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

AWS Batch

88
249
+ 1
6
Kubernetes

59K
51K
+ 1
677
Add tool

AWS Batch vs Kubernetes: What are the differences?

Introduction

In this article, we will compare AWS Batch and Kubernetes, two popular technologies for managing containerized workloads.

  1. Scalability and Elasticity: AWS Batch is a fully managed service that automatically provisions and scales compute resources based on the workload submitted, allowing you to dynamically adjust resources as needed. In contrast, Kubernetes requires manual configuration and scaling of nodes to handle workload demands.

  2. Job Scheduling and Management: AWS Batch provides a job queueing system that handles the scheduling and resource management for executing batch computing workloads. It allows you to define job dependencies, priorities, and constraints. Kubernetes, on the other hand, is a container orchestration platform that primarily focuses on managing and scheduling long-running services rather than batch jobs.

  3. Container Lifecycle Management: Kubernetes has a powerful set of tools for managing the lifecycle of containers, including rolling updates, self-healing, and scaling based on metrics. AWS Batch, while it also supports containers, does not provide the same level of control and automation for container lifecycle management.

  4. Ease of Use and Deployment: AWS Batch is a fully managed service that abstracts away the underlying infrastructure, making it easier to get started and deploy batch workloads. Kubernetes, on the other hand, requires manual setup and configuration of the cluster, which can be more complex and time-consuming.

  5. Integration with Other Services: AWS Batch seamlessly integrates with other AWS services such as Amazon S3, DynamoDB, and CloudWatch, allowing you to easily incorporate these services into your batch jobs. While Kubernetes can also integrate with various services, it requires additional setup and configuration.

  6. Cost Management: AWS Batch offers cost optimization features like spot instances that allow you to use available unused EC2 instances at a lower cost. Kubernetes does not provide such built-in cost management features, requiring manual optimization efforts to keep costs under control.

In summary, AWS Batch provides a fully managed solution with seamless integration to other AWS services and ease of use, while Kubernetes offers more control and flexibility in managing containerized services with powerful lifecycle management capabilities.

Decisions about AWS Batch and Kubernetes
Simon Reymann
Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 9.3M 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.
See more
Get Advice from developers at your company using StackShare Enterprise. Sign up for StackShare Enterprise.
Learn More
Pros of AWS Batch
Pros of Kubernetes
  • 3
    Containerized
  • 3
    Scalable
  • 164
    Leading docker container management solution
  • 128
    Simple and powerful
  • 106
    Open source
  • 76
    Backed by google
  • 58
    The right abstractions
  • 25
    Scale services
  • 20
    Replication controller
  • 11
    Permission managment
  • 9
    Supports autoscaling
  • 8
    Cheap
  • 8
    Simple
  • 6
    Self-healing
  • 5
    No cloud platform lock-in
  • 5
    Promotes modern/good infrascture practice
  • 5
    Open, powerful, stable
  • 5
    Reliable
  • 4
    Scalable
  • 4
    Quick cloud setup
  • 3
    Cloud Agnostic
  • 3
    Captain of Container Ship
  • 3
    A self healing environment with rich metadata
  • 3
    Runs on azure
  • 3
    Backed by Red Hat
  • 3
    Custom and extensibility
  • 2
    Sfg
  • 2
    Gke
  • 2
    Everything of CaaS
  • 2
    Golang
  • 2
    Easy setup
  • 2
    Expandable

Sign up to add or upvote prosMake informed product decisions

Cons of AWS Batch
Cons of Kubernetes
  • 3
    More overhead than lambda
  • 1
    Image management
  • 16
    Steep learning curve
  • 15
    Poor workflow for development
  • 8
    Orchestrates only infrastructure
  • 4
    High resource requirements for on-prem clusters
  • 2
    Too heavy for simple systems
  • 1
    Additional vendor lock-in (Docker)
  • 1
    More moving parts to secure
  • 1
    Additional Technology Overhead

Sign up to add or upvote consMake informed product decisions

What is 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.

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.

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

What companies use AWS Batch?
What companies use Kubernetes?
See which teams inside your own company are using AWS Batch or Kubernetes.
Sign up for StackShare EnterpriseLearn More

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

What tools integrate with AWS Batch?
What tools integrate with Kubernetes?

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

Blog Posts

Kubernetesetcd+2
2
1170
Dec 8 2020 at 5:50PM

DigitalOcean

GitHubMySQLPostgreSQL+11
2
2374
PythonDockerKubernetes+7
3
1111
May 21 2020 at 12:02AM

Rancher Labs

KubernetesAmazon EC2Grafana+12
5
1500
Apr 16 2020 at 5:34AM

Rancher Labs

KubernetesRancher+2
2
946
What are some alternatives to AWS Batch and Kubernetes?
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.
Beanstalk
A single process to commit code, review with the team, and deploy the final result to your customers.
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.
JavaScript
JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles.
Git
Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency.
See all alternatives