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  5. AWS Copilot vs Helm

AWS Copilot vs Helm

OverviewComparisonAlternatives

Overview

Helm
Helm
Stacks1.4K
Followers911
Votes18
AWS Copilot
AWS Copilot
Stacks13
Followers21
Votes0
GitHub Stars3.7K
Forks435

AWS Copilot vs Helm: What are the differences?

Introduction

AWS Copilot and Helm are both tools used for managing and deploying containerized applications on Kubernetes. While they share similar goals, there are several key differences between the two.

  1. CLI Experience: AWS Copilot provides a simplified CLI experience specifically designed for developers working within the AWS ecosystem. It abstracts away many of the complexities of Kubernetes and streamlines the deployment process through simple commands such as "copilot init" and "copilot deploy". On the other hand, Helm is a more general-purpose package manager for Kubernetes, offering a broader range of features and flexibility but requiring a steeper learning curve.

  2. Built-in Deployment Patterns: AWS Copilot includes predefined deployment patterns, such as "request-driven web services" and "backend services". These patterns encapsulate best practices and automate the creation of necessary resources, making it easier for developers to get started and follow recommended architectural patterns. Helm, on the other hand, does not provide built-in deployment patterns and requires manual configuration and customization for each application.

  3. Integration with AWS Resources: AWS Copilot has deep integration with various AWS services. It can automatically provision and manage related AWS resources, such as Amazon ECS clusters, Application Load Balancers, and Amazon RDS databases, based on the requirements of a given application. This integration simplifies the deployment process and ensures consistent configuration. Helm is not specifically designed for AWS and does not provide direct integration with AWS resources, requiring additional manual configuration.

  4. Code-centric Approach: AWS Copilot focuses on a code-centric approach, where the application's code repository serves as the source of truth for deployment configuration. Developers can define application infrastructure using a "copilot.yml" file in their code repository, allowing for version-controlled, reproducible deployments. Helm, on the other hand, uses separate configuration files called "charts" that describe the desired state of the application's deployment.

  5. Ease of Use: AWS Copilot aims to provide a simplified and opinionated experience for deploying containerized applications. It offers a faster learning curve and reduces the need for manual intervention by automatically handling many aspects of the deployment process. Helm, with its broader feature set and flexibility, requires more manual configuration and customization, making it suitable for advanced users who require fine-grained control over their deployments.

  6. Community Support and Ecosystem: Helm has a larger and more mature community compared to AWS Copilot. This translates into a wider range of available charts and plugins, as well as more extensive documentation and community support. AWS Copilot, being a relative newcomer, is still growing its community and ecosystem.

In Summary, AWS Copilot provides a simplified CLI experience, includes built-in deployment patterns, offers deep integration with AWS resources, follows a code-centric approach, aims for ease of use, and is still in the process of building its community and ecosystem. Helm, on the other hand, offers a more feature-rich and flexible package manager for Kubernetes with a larger and more mature community.

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Detailed Comparison

Helm
Helm
AWS Copilot
AWS Copilot

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

It is a tool for developers to develop, release, and operate production-ready containerized applications on Amazon ECS. From getting started, pushing to staging and releasing to production, Copilot can help manage the entire lifecycle of your application development.

-
Organize all your related micro-services in one application; Set up test and production environments, across regions and accounts; Set up production-ready, scalable ECS services and infrastructure; Set up CI/CD Pipelines for all of the micro-services; Monitor and debug your services from your terminal
Statistics
GitHub Stars
-
GitHub Stars
3.7K
GitHub Forks
-
GitHub Forks
435
Stacks
1.4K
Stacks
13
Followers
911
Followers
21
Votes
18
Votes
0
Pros & Cons
Pros
  • 8
    Infrastructure as code
  • 6
    Open source
  • 2
    Easy setup
  • 1
    Testa­bil­i­ty and re­pro­ducibil­i­ty
  • 1
    Support
No community feedback yet
Integrations
Docker
Docker
Kubernetes
Kubernetes
Linux
Linux
AWS Fargate
AWS Fargate
macOS
macOS

What are some alternatives to Helm, AWS Copilot?

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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