex workflows and dependencies within Kubernetes clusters.

In Summary, AWS Controllers for Kubernetes focuses on deep integration with AWS services, while Argo offers versatile workflow automation and support for various resources on Kubernetes clusters.

Manage your open source components, licenses, and vulnerabilities
Learn More
Pros of Argo
Pros of AWS Controllers for Kubernetes
  • 3
    Open Source
  • 2
    Autosinchronize the changes to deploy
  • 1
    Online service, no need to install anything
    Be the first to leave a pro

    Sign up to add or upvote prosMake 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 AWS Controllers for Kubernetes?

    It lets you define and use AWS service resources directly from Kubernetes. With ACK, you can take advantage of AWS managed services for your Kubernetes applications without needing to define resources outside of the cluster or run services that provide supporting capabilities like databases or message queues within the cluster.

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

    What companies use Argo?
    What companies use AWS Controllers for Kubernetes?
    Manage your open source components, licenses, and vulnerabilities
    Learn More

    Sign up to get full access to all the companiesMake informed product decisions

    What tools integrate with Argo?
    What tools integrate with AWS Controllers for Kubernetes?

    Sign up to get full access to all the tool integrationsMake informed product decisions

    Blog Posts

    PythonDockerKubernetes+14
    12
    2736
    What are some alternatives to Argo and AWS Controllers for 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