This document discusses the transition to modern enterprise applications using containers, microservices, and big data technologies. It provides examples of how Mayo Clinic and Uber have revolutionized their industries using these technologies. The key benefits of DC/OS are that it provides a datacenter operating system that simplifies deploying and managing modern apps at scale. It allows turning infrastructure into a unified pool of resources and installing distributed services like Spark, Kafka with one command. The DC/OS community contributes many open services and it can be tried locally in under 20 minutes. Mesosphere Enterprise DC/OS provides additional support for production use.

1. © 2016 Mesosphere, Inc. All Rights Reserved.
Edward Hsu, VP of Enterprise DC/OS
@edwardihsu
JOURNEY TO THE MODERN APP WITH
CONTAINERS, MICROSERVICES AND BIG DATA
Datacenter Operating System (DC/OS)
The simplest way to build, run, scale and manage modern enterprise apps

2. © 2016 Mesosphere, Inc. All Rights Reserved.

3. © 2016 Mesosphere, Inc. All Rights Reserved.
INDUSTRY TRANSITIONS
Customer analytics
2000s
Electronic customer
records
1980s
Online customer
engagement
1990s
Real-time & predictive
customer engagement
2013+

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5. © 2016 Mesosphere, Inc. All Rights Reserved.

6. © 2016 Mesosphere, Inc. All Rights Reserved.
MAYO CLINIC REVOLUTIONIZING HEALTHCARE
Individualized care
recommendations based on
5 million patient records
Key technologies:
● Real-time data ingestion
● Distributed search engine
● Large-scale processing
● Distributed database

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UBER DISRUPTING MULTIPLE INDUSTRIES
Operations in over 300 cities around
the world
Key technologies:
● Distributed logging
● Large-scale data processing
● Distributed datastore

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ARCHITECTURAL SHIFT
TRADITIONAL
ENTERPRISE
APPLICATIONS
MODERN
ENTERPRISE
APPLICATIONS
Data
Code
Latency
Users
2+ Billion smartphone users
3+ Billion internet users
Enterprise data growth (CAGR): 40%+
Source: KPCB Internet Trends 2016, EMC Digital Universe 2014

9. © 2016 Mesosphere, Inc. All Rights Reserved.
ARCHITECTING FOR SCALE AT TWITTER
BEFORE AFTER

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Streaming
10
THE MODERN ENTERPRISE APP
BIG DATA SERVICESMICROSERVICES
STATELESS CONTAINERS ANALYTICS
Batch
Machine
Learning
Search
DATABASES
Time
Series
SQL /
NoSQL

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MODERN ENTERPRISE APPS
Containers Data Services
MicroservicesOpen source & Social coding1
2
3
4

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OPEN SOURCE SOFTWARE PROVIDES LEVERAGE1

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CONTAINERS SIMPLIFY PACKAGING AND DEPLOYMENT
Private Copy
Shared
App 3
Libraries
Guest
Operating
System
Infrastructure
App 1
Libs
Host Operating System
Start / stop time One minute to few seconds Milliseconds
Workload density 10 - 100x1x
App 2
Libraries
Guest
Operating
System
App 1
Libraries
Guest
Operating
System
App 2
Libs
App 3
Libs
Virtual Machines Containers
Host Operating System
Hypervisor
Infrastructure
App 4
Libs
App 5
Libs
2

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JUST HOW FAST ARE CONTAINERS?
Larry Rau from @Verizon
with @flo Launching 50,000
containers in seconds with
@mesosphere #DC/OS

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MICROSERVICES ENABLE FAST AND FREQUENT RELEASES
Traditional Architecture
Many functions
in a single process
Siloed
teams
RESTAPIs
Microservices Architecture
Cross-functional
teams organized
around capabilities
Scales
individually
Each element of
functionality defined as
“microservices”
Scales
monolithically
3

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DATA SERVICES PROVIDE CONNECTION AND PERSISTENCE
Data Ingestion
Response
Devices
ClientSensors
Event Bus
Reactive
App
Database
Analytics
Use Case Examples
● Anomaly detection
● Personalization
● IoT Applications
● Predictive Analytics
● Machine Learning
4

17. © 2016 Mesosphere, Inc. All Rights Reserved. 17
BUT WHAT ABOUT THE INFRASTRUCTURE?
CaaSPaaS
Container
AppContainer App
Stateful
Service #1
V1
Big Data
Analytics #1
V1
Stateful
Service #2
V1
Stateful
Service #2
V2
PaaS
Container
App
Team A
Big Data
Analytics #1
V2
Big Data
Analytics
#2
V1
Team B

18. © 2016 Mesosphere, Inc. All Rights Reserved. 18
BUT WHAT ABOUT THE INFRASTRUCTURE?
CaaSPaaS
Container
AppContainer App
Stateful
Service #1
V1
Big Data
Analytics #1
V1
Stateful
Service #2
V1
Stateful
Service #2
V2
PaaS
Container
App
Team A
Big Data
Analytics #1
V2
Big Data
Analytics
#2
V1
Team B
● Extremely low utilization - less than 10%, due to static
partitioning
● Manual operations - Weeks to provision, wasted time
managing individual machines
● Difficult to experiment with new tech - months to
provision environments to evaluate new technologies
● High risk - Failure from manual operations and
difficulties maintaining high availability

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WHERE HAVE WE SEEN THIS PROBLEM BEFORE?
You are launching Google Chrome.
Which core would you like to use?
Core 1 Core 2
Core 3 Core 4
You are launching a distributed app requiring 500 cores.
Which of your 50,000 cores would you like to use?
Core 1 Core 2 Core 3 Core 4 Core 5
Core 6 Core 8 Core 9 Core 10Core 7
Core 11 Core 13 Core 14 Core 15Core 12
Core 16 Core 18 Core 19 Core 20Core 17
Core 21 Core 23 Core 24 Core 25Core 22
Core 26 Core 28 Core 29 Core 30Core 27
Core 31 Core 33 Core 34 Core 35Core 32
Core 36 Core 38 Core 39 Core 40Core 37
Core 41 Core 43 Core 44 Core 45Core 42

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MODERN ENTERPRISE APPS REQUIRE WE OPERATE
AT THE LOGICAL DATACENTER LEVEL
Traditional App Modern Enterprise App

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YES, THIS TOO CAN BE SOLVED WITH ABSTRACTION
Scheduler
Executor
Task
Launch
Task
Launch
Task
Status
Task
Status
Resource
Offer
Executor
Executor
Executor
Scheduler
Executor
Task
Launch
Executor
Executor
Task
Status
Scheduler
Executor
Task
Launch
Executor
Executor
Task
Status
Distributed System A Distributed System B Datacenter Operating System
Approach
Distributed
Systems
A+B+C+...
Apache Mesos Two-level Scheduling

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Datacenter Operating System (DC/OS)
DC/OS
...
Agent 1 Agent 2 Agent 3 Agent n
Server VM Cloud VM
...
Modern App
Components
FROM SERVER TO DATACENTER-SCALE
Server Operating System
OS (e.g., Windows, Linux)
...
Core 0 Core 1 Core 2 Core n
Server
Process

23. © 2016 Mesosphere, Inc. All Rights Reserved. 23
MODERN APPS WITH THE DC/OS MODEL
Traditional Approach
Big Data
Analytics
Stateful
Service
DC/OS Model
Container
App
Container
App
CaaS PaaS
● Turnkey install of datacenter-wide services
● Simplified operations & efficiency
● Lowers barriers to experiment with new tech (e.g., Spark)
Container
App
Datacenter-scale operating system

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BRINGING
MODERN
APPS TO
EVERYONE
● 100% Open source
● No limits

25. 25
THE DC/OS COMMUNITY

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DC/OS
Operations

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DC/OS
SERVICE
INSTALL:
SPARK

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DC/OS
SERVICE
INSTALL:
KAFKA

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DC/OS
SERVICE
UPDATE &
CONFIG:
KAFKA

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DC/OS UNIVERSE: STORE FOR APP SERVICES
DC/OS
Anyone can publish on DC/OS Universe
app store - partners & OSS contributors
Popular services include Spark,
Cassandra, Jenkins, and Kafka
Services include distributed systems that
run elastically across the datacenter
Install these services with a single
command
Spark
Jenkins
Riak
DataStax Enterprise
Confluent Kafka
ArangoDB
GitLab
Cassandra
JFrog Artifactory
Elasticsearch
MariaDB
Storm
HDFS
Zeppelin
MemSQL
Over 40 Services Made For DC/OS

31. © 2016 Mesosphere, Inc. All Rights Reserved.
TRY DC/OS IN
UNDER 20
MINUTES
dcos.io

32. © 2016 Mesosphere, Inc. All Rights Reserved.
MESOSPHERE ENTERPRISE DC/OS

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“We’re running real time analytics and
visualization of data from connected sensors
Before DC/OS we had no where near the scale
we had today, from thousands of to millions of
events per second.
Next, we’re doing predictive GIS”
Adam Mollenkopf, Real Time Geospatial
Information Systems Capability Lead

34. © 2016 Mesosphere, Inc. All Rights Reserved.
“We are building a PaaS and services on an
existing OpenStack cloud to enable developers to
build microservices on Docker containers and use
big data technologies...
DC/OS was a force multiplier for us to get these
new services out the door fast...
We transitioned the full enterprise infrastructure
at 2X the speed of previous efforts.”
Tim Pletcher
Engineering Director, Application Services

35. © 2016 Mesosphere, Inc. All Rights Reserved.
“We came across Mesosphere while planning for the
coming IoT market..
If I build everything in a silo, I have no chance...
With DC/OS, I have one single contiguous cluster
and I can bring my data and store it and I can run all
my applications as well..
and I think that's a huge advantage”
Larry Rau, Director Architecture & Infrastructure,
Verizon Labs

36. © 2016 Mesosphere, Inc. All Rights Reserved.
SPEED MATTERS
McKinsey Quarterly 2015: “The perils of ignoring software development”
Based on assessment of software development projects at 1,300 companies
Top quartile companies
bring new software
features to market
3x faster
than bottom quartile

37. © 2016 Mesosphere, Inc. All Rights Reserved.
Thank You
Questions?
@edwardihsu
Learn more at mesosphere.com, including our whitepaper:
Modern Enterprise App Operations with DC/OS
Lessons from Running Containers, Microservices, and
Stateful Big Data Services in Production