When comparing Kubernetes vs Apache Mesos, the Slant community recommends Kubernetes for most people. In the question“What are the best cluster managers?” Kubernetes is ranked 1st while Apache Mesos is ranked 3rd. The most important reason people chose Kubernetes is:
Kubernetes is free and open source.
Ranked in these QuestionsQuestion Ranking
Pro Open Source
Kubernetes is free and open source.
Pro Built on several years of experience with containers
Kubernetes was built on top of several years of experience from Google working on containers in production. It's a little opinionated on how containers should work and behave, but if used correctly it can help you achieve fault-tolerant systems.
Pro Fault tolerant
Almost everything in Kubernetes is designed to handle if parts of it fail or if your service crashed for whatever reason. So it's particularly adapted if you've a cluster (even a very small one).
Pro Works well with modern operating systems
Kubernetes works very well with modern environments (such as CoreOS or Red Hat Atomc) which offer lightweight computing nodes that you don't have to manage, since they are managed for you.
Pro Supported on several PaaS
Kubernetes is currently supported by Google Compute Engine, Rackspace, Microsoft Azure, and vSphere. Work is being done to support Kubernetes on OpenShift and CloudFoundry.
Pro Easy to do grouping tasks
Kubernetes uses labels which are key-value pairs that are attached to objects, usually pods. They are used to specify the characteristics of an object like the version, tier, etc. Labels are used to identify objects or groups of objects according to different characteristics that they may have, for example they can be used to identify all the pods that are included in the backend tier.
Through labels it's easier to do grouping tasks for pods or containers, like moving pods to different groups or assigning them to load-balanced groups.
Pro Great starting point for beginners
Kubernetes great for beginners who are just starting to work on clustering. It's probably the quickest and easiest way to start experimenting and learning cluster oriented development.
Pro Good for existing workloads
If you have existing workloads, for example (Hadoop, Kafka, Spark, etc), Mesos makes it very easy to use these workloads together.
Pro Good with data processing applications
Many modern data processing applications (Hadoop, Kafka, Spark) run very well on Mesos. This is especially nice because they can all be run on the same resource pool, along with new container packaged apps.
Pro Scales very well
Mesos is a battle-proven piece of software which has been used in many large-scale projects (it's used by Twitter, Ebay and AirBnB) and can support hundreds of thousands of nodes.
Con Cannot define containers through the Docker CLI
Kubernetes was not written for docker clustering alone. It uses a different API, configuration and different YAML definitions. So you can't use the Docker CLI or Docker Compose to define your containers. Everything has to be done from scratch.
Con Windows restrictions
Windows compatibility rules, the host OS version must match the container base image OS version. Only Windows containers with Windows Server 2019 are supported. Also other restrictions are present.
Con If used on an existing system, some re-organizing may be needed
Because of how opinionated Kubernetes is, it may be necessary to change some things if you decide to use Kubernetes as an orchestration tool in an existing application.
Con Sometimes Pods refuse to (re)start automatically
It happens that a Pod needs a manual kick before it runs properly, especially if you're near full utilisation of your machine resources. Sometimes it is just a long delay.
Con May be over-complicated for small clusters
When working with small clusters (less than a dozen nodes), Mesos may be an over-complicated solution since it's rather low level and designed for large clusters and scaling.