Alternatives to kops logo

Alternatives to kops

Amazon EKS, Rancher, Terraform, Helm, and minikube are the most popular alternatives and competitors to kops.
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What is kops and what are its top alternatives?

It helps you create, destroy, upgrade and maintain production-grade, highly available, Kubernetes clusters from the command line. AWS (Amazon Web Services) is currently officially supported, with GCE in beta support , and VMware vSphere in alpha, and other platforms planned.
kops is a tool in the Cluster Management category of a tech stack.
kops is an open source tool with 13K GitHub stars and 4K GitHub forks. Here’s a link to kops's open source repository on GitHub

Top Alternatives to kops

  • Amazon EKS

    Amazon EKS

    Amazon Elastic Container Service for Kubernetes (Amazon EKS) is a managed service that makes it easy for you to run Kubernetes on AWS without needing to install and operate your own Kubernetes clusters. ...

  • 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. ...

  • Terraform

    Terraform

    With Terraform, you describe your complete infrastructure as code, even as it spans multiple service providers. Your servers may come from AWS, your DNS may come from CloudFlare, and your database may come from Heroku. Terraform will build all these resources across all these providers in parallel. ...

  • Helm

    Helm

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

  • minikube

    minikube

    It implements a local Kubernetes cluster on macOS, Linux, and Windows. Its goal is to be the tool for local Kubernetes application development and to support all Kubernetes features that fit. ...

  • Apache Mesos

    Apache Mesos

    Apache Mesos is a cluster manager that simplifies the complexity of running applications on a shared pool of servers. ...

  • Nomad

    Nomad

    Nomad is a cluster manager, designed for both long lived services and short lived batch processing workloads. Developers use a declarative job specification to submit work, and Nomad ensures constraints are satisfied and resource utilization is optimized by efficient task packing. Nomad supports all major operating systems and virtualized, containerized, or standalone applications. ...

  • DC/OS

    DC/OS

    Unlike traditional operating systems, DC/OS spans multiple machines within a network, aggregating their resources to maximize utilization by distributed applications. ...

kops alternatives & related posts

Amazon EKS logo

Amazon EKS

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Highly available and scalable Kubernetes service
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PROS OF AMAZON EKS
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    CONS OF AMAZON EKS
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      related Amazon EKS posts

      We are looking for a centralised monitoring solution for our application deployed on Amazon EKS. We would like to monitor using metrics from Kubernetes, AWS services (NeptuneDB, AWS Elastic Load Balancing (ELB), Amazon EBS, Amazon S3, etc) and application microservice's custom metrics.

      We are expected to use around 80 microservices (not replicas). I think a total of 200-250 microservices will be there in the system with 10-12 slave nodes.

      We tried Prometheus but it looks like maintenance is a big issue. We need to manage scaling, maintaining the storage, and dealing with multiple exporters and Grafana. I felt this itself needs few dedicated resources (at least 2-3 people) to manage. Not sure if I am thinking in the correct direction. Please confirm.

      You mentioned Datadog and Sysdig charges per host. Does it charge per slave node?

      See more
      Sebastian Gębski

      Heroku was a decent choice to start a business, but at some point our platform was too big, too complex & too heterogenic, so Heroku started to be a constraint, not a benefit. First, we've started containerizing our apps with Docker to eliminate "works in my machine" syndrome & uniformize the environment setup. The first orchestration was composed with Docker Compose , but at some point it made sense to move it to Kubernetes. Fortunately, we've made a very good technical decision when starting our work with containers - all the container configuration & provisions HAD (since the beginning) to be done in code (Infrastructure as Code) - we've used Terraform & Ansible for that (correspondingly). This general trend of containerisation was accompanied by another, parallel & equally big project: migrating environments from Heroku to AWS: using Amazon EC2 , Amazon EKS, Amazon S3 & Amazon RDS.

      See more
      Rancher logo

      Rancher

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      Open Source Platform for Running a Private Container Service
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      PROS OF RANCHER
      • 103
        Easy to use
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        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

      Terraform logo

      Terraform

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      Describe your complete infrastructure as code and build resources across providers
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      PROS OF TERRAFORM
      • 103
        Infrastructure as code
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        Declarative syntax
      • 43
        Planning
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        Simple
      • 23
        Parallelism
      • 6
        Cloud agnostic
      • 5
        It's like coding your infrastructure in simple English
      • 4
        Well-documented
      • 3
        Automates infrastructure deployments
      • 3
        Platform agnostic
      • 3
        Immutable infrastructure
      • 2
        Automation
      • 2
        Portability
      • 2
        Scales to hundreds of hosts
      • 2
        Extendable
      • 1
        Lightweight
      CONS OF TERRAFORM
      • 1
        Doesn't have full support to GKE

      related Terraform posts

      Context: I wanted to create an end to end IoT data pipeline simulation in Google Cloud IoT Core and other GCP services. I never touched Terraform meaningfully until working on this project, and it's one of the best explorations in my development career. The documentation and syntax is incredibly human-readable and friendly. I'm used to building infrastructure through the google apis via Python , but I'm so glad past Sung did not make that decision. I was tempted to use Google Cloud Deployment Manager, but the templates were a bit convoluted by first impression. I'm glad past Sung did not make this decision either.

      Solution: Leveraging Google Cloud Build Google Cloud Run Google Cloud Bigtable Google BigQuery Google Cloud Storage Google Compute Engine along with some other fun tools, I can deploy over 40 GCP resources using Terraform!

      Check Out My Architecture: CLICK ME

      Check out the GitHub repo attached

      See more
      Praveen Mooli
      Engineering Manager at Taylor and Francis · | 14 upvotes · 1.8M views

      We are in the process of building a modern content platform to deliver our content through various channels. We decided to go with Microservices architecture as we wanted scale. Microservice architecture style is an approach to developing an application as a suite of small independently deployable services built around specific business capabilities. You can gain modularity, extensive parallelism and cost-effective scaling by deploying services across many distributed servers. Microservices modularity facilitates independent updates/deployments, and helps to avoid single point of failure, which can help prevent large-scale outages. We also decided to use Event Driven Architecture pattern which is a popular distributed asynchronous architecture pattern used to produce highly scalable applications. The event-driven architecture is made up of highly decoupled, single-purpose event processing components that asynchronously receive and process events.

      To build our #Backend capabilities we decided to use the following: 1. #Microservices - Java with Spring Boot , Node.js with ExpressJS and Python with Flask 2. #Eventsourcingframework - Amazon Kinesis , Amazon Kinesis Firehose , Amazon SNS , Amazon SQS, AWS Lambda 3. #Data - Amazon RDS , Amazon DynamoDB , Amazon S3 , MongoDB Atlas

      To build #Webapps we decided to use Angular 2 with RxJS

      #Devops - GitHub , Travis CI , Terraform , Docker , Serverless

      See more
      Helm logo

      Helm

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      The Kubernetes Package Manager
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      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 · 578.7K 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
        minikube logo

        minikube

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        Local Kubernetes engine
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        PROS OF MINIKUBE
          Be the first to leave a pro
          CONS OF MINIKUBE
            Be the first to leave a con

            related minikube posts

            Apache Mesos logo

            Apache Mesos

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            Develop and run resource-efficient distributed systems
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            PROS OF APACHE MESOS
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              Easy scaling
            • 6
              Web UI
            • 2
              Fault-Tolerant
            • 1
              Elastic Distributed System
            • 1
              High-Available
            CONS OF APACHE MESOS
            • 1
              Not for long term
            • 1
              Depends on Zookeeper

            related Apache Mesos posts

            Docker containers on Mesos run their microservices with consistent configurations at scale, along with Aurora for long-running services and cron jobs.

            See more
            Nomad logo

            Nomad

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            A cluster manager and scheduler
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            PROS OF NOMAD
            • 6
              Built in Consul integration
            • 5
              Easy setup
            • 4
              Bult-in Vault integration
            • 3
              Built-in federation support
            • 1
              Autoscaling support
            • 1
              Self-healing
            • 1
              Nice ACL
            • 1
              Managable by terraform
            • 1
              Open source
            • 1
              Simple
            • 1
              Flexible
            • 1
              Multiple workload support
            • 1
              Bult-in Vault inegration
            • 1
              Stable
            CONS OF NOMAD
            • 3
              Easy to start with
            • 1
              HCL language for configuration, an unpopular DSL
            • 1
              Small comunity

            related Nomad posts

            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
            DC/OS logo

            DC/OS

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            The Datacenter Operating System. The easiest way to run microservices, big data, and containers in production.
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            PROS OF DC/OS
            • 5
              Easy to setup a HA cluster
            • 3
              Open source
            • 2
              Has templates to install via AWS and Azure
            • 1
              Easy Setup
            • 1
              Easy to get services running and operate them
            CONS OF DC/OS
              Be the first to leave a con

              related DC/OS posts