The size and variety of big data means traditional scale-up strategies are no longer adequate for modern workloads. The need to consider a large number of commodity machines as a single computer, and the ability to share resources in an elastic manner by all the frameworks requires a cluster computing framework. Mesos is inspired by the idea of sharing resources in a cluster between multiple frameworks while providing resource isolation.

1. BASLE BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA
HAMBURG COPENHAGEN LAUSANNE MUNICH STUTTGART VIENNA ZURICH
Introducing Apache Mesos
Matthias Furrer
Bruno Fuss
A modern cluster manager optimizing resource utilization

2. Agenda
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1. Introduction
Architecture (components)
Distributions
Other Offerings
2. Frameworks
Service Scheduling and
Management Frameworks
Big Data Frameworks
3. HA Components
Zookeeper
Marathon
3. Configuration
Mesos
Marathon
Kafka
4. Live Demo
Mesos
Kafka
5. Summary
Use Cases / Benefits

3. TechEvent March 2017 - Introducing Apache Mesos3 03/2017
Introduction

4. Introducing Apache Mesos
A software layer to aggregate servers into one processing unit
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Distributed Cluster Management Software
System Resources (Memory, Storage) abstraction from Hardware
Metascheduler („scheduler of schedulers“)
Distributed Systems Kernel / Distributed Datacenter OS
Supports Mesos and Docker Containers
Open Source
– Runs under Apache License 2.0
Cross Plattform
– Written in C++
– Runs on Linux/Posix systems, Experimental for Windows

5. Architecture - Features
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Scalability
– Scales up to over 50‘000 nodes
Resource isolation
– Linux cgroups or Docker containers
Efficiency
– Resource scheduling accross multiple frameworks/applications
High availability
– Uses Apache Zookeeper (distributed configuration and synchronization service)
Monitoring Interface
– Web UI

6. Components
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Master
– Mediating agent resources
Agents
– Manage resources on individual nodes and executes
tasks
Frameworks
Applications
– Systems running on mesos consisting of a scheduler and an
executor (e.g. Spark, Storm ,Cassandra)
Chronos
– Fault tolerant job scheduler, can handle dependencies - acts
as a cron for mesos
Marathon
– Framework for running long-running services – init.d for
mesos

7. Architecture – High Level Overview
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Zookeeper ensures high availability of masters
Master daemon manages agent (slave) daemons
Mesos frameworks run tasks on agents (slaves)
Master decides how many resources to offer to each
framework according to a given organizational policy
(e.g fair sharing or strict priority).
Framework running on top of Mesos consists of two
components: a scheduler that registers with the master
to be offered resources, and an executor process that
is launched on agent nodes to run the framework’s
taskSource: https://mesos.apache.org/documentation/latest/architecture

8. Architecture – Resource Offering
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1. Agent 1 reports to the master that it has 4
CPUs and 4 GB of memory free. The master
then invokes the allocation policy module
2. The master sends a resource offer describing
what is available on agent 1 to framework
3. The framework’s scheduler replies to the
master with information about two tasks to
run on the agent
4. Master sends the tasks to the agent, which
allocates appropriate resources to the
framework’s executor, which launches the
two tasks. Because CPU/RAM Resources
are still unallocated, the allocation module
may now offer them to framework 2.
Source: https://mesos.apache.org/documentation/latest/architecture

9. Distributions– Mesosphere DC/OS
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Commercial version: Mesosphere Datacenter Operating System
Open Source version: DC/OS available - derived from Mesosphere’s Datacenter
Operating System
Based on Mesos and Marathon
Supports Docker as well as native Mesos containers
Container orchestration capabilities for Docker and Mesos containers including
automatic workload recovery, security, networking, service discovery
“Push-button installation” of complex distributed systems (including HDFS, Apache
Spark, Apache Kafka, Apache Cassandra and more) with DC/OS Universe
Runs on bare-metal, virtual (vSphere or OpenStack) and cloud (AWS, Azure, GCE)

10. Other Offerings
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Kubernetes (Google / Cloud Native Computing Foundation CNCF)
Docker Swarm (Docker, Inc.)
Rkt fleet (CoreOS, Inc.)
Shipyard (Shipyard Project)
CloudSlang (Hewlett Packard Enterprise)
Ranger (Ranger Labs)
Azure Service Fabric (Microsoft)

11. TechEvent March 2017 - Introducing Apache Mesos11 03/2017
Frameworks

12. Service Scheduling and Management Frameworks
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Marathon
– Launch and monitor long-running applications. Controlling a high availability
environment, checking the applications' health and restarting services if nodes go
down
Chronos
– Distributed, fully fault-tolerant job scheduler. Can interact with systems (e.g.
Hadoop) even if the Mesos worker machine does not have the system installed
Apache Aurora
– Manages long-running services, cron jobs, and ad-hoc jobs
Consul
– Service Discovery and orchestration

13. Big Data Frameworks
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Apache Hadoop
– Distributed Data Processing, MapReduce and Distributed File System (HDFS)
Apache Spark
– Execution engine for large-scale data processing. Batch processing, iterative
processing, near real-time processing, and stream processing. Caching data in
memory with Resilient Distributed Datasets (RDD)
Apache Storm
– Real-time distributed stream event-processing engine
Apache Cassandra
– Open source scalable NoSQL database. Provides query language Cassandra
Query Language or CQL to communicate with database

14. Big Data Frameworks (II)
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Apache Kafka
– distributed publish-subscribe messaging system designed for speed, scalability,
reliability, and durability
Apache Samza
– Distributed stream processing framework. Using Kafka for messaging and Hadoop
YARN for resource management
Elasticsearch-Logstash-Kibana (ELK) stack
– End-to-End log analytics solution: Elasticsearch for search capabilities, Logstash
as a log management software and Kibana as the visualization layer
Mesos API
– Develop custom frameworks – schedulers and executors

15. TechEvent March 2017 - Introducing Apache Mesos15 03/2017
High Availability
Components

16. Apache Zookeeper
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ZooKeeper
– is a centralized service for maintaining configuration information, naming, providing distributed
synchronization, and providing group services.
Independent Apache Project
Characteristics
– Central Key/Value Store
– Containing additional Information like time stamps, versioning, …
– Simple
– Fast
– Designed for High Availability

17. Apache Zookeeper
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High Availability
– one Leader
– two or more Followers
– Quorum
Follower

18. Apache Zookeeper
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Data Model
– Hierarchical Namespace
– Z-Nodes (Zookeeper Nodes)
– Nodes identified by Path
• Ex.: /app1/p_1
Ephemeral Nodes
Leader Election
Conditional updates and watches
Atomic Transactions

19. Apache Zookeeper on Mesos
Zookeeper takes hand in everywhere Mesos needs to store and call up distributed
dynamic information
– Service Locations
– Service States
– Client Notifications
– Leader election for Mesos Masters and Frameworks (e.g. Marathon, etc.)
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20. Marathon
Marathon is a Apache Mesos framework for container orchestration
– designed for long running and stateful Apps (e.g. Database, App. Server, etc.)
Marathon is a meta framework
– used for managing other Mesos Frameworks (Chronos, Storm, …)
Container Support
– Mesos Containers (default)
– Docker Constainers (must be configured)
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21. Marathon
Features
– High Availability
– Constraints
– Service Discovery & Load Balancing (Mesos-DNS, Marathon-LB)
– Health Checking
– Event Subscription
– User Interfaces for managing services (start, stop, check, …)
• Marathon UI (GUI)
• REST API
– Basic Security (Authorisation, SSL, …)
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22. Marathon Example
Mesos Master and Agents (Slaves),
Zookeeper and Marathon started by
OS on each server (initd, systemd)
Marathon starts frameworks on
Mesos Agents (Chronos, JBoss,
Jetty, Rails)
Chronos, a fault tolerant job
scheduler acts itself as framework
and starts jobs (e.g. dumps a
database, send Emails)
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23. TechEvent March 2017 - Introducing Apache Mesos23 03/2017
Installation & Configuration

24. Installing and Configuring Apache Mesos
Installation
– http://mesos.apache.org/gettingstarted
– Different between CentOS 6 / 7
• Different Requirements (OS Packages, Libraries, …)
– configure / make / make install
– Zookeeper included
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25. Installing and Configuring Apache Mesos
Configuration
– http://mesos.apache.org/documentation/latest/configuration
– Provide parameters by config file or as startup parameter
– Required parameters (M: on Master, A: on Agent)
--zk="zk://mesos1:2181,mesos2:2181,mesos3:2181/mesos" (M,A)
--quorum=2 (M)
--work_dir=<workdir_path> (M,A)
--containerizers=mesos,docker (A)
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26. Installing and Configuring Marathon
Requirements
• Apache Mesos 1.1.1+
• Apache ZooKeeper
• JDK 1.8+
• Default JVM set to Java 8
Installation
– https://mesosphere.github.io/marathon/docs/
– Dowload/unpack Kit (tar)
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27. Installing and Configuring Marathon
Configuration
– Library: MESOS_NATIVE_JAVA_LIBRARY
• searches the common installation paths, /usr/lib and /usr/local/lib, for the Mesos native library.
If the library lives elsewhere in your configuration, set the environment variable
MESOS_NATIVE_JAVA_LIBRARY to its full path.
– Parameters: Marathon uses --master to find the Mesos masters, and --zk to find
ZooKeepers for storing state
--master="zk://mesos1:2181,mesos2:2181,mesos3:2181/mesos"
--zk="zk://mesos1:2181,mesos2:2181,mesos3:2181/marathon"
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28. Installing and Configuring Apache Kafka for Mesos
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Installation
• According to https://github.com/mesos/kafka
• Make sure to retrieve the Kafka download from https://archive.apache.org/dist/kafka from a
version containing a fitting Scala library (Version indicated on the Mesos page may not be
correct) to avoid java.lang.NoSuchMethodError
Configuration
• Set Mesos connection info in kafka-mesos.properties
• Start Scheduler on ONE Mesos agent (Marathon can be used to manage)
• Add Broker(s)
• Start Broker(s)

29. TechEvent March 2017 - Introducing Apache Mesos29 03/2017
Demo

30. mesos1 mesos2
mesos3 mesos4 mesosn
…
mesosn-1
TVD Mesos Platform / Server
extendable
• additional Servers (on-premise)
• Cloud
• …
03/2017 TechEvent March 2017 - Introducing Apache Mesos30
BF2

31. Slide 30
BF2 Bruno Fuss, 3/8/2017

32. mesos1 mesos2
mesos3 mesos4 mesosn
…
mesosn-1
Mesos
Master
Mesos
Master
Mesos
Agent
Mesos
Agent
TVD Mesos Platform / Mesos Components
Mesos
Agent
Mesos
Agent
HA concept Master: active/passive
03/2017 TechEvent March 2017 - Introducing Apache Mesos31

33. mesos1 mesos2
mesos3 mesos4
Mesos
Master
Mesos
Master
Mesos
Agent
Mesos
Agent
Zoo
keeper
Zoo
keeper
Zoo
keeper
TVD Mesos Platform / Zookeeper Components
HA concept: active/active
1 leader
2-n followers
Zookeeper quorum= 2
mesosn
…
mesosn-1
Mesos
Agent
Mesos
Agent
03/2017 TechEvent March 2017 - Introducing Apache Mesos32
BF3

34. Slide 32
BF3 Bruno Fuss, 3/8/2017

35. TechEvent March 2017 - Introducing Apache Mesos33 03/2017
Summary

36. Use Cases / Why use Mesos
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Enhance resilience against failure
Need for application-specific scaling
Increase resource utilization
Wide range of workloads must be supported – e.g. Batch (Hadoop), Analysis
(Spark), real-time (Storm), data storage (HDFS, Cassandra)
Open source with vivid community
Developer API – minimal considerations about infrastructure details

37. Matthias Furrer
Principal Consultant, Application Integration & SOA
matthias.furrer@trivadis.com
03/2017 TechEvent March 2017 - Introducing Apache Mesos35
Bruno Fuss
Senior Consultant, Infrastructure Managed Services
Bruno.fuss@trivadis.com

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