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  1. Stackups
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  3. Container Registry
  4. Container Tools
  5. Atlas vs Kubernetes

Atlas vs Kubernetes

OverviewDecisionsComparisonAlternatives

Overview

Kubernetes
Kubernetes
Stacks61.2K
Followers52.8K
Votes685
Atlas
Atlas
Stacks33
Followers125
Votes0

Atlas vs Kubernetes: What are the differences?

  1. Architecture: Atlas is a proprietary cloud-hosted solution provided by MongoDB that automates database management tasks, while Kubernetes is an open-source container orchestration platform that manages containerized workloads. Atlas focuses on database management, while Kubernetes is more generalized for container orchestration.

  2. Scalability: Atlas offers automated scaling options for MongoDB databases based on workload demands, making it easier to handle fluctuating traffic. On the other hand, Kubernetes provides horizontal scaling capabilities for containers, allowing applications to scale up or down based on resource requirements.

  3. Compatibility: Atlas is specifically designed for MongoDB databases, providing specialized tools and features to optimize MongoDB performance. In contrast, Kubernetes is agnostic to the applications it orchestrates, allowing users to deploy various types of workloads regardless of the underlying technology.

  4. Deployment Models: Atlas is primarily a cloud-based platform that offers fully managed services for MongoDB deployment, eliminating the need for infrastructure management. Kubernetes, on the other hand, can be deployed on-premises, in the cloud, or in hybrid environments, providing more flexibility in deployment options.

  5. Community Support: Kubernetes has a large and active open-source community contributing to its development, resulting in frequent updates, new features, and a wide range of plugins and integrations. Although Atlas provides enterprise-grade support for its users, it lacks the extensive community-driven ecosystem of Kubernetes.

  6. Complexity: Atlas is designed to simplify database management tasks and abstract away the complexities of scaling, backups, and monitoring for MongoDB databases. In contrast, Kubernetes requires a deeper understanding of containerization and orchestration concepts, making it more complex to configure and manage for users without the necessary expertise.

In Summary, Atlas and Kubernetes differ in architecture focus, scalability options, compatibility, deployment models, community support, and complexity levels.

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Advice on Kubernetes, Atlas

Simon
Simon

Senior Fullstack Developer at QUANTUSflow Software GmbH

Apr 27, 2020

DecidedonGitHubGitHubGitHub PagesGitHub PagesMarkdownMarkdown

Our whole DevOps stack consists of the following tools:

  • @{GitHub}|tool:27| (incl. @{GitHub Pages}|tool:683|/@{Markdown}|tool:1147| for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
  • Respectively @{Git}|tool:1046| as revision control system
  • @{SourceTree}|tool:1599| as @{Git}|tool:1046| GUI
  • @{Visual Studio Code}|tool:4202| as IDE
  • @{CircleCI}|tool:190| for continuous integration (automatize development process)
  • @{Prettier}|tool:7035| / @{TSLint}|tool:5561| / @{ESLint}|tool:3337| as code linter
  • @{SonarQube}|tool:2638| as quality gate
  • @{Docker}|tool:586| as container management (incl. @{Docker Compose}|tool:3136| for multi-container application management)
  • @{VirtualBox}|tool:774| for operating system simulation tests
  • @{Kubernetes}|tool:1885| as cluster management for docker containers
  • @{Heroku}|tool:133| for deploying in test environments
  • @{nginx}|tool:1052| as web server (preferably used as facade server in production environment)
  • @{SSLMate}|tool:2752| (using @{OpenSSL}|tool:3091|) for certificate management
  • @{Amazon EC2}|tool:18| (incl. @{Amazon S3}|tool:25|) for deploying in stage (production-like) and production environments
  • @{PostgreSQL}|tool:1028| as preferred database system
  • @{Redis}|tool:1031| 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.
12.8M views12.8M
Comments
Anis
Anis

Founder at Odix

Nov 7, 2020

Review

I recommend this : -Spring reactive for back end : the fact it's reactive (async) it consumes half of the resources that a sync platform needs (so less CPU -> less money). -Angular : Web Front end ; it's gives you the possibility to use PWA which is a cheap replacement for a mobile app (but more less popular). -Docker images. -Kubernetes to orchestrate all the containers. -I Use Jenkins / blueocean, ansible for my CI/CD (with Github of course) -AWS of course : u can run a K8S cluster there, make it multi AZ (availability zones) to be highly available, use a load balancer and an auto scaler and ur good to go. -You can store data by taking any managed DB or u can deploy ur own (cheap but risky).

You pay less money, but u need some technical 2 - 3 guys to make that done.

Good luck

115k views115k
Comments
Michael
Michael

CEO at asencis Ltd

Jan 5, 2021

Needs advice

We develop rapidly with docker-compose orchestrated services, however, for production - we utilise the very best ideas that Kubernetes has to offer: SCALE! We can scale when needed, setting a maximum and minimum level of nodes for each application layer - scaling only when the load balancer needs it. This allowed us to reduce our devops costs by 40% whilst also maintaining an SLA of 99.87%.

272k views272k
Comments

Detailed Comparison

Kubernetes
Kubernetes
Atlas
Atlas

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.

Atlas is one foundation to manage and provide visibility to your servers, containers, VMs, configuration management, service discovery, and additional operations services.

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
One command to develop any application: vagrant up;One command to deploy any application: vagrant push
Statistics
Stacks
61.2K
Stacks
33
Followers
52.8K
Followers
125
Votes
685
Votes
0
Pros & Cons
Pros
  • 166
    Leading docker container management solution
  • 130
    Simple and powerful
  • 108
    Open source
  • 76
    Backed by google
  • 58
    The right abstractions
Cons
  • 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
No community feedback yet
Integrations
Vagrant
Vagrant
Docker
Docker
Rackspace Cloud Servers
Rackspace Cloud Servers
Microsoft Azure
Microsoft Azure
Google Compute Engine
Google Compute Engine
Ansible
Ansible
Google Kubernetes Engine
Google Kubernetes Engine
No integrations available

What are some alternatives to Kubernetes, Atlas?

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.

AWS CloudFormation

AWS CloudFormation

You can use AWS CloudFormation’s sample templates or create your own templates to describe the AWS resources, and any associated dependencies or runtime parameters, required to run your application. You don’t need to figure out the order in which AWS services need to be provisioned or the subtleties of how to make those dependencies work.

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.

Packer

Packer

Packer automates the creation of any type of machine image. It embraces modern configuration management by encouraging you to use automated scripts to install and configure the software within your Packer-made images.

Scalr

Scalr

Scalr is a remote state & operations backend for Terraform with access controls, policy as code, and many quality of life features.

Pulumi

Pulumi

Pulumi is a cloud development platform that makes creating cloud programs easy and productive. Skip the YAML and just write code. Pulumi is multi-language, multi-cloud and fully extensible in both its engine and ecosystem of packages.

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