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  1. Stackups
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  4. Container Tools
  5. Kubernetes vs dockersh

Kubernetes vs dockersh

OverviewDecisionsComparisonAlternatives

Overview

dockersh
dockersh
Stacks7
Followers15
Votes4
GitHub Stars1.3K
Forks79
Kubernetes
Kubernetes
Stacks61.2K
Followers52.8K
Votes685

Kubernetes vs dockersh: What are the differences?

Introduction

Kubernetes and Docker are both popular tools in the world of containerization, each serving distinct purposes and having unique features. Understanding the key differences between Kubernetes and Docker can help in making informed decisions about their usage in different scenarios.

  1. Orchestration vs. Runtime Environment: Kubernetes is primarily an orchestration tool used to manage containerized applications across a cluster of nodes, providing features like scaling, load balancing, and automated deployment, while Docker acts as a runtime environment for containers, facilitating the creation and execution of individual containers.

  2. Scope of Management: Kubernetes is designed for managing complex applications with multiple containers, handling tasks such as service discovery, load balancing, and auto-scaling, providing a more comprehensive solution for large-scale deployments. On the other hand, Docker focuses more on the development and deployment of single containerized applications, offering simpler management for smaller-scale projects.

  3. Cluster Management: Kubernetes excels in managing clusters of containers, offering features like automatic scheduling, self-healing capabilities, and horizontal scaling, making it suitable for deploying and managing applications at scale. Docker, while capable of clustering through Docker Swarm, is more limited in terms of cluster management functionalities compared to Kubernetes.

  4. Community Support and Ecosystem: Kubernetes has a larger and more active community, backed by major tech companies like Google, which contributes to its robust ecosystem of tools, plugins, and resources. Docker also has a strong community support, but Kubernetes' widespread adoption and extensive ecosystem provide a wider range of solutions and integrations for developers.

  5. Container Orchestration Model: Kubernetes follows a declarative model for defining desired states and letting the system handle the execution details, leading to higher level of automation and abstraction. In contrast, Docker relies more on imperative commands for managing containers, requiring explicit instructions for each action, which can be less automated and more manual compared to Kubernetes.

  6. Scalability and Extensibility: Kubernetes offers more advanced scalability options, including support for auto-scaling based on resource usage metrics, manual scaling, and fine-grained control over cluster resources. Docker's scalability capabilities are more basic in comparison, with limited auto-scaling features and less flexibility in resource management.

In Summary, understanding the differences between Kubernetes and Docker is crucial for selecting the right tool based on the specific requirements and scale of containerized applications.

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Advice on dockersh, Kubernetes

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

dockersh
dockersh
Kubernetes
Kubernetes

dockersh is designed to be used as a login shell on machines with multiple interactive users. When a user invokes dockersh, it will bring up a Docker container (if not already running), and then spawn a new interactive shell in the container's namespace.

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.

-
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
Statistics
GitHub Stars
1.3K
GitHub Stars
-
GitHub Forks
79
GitHub Forks
-
Stacks
7
Stacks
61.2K
Followers
15
Followers
52.8K
Votes
4
Votes
685
Pros & Cons
Pros
  • 1
    Privacy
  • 1
    Isolation
  • 1
    Multiple users to ssh onto a single box
  • 1
    Secure
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
Integrations
Docker
Docker
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

What are some alternatives to dockersh, Kubernetes?

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.

Kitematic

Kitematic

Simple Docker App management for Mac OS X

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