Alternatives to Portainer logo

Alternatives to Portainer

Kubernetes, Mesosphere, Kitematic, Cockpit, and Docker Compose are the most popular alternatives and competitors to Portainer.
485
825
+ 1
144

What is Portainer and what are its top alternatives?

Portainer is a user-friendly and open-source container management tool that simplifies the management of Docker environments. Its key features include a web-based user interface for managing containers, images, networks, and volumes, support for Swarm and Kubernetes, application templates for quick deployment, and role-based access control. However, Portainer has limitations in terms of scalability for large environments and lacks some advanced features compared to other container management platforms in the market.

  1. Rancher: Rancher is a robust container management platform that supports multiple Kubernetes clusters, monitoring, and centralized management of containers across environments. It offers extensive features for application deployment, load balancing, and scaling. Pros include a user-friendly interface and integration with various cloud providers, while cons may include the learning curve for beginners.
  2. Kubernetes Dashboard: Kubernetes Dashboard is an official web-based UI for managing Kubernetes clusters, providing an overview of cluster resources, logs, and monitoring. Its pros include direct integration with Kubernetes without the need for additional tools, but it may lack some advanced features compared to dedicated container management platforms.
  3. Docker Swarm: Docker Swarm is a container orchestration tool built into Docker Engine, offering high availability, scaling, and load balancing for containerized applications. Its key features include simplicity in setup and management, but it may lack some advanced features compared to other orchestration platforms.
  4. Nomad: Nomad is a container orchestrator by HashiCorp that supports Docker, Kubernetes, and other workloads. It provides flexible scheduling, autoscaling, and multi-region support. Pros include seamless integration with HashiCorp tools, while cons may include the learning curve for new users.
  5. D2iQ Konvoy: D2iQ Konvoy is a Kubernetes distribution that simplifies the deployment, management, and operations of Kubernetes clusters. It offers a production-ready platform with built-in monitoring, logging, and CI/CD integration. Pros include enterprise-grade support and stability, but cons may include the cost for premium features.
  6. OpenShift: OpenShift by Red Hat is an enterprise Kubernetes platform that provides automated operations, security, and scalability for containerized applications. It offers developer-friendly tools, CI/CD pipelines, and support for hybrid cloud environments. Pros include robust security features and developer workflows, while cons may include licensing costs for enterprise support.
  7. RudderStack: RudderStack is an open-source alternative that simplifies the orchestration, collection, and routing of data across multiple platforms. It offers support for cloud-native technologies, compliance, and data privacy. Pros include flexibility in integrating with various data sources and destinations, while cons may include the need for customization for specific use cases.
  8. Portus: Portus is an open-source authorization service and user interface for Docker registries that provides authentication, access control, and security features. It integrates with existing Docker setups and offers audit logs and role-based access control. Pros include enhanced security measures for Docker images, while cons may include additional setup and configuration compared to container management platforms.
  9. Supervisor: Supervisor is a client/server system for managing processes on Unix-like operating systems, providing tools for controlling and monitoring multiple processes. It offers features for process groups, auto-restart, and log management. Pros include lightweight resource usage and easy configuration, while cons may include limited scalability compared to full-fledged container orchestration tools.
  10. Octopus Deploy: Octopus Deploy is a deployment automation tool for Microsoft.NET applications, providing release management, deployment orchestration, and infrastructure automation. It supports various platforms, environments, and deployment strategies. Pros include integration with popular DevOps tools and ease of use, while cons may include licensing costs for enterprise features.

Top Alternatives to Portainer

  • 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. ...

  • Mesosphere
    Mesosphere

    Mesosphere offers a layer of software that organizes your machines, VMs, and cloud instances and lets applications draw from a single pool of intelligently- and dynamically-allocated resources, increasing efficiency and reducing operational complexity. ...

  • Kitematic
    Kitematic

    Simple Docker App management for Mac OS X

  • Cockpit
    Cockpit

    An API-driven CMS without forcing you to make compromises in how you implement your site. The CMS for developers. Manage content like collections, regions, forms and galleries which you can reuse anywhere on your website. ...

  • 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. ...

  • 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
    Docker

    The Docker Platform is the industry-leading container platform for continuous, high-velocity innovation, enabling organizations to seamlessly build and share any application — from legacy to what comes next — and securely run them anywhere ...

  • Watchtower
    Watchtower

    It is an application that will monitor your running Docker containers and watch for changes to the images that those containers were originally started from. If it detects that an image has changed, it will automatically restart the container using the new image. ...

Portainer alternatives & related posts

Kubernetes logo

Kubernetes

59K
51K
677
Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops
59K
51K
+ 1
677
PROS OF KUBERNETES
  • 164
    Leading docker container management solution
  • 128
    Simple and powerful
  • 106
    Open source
  • 76
    Backed by google
  • 58
    The right abstractions
  • 25
    Scale services
  • 20
    Replication controller
  • 11
    Permission managment
  • 9
    Supports autoscaling
  • 8
    Cheap
  • 8
    Simple
  • 6
    Self-healing
  • 5
    No cloud platform lock-in
  • 5
    Promotes modern/good infrascture practice
  • 5
    Open, powerful, stable
  • 5
    Reliable
  • 4
    Scalable
  • 4
    Quick cloud setup
  • 3
    Cloud Agnostic
  • 3
    Captain of Container Ship
  • 3
    A self healing environment with rich metadata
  • 3
    Runs on azure
  • 3
    Backed by Red Hat
  • 3
    Custom and extensibility
  • 2
    Sfg
  • 2
    Gke
  • 2
    Everything of CaaS
  • 2
    Golang
  • 2
    Easy setup
  • 2
    Expandable
CONS OF KUBERNETES
  • 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
  • 1
    Additional vendor lock-in (Docker)
  • 1
    More moving parts to secure
  • 1
    Additional Technology Overhead

related Kubernetes posts

Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber · | 44 upvotes · 10.9M 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
Ashish Singh
Tech Lead, Big Data Platform at Pinterest · | 38 upvotes · 3M views

To provide employees with the critical need of interactive querying, we’ve worked with Presto, an open-source distributed SQL query engine, over the years. Operating Presto at Pinterest’s scale has involved resolving quite a few challenges like, supporting deeply nested and huge thrift schemas, slow/ bad worker detection and remediation, auto-scaling cluster, graceful cluster shutdown and impersonation support for ldap authenticator.

Our infrastructure is built on top of Amazon EC2 and we leverage Amazon S3 for storing our data. This separates compute and storage layers, and allows multiple compute clusters to share the S3 data.

We have hundreds of petabytes of data and tens of thousands of Apache Hive tables. Our Presto clusters are comprised of a fleet of 450 r4.8xl EC2 instances. Presto clusters together have over 100 TBs of memory and 14K vcpu cores. Within Pinterest, we have close to more than 1,000 monthly active users (out of total 1,600+ Pinterest employees) using Presto, who run about 400K queries on these clusters per month.

Each query submitted to Presto cluster is logged to a Kafka topic via Singer. Singer is a logging agent built at Pinterest and we talked about it in a previous post. Each query is logged when it is submitted and when it finishes. When a Presto cluster crashes, we will have query submitted events without corresponding query finished events. These events enable us to capture the effect of cluster crashes over time.

Each Presto cluster at Pinterest has workers on a mix of dedicated AWS EC2 instances and Kubernetes pods. Kubernetes platform provides us with the capability to add and remove workers from a Presto cluster very quickly. The best-case latency on bringing up a new worker on Kubernetes is less than a minute. However, when the Kubernetes cluster itself is out of resources and needs to scale up, it can take up to ten minutes. Some other advantages of deploying on Kubernetes platform is that our Presto deployment becomes agnostic of cloud vendor, instance types, OS, etc.

#BigData #AWS #DataScience #DataEngineering

See more
Mesosphere logo

Mesosphere

80
108
6
Combine your datacenter servers and cloud instances into one shared pool
80
108
+ 1
6
PROS OF MESOSPHERE
  • 6
    Devops
CONS OF MESOSPHERE
    Be the first to leave a con

    related Mesosphere posts

    Kitematic logo

    Kitematic

    68
    116
    14
    The easiest way to start using Docker on your Mac
    68
    116
    + 1
    14
    PROS OF KITEMATIC
    • 8
      I like it because it sucks
    • 3
      No command line, Docker in one app, gui, easy to set up
    • 2
      Good for first timer
    • 1
      Easy to get started
    CONS OF KITEMATIC
      Be the first to leave a con

      related Kitematic posts

      Amarin Boonkirt
      Full Stack Developer at UzaWeb · | 1 upvote · 47.7K views

      Python PHP Eclipse GitLab Kitematic Docker #DevEnv I selected PHP for General Web Platform, And Python for other special things.

      See more
      Cockpit logo

      Cockpit

      55
      234
      17
      Add content management functionality to any site - plug & play CMS
      55
      234
      + 1
      17
      PROS OF COCKPIT
      • 3
        Flexible and plays nicely with any frontend
      • 3
        Easy for Content Managers to understand and use
      • 3
        Open Source
      • 2
        Fast & lightweight
      • 2
        Modular
      • 2
        GraphQL
      • 2
        Self hosted
      CONS OF COCKPIT
        Be the first to leave a con

        related Cockpit posts

        Docker Compose logo

        Docker Compose

        21.3K
        16.1K
        501
        Define and run multi-container applications with Docker
        21.3K
        16.1K
        + 1
        501
        PROS OF DOCKER COMPOSE
        • 123
          Multi-container descriptor
        • 110
          Fast development environment setup
        • 79
          Easy linking of containers
        • 68
          Simple yaml configuration
        • 60
          Easy setup
        • 16
          Yml or yaml format
        • 12
          Use Standard Docker API
        • 8
          Open source
        • 5
          Go from template to application in minutes
        • 5
          Can choose Discovery Backend
        • 4
          Scalable
        • 4
          Easy configuration
        • 4
          Kubernetes integration
        • 3
          Quick and easy
        CONS OF DOCKER COMPOSE
        • 9
          Tied to single machine
        • 5
          Still very volatile, changing syntax often

        related Docker Compose posts

        Simon Reymann
        Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 9.7M 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
        Rancher logo

        Rancher

        944
        1.5K
        644
        Open Source Platform for Running a Private Container Service
        944
        1.5K
        + 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
        • 10
          Hosting Rancher can be complicated

        related Rancher posts

        Docker logo

        Docker

        171.4K
        137.7K
        3.9K
        Enterprise Container Platform for High-Velocity Innovation.
        171.4K
        137.7K
        + 1
        3.9K
        PROS OF DOCKER
        • 823
          Rapid integration and build up
        • 691
          Isolation
        • 521
          Open source
        • 505
          Testa­bil­i­ty and re­pro­ducibil­i­ty
        • 460
          Lightweight
        • 218
          Standardization
        • 185
          Scalable
        • 106
          Upgrading / down­grad­ing / ap­pli­ca­tion versions
        • 88
          Security
        • 85
          Private paas environments
        • 34
          Portability
        • 26
          Limit resource usage
        • 17
          Game changer
        • 16
          I love the way docker has changed virtualization
        • 14
          Fast
        • 12
          Concurrency
        • 8
          Docker's Compose tools
        • 6
          Easy setup
        • 6
          Fast and Portable
        • 5
          Because its fun
        • 4
          Makes shipping to production very simple
        • 3
          Highly useful
        • 3
          It's dope
        • 2
          Very easy to setup integrate and build
        • 2
          HIgh Throughput
        • 2
          Package the environment with the application
        • 2
          Does a nice job hogging memory
        • 2
          Open source and highly configurable
        • 2
          Simplicity, isolation, resource effective
        • 2
          MacOS support FAKE
        • 2
          Its cool
        • 2
          Docker hub for the FTW
        • 2
          Super
        • 0
          Asdfd
        CONS OF DOCKER
        • 8
          New versions == broken features
        • 6
          Unreliable networking
        • 6
          Documentation not always in sync
        • 4
          Moves quickly
        • 3
          Not Secure

        related Docker posts

        Simon Reymann
        Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 9.7M 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
        Tymoteusz Paul
        Devops guy at X20X Development LTD · | 23 upvotes · 8.7M views

        Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

        It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

        I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

        We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

        If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

        The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

        Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

        See more
        Watchtower logo

        Watchtower

        25
        36
        6
        A process for automating Docker container base image updates
        25
        36
        + 1
        6
        PROS OF WATCHTOWER
        • 2
          Automation Friendly
        • 1
          Open-source
        • 1
          Great community
        • 1
          Small footprint
        • 1
          Easy setup
        CONS OF WATCHTOWER
          Be the first to leave a con

          related Watchtower posts