Mesos vs kubernetes comparison

HUAWEI TECHNOLOGIES CO., LTD.

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www.huawei.com

Mesos vs. Kubernetes … a quick look …

Krishna M Kumar

Lead Architect

Bangalore Cloud Foundry Meetup – 28th Mar 2015



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contents - mesos vs. kubernetes – the TOP TEN

1. We are comparing – The what part!

10. Where to look further – The References

5. The bits and pieces – The Components

3. The guys who plays together – The Partners/Customers

4. Unknown internals – The Architecture

7. The comparative landscape – The Competitors

2. What you get it – The Features

9. So Finally What – The Conclusion

6. Who does the real job – The Scheduler

8. What the world is going to do – The Future



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Mesos Kubernetes

Apache Mesos is a cluster manager that provides efficient

resource isolation and sharing across distributed

applications, or frameworks.

Apache Mesos abstracts CPU, memory, storage, and other

compute resources away from machines (physical or virtual),

enabling fault-tolerant and elastic distributed systems.

Google Kubernetes brings 'Google style' cluster

management capabilities to the world of virtual machines, or

'on the metal' scenarios.

For production Google uses Omega/Borg, not Kubernetes

which is in beta.

• Mesos using same principle as Linux Kernel but higher layer

of abstraction.

• It can run Hadoop, MPI, Hypertable, Spark, and other

frameworks on a dynamically shared pool of nodes.

• Manage a cluster of Linux containers as a single system.

• Kubernetes works with Mesos as Framework like Marathon

Frameworks.

Was developed at the University of California, Berkeley year

2009 developed by Benjamin Hindman, Andy Konwinski, Matel

Zaharia as well as professor Ion Stoica

Become top level Apache project from July 2013

Project Started at Google

It is still in Beta stage

Works with various Frameworks like Marathon, Cronos. You can

write your own. There is a core algorithm(DRF) to share

resources and you can define your own scheduling policy.

Frameworks does Fault Tolerance, Load balancing, Quotas,

Discovery, etc.

Kubernetes establishes robust declarative primitives for

maintaining the desired state requested by the user. Self-healing

mechanisms, such as auto-restarting, re-scheduling, and

replicating containers require active controllers, not just

imperative orchestration.

1. We are comparing – The what part!



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Mesos Kubernetes

Written in C++, Create a big resource pool from all

resources.

Written in Golang, works well with CoreOS, Red Hat

Atomic. Easy to run cluster resources.

Full control of the containers scheduled. Custom schedule

can manage the containers and VMs as desired.

Kubernetes will do the containers. Pods – a group of

containers scheduled on the same host supports

composable micro services.

Since Mesos enables you to run stateless services such

as web servers or application servers on the same cluster

as Spark for analytics purposes, it increases the overall

cluster utilization and accommodates the effects of data

gravity.

You can deploy any service you like into Kubernetes.

There are also some services with built-in Kubernetes

support. Cassandra, RethinkDB and Spark are some of

them. This makes better utilization, reduce complexity and

service discovery much easier.

Project Features • Scalability to 10,000s of nodes

• Fault-tolerant replicated master and slaves using ZooKeeper

• Support for Docker containers

• Native isolation between tasks with Linux Containers

• Multi-resource scheduling (memory, CPU, disk, and ports)

• Java, Python and C++ APIs for developing new parallel applications

• Web UI for viewing cluster state

Project Features • Primarily targeted at applications composed of multiple containers,

• such as elastic, distributed micro-services.

• Support multiple platforms

• Easy to get up and running & portable

• Manages Docker deployment well

• Scheduling provides out of the box

• Monitoring Dashboard

2. What you get it – The Features



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Mesos Kubernetes

4. The guys who plays together – The Partners/Customers

Organizations using Mesos: http://mesos.apache.org/documentation/latest/powered-by-mesos/

Twitter Airbnb Apple Cisco Ericson Ebay Mesosphere Netflix

Google Microsoft IBM RedHat Docker Mesosphere SaltStack CoreOS Tectonic Mirantis Openstack VMWare

http://mesos.apache.org/documentation/latest/powered-by-mesos/







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Mesos Kubernetes

5. Unknown internals – The Architecture

See Components in next slide for more details.



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Mesos Kubernetes

1. Master – Enable sharing of resource

2. Slave – Execute the task in it

3. Cluster – a group of machines

4. ZooKeeper – distributed synchroniztion/configuration

5. Framework – scheduler + executor

6. Scheduler – Offer resources

7. Executor – Run the Framework task

8. Task – a job to run

9. Containerizer – run & monitor executors

1. Master – Cluster controlling unit

2. etcd – HA Key/value store

3. API Server - Observing the state of the cluster

4. Controller Manager – runs multiple controllers

5. Scheduler Server – assigns workloads to nodes

6. Minion – server that perform work

7. Kubelet - server/slave node that runs pods

8. Proxy Service – host subnetting to external parties

9. Pods – One or more containers

10.Services – load balancer for containers

11.Replication Controller – For horizontally-scaled pods

12.Labels – A tag for work unit for grouping

Related:

1. CoreOS – Chrome OS based Linux distro

2. Fleet – Orchestrate CoreOS Clusters

3. Borg – massive scale resource manager

4. Omega – massive scale cluster manager

More detailed explanations of the components: https://github.com/mesosphere/kubernetes-mesos/issues/285

6. The bits and pieces – The Components

https://github.com/mesosphere/kubernetes-mesos/issues/285





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Mesos Kubernetes

7. Who does the real job – The Scheduler

The scheduler is configurable and at compile time which fit predicates and priority functions you want Kubernetes to apply. It has two types of policies, FitPredicate - The sum of the requested resources of the container(s) already running on the machine plus the requested resources of the new container(s) you are considering scheduling onto the machine must not be greater than the capacity of the machine& PriorityFunction - The scheduler may find that multiple machines "fit" the pod and it prefers the machine whose already-running pod consume the least resources. Future Goals -- Scheduling is a policy-rich, topology-aware, workload-specific function that significantly impacts availability, performance, and capacity. The scheduler needs to take into account individual and collective resource requirements, quality of service requirements, hardware/software/policy constraints, affinity and anti-affinity specifications, data locality, inter-workload interference, deadlines, and so on. Workload-specific requirements will be exposed through the API as necessary.

Mesos has two levels of scheduling; first one intra-Frameworks level as in below and second at inter-Framework level application specific.



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8. The comparative landscape – The Competitors



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Mesos Kubernetes

Silicon Valley startup Mesosphere is

betting big on Mesos to create its future

Data Center Operating System.

Several top companies are using Mesos

in their production environment.

Google’s Flagship Data Center product

for cloud hosting with lots of industry

backing.

Mesosphere have integrated Mesos and

Kubernetes together.

Focusing more on Enterprise adoption like Security,

Encryption, Reliability and Authentication

by Ben Hindman – Mesos Creator.

Better scheduling algorithm & Spanning across

multiple location is challenge.

By Eric Brewer, VP Google & CAP Theorem Creator.

Customers can choose utilization in datacenters,

security and reliability at scale – can be brought to

container- and VM-based environments using

Mesos. Huge flexibility of integrating any kind of

framework and so continue to grow popularly.

Kubernetes to be awesome everywhere, even for

customers who will run their apps on other clouds or

in their own datacenters - goal for Kubernetes is

ubiquity. AS more and more Docker deployment

happens and Kubernetes gets more maturity, it may

act alone without Mesos to deliver similar value what

Mesos provides!

9. What the world is going to do – The Future



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10. So Finally What – The Conclusion

Together Kubernetes and Mesos are a match made in heaven. Kubernetes enables the Pod (group of co-located containers) abstraction, along with Pod labels for service discovery, load-

balancing, and replication control. Mesos provides the fine-grained resource allocations for pods across nodes in a cluster, and can make Kubernetes play nicely

with other frameworks running on the same cluster resources - Stackoverflow

Use Mesos for: Heavy Duty Production

Implement a new capability Need multiple Framework

For existing workloads Full control of workloads

Use Kubernetes for: Testing alpha/beta Very easy to setup and start Pre-built scheduler algorithm Container only world More features on the way



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10. Where to look further – The References 1. Mesos - https://github.com/apache/mesos/ 2. Kubernetes - https://github.com/googlecloudplatform/kubernetes 3. Mesos Architecture - http://mesos.apache.org/documentation/latest/mesos-architecture/ 4. Kubernetes Design - https://github.com/GoogleCloudPlatform/kubernetes/tree/master/docs/design 5. Kubernetes Scheduler - http://stackoverflow.com/questions/28857993/how-does-kubernetes-scheduler-work 6. Mesos Scheduler - http://cloudarchitectmusings.com/2015/04/08/playing-traffic-cop-resource-allocation-in-apache-

mesos/ 7. Kubernetes Deployment - https://news.ycombinator.com/item?id=9653118 8. Mesosphere – Kubernetes-Mesos - https://github.com/mesosphere/kubernetes-mesos 9. Mesos and Kubernetes at scale - https://www.youtube.com/watch?v=pFCJ3WiVjyA 10. Mesos vs. Kubernetes - http://stackoverflow.com/questions/26705201/whats-the-difference-between-apaches-mesos-

and-googles-kubernetes 11. Kubernetes – Marathon - https://www.quora.com/What-is-the-difference-between-Googles-Kubernetes-and-

Mesospheres-Marathon 12. Mesos - Kubernetes PaaS - http://www.slideshare.net/MiguelZuniga1/platform-as-a-service-with-kubernetes-and-mesos 13. Mesos, Docker, Kubernetes - http://www.slideshare.net/timothysc/apache-coneu 14. Future of computing - https://medium.com/s-c-a-l-e/google-systems-guru-explains-why-containers-are-the-future-of-

computing-87922af2cf95 15. Future of Resource Manager by IBM - https://www.ibm.com/developerworks/community/blogs/1ba56fe3-efad-432f-

a1ab-58ba3910b073/entry/thoughts_on_future_of_resource_managers_and_schedulers_in_the_cloud?lang=en

https://github.com/apache/mesos/



https://github.com/googlecloudplatform/kubernetes



http://mesos.apache.org/documentation/latest/mesos-architecture/




https://github.com/GoogleCloudPlatform/kubernetes/tree/master/docs/design

https://github.com/GoogleCloudPlatform/kubernetes/tree/master/docs/design

http://stackoverflow.com/questions/28857993/how-does-kubernetes-scheduler-work











http://cloudarchitectmusings.com/2015/04/08/playing-traffic-cop-resource-allocation-in-apache-mesos/
















https://news.ycombinator.com/item?id=9653118

https://news.ycombinator.com/item?id=9653118

https://github.com/mesosphere/kubernetes-mesos




https://www.youtube.com/watch?v=pFCJ3WiVjyA

https://www.youtube.com/watch?v=pFCJ3WiVjyA

http://stackoverflow.com/questions/26705201/whats-the-difference-between-apaches-mesos-and-googles-kubernetes


















https://www.quora.com/What-is-the-difference-between-Googles-Kubernetes-and-Mesospheres-Marathon




















http://www.slideshare.net/MiguelZuniga1/platform-as-a-service-with-kubernetes-and-mesos
















http://www.slideshare.net/timothysc/apache-coneu




https://medium.com/s-c-a-l-e/google-systems-guru-explains-why-containers-are-the-future-of-computing-87922af2cf95
































https://www.ibm.com/developerworks/community/blogs/1ba56fe3-efad-432f-a1ab-58ba3910b073/entry/thoughts_on_future_of_resource_managers_and_schedulers_in_the_cloud?lang=en










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