cloudy with a chance of on-prem - jim scott, strata hadoop 2017 sj
TRANSCRIPT
1© 2017 MapR Technologies 1© 2017 MapR Technologies
Cloudy with a Chance of On-PremJim Scott@kingmesal
2© 2017 MapR Technologies 2
Data is at the Core of Business Transformation
1980s Now
Early databases
Enterprise applications
The Internet Digital Transformation
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Data Drives Market Disruption
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Market Disruptors Use DataTo Impact Business Outcomes in Real-Time
Real-timeoperational impact
Higher customer engagement and lower acquisition cost
Eliminate cost,waste, time delay
Continuous insight analysis and application
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Industry Leaders Are Investing in Disruptive Technology Now
Legacy technology investmentNext-Gen technology investment
2013 2014 2015 2016 2017 2018 2019 2020 (80,000)
(40,000)
-
40,000
80,000
120,000
$ (millions) Investment in Next-Gen vs. Legacy Technologies for Data
Total $ growth of IT market
Innovating and reducing costs at the same time90% of data is on
next-gen technology in just four years
Source: IDC, Gartner; Analysis & Estimates: MapRNext-gen consists of cloud, big data, software and hardware related expenses
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MapRHadoop
Pressure to deal with Volume, variety,
velocity of new data
Customers
Pressure to deliver more to customer
base
Pressure to figure out the cloud and
containersOn
premAzureAWS
Your partner’ssystems
Yourlegacy
Business systems
Pressure to reduce cost of
legacy
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Time to pause fora moment...
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Cloud and Container Terminology• Data Gravity
– Data ingress and egress
• Cloud Neutrality– Freedom of choice– Prevent vendor lock-in
• Container Image and Repository
Other terms that I can explain ???
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Anything Can Fail!
Prepare for the worst, hope for the best…
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Customer 360
Website
User Profiles
Click Stream
Activity Stream
Website
User Profiles
Click Stream
Activity Stream
Amazon Google Cloud
On-Prem
User Profiles
Click Stream
Activity Stream
Salesforce
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Hadoop & Spark
Cluster
Document DB
Classic Data Warehouse
NoSQL
Application Server
MessageMiddleware
Search ServerIts not the circles,
It’s the lines that are hard
Expensive to Stitch | Fragile | Limitations for Speed, Scale, Reliability
Cloud Processing Alone Does not Solve the Crisis of Complexity
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Putting It In One Distribution Does Not Converge Anything!
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Global Cloud Processing Requirements
Global single namespaceOmni-directional replication
Location awareness
Strong consistency by default
Continuous, Coordinated, Data flows
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Source: 2016 Docker Survey
Cloud and Containers
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Challenge with Containers
• Organizations using containers to improve resource utilization, increase developer efficiency, deploy microservices
• Most of containerized applications today are stateless– If destroyed and re-deployed, no data is lost and no services are
disrupted (ex: simple web front-ends)– Sharing state across many nodes is difficult and/or cost-prohibitive
• Container environments don’t provide the reliable storage needed to support stateful applications
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New Product
MapR Announces the Converged Data Platform for Docker
Supports containerization of existing and new applications by providing containers with
persistent data access from anywhere
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MapR Expands and Simplifies Container Usage
Flexible Hybrid/Multi Cloud Infrastructure
Shared Data Services
Per-tenant Processing & Microservices
Converged App Containers
Enterprise Apps
Data Center
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MapR Data Services for Containers
• Pre-built, certified container image for connecting to MapR services
• Secure authentication at container level, secure connection
• High performance
• Extensible support for application layers
• Available in Docker Hub, Dockerfile for customizability
Space for Customer Application
MapR Persistent Application Client Container(PACC)
MapR POSIX Client for Containers
MapR Converged Client for
Containers
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MapR Lets Enterprises Run Existing Apps in Containers
MapR Cluster
Advantages• Stateful containers that can restart/move
to any node or data center and access data• Shared data repository for multiple apps,
operations & analytics• Decoupled scaling of compute & storage
Use Cases• RDBMS Persistence (MySQL, Vertica, SAP)• Container Image Store (Docker Registry)• Rapid-ingest Logging (Impressions, Clicks)• Source Control Persistence (Git, Mercurial)• Image Store (Thumbnails, High Res)
Container Environment (Mesos, Kubernetes,Docker Swarm)
MariaDB Volume Logs Volume
Reliable, Persistent, High-throughput Storage
Solution: MapR PACC allows existing applications to store state in MapR Converged Data Platform, ensuring resilience and availability across application and infrastructure failures.
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While Allowing Enterprises to Adopt Microservices
Advantages• Ubiquitous, reliable, high performance data services,
no per-app data containers
Use Cases• Stateful microservices• Inter-microservice Communication• Per-microservice database
MapR Cluster
Container Environment (Mesos, Kubernetes)
MariaDB Volume
Reliable, Persistent, High-throughput Storage
Solution: MapR PACC establishes secure connection to MapR Converged Data platform, which provides all three types of persistence.
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Container Summary• Huge Opportunity – Organizations are
rapidly moving to containerize
• Huge Gap for stateful application support
• MapR provides a high value, highly differentiated solution
• Our tactical solution is part of a much larger strategic initiative
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Converged Data Platform
Analytical Applications
Operational Applications
Converged ApplicationsComplete Access to Real-time and
Historical Data in One Platform
Developers Creating Database and Event Based
Applications
(Bottom Line Initiatives) (Top Line Initiatives)
Analysts Creating BI Reports and KPIs on Data
Warehouse
Historical Data Current Data
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Web-Scale StorageMapR-FS MapR-DB
Real Time Unified Security Multi-tenancy Disaster Recovery Global NamespaceHigh Availability
MapR StreamsEvent StreamingDatabase
MapR Platform Services: Open API ArchitectureAssures interoperability, avoids lock-in
HDFS API
POSIXNFS
SQL,HBase
APIJSONAPI
KafkaAPI
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Converged Application Benefits
• Consumers scale horizontally with partitions• 1:1 mapping between consumer and partition• Enables predictable scaling as production needs grow
• Data can be seamlessly replicated to another cluster• Enables HA with zero code changes
• Data is indexed dynamically according to receivers, senders• Scales beyond the capabilities of Kafka
• Snapshots can be taken to capture state• Enables faster testing and deployment of applications
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Reduce costs to improve efficiency
Extend capabilities
to grow revenues
Innovate for disruptiveadvantage
Put the Power of MapR to Work for Your BusinessWherever you are on your big data journey
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Converge, Transform and Grow with MapR
Innovatefor Growth
RealizeCost Savings