Alternatives to Okteto logo

Alternatives to Okteto

Skaffold, Kubernetes, Docker Compose, Helm, and Rancher are the most popular alternatives and competitors to Okteto.
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What is Okteto and what are its top alternatives?

An application development platform for Kubernetes that helps developers to quickly iterate and improve their test decision time by 4x.
Okteto is a tool in the Container Tools category of a tech stack.

Top Alternatives to Okteto

  • Skaffold

    Skaffold

    Skaffold is a command line tool that facilitates continuous development for Kubernetes applications. You can iterate on your application source code locally then deploy to local or remote Kubernetes clusters. Skaffold handles the workflow for building, pushing and deploying your application. It can also be used in an automated context such as a CI/CD pipeline to leverage the same workflow and tooling when moving applications to production. ...

  • 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. ...

  • 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. ...

  • 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. ...

  • Spring Cloud

    Spring Cloud

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

  • 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. ...

  • 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. ...

Okteto alternatives & related posts

Skaffold logo

Skaffold

69
144
0
Easy and Repeatable Kubernetes Development
69
144
+ 1
0
PROS OF SKAFFOLD
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    CONS OF SKAFFOLD
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      Kubernetes logo

      Kubernetes

      38.8K
      33K
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      Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops
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      PROS OF KUBERNETES
      • 159
        Leading docker container management solution
      • 124
        Simple and powerful
      • 101
        Open source
      • 75
        Backed by google
      • 56
        The right abstractions
      • 24
        Scale services
      • 18
        Replication controller
      • 9
        Permission managment
      • 7
        Simple
      • 7
        Supports autoscaling
      • 6
        Cheap
      • 4
        Self-healing
      • 4
        Reliable
      • 4
        No cloud platform lock-in
      • 3
        Open, powerful, stable
      • 3
        Scalable
      • 3
        Quick cloud setup
      • 3
        Promotes modern/good infrascture practice
      • 2
        Backed by Red Hat
      • 2
        Runs on azure
      • 2
        Cloud Agnostic
      • 2
        Custom and extensibility
      • 2
        Captain of Container Ship
      • 2
        A self healing environment with rich metadata
      • 1
        Golang
      • 1
        Easy setup
      • 1
        Everything of CaaS
      • 1
        Sfg
      • 1
        Expandable
      • 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 · | 39 upvotes · 4.2M 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
      Docker Compose logo

      Docker Compose

      14.8K
      10.8K
      477
      Define and run multi-container applications with Docker
      14.8K
      10.8K
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      477
      PROS OF DOCKER COMPOSE
      • 121
        Multi-container descriptor
      • 109
        Fast development environment setup
      • 75
        Easy linking of containers
      • 66
        Simple yaml configuration
      • 58
        Easy setup
      • 15
        Yml or yaml format
      • 11
        Use Standard Docker API
      • 7
        Open source
      • 4
        Can choose Discovery Backend
      • 4
        Go from template to application in minutes
      • 2
        Scalable
      • 2
        Easy configuration
      • 2
        Kubernetes integration
      • 1
        Quick and easy
      CONS OF DOCKER COMPOSE
      • 8
        Tied to single machine
      • 5
        Still very volatile, changing syntax often

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      Simon Reymann
      Senior Fullstack Developer at QUANTUSflow Software GmbH · | 28 upvotes · 3.3M 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

      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
      Helm logo

      Helm

      963
      649
      11
      The Kubernetes Package Manager
      963
      649
      + 1
      11
      PROS OF HELM
      • 5
        Infrastructure as code
      • 3
        Open source
      • 2
        Easy setup
      • 1
        Testa­bil­i­ty and re­pro­ducibil­i­ty
      CONS OF HELM
        Be the first to leave a con

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        Emanuel Evans
        Senior Architect at Rainforest QA · | 16 upvotes · 698.6K 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.

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        Rancher logo

        Rancher

        805
        1.2K
        644
        Open Source Platform for Running a Private Container Service
        805
        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
        • 8
          Hosting Rancher can be complicated

        related Rancher posts

        Spring Cloud logo

        Spring Cloud

        708
        627
        0
        Spring helps development teams everywhere build simple, portable,fast and flexible JVM-based systems and applications.
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        PROS OF SPRING CLOUD
          Be the first to leave a pro
          CONS OF SPRING CLOUD
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            related Spring Cloud posts

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

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            Docker Swarm logo

            Docker Swarm

            705
            839
            267
            Native clustering for Docker. Turn a pool of Docker hosts into a single, virtual host.
            705
            839
            + 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

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            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 · 3.3M 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
            Docker Machine logo

            Docker Machine

            423
            489
            12
            Machine management for a container-centric world
            423
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            + 1
            12
            PROS OF DOCKER MACHINE
            • 12
              Easy docker hosts management
            CONS OF DOCKER MACHINE
              Be the first to leave a con

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