Apache’Mesos - Meetupfiles.meetup.com/15980712/mesos-london-09-25-14.pdf · agenda ①...

Benjamin Hindman – @benh

Apache Mesos (at Twitter) mesos.apache.org

@ApacheMesos

agenda ① Cluster Management at Twitter

② Mesos

③ Mesos at Twitter

④ VMs, IaaS, and Mesos

⑤ …

Monorail

cluster management

(configuration/package management) (deployment)

circa 2010

Woodstar Monorail Macaw TweetyPie memcached

challenges

challenges ①  failures

failures

challenges ②  maintenance

(aka “planned failures”)

planning for failure/maintenance

challenges ③  utilization

Hadoop

memcached

utilization

Hadoop

memcached

utilization

Hadoop

memcached buy less machines

or run more applications!

planning for utilization intra-‐machine resource sharing:

share a single machine’s resources between multiple applications (multi-‐tenancy)

intra-‐datacenter resource sharing:

share multiple machine’s resources between multiple applications

② Mesos

⑤ …

origins Mesos started as a research project at Berkeley in early 2009 by Benjamin Hindman, Andy Konwinski, Matei Zaharia, Ali Ghodsi, Anthony D. Joseph, Randy Katz, Scott Shenker, Ion Stoica

our motivation

increase performance and utilization of

clusters

our intuition

① static partitioning considered harmful

our intuition

② build new applications

“Map/Reduce is a big hammer, but not everything is a nail!”

workers

distributed system* anatomy

coordinator

* overlooking peer-to-peer distributed systems

static partitioning

coordinator coordinator

Mesos (slaves)

Mesos: level of indirection

coordinator

Mesos (master)

coordinator

Mesos (slaves)

coordinator

Mesos (master)

coordinator

Mesos (slaves)

coordinator

Mesos (master)

coordinator

Mesos (slaves)

coordinator

Mesos (master)

coordinator

Mesos (slaves)

coordinator

Mesos (master)

coordinator

Mesos: a level of indirection ①  enable running multiple distributed systems

on the same cluster of machines and dynamically share the resources more efficiently!

static partitioning considered harmful

Mesos: a level of indirection ②  provide common functionality every new

distributed system re-‐implements like failure detection, task distribution, task starting, task monitoring, task killing, task cleanup!

build new applications

Mesos ≈ cluster manager

cluster management

•  PBS (Portable Batch System) •  TORQUE •  SGE (Sun Grid Engine)

cluster management

•  PBS (Portable Batch System) •  TORQUE •  SGE (Sun Grid Engine)

batch computation!

Mesos is an evolution of the cluster manager, designed to run general purpose distributed systems (i.e., not just focused on batch)

batch service storage …

streaming

support many different types of distributed systems

batch service storage … streaming

(1) coordinate for resources (aka resource allocation)

(2) launch tasks

(3) launch tasks

(4) task termination

(5) task status update

(1) coordinate for resources (aka resource allocation)

② Mesos

⑤ …

stateless services!

batch service storage …

streaming

Apache Aurora (incubating)

Apache Aurora (incubating), a scheduler for running stateless services written in any language (but primarily used at Twitter for JVM services)

developer workflow

(1) describe service using Python based DSL

(2) submit service to Aurora using CLI

(1) bundle services as jar, tar/gzip

(2) upload to HDFS

configuration/package management

deployment

service.aurora

developer workflow

(1) describe service using JSON

(2) submit service to Marathon via REST

(1) bundle services as jar, tar/gzip

(2) upload to HDFS

configuration/package management

deployment

service.json

service discovery

Apache ZooKeeper

using Apache ZooKeeper and server sets (github.com/twitter/commons)

service discovery

Apache ZooKeeper

(1)  service gets launched on machine

service discovery

(2) service gets registered in a server set in ZooKeeper

Apache ZooKeeper

service discovery

(3) other services use ZooKeeper to find services they need

Apache ZooKeeper

service discovery

(3) other services use ZooKeeper to find services they need

(4) services connect directly with one another

Apache ZooKeeper

service discovery alternative

(2) update HAProxy with new service location

(3) other services send traffic through HAProxy

ZooKeeper/server sets requires injecting code into your clients!

where are we today?

ops developers

deploys decoupled from ops (many deploys per day, per service)

maintenance consists of “draining” hosts, getting tasks rescheduled, then pulling the cord

challenges revisited ①  failures

② maintenance

③  utilization

② maintenance

③  utilization

(5) task status update

② maintenance

③  utilization

(1)  when resources become idle, can be scheduled and reused by other schedulers

(2)  multi-‐tenancy on individual machines

multi-‐tenancy

containers

containerization started leveraging containerization technology

in ~2010

cgroups

namespaces (preliminary)

② Mesos

⑤ …

wait … don’t virtual machines solve my cluster management

challenges?

wait … don’t virtual machines solve my cluster management

challenges?

No. VMs are neither sufficient nor necessary!

② maintenance

③  utilization

② maintenance

③  utilization

public or private IaaS, failures still occur (on EC2, instead of racks, have availability zones, instead of datacenters, have regions)

② maintenance

③  utilization provider wins with public IaaS, better resource sharing with private IaaS, but a static partition of VMs is still a static partition!

physical machines virtual machines

aggregation not virtualization

physical machines “datacenter computer”

aggregation not virtualization

coordinator

Mesos (master)

Mesos: level of abstraction

resources

machines

Mesos build and run

distributed systems using resources

provision and manage machines

build and run distributed systems

using resources

deploy and manage applications/services

provision and manage machines

build and run distributed systems

using resources

PaaS on Mesos

build and run a PaaS on top of Mesos:

Apache Aurora and Marathon

Mesos on IaaS

use OpenStack or EC2 to run Mesos

Mesos on IaaS/bare metal

hardware use OpenStack or EC2 or physical machines

to run Mesos

② Mesos

⑤ Mesos Deeper Dive

cluster manager status quo before Mesos was batch scheduling

cluster manager status quo

cluster manager

application/human

specification

the specification includes as much information as possible to assist the cluster manager in scheduling and execution

cluster manager

application/human wait for task

to be executed

cluster manager

application/human

result

problems with specifications

①  hard to specify certain desires or constraints

②  hard to update specifications dynamically as tasks execute and finish/fail

MapReduce specification

①   what would it look like? ②   who submits it?

an alternative model

masters

scheduler

request 3 CPUs 2 GB RAM

a request is purposely simplified subset of a specification, mainly including the required resources at that point in time

an alternative model

masters

scheduler

request 3 CPUs 2 GB RAM

a request is purposely simplified subset of a specification, mainly including the required resources at that point in time

what should you do if you can’t satisfy a request?

①   wait until you can …

②   offer best you can immediately

Mesos model

masters

scheduler

offer hostname 4 CPUs 4 GB RAM

resources are allocated via resource offers a resource offer represents a snapshot of available resources that a scheduler can use to run tasks

an analogue: non-‐blocking sockets

kernel

application

write(s, buffer, size);!

an analogue: non-‐blocking sockets

kernel

application

42 of 100 bytes written!!

Mesos model

masters

scheduler

Mesos model

masters

scheduler

Mesos model

masters

scheduler

scheduler uses the offers to decide what tasks to run

Mesos model

masters

scheduler

scheduler uses the offers to decide what tasks to run

task 3 CPUs 2 GB RAM

Mesos model

masters

scheduler

scheduler uses the offers to decide what tasks to run “two-‐level scheduling”

“two-‐level scheduling” Mesos: controls resource allocations to schedulers

schedulers: make decisions about what tasks to run given allocated resources

two-‐level scheduling Mesos influenced by operating system supported user-‐space scheduling and ideas behind scheduler activations

Mesos is designed less like a “cluster manager” and more like an operating system (or kernel)

design comparison: Google’s Omega

database

scheduler

snapshot scheduler receives snapshot of all available resources

database

scheduler

transaction scheduler submits transaction to “acquire” resources

proposal: Mesos is isomorphic to Omega if makes offers for everything available

Omega and Mesos

database

scheduler

snapshot

masters

scheduler

Omega and Mesos

database

scheduler

transaction

masters

scheduler

offers represent the current snapshot of available resources a framework can use

concurrency control

optimistic pessimistic

all offers overlap with one another, thus causing frameworks to “compete” first-‐come-‐first-‐served

concurrency control

optimistic pessimistic

offers made to different frameworks are disjoint

Omega: requests are complimentary, but not necessary

② Mesos

⑥ Mesos Ecosystem

built on Mesos:

2009 2010 2013 2014

ported to Mesos:

2011 2012 2013 2014

some of our adopters …

2010 2013 2014 …

releases

0.18.0 (2013-‐04-‐01)

0.18.1 (2014-‐04-‐29)

0.18.2 (2014-‐05-‐13)

0.19.0 (2014-‐06-‐04)

0.19.1 (2014-‐07-‐14)

0.20.0 (2014-‐08-‐21)

contributors

38 contributors in the past 6 months

23 committers (also PMC members)

(Storm: 13; Kasa: 15; ZooKeeper: 16; Cassandra: 25; Thrift: 26; Spark: 32; Hadoop: 82)

3 new committers in past 3 months!

why have they been up to?

①   containerization and isolation

in ~2010

cgroups

namespaces (network)

in ~2010

cgroups

namespaces (network)

Docker (0.20.0)

first-‐class Docker support, i.e., use Docker images to run containers with Docker primitives like volumes, entrypoints, etc (0.20.0)

Learn More:

https://github.com/apache/mesos/blob/master/docs/docker-‐containerizer.md

②   container statistics

monitor all the things CPU, memory, network (0.20.0)

mesos-‐slave GET /monitor/statistics.json HTTP/1.1

{ "source": "sample_executor", "statistics": { "cpus_system_time_secs": 154.42, "cpus_user_time_secs": 258.74, "mem_file_bytes": 30613504, "mem_rss_bytes": 140341248, "net_rx_bytes": 2402099, "net_rx_dropped": 0, "net_tx_bytes": 1507798, "net_tx_dropped": 0, }}

monitor all the things CPU, memory, network (0.20.0)

Learn More:

https://github.com/apache/mesos/blob/master/docs/network-‐monitoring.md

③   authentication and authorization

authentication

credentials: principals and secrets

protocol built using SASL, designed to swap in/out other mechanisms, e.g., kerberos

authorization

introduced access control lists (ACLs)

“run_tasks”: [

{ “principals”: { “type”: “NONE” },

“users”: { “values”: “root” } }]

action

subjects

objects

“action performed by subjects on objects”

authorization

Learn More:

https://github.com/apache/mesos/blob/master/docs/authorization.md

④   fault tolerance and high availability

mesos-‐slave recovery

mesos-slave!

executor!

containers

mesos-slave!

executor!

containers

executor!

containers

executor!

containers

mesos-slave!

executor!

containers

mesos-slave!

Since 0.14.0! Running in production at Twitter for ~ 1 year (enabled by default since 0.15.0)

Learn More:

https://github.com/apache/mesos/blob/master/docs/slave-‐recovery.md

what’s being built?

①   primitives for stateful applications

stateful applications

better support for running frameworks like HDFS, Cassandra, directly on Mesos!

Learn More:

https://issues.apache.org/jira/browse/MESOS-‐1554

②   primitives for maintenance

aka “planned failures”

maintenance

mesos-‐slave

maintenance

mesos-‐slave

maintenance

mesos-‐slave

maintenance

mesos-‐slave mesos-‐slave

maintenance

task! task! (staging)

maintenance

task! (running)

Learn More:

maintenance

③   primitives for smarter resource allocation and scheduling

resource allocation original implementation of resource allocation in Mesos was “pessimistic”

Google’s Omega introduced the concept of “optimistic” resource allocation, which Mesos is a natural fit for!

Learn More:

④   improvements in resource isolation

resource isolation ①  network bandwidth

②  disk block I/O

③  ...

Learn More:

⑤   revised scheduler/executor API

API 2009 relic: HTTP (instead of Thrift) but not REST

(still evaluating JSON-‐RPC vs REST)

Last major change before 1.0! Existing API and libraries will remain backwards compatible, but be deprecated till 2.0 and then removed

② Mesos

⑥ Mesos Ecosystem

⑦ Conclusion

my other computer is a datacenter

my other computer is a datacenter*

* collection of physical and/or virtual machines

the ops perspective

the datacenter is just another form factor

why can’t we run apps on our datacenters just like we run applications on our mobile phones?

Hadoop Cassandra Rails Jenkins memcached

the dev perspective

applications don’t fit on a single computer anymore

(1) lots of data … (2) lots of users … growing everyday

today’s applications need lots of resources (CPUs, memory, disk)

we’re all building distributed systems

but everybody keeps reinventing the wheel

how many more buggy failure detectors will we build until we stop?

desktop computer

server datacenter

the datacenter computer needs an operating system

operating system “a collection of software that manages the computer hardware resources and provides common services for computer programs”

- Wikipedia

datacenter operating system “a collection of software that manages the datacenter computer hardware resources and provides common services for computer programs”

- Wikipedia

datacenter operating system “a collection of software that manages the datacenter computer hardware resources and provides common services for computer programs”

- Wikipedia

Apache Mesos: datacenter kernel

Apache Mesos: distributed systems kernel

Thank You!

mesos.apache.org

mesos.apache.org/blog

@ApacheMesos

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