Alternatives to kubernetes-deploy logo

Alternatives to kubernetes-deploy

Docker Compose, Octopus Deploy, Kubernetes, Helm, and Rancher are the most popular alternatives and competitors to kubernetes-deploy.
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What is kubernetes-deploy and what are its top alternatives?

kubernetes-deploy is a command line tool that helps you ship changes to a Kubernetes namespace and understand the result. At Shopify, we use it within our much-beloved, open-source Shipit deployment app.
kubernetes-deploy is a tool in the Container Tools category of a tech stack.
kubernetes-deploy is an open source tool with 1.2K GitHub stars and 96 GitHub forks. Here’s a link to kubernetes-deploy's open source repository on GitHub

Top Alternatives to kubernetes-deploy

  • 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. ...

  • Octopus Deploy

    Octopus Deploy

    Octopus Deploy helps teams to manage releases, automate deployments, and operate applications with automated runbooks. It's free for small teams. ...

  • Kubernetes

    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. ...

  • Helm

    Helm

    Helm is the best way to find, share, and use software built for 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 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. ...

  • Spring Cloud

    Spring Cloud

    It provides tools for developers to quickly build some of the common patterns in distributed systems. ...

  • 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. ...

kubernetes-deploy alternatives & related posts

Docker Compose logo

Docker Compose

13.2K
9.5K
473
Define and run multi-container applications with Docker
13.2K
9.5K
+ 1
473
PROS OF DOCKER COMPOSE
  • 119
    Multi-container descriptor
  • 108
    Fast development environment setup
  • 75
    Easy linking of containers
  • 65
    Simple yaml configuration
  • 58
    Easy setup
  • 15
    Yml or yaml format
  • 11
    Use Standard Docker API
  • 7
    Open source
  • 4
    Go from template to application in minutes
  • 4
    Can choose Discovery Backend
  • 2
    Kubernetes integration
  • 2
    Easy configuration
  • 2
    Scalable
  • 1
    Quick and easy
CONS OF DOCKER COMPOSE
  • 7
    Tied to single machine
  • 4
    Still very volatile, changing syntax often

related Docker Compose posts

Simon Reymann
Senior Fullstack Developer at QUANTUSflow Software GmbH · | 28 upvotes · 2.6M 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

Recently I have been working on an open source stack to help people consolidate their personal health data in a single database so that AI and analytics apps can be run against it to find personalized treatments. We chose to go with a #containerized approach leveraging Docker #containers with a local development environment setup with Docker Compose and nginx for container routing. For the production environment we chose to pull code from GitHub and build/push images using Jenkins and using Kubernetes to deploy to Amazon EC2.

We also implemented a dashboard app to handle user authentication/authorization, as well as a custom SSO server that runs on Heroku which allows experts to easily visit more than one instance without having to login repeatedly. The #Backend was implemented using my favorite #Stack which consists of FeathersJS on top of Node.js and ExpressJS with PostgreSQL as the main database. The #Frontend was implemented using React, Redux.js, Semantic UI React and the FeathersJS client. Though testing was light on this project, we chose to use AVA as well as ESLint to keep the codebase clean and consistent.

See more
Octopus Deploy logo

Octopus Deploy

323
359
113
A single place to release, deploy and operate your software
323
359
+ 1
113
PROS OF OCTOPUS DEPLOY
  • 29
    Powerful
  • 25
    Simplicity
  • 19
    Easy to learn
  • 15
    .Net oriented
  • 14
    Easy to manage releases and rollback
  • 7
    Allows multitenancy
  • 4
    Nice interface
CONS OF OCTOPUS DEPLOY
  • 4
    Poor UI
  • 2
    Config & variables not versioned (e.g. in git)
  • 2
    Management of Config

related Octopus Deploy posts

Oliver Burn

We recently added new APIs to Jira to associate information about Builds and Deployments to Jira issues.

The new APIs were developed using a spec-first API approach for speed and sanity. The details of this approach are described in this blog post, and we relied on using Swagger and associated tools like Swagger UI.

A new service was created for managing the data. It provides a REST API for external use, and an internal API based on GraphQL. The service is built using Kotlin for increased developer productivity and happiness, and the Spring-Boot framework. PostgreSQL was chosen for the persistence layer, as we have non-trivial requirements that cannot be easily implemented on top of a key-value store.

The front-end has been built using React and querying the back-end service using an internal GraphQL API. We have plans of providing a public GraphQL API in the future.

New Jira Integrations: Bitbucket CircleCI AWS CodePipeline Octopus Deploy jFrog Azure Pipelines

See more
Shared insights
on
Octopus Deploy
Jenkins

What is the difference between Jenkins deployment and Octopus Deploy? Please suggest which is better?

See more
Kubernetes logo

Kubernetes

33.8K
28.3K
601
Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops
33.8K
28.3K
+ 1
601
PROS OF KUBERNETES
  • 152
    Leading docker container management solution
  • 121
    Simple and powerful
  • 96
    Open source
  • 73
    Backed by google
  • 56
    The right abstractions
  • 24
    Scale services
  • 17
    Replication controller
  • 9
    Permission managment
  • 6
    Simple
  • 5
    Supports autoscaling
  • 5
    Cheap
  • 3
    Reliable
  • 3
    No cloud platform lock-in
  • 3
    Self-healing
  • 3
    Open, powerful, stable
  • 3
    Scalable
  • 3
    Promotes modern/good infrascture practice
  • 2
    Cloud Agnostic
  • 2
    Backed by Red Hat
  • 2
    Custom and extensibility
  • 2
    Quick cloud setup
  • 2
    Captain of Container Ship
  • 2
    A self healing environment with rich metadata
  • 1
    Everything of CaaS
  • 1
    Easy setup
  • 1
    Expandable
  • 1
    Runs on azure
  • 1
    Sfg
  • 1
    Golang
  • 1
    Gke
CONS OF KUBERNETES
  • 13
    Poor workflow for development
  • 11
    Steep learning curve
  • 5
    Orchestrates only infrastructure
  • 2
    High resource requirements for on-prem clusters

related Kubernetes posts

Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber · | 38 upvotes · 3.7M views

How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:

Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.

Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:

https://eng.uber.com/distributed-tracing/

(GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)

Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark

See more
Yshay Yaacobi

Our first experience with .NET core was when we developed our OSS feature management platform - Tweek (https://github.com/soluto/tweek). We wanted to create a solution that is able to run anywhere (super important for OSS), has excellent performance characteristics and can fit in a multi-container architecture. We decided to implement our rule engine processor in F# , our main service was implemented in C# and other components were built using JavaScript / TypeScript and Go.

Visual Studio Code worked really well for us as well, it worked well with all our polyglot services and the .Net core integration had great cross-platform developer experience (to be fair, F# was a bit trickier) - actually, each of our team members used a different OS (Ubuntu, macos, windows). Our production deployment ran for a time on Docker Swarm until we've decided to adopt Kubernetes with almost seamless migration process.

After our positive experience of running .Net core workloads in containers and developing Tweek's .Net services on non-windows machines, C# had gained back some of its popularity (originally lost to Node.js), and other teams have been using it for developing microservices, k8s sidecars (like https://github.com/Soluto/airbag), cli tools, serverless functions and other projects...

See more
Helm logo

Helm

843
573
10
The Kubernetes Package Manager
843
573
+ 1
10
PROS OF HELM
  • 4
    Infrastructure as code
  • 3
    Open source
  • 2
    Easy setup
  • 1
    Testa­bil­i­ty and re­pro­ducibil­i­ty
CONS OF HELM
    Be the first to leave a con

    related Helm posts

    Emanuel Evans
    Senior Architect at Rainforest QA · | 14 upvotes · 580.3K views

    We recently moved our main applications from Heroku to Kubernetes . The 3 main driving factors behind the switch were scalability (database size limits), security (the inability to set up PostgreSQL instances in private networks), and costs (GCP is cheaper for raw computing resources).

    We prefer using managed services, so we are using Google Kubernetes Engine with Google Cloud SQL for PostgreSQL for our PostgreSQL databases and Google Cloud Memorystore for Redis . For our CI/CD pipeline, we are using CircleCI and Google Cloud Build to deploy applications managed with Helm . The new infrastructure is managed with Terraform .

    Read the blog post to go more in depth.

    See more
    Robert Zuber

    Our backend consists of two major pools of machines. One pool hosts the systems that run our site, manage jobs, and send notifications. These services are deployed within Docker containers orchestrated in Kubernetes. Due to Kubernetes’ ecosystem and toolchain, it was an obvious choice for our fairly statically-defined processes: the rate of change of job types or how many we may need in our internal stack is relatively low.

    The other pool of machines is for running our users’ jobs. Because we cannot dynamically predict demand, what types of jobs our users need to have run, nor the resources required for each of those jobs, we found that Nomad excelled over Kubernetes in this area.

    We’re also using Helm to make it easier to deploy new services into Kubernetes. We create a chart (i.e. package) for each service. This lets us easily roll back new software and gives us an audit trail of what was installed or upgraded.

    See more
    Rancher logo

    Rancher

    778
    1.2K
    644
    Open Source Platform for Running a Private Container Service
    778
    1.2K
    + 1
    644
    PROS OF RANCHER
    • 103
      Easy to use
    • 79
      Open source and totally free
    • 63
      Multi-host docker-compose support
    • 58
      Load balancing and health check included
    • 58
      Simple
    • 44
      Rolling upgrades, green/blue upgrades feature
    • 42
      Dns and service discovery out-of-the-box
    • 37
      Only requires docker
    • 34
      Multitenant and permission management
    • 29
      Easy to use and feature rich
    • 11
      Cross cloud compatible
    • 11
      Does everything needed for a docker infrastructure
    • 8
      Simple and powerful
    • 8
      Next-gen platform
    • 7
      Very Docker-friendly
    • 6
      Support Kubernetes and Swarm
    • 6
      Application catalogs with stack templates (wizards)
    • 6
      Supports Apache Mesos, Docker Swarm, and Kubernetes
    • 6
      Rolling and blue/green upgrades deployments
    • 6
      High Availability service: keeps your app up 24/7
    • 5
      Easy to use service catalog
    • 4
      Very intuitive UI
    • 4
      IaaS-vendor independent, supports hybrid/multi-cloud
    • 4
      Awesome support
    • 3
      Scalable
    • 2
      Requires less infrastructure requirements
    CONS OF RANCHER
    • 7
      Hosting Rancher can be complicated

    related Rancher posts

    Docker Swarm logo

    Docker Swarm

    679
    806
    267
    Native clustering for Docker. Turn a pool of Docker hosts into a single, virtual host.
    679
    806
    + 1
    267
    PROS OF DOCKER SWARM
    • 54
      Docker friendly
    • 45
      Easy to setup
    • 39
      Standard Docker API
    • 37
      Easy to use
    • 22
      Native
    • 21
      Free
    • 12
      Clustering made easy
    • 11
      Simple usage
    • 10
      Integral part of docker
    • 5
      Cross Platform
    • 4
      Labels and annotations
    • 3
      Performance
    • 2
      Shallow learning curve
    • 2
      Easy Networking
    CONS OF DOCKER SWARM
    • 7
      Low adoption

    related Docker Swarm posts

    Yshay Yaacobi

    Our first experience with .NET core was when we developed our OSS feature management platform - Tweek (https://github.com/soluto/tweek). We wanted to create a solution that is able to run anywhere (super important for OSS), has excellent performance characteristics and can fit in a multi-container architecture. We decided to implement our rule engine processor in F# , our main service was implemented in C# and other components were built using JavaScript / TypeScript and Go.

    Visual Studio Code worked really well for us as well, it worked well with all our polyglot services and the .Net core integration had great cross-platform developer experience (to be fair, F# was a bit trickier) - actually, each of our team members used a different OS (Ubuntu, macos, windows). Our production deployment ran for a time on Docker Swarm until we've decided to adopt Kubernetes with almost seamless migration process.

    After our positive experience of running .Net core workloads in containers and developing Tweek's .Net services on non-windows machines, C# had gained back some of its popularity (originally lost to Node.js), and other teams have been using it for developing microservices, k8s sidecars (like https://github.com/Soluto/airbag), cli tools, serverless functions and other projects...

    See more
    Simon Reymann
    Senior Fullstack Developer at QUANTUSflow Software GmbH · | 28 upvotes · 2.6M 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
    Spring Cloud logo

    Spring Cloud

    640
    582
    0
    Spring helps development teams everywhere build simple, portable,fast and flexible JVM-based systems and applications.
    640
    582
    + 1
    0
    PROS OF SPRING CLOUD
      Be the first to leave a pro
      CONS OF SPRING CLOUD
        Be the first to leave a con

        related Spring Cloud posts

        Spring-Boot Spring Cloud Elasticsearch MySQL Redis RabbitMQ Kafka MongoDB GitHub Linux IntelliJ IDEA

        See more
        Docker Machine logo

        Docker Machine

        414
        481
        12
        Machine management for a container-centric world
        414
        481
        + 1
        12
        PROS OF DOCKER MACHINE
        • 12
          Easy docker hosts management
        CONS OF DOCKER MACHINE
          Be the first to leave a con

          related Docker Machine posts