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  1. Stackups
  2. Application & Data
  3. Container Registry
  4. Container Tools
  5. Flocker vs Kubernetes

Flocker vs Kubernetes

OverviewDecisionsComparisonAlternatives

Overview

Flocker
Flocker
Stacks12
Followers59
Votes15
GitHub Stars3.4K
Forks288
Kubernetes
Kubernetes
Stacks61.2K
Followers52.8K
Votes685

Flocker vs Kubernetes: What are the differences?

Introduction:

Flocker and Kubernetes are both container orchestration platforms that help manage and scale containers, but they differ in several key aspects.

  1. Architecture: Flocker is a data management solution that focuses on stateful application management, allowing users to move data alongside containers. In contrast, Kubernetes is a full-fledged container management platform that provides an extensive set of features for orchestration, scaling, and monitoring of containerized applications.

  2. Flexibility: Flocker is designed to offer flexibility in data management and data portability for stateful applications in containerized environments. On the other hand, Kubernetes provides a more extensive range of services and resources, enabling users to deploy, manage, and scale applications across various clusters with ease.

  3. Community Support: Kubernetes has a larger and more active community compared to Flocker, leading to better support, continuous development, and a broader range of integrations and third-party tools. This vibrant community ecosystem is crucial in learning, troubleshooting, and expanding the capabilities of the platform.

  4. Scalability: Kubernetes is known for its robust scalability features, allowing users to manage thousands of containers across multiple nodes efficiently. Flocker, while capable of scaling, is more focused on data management and portability rather than orchestrating large-scale container deployments.

  5. Ecosystem Integration: Kubernetes offers seamless integration with various cloud providers, storage solutions, networking tools, and monitoring systems, making it easier to build complex containerized applications with external services. Flocker, although versatile in data management, may not have the same level of integration options compared to Kubernetes.

  6. Ease of Use: Kubernetes has a steeper learning curve due to its comprehensive feature set and complex architecture, requiring more effort to set up and configure compared to Flocker. Flocker, with its focus on simplicity and data management, may be easier to deploy and operate for users primarily concerned with stateful application requirements.

In Summary, Flocker and Kubernetes differ in architecture, flexibility, community support, scalability, ecosystem integration, and ease of use, offering distinct advantages based on users' specific needs and priorities.

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Advice on Flocker, 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

Flocker
Flocker
Kubernetes
Kubernetes

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.

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.

Move containers and their data together between hosts Run multiple containers on multiple machines Define your application as a set of connected containers Easily move between dev, staging and production
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
3.4K
GitHub Stars
-
GitHub Forks
288
GitHub Forks
-
Stacks
12
Stacks
61.2K
Followers
59
Followers
52.8K
Votes
15
Votes
685
Pros & Cons
Pros
  • 4
    Open-Source
  • 3
    Easily manage Docker containers with Data
  • 2
    Only requires docker
  • 2
    Great support from their team
  • 2
    Easy setup
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
Amazon EC2
Amazon EC2
Amazon EBS
Amazon EBS
Docker
Docker
Mesosphere
Mesosphere
Docker Compose
Docker Compose
Docker Swarm
Docker Swarm
CoreOS
CoreOS
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 Flocker, 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.

Kitematic

Kitematic

Simple Docker App management for Mac OS X

Docker Machine

Docker Machine

Machine lets you create Docker hosts on your computer, on cloud providers, and inside your own data center. It creates servers, installs Docker on them, then configures the Docker client to talk to them.

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