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Argo vs Skaffold: What are the differences?

Introduction

In the world of Kubernetes deployment tools, Argo and Skaffold are two popular choices. While both tools have the objective of simplifying the deployment process, there are key differences between the two. In this article, we will explore six significant differences between Argo and Skaffold.

  1. Architecture: The fundamental difference between Argo and Skaffold lies in their architecture. Argo is built as a workflow engine, while Skaffold is designed as a local development tool. Argo focuses on defining and executing complex workflows, making it ideal for CI/CD pipelines and automation tasks. On the other hand, Skaffold enables developers to rapidly iterate their applications locally with ease.

  2. Workflow vs. Configuration: Argo emphasizes defining and managing workflows using YAML or JSON configuration files. These workflows consist of various steps that can be executed sequentially, in parallel, or conditionally. In contrast, Skaffold's configuration is centered around defining how to build, push, and deploy applications to a Kubernetes cluster. It provides an intuitive way to automate these processes and enables developers to focus on writing code.

  3. Support for Helm: Helm, a popular package manager for Kubernetes, can be utilized with both Argo and Skaffold. However, the level of support differs. Argo has first-class integration with Helm charts, allowing users to define Helm-based workflow steps easily. While Skaffold does not directly integrate with Helm, it provides extensibility through custom scripts and allows developers to invoke Helm commands within their build and deployment pipeline.

  4. Developer Experience: Skaffold places a strong emphasis on developer experience by providing fast iterative development cycles. It automatically synchronizes local code changes into the deployment environment, allowing developers to see their changes in real-time. Argo, on the other hand, is more focused on automation and orchestration, making it less developer-centric.

  5. Integration with GitOps: Argo has native support for GitOps workflows, which promote declarative and version-controlled deployment practices. It seamlessly integrates with Git repositories and continuously monitors changes to automatically trigger the desired workflows. Skaffold, while not specifically designed for GitOps, can be incorporated into a GitOps workflow by integrating with other tools such as Flux or Argo CD.

  6. Community and Maturity: Both Argo and Skaffold have active and growing communities, but Argo benefits from being a part of the Cloud Native Computing Foundation (CNCF) ecosystem. It has a larger user base and a more significant number of contributors, leading to a more mature tool with extensive documentation, support, and regular updates. Skaffold, although still widely used, may be considered relatively newer in comparison.

In Summary, Argo and Skaffold differ in terms of their architecture, focus (workflow vs. configuration), support for Helm, developer experience, integration with GitOps, and community maturity. These tools cater to different needs and use cases, with Argo excelling in automation and orchestration, while Skaffold enhances the local development experience.

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    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 Skaffold?

    Skaffold is a command line tool that facilitates continuous development for Kubernetes applications. You can iterate on your application source code locally then deploy to local or remote Kubernetes clusters. Skaffold handles the workflow for building, pushing and deploying your application. It can also be used in an automated context such as a CI/CD pipeline to leverage the same workflow and tooling when moving applications to production.

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    What are some alternatives to Argo and Skaffold?
    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