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AWS Fargate vs Kubernetes: What are the differences?
AWS Fargate: Run Containers Without Managing Infrastructure. AWS Fargate is a technology for Amazon ECS and EKS* that allows you to run containers without having to manage servers or clusters. With AWS Fargate, you no longer have to provision, configure, and scale clusters of virtual machines to run containers; Kubernetes: Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops. 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.
AWS Fargate can be classified as a tool in the "Containers as a Service" category, while Kubernetes is grouped under "Container Tools".
Some of the features offered by AWS Fargate are:
- No clusters to manage
- seamless scaling
- integrated with Amazon ECS and EKS
On the other hand, Kubernetes provides the following key features:
- Lightweight, simple and accessible
- Built for a multi-cloud world, public, private or hybrid
- Highly modular, designed so that all of its components are easily swappable
Kubernetes is an open source tool with 55.1K GitHub stars and 19.1K GitHub forks. Here's a link to Kubernetes's open source repository on GitHub.
Google, Slack, and Shopify are some of the popular companies that use Kubernetes, whereas AWS Fargate is used by MAK IT, Third Iron, and Even Financial. Kubernetes has a broader approval, being mentioned in 1048 company stacks & 1099 developers stacks; compared to AWS Fargate, which is listed in 37 company stacks and 12 developer stacks.
Decisions about AWS Fargate and Kubernetes
Simon Reymann
Senior Fullstack Developer at QUANTUSflow Software GmbH · | 29 upvotes · 5.5M views
Our whole DevOps stack consists of the following tools:
- GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
- Respectively Git as revision control system
- SourceTree as Git GUI
- Visual Studio Code as IDE
- CircleCI for continuous integration (automatize development process)
- Prettier / TSLint / ESLint as code linter
- SonarQube as quality gate
- Docker as container management (incl. Docker Compose for multi-container application management)
- VirtualBox for operating system simulation tests
- Kubernetes as cluster management for docker containers
- Heroku for deploying in test environments
- nginx as web server (preferably used as facade server in production environment)
- SSLMate (using OpenSSL) for certificate management
- Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
- PostgreSQL as preferred database system
- Redis as preferred in-memory database/store (great for caching)
The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:
- Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
- Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
- Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
- Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
- Scalability: All-in-one framework for distributed systems.
- Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
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Learn MorePros of AWS Fargate
Pros of Kubernetes
Pros of AWS Fargate
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Pros of Kubernetes
- Leading docker container management solution162
- Simple and powerful127
- Open source104
- Backed by google75
- The right abstractions57
- Scale services24
- Replication controller19
- Permission managment10
- Cheap7
- Simple7
- Supports autoscaling7
- No cloud platform lock-in4
- Self-healing4
- Reliable4
- Quick cloud setup3
- Open, powerful, stable3
- Scalable3
- Promotes modern/good infrascture practice3
- Custom and extensibility2
- Cloud Agnostic2
- Captain of Container Ship2
- A self healing environment with rich metadata2
- Runs on azure2
- Backed by Red Hat2
- Golang1
- Expandable1
- Sfg1
- Everything of CaaS1
- Easy setup1
- Gke1
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Cons of AWS Fargate
Cons of Kubernetes
Cons of AWS Fargate
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Cons of Kubernetes
- Steep learning curve15
- Poor workflow for development15
- Orchestrates only infrastructure8
- High resource requirements for on-prem clusters4
- Too heavy for simple systems2
- Additional vendor lock-in (Docker)1
- More moving parts to secure1
- Additional Technology Overhead1
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What is AWS Fargate?
AWS Fargate is a technology for Amazon ECS and EKS* that allows you to run containers without having to manage servers or clusters. With AWS Fargate, you no longer have to provision, configure, and scale clusters of virtual machines to run containers.
What is 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.
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Jobs that mention AWS Fargate and Kubernetes as a desired skillset
What companies use AWS Fargate?
What companies use Kubernetes?
See which teams inside your own company are using AWS Fargate or Kubernetes.
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What tools integrate with AWS Fargate?
What tools integrate with Kubernetes?
What tools integrate with AWS Fargate?
What tools integrate with Kubernetes?
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What are some alternatives to AWS Fargate and Kubernetes?
Google App Engine
Google has a reputation for highly reliable, high performance infrastructure. With App Engine you can take advantage of the 10 years of knowledge Google has in running massively scalable, performance driven systems. App Engine applications are easy to build, easy to maintain, and easy to scale as your traffic and data storage needs grow.
AWS Batch
It enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. It dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted.
AWS Lambda
AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying compute resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate at AWS scale, performance, and security.
Batch
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Google Cloud Run
A managed compute platform that enables you to run stateless containers that are invocable via HTTP requests. It's serverless by abstracting away all infrastructure management.