SlideShare a Scribd company logo
1 of 31
®
© 2014 MapR Technologies 1
®
© 2014 MapR Technologies
Zeta Architecture
Jim Scott – Director, Enterprise Strategy & Architecture
Houston - March 25, 2015
®
© 2014 MapR Technologies 2
Agenda
•  Current State
–  History
–  Moving Forward
•  The Next Enterprise Architecture
•  Business Implications
•  Concrete Implementations
®
© 2014 MapR Technologies 3© 2014 MapR Technologies
®
Current State
®
© 2014 MapR Technologies 4
Study History to Prepare for the Future
•  A data center was built
•  The servers were statically
partitioned
•  If we want to break the cycle
we have to break the
partitions and become
dynamic
®
© 2014 MapR Technologies 5
Understanding the Why’s
•  Isolation of resources
–  Assists in troubleshooting
–  Prevents the analytics team from impacting production
•  Maximum throughput of an application
–  Guaranteed volume (maximum): compute, memory and storage
•  Business Continuity
–  We know exactly what is backed up, when, and where
–  Difficult to perfect and to test
®
© 2014 MapR Technologies 6
Issues with Isolated Workloads
•  Segregated servers lead to under utilized hardware
–  Wasted capacity and energy
•  Complicated processes to move data to the required processing
servers
–  Operational impact, including extra monitoring
–  Time delays moving data (not real-time)
–  Troubleshooting time when there are issues
•  Difficult to thoroughly test DEV vs. QA vs. Production
–  Environments have different shapes and sizes
–  They will not have identical configurations
®
© 2014 MapR Technologies 7
Goals Moving Forward
•  Leverage all existing hardware
•  Create isolation in a different way
•  Improve production operational processes
•  Fix process of moving from DEV to QA to Production
•  Support real-time business continuity
®
© 2014 MapR Technologies 8© 2014 MapR Technologies
®
The Next “Last” Enterprise Architecture
®
© 2014 MapR Technologies 9
The Next Generation Enterprise Architecture
•  Dynamic compute resources
•  Common storage platform
•  Real-time application support
•  Flexible programming models
•  Deployment management
•  Solution based approach
•  Applications to operate a
business
* This is a pluggable architecture
Distributed
File System
Enterprise
Applications
Global Resource
Management
®
© 2014 MapR Technologies 10
Technologies That Work
Global Resource
Management
Distributed
File System
Enterprise
Applications
Mesos + Myriad
YARN
MapR-FS HDFSS3
Web
Servers
Business
Applications
®
© 2014 MapR Technologies 11
We Will Call This Architecture…
®
© 2014 MapR Technologies 12
What’s in a Name
•  The letter Z is the last letter in the English
alphabet, but Zeta is not the last letter of the
Greek alphabet
–  But this is the last generalized architecture you
will need.
•  Sixth letter of the Greek alphabet
–  Hexagon represents the 6 surrounding pieces
•  Zeta represents the number 7
–  7 total components in this architecture
–  Components work with a global resource
manager
®
© 2014 MapR Technologies 13
Origin Story of the Zeta Architecture
•  Cultivated by Jim Scott
–  Created the pretty diagrams
–  Put a nice name on it
–  Documented the concepts
•  Not really a new concept
–  Google pretty much pioneered these
technology concepts
–  They have never really discussed it
cohesively in this way
®
© 2014 MapR Technologies 14
Zeta Architecture at Google
Global Resource
Management
Distributed
File System
Enterprise
Applications
Borg & Omega
GoogleFS
HTTP
Servers
GMail
®
© 2014 MapR Technologies 15© 2014 MapR Technologies
®
Concrete Implementations
®
© 2014 MapR Technologies 16
Web Server Logs
•  Web server generates logs
•  Land on local disk
–  Logs periodically rotated
•  Shipped to other servers
•  Run jobs on logs
®
© 2014 MapR Technologies 17
Web Server Logs
•  Web server generates logs
•  Land on DFS
–  Logs still rotate
–  Logs now tolerant of a server
failure prior to rotation
–  Logs are instantaneously
available for computation
•  Run jobs on logs
–  Data locality
®
© 2014 MapR Technologies 18
Advertising Platform
®
© 2014 MapR Technologies 19
Advertising Platform - Simplified
®
© 2014 MapR Technologies 20
Advertising Platform on Zeta
®
© 2014 MapR Technologies 21© 2014 MapR Technologies
®
Business Implications
®
© 2014 MapR Technologies 22
Integration of Existing Systems
•  Use standards like NFS to connect existing
systems
•  Pluggable security models fit into your
companies current standards
•  Not everything works well in this model
–  Oracle, DB2, SQL Server, PostgreSQL, MySQL
•  They tend to not support being resource managed,
containers or other DFS
•  Applications in this architecture can still use them
•  If they start supporting these technologies then
things change
®
®
© 2014 MapR Technologies 23
Rethink the Data Center
•  All Servers
–  Run Mesos
–  Participate in the Distributed File System
•  Dynamic Allocation of Resources
–  Spin up more web servers
–  Custom Business Applications
–  Big Data Analytics
•  Data Locality
–  No more shipping data
–  Store and process the data where it was created
®
© 2014 MapR Technologies 24
Simplified Architecture
•  Less moving parts
–  Less things to go wrong
•  Better resource utilization
–  Scale any application up or down on demand
•  Common deployment model (new isolation model)
–  Repeatability between environments (dev, qa, production)
•  Shared file system
–  Get at the data anywhere in the cluster
–  Simplifies business continuity
®
© 2014 MapR Technologies 25
Business Continuity
•  Resilience
–  Redundancy
–  High Availability
–  Spare Capacity
•  Recovery
–  Snapshots
–  Disaster Recovery
•  Contingency
–  Protect against the unforeseen
–  Multisite Capability
Production
WAN
Production Research
Datacenter	
  1	
   Datacenter	
  2	
  
WAN EC2
®
© 2014 MapR Technologies 26
Platform-wide Security and Compliance
•  Authentication, Authorization, Auditing
–  Users and jobs
–  All tiers
•  Data protection
–  Wire-level encryption between servers
–  Masking
•  Regulatory Compliance
–  Automatic expiration of “old” data
–  Data locality supported by distributed file system
®
© 2014 MapR Technologies 27
Net Benefit
•  Reduced operating expenses (OPEX)
–  Better utilization of available capacity and data center space
•  Reduced capital expenses (CAPEX)
–  Less total hardware needed
•  Improves time to market
–  Streamlined deployments
–  Environments become consistent and predictable
•  Delivers a competitive advantage
–  Via platform scaling
–  Performance improvements
®
© 2014 MapR Technologies 28
Recap
•  Saves valuable time and money
•  Enables stronger business continuity capabilities
•  Google has been doing this for years
–  Real-time is the crux of everything Google does
•  Time for the rest of us to operate at Google scale
–  The technologies are there and they play together nicely
–  Process changes must occur internally to achieve this architecture
•  This approach will become the “traditional” way of thinking
–  Don’t get beat to it by your competitors
®
© 2014 MapR Technologies 29
Go Forth and Implement the Zeta Architecture
®
© 2014 MapR Technologies 30
$50M$50Min Free Training
www.mapr.com/odt
®
© 2014 MapR Technologies 31
Q&A
@kingmesal maprtech
jscott@mapr.com
Engage with us!
MapR
maprtech
mapr-technologies

More Related Content

What's hot

MapR and Cisco Make IT Better
MapR and Cisco Make IT BetterMapR and Cisco Make IT Better
MapR and Cisco Make IT BetterMapR Technologies
 
SplunkLive! Nutanix Session - Turnkey and scalable infrastructure for Splunk ...
SplunkLive! Nutanix Session - Turnkey and scalable infrastructure for Splunk ...SplunkLive! Nutanix Session - Turnkey and scalable infrastructure for Splunk ...
SplunkLive! Nutanix Session - Turnkey and scalable infrastructure for Splunk ...Splunk
 
MapR 5.2: Getting More Value from the MapR Converged Community Edition
MapR 5.2: Getting More Value from the MapR Converged Community EditionMapR 5.2: Getting More Value from the MapR Converged Community Edition
MapR 5.2: Getting More Value from the MapR Converged Community EditionMapR Technologies
 
How to Integrate Hyperconverged Systems with Existing SANs
How to Integrate Hyperconverged Systems with Existing SANsHow to Integrate Hyperconverged Systems with Existing SANs
How to Integrate Hyperconverged Systems with Existing SANsDataCore Software
 
What's the Hadoop-la about Kubernetes?
What's the Hadoop-la about Kubernetes?What's the Hadoop-la about Kubernetes?
What's the Hadoop-la about Kubernetes?DataWorks Summit
 
Sahara presentation latest - Codemotion Rome 2015
Sahara presentation latest - Codemotion Rome 2015Sahara presentation latest - Codemotion Rome 2015
Sahara presentation latest - Codemotion Rome 2015Codemotion
 
Apache Kudu: Technical Deep Dive


Apache Kudu: Technical Deep Dive

Apache Kudu: Technical Deep Dive


Apache Kudu: Technical Deep Dive

Cloudera, Inc.
 
Manage Microservices & Fast Data Systems on One Platform w/ DC/OS
Manage Microservices & Fast Data Systems on One Platform w/ DC/OSManage Microservices & Fast Data Systems on One Platform w/ DC/OS
Manage Microservices & Fast Data Systems on One Platform w/ DC/OSMesosphere Inc.
 
Back to School - St. Louis Hadoop Meetup September 2016
Back to School - St. Louis Hadoop Meetup September 2016Back to School - St. Louis Hadoop Meetup September 2016
Back to School - St. Louis Hadoop Meetup September 2016Adam Doyle
 
Hadoop Virtualization - Intel White Paper
Hadoop Virtualization - Intel White PaperHadoop Virtualization - Intel White Paper
Hadoop Virtualization - Intel White PaperBlueData, Inc.
 
Building Enterprise Clouds - Key Considerations and Strategies - RED HAT
Building Enterprise Clouds - Key Considerations and Strategies - RED HATBuilding Enterprise Clouds - Key Considerations and Strategies - RED HAT
Building Enterprise Clouds - Key Considerations and Strategies - RED HATFadi Semaan
 
Free Servers to Build Big Data System on: Bing’s Approach
Free Servers to Build Big Data System on: Bing’s ApproachFree Servers to Build Big Data System on: Bing’s Approach
Free Servers to Build Big Data System on: Bing’s ApproachDataWorks Summit
 
Provisioning Big Data Platform using Cloudbreak & Ambari
Provisioning Big Data Platform using Cloudbreak & AmbariProvisioning Big Data Platform using Cloudbreak & Ambari
Provisioning Big Data Platform using Cloudbreak & AmbariDataWorks Summit/Hadoop Summit
 
Wrangling Customer Usage Data with Hadoop
Wrangling Customer Usage Data with HadoopWrangling Customer Usage Data with Hadoop
Wrangling Customer Usage Data with HadoopDataWorks Summit
 
Introduction to cloud computing
Introduction to cloud computingIntroduction to cloud computing
Introduction to cloud computingPUBLEAD (R)
 
Key Database Criteria for Cloud Applications
Key Database Criteria for Cloud ApplicationsKey Database Criteria for Cloud Applications
Key Database Criteria for Cloud ApplicationsNuoDB
 
Extending Twitter's Data Platform to Google Cloud
Extending Twitter's Data Platform to Google CloudExtending Twitter's Data Platform to Google Cloud
Extending Twitter's Data Platform to Google CloudDataWorks Summit
 
Part 2: Cloudera’s Operational Database: Unlocking New Benefits in the Cloud
Part 2: Cloudera’s Operational Database: Unlocking New Benefits in the CloudPart 2: Cloudera’s Operational Database: Unlocking New Benefits in the Cloud
Part 2: Cloudera’s Operational Database: Unlocking New Benefits in the CloudCloudera, Inc.
 
IDC Nutanix - Hyperconvergence and the Pulling Forces in the Datacenter
IDC Nutanix - Hyperconvergence and the Pulling Forces in the DatacenterIDC Nutanix - Hyperconvergence and the Pulling Forces in the Datacenter
IDC Nutanix - Hyperconvergence and the Pulling Forces in the DatacenterNEXTtour
 
Achieving cloud scale with microservices based applications on azure
Achieving cloud scale with microservices based applications on azureAchieving cloud scale with microservices based applications on azure
Achieving cloud scale with microservices based applications on azureUtkarsh Pandey
 

What's hot (20)

MapR and Cisco Make IT Better
MapR and Cisco Make IT BetterMapR and Cisco Make IT Better
MapR and Cisco Make IT Better
 
SplunkLive! Nutanix Session - Turnkey and scalable infrastructure for Splunk ...
SplunkLive! Nutanix Session - Turnkey and scalable infrastructure for Splunk ...SplunkLive! Nutanix Session - Turnkey and scalable infrastructure for Splunk ...
SplunkLive! Nutanix Session - Turnkey and scalable infrastructure for Splunk ...
 
MapR 5.2: Getting More Value from the MapR Converged Community Edition
MapR 5.2: Getting More Value from the MapR Converged Community EditionMapR 5.2: Getting More Value from the MapR Converged Community Edition
MapR 5.2: Getting More Value from the MapR Converged Community Edition
 
How to Integrate Hyperconverged Systems with Existing SANs
How to Integrate Hyperconverged Systems with Existing SANsHow to Integrate Hyperconverged Systems with Existing SANs
How to Integrate Hyperconverged Systems with Existing SANs
 
What's the Hadoop-la about Kubernetes?
What's the Hadoop-la about Kubernetes?What's the Hadoop-la about Kubernetes?
What's the Hadoop-la about Kubernetes?
 
Sahara presentation latest - Codemotion Rome 2015
Sahara presentation latest - Codemotion Rome 2015Sahara presentation latest - Codemotion Rome 2015
Sahara presentation latest - Codemotion Rome 2015
 
Apache Kudu: Technical Deep Dive


Apache Kudu: Technical Deep Dive

Apache Kudu: Technical Deep Dive


Apache Kudu: Technical Deep Dive


 
Manage Microservices & Fast Data Systems on One Platform w/ DC/OS
Manage Microservices & Fast Data Systems on One Platform w/ DC/OSManage Microservices & Fast Data Systems on One Platform w/ DC/OS
Manage Microservices & Fast Data Systems on One Platform w/ DC/OS
 
Back to School - St. Louis Hadoop Meetup September 2016
Back to School - St. Louis Hadoop Meetup September 2016Back to School - St. Louis Hadoop Meetup September 2016
Back to School - St. Louis Hadoop Meetup September 2016
 
Hadoop Virtualization - Intel White Paper
Hadoop Virtualization - Intel White PaperHadoop Virtualization - Intel White Paper
Hadoop Virtualization - Intel White Paper
 
Building Enterprise Clouds - Key Considerations and Strategies - RED HAT
Building Enterprise Clouds - Key Considerations and Strategies - RED HATBuilding Enterprise Clouds - Key Considerations and Strategies - RED HAT
Building Enterprise Clouds - Key Considerations and Strategies - RED HAT
 
Free Servers to Build Big Data System on: Bing’s Approach
Free Servers to Build Big Data System on: Bing’s ApproachFree Servers to Build Big Data System on: Bing’s Approach
Free Servers to Build Big Data System on: Bing’s Approach
 
Provisioning Big Data Platform using Cloudbreak & Ambari
Provisioning Big Data Platform using Cloudbreak & AmbariProvisioning Big Data Platform using Cloudbreak & Ambari
Provisioning Big Data Platform using Cloudbreak & Ambari
 
Wrangling Customer Usage Data with Hadoop
Wrangling Customer Usage Data with HadoopWrangling Customer Usage Data with Hadoop
Wrangling Customer Usage Data with Hadoop
 
Introduction to cloud computing
Introduction to cloud computingIntroduction to cloud computing
Introduction to cloud computing
 
Key Database Criteria for Cloud Applications
Key Database Criteria for Cloud ApplicationsKey Database Criteria for Cloud Applications
Key Database Criteria for Cloud Applications
 
Extending Twitter's Data Platform to Google Cloud
Extending Twitter's Data Platform to Google CloudExtending Twitter's Data Platform to Google Cloud
Extending Twitter's Data Platform to Google Cloud
 
Part 2: Cloudera’s Operational Database: Unlocking New Benefits in the Cloud
Part 2: Cloudera’s Operational Database: Unlocking New Benefits in the CloudPart 2: Cloudera’s Operational Database: Unlocking New Benefits in the Cloud
Part 2: Cloudera’s Operational Database: Unlocking New Benefits in the Cloud
 
IDC Nutanix - Hyperconvergence and the Pulling Forces in the Datacenter
IDC Nutanix - Hyperconvergence and the Pulling Forces in the DatacenterIDC Nutanix - Hyperconvergence and the Pulling Forces in the Datacenter
IDC Nutanix - Hyperconvergence and the Pulling Forces in the Datacenter
 
Achieving cloud scale with microservices based applications on azure
Achieving cloud scale with microservices based applications on azureAchieving cloud scale with microservices based applications on azure
Achieving cloud scale with microservices based applications on azure
 

Viewers also liked

Porting your hadoop app to horton works hdp
Porting your hadoop app to horton works hdpPorting your hadoop app to horton works hdp
Porting your hadoop app to horton works hdpMark Kerzner
 
Introduction to pig
Introduction to pigIntroduction to pig
Introduction to pigRavi Mutyala
 
Night owl by Boyd Meyer of PROS
Night owl by Boyd Meyer of PROS Night owl by Boyd Meyer of PROS
Night owl by Boyd Meyer of PROS Mark Kerzner
 
Nutch + Hadoop scaled, for crawling protected web sites (hint: Selenium)
Nutch + Hadoop scaled, for crawling protected web sites (hint: Selenium)Nutch + Hadoop scaled, for crawling protected web sites (hint: Selenium)
Nutch + Hadoop scaled, for crawling protected web sites (hint: Selenium)Mark Kerzner
 
Hadoop as a service presented by Ajay Jha at Houston Hadoop Meetup
Hadoop as a service presented by Ajay Jha at Houston Hadoop MeetupHadoop as a service presented by Ajay Jha at Houston Hadoop Meetup
Hadoop as a service presented by Ajay Jha at Houston Hadoop MeetupMark Kerzner
 
Oil and gas big data edition
Oil and gas  big data editionOil and gas  big data edition
Oil and gas big data editionMark Kerzner
 
Launching your career in Big Data
Launching your career in Big DataLaunching your career in Big Data
Launching your career in Big DataSujee Maniyam
 
Intro to Apache Spark by Marco Vasquez
Intro to Apache Spark by Marco VasquezIntro to Apache Spark by Marco Vasquez
Intro to Apache Spark by Marco VasquezMapR Technologies
 
Big data real time architectures
Big data real time architecturesBig data real time architectures
Big data real time architecturesDaniel Marcous
 
Joe Witt presentation on Apache NiFi
Joe Witt presentation on Apache NiFiJoe Witt presentation on Apache NiFi
Joe Witt presentation on Apache NiFiMark Kerzner
 

Viewers also liked (13)

Porting your hadoop app to horton works hdp
Porting your hadoop app to horton works hdpPorting your hadoop app to horton works hdp
Porting your hadoop app to horton works hdp
 
Introduction to pig
Introduction to pigIntroduction to pig
Introduction to pig
 
Night owl by Boyd Meyer of PROS
Night owl by Boyd Meyer of PROS Night owl by Boyd Meyer of PROS
Night owl by Boyd Meyer of PROS
 
Nutch + Hadoop scaled, for crawling protected web sites (hint: Selenium)
Nutch + Hadoop scaled, for crawling protected web sites (hint: Selenium)Nutch + Hadoop scaled, for crawling protected web sites (hint: Selenium)
Nutch + Hadoop scaled, for crawling protected web sites (hint: Selenium)
 
Cloudera search
Cloudera searchCloudera search
Cloudera search
 
Hadoop as a service presented by Ajay Jha at Houston Hadoop Meetup
Hadoop as a service presented by Ajay Jha at Houston Hadoop MeetupHadoop as a service presented by Ajay Jha at Houston Hadoop Meetup
Hadoop as a service presented by Ajay Jha at Houston Hadoop Meetup
 
Oil and gas big data edition
Oil and gas  big data editionOil and gas  big data edition
Oil and gas big data edition
 
Launching your career in Big Data
Launching your career in Big DataLaunching your career in Big Data
Launching your career in Big Data
 
Hadoop to spark_v2
Hadoop to spark_v2Hadoop to spark_v2
Hadoop to spark_v2
 
Intro to Apache Spark by Marco Vasquez
Intro to Apache Spark by Marco VasquezIntro to Apache Spark by Marco Vasquez
Intro to Apache Spark by Marco Vasquez
 
SHMcloud vision
SHMcloud visionSHMcloud vision
SHMcloud vision
 
Big data real time architectures
Big data real time architecturesBig data real time architectures
Big data real time architectures
 
Joe Witt presentation on Apache NiFi
Joe Witt presentation on Apache NiFiJoe Witt presentation on Apache NiFi
Joe Witt presentation on Apache NiFi
 

Similar to Zeta Architecture Overview

Next Generation Enterprise Architecture
Next Generation Enterprise ArchitectureNext Generation Enterprise Architecture
Next Generation Enterprise ArchitectureMapR Technologies
 
Real time-hadoop
Real time-hadoopReal time-hadoop
Real time-hadoopTed Dunning
 
Redefining End-to-End Monitoring: The Foundation - High-Performance Architect...
Redefining End-to-End Monitoring: The Foundation - High-Performance Architect...Redefining End-to-End Monitoring: The Foundation - High-Performance Architect...
Redefining End-to-End Monitoring: The Foundation - High-Performance Architect...SL Corporation
 
MapR on Azure: Getting Value from Big Data in the Cloud -
MapR on Azure: Getting Value from Big Data in the Cloud -MapR on Azure: Getting Value from Big Data in the Cloud -
MapR on Azure: Getting Value from Big Data in the Cloud -MapR Technologies
 
Managing Performance in the Cloud
Managing Performance in the CloudManaging Performance in the Cloud
Managing Performance in the CloudDevOpsGroup
 
Integrating Hadoop into your enterprise IT environment
Integrating Hadoop into your enterprise IT environmentIntegrating Hadoop into your enterprise IT environment
Integrating Hadoop into your enterprise IT environmentMapR Technologies
 
VMworld 2013: Separating Cloud Hype from Reality in Healthcare – a Real-Life ...
VMworld 2013: Separating Cloud Hype from Reality in Healthcare – a Real-Life ...VMworld 2013: Separating Cloud Hype from Reality in Healthcare – a Real-Life ...
VMworld 2013: Separating Cloud Hype from Reality in Healthcare – a Real-Life ...VMworld
 
Apache Hadoop YARN - The Future of Data Processing with Hadoop
Apache Hadoop YARN - The Future of Data Processing with HadoopApache Hadoop YARN - The Future of Data Processing with Hadoop
Apache Hadoop YARN - The Future of Data Processing with HadoopHortonworks
 
MapR-DB – The First In-Hadoop Document Database
MapR-DB – The First In-Hadoop Document DatabaseMapR-DB – The First In-Hadoop Document Database
MapR-DB – The First In-Hadoop Document DatabaseMapR Technologies
 
Advanced Spark and TensorFlow Meetup - Dec 12 2017 - Dong Meng, MapR + Kubern...
Advanced Spark and TensorFlow Meetup - Dec 12 2017 - Dong Meng, MapR + Kubern...Advanced Spark and TensorFlow Meetup - Dec 12 2017 - Dong Meng, MapR + Kubern...
Advanced Spark and TensorFlow Meetup - Dec 12 2017 - Dong Meng, MapR + Kubern...Chris Fregly
 
Real-time Hadoop: The Ideal Messaging System for Hadoop
Real-time Hadoop: The Ideal Messaging System for Hadoop Real-time Hadoop: The Ideal Messaging System for Hadoop
Real-time Hadoop: The Ideal Messaging System for Hadoop DataWorks Summit/Hadoop Summit
 
Designing your XenApp 7.5 Environment
Designing your XenApp 7.5 EnvironmentDesigning your XenApp 7.5 Environment
Designing your XenApp 7.5 EnvironmentDavid McGeough
 
The Need For Speed - Strategies to Modernize Your Data Center
The Need For Speed - Strategies to Modernize Your Data CenterThe Need For Speed - Strategies to Modernize Your Data Center
The Need For Speed - Strategies to Modernize Your Data CenterEDB
 
CEP - simplified streaming architecture - Strata Singapore 2016
CEP - simplified streaming architecture - Strata Singapore 2016CEP - simplified streaming architecture - Strata Singapore 2016
CEP - simplified streaming architecture - Strata Singapore 2016Mathieu Dumoulin
 
Drill into Drill – How Providing Flexibility and Performance is Possible
Drill into Drill – How Providing Flexibility and Performance is PossibleDrill into Drill – How Providing Flexibility and Performance is Possible
Drill into Drill – How Providing Flexibility and Performance is PossibleMapR Technologies
 
Postgres for the Future
Postgres for the FuturePostgres for the Future
Postgres for the FutureEDB
 
Multidisziplinäre Analyseanwendungen auf einer gemeinsamen Datenplattform ers...
Multidisziplinäre Analyseanwendungen auf einer gemeinsamen Datenplattform ers...Multidisziplinäre Analyseanwendungen auf einer gemeinsamen Datenplattform ers...
Multidisziplinäre Analyseanwendungen auf einer gemeinsamen Datenplattform ers...Cloudera, Inc.
 

Similar to Zeta Architecture Overview (20)

Next Generation Enterprise Architecture
Next Generation Enterprise ArchitectureNext Generation Enterprise Architecture
Next Generation Enterprise Architecture
 
Keys for Success from Streams to Queries
Keys for Success from Streams to QueriesKeys for Success from Streams to Queries
Keys for Success from Streams to Queries
 
Real time-hadoop
Real time-hadoopReal time-hadoop
Real time-hadoop
 
Redefining End-to-End Monitoring: The Foundation - High-Performance Architect...
Redefining End-to-End Monitoring: The Foundation - High-Performance Architect...Redefining End-to-End Monitoring: The Foundation - High-Performance Architect...
Redefining End-to-End Monitoring: The Foundation - High-Performance Architect...
 
MapR on Azure: Getting Value from Big Data in the Cloud -
MapR on Azure: Getting Value from Big Data in the Cloud -MapR on Azure: Getting Value from Big Data in the Cloud -
MapR on Azure: Getting Value from Big Data in the Cloud -
 
Managing Performance in the Cloud
Managing Performance in the CloudManaging Performance in the Cloud
Managing Performance in the Cloud
 
Integrating Hadoop into your enterprise IT environment
Integrating Hadoop into your enterprise IT environmentIntegrating Hadoop into your enterprise IT environment
Integrating Hadoop into your enterprise IT environment
 
VMworld 2013: Separating Cloud Hype from Reality in Healthcare – a Real-Life ...
VMworld 2013: Separating Cloud Hype from Reality in Healthcare – a Real-Life ...VMworld 2013: Separating Cloud Hype from Reality in Healthcare – a Real-Life ...
VMworld 2013: Separating Cloud Hype from Reality in Healthcare – a Real-Life ...
 
Apache Hadoop YARN - The Future of Data Processing with Hadoop
Apache Hadoop YARN - The Future of Data Processing with HadoopApache Hadoop YARN - The Future of Data Processing with Hadoop
Apache Hadoop YARN - The Future of Data Processing with Hadoop
 
MapR-DB – The First In-Hadoop Document Database
MapR-DB – The First In-Hadoop Document DatabaseMapR-DB – The First In-Hadoop Document Database
MapR-DB – The First In-Hadoop Document Database
 
Advanced Spark and TensorFlow Meetup - Dec 12 2017 - Dong Meng, MapR + Kubern...
Advanced Spark and TensorFlow Meetup - Dec 12 2017 - Dong Meng, MapR + Kubern...Advanced Spark and TensorFlow Meetup - Dec 12 2017 - Dong Meng, MapR + Kubern...
Advanced Spark and TensorFlow Meetup - Dec 12 2017 - Dong Meng, MapR + Kubern...
 
Real-time Hadoop: The Ideal Messaging System for Hadoop
Real-time Hadoop: The Ideal Messaging System for Hadoop Real-time Hadoop: The Ideal Messaging System for Hadoop
Real-time Hadoop: The Ideal Messaging System for Hadoop
 
Designing your XenApp 7.5 Environment
Designing your XenApp 7.5 EnvironmentDesigning your XenApp 7.5 Environment
Designing your XenApp 7.5 Environment
 
Rev Up Your HPC Engine
Rev Up Your HPC EngineRev Up Your HPC Engine
Rev Up Your HPC Engine
 
The Need For Speed - Strategies to Modernize Your Data Center
The Need For Speed - Strategies to Modernize Your Data CenterThe Need For Speed - Strategies to Modernize Your Data Center
The Need For Speed - Strategies to Modernize Your Data Center
 
CEP - simplified streaming architecture - Strata Singapore 2016
CEP - simplified streaming architecture - Strata Singapore 2016CEP - simplified streaming architecture - Strata Singapore 2016
CEP - simplified streaming architecture - Strata Singapore 2016
 
Drill into Drill – How Providing Flexibility and Performance is Possible
Drill into Drill – How Providing Flexibility and Performance is PossibleDrill into Drill – How Providing Flexibility and Performance is Possible
Drill into Drill – How Providing Flexibility and Performance is Possible
 
Postgres for the Future
Postgres for the FuturePostgres for the Future
Postgres for the Future
 
Multidisziplinäre Analyseanwendungen auf einer gemeinsamen Datenplattform ers...
Multidisziplinäre Analyseanwendungen auf einer gemeinsamen Datenplattform ers...Multidisziplinäre Analyseanwendungen auf einer gemeinsamen Datenplattform ers...
Multidisziplinäre Analyseanwendungen auf einer gemeinsamen Datenplattform ers...
 
MapR & Skytree:
MapR & Skytree: MapR & Skytree:
MapR & Skytree:
 

More from MapR Technologies

Converging your data landscape
Converging your data landscapeConverging your data landscape
Converging your data landscapeMapR Technologies
 
ML Workshop 2: Machine Learning Model Comparison & Evaluation
ML Workshop 2: Machine Learning Model Comparison & EvaluationML Workshop 2: Machine Learning Model Comparison & Evaluation
ML Workshop 2: Machine Learning Model Comparison & EvaluationMapR Technologies
 
Self-Service Data Science for Leveraging ML & AI on All of Your Data
Self-Service Data Science for Leveraging ML & AI on All of Your DataSelf-Service Data Science for Leveraging ML & AI on All of Your Data
Self-Service Data Science for Leveraging ML & AI on All of Your DataMapR Technologies
 
Enabling Real-Time Business with Change Data Capture
Enabling Real-Time Business with Change Data CaptureEnabling Real-Time Business with Change Data Capture
Enabling Real-Time Business with Change Data CaptureMapR Technologies
 
Machine Learning for Chickens, Autonomous Driving and a 3-year-old Who Won’t ...
Machine Learning for Chickens, Autonomous Driving and a 3-year-old Who Won’t ...Machine Learning for Chickens, Autonomous Driving and a 3-year-old Who Won’t ...
Machine Learning for Chickens, Autonomous Driving and a 3-year-old Who Won’t ...MapR Technologies
 
ML Workshop 1: A New Architecture for Machine Learning Logistics
ML Workshop 1: A New Architecture for Machine Learning LogisticsML Workshop 1: A New Architecture for Machine Learning Logistics
ML Workshop 1: A New Architecture for Machine Learning LogisticsMapR Technologies
 
Machine Learning Success: The Key to Easier Model Management
Machine Learning Success: The Key to Easier Model ManagementMachine Learning Success: The Key to Easier Model Management
Machine Learning Success: The Key to Easier Model ManagementMapR Technologies
 
Data Warehouse Modernization: Accelerating Time-To-Action
Data Warehouse Modernization: Accelerating Time-To-Action Data Warehouse Modernization: Accelerating Time-To-Action
Data Warehouse Modernization: Accelerating Time-To-Action MapR Technologies
 
Live Tutorial – Streaming Real-Time Events Using Apache APIs
Live Tutorial – Streaming Real-Time Events Using Apache APIsLive Tutorial – Streaming Real-Time Events Using Apache APIs
Live Tutorial – Streaming Real-Time Events Using Apache APIsMapR Technologies
 
Bringing Structure, Scalability, and Services to Cloud-Scale Storage
Bringing Structure, Scalability, and Services to Cloud-Scale StorageBringing Structure, Scalability, and Services to Cloud-Scale Storage
Bringing Structure, Scalability, and Services to Cloud-Scale StorageMapR Technologies
 
Live Machine Learning Tutorial: Churn Prediction
Live Machine Learning Tutorial: Churn PredictionLive Machine Learning Tutorial: Churn Prediction
Live Machine Learning Tutorial: Churn PredictionMapR Technologies
 
An Introduction to the MapR Converged Data Platform
An Introduction to the MapR Converged Data PlatformAn Introduction to the MapR Converged Data Platform
An Introduction to the MapR Converged Data PlatformMapR Technologies
 
How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...
How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...
How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...MapR Technologies
 
Best Practices for Data Convergence in Healthcare
Best Practices for Data Convergence in HealthcareBest Practices for Data Convergence in Healthcare
Best Practices for Data Convergence in HealthcareMapR Technologies
 
Geo-Distributed Big Data and Analytics
Geo-Distributed Big Data and AnalyticsGeo-Distributed Big Data and Analytics
Geo-Distributed Big Data and AnalyticsMapR Technologies
 
MapR Product Update - Spring 2017
MapR Product Update - Spring 2017MapR Product Update - Spring 2017
MapR Product Update - Spring 2017MapR Technologies
 
3 Benefits of Multi-Temperature Data Management for Data Analytics
3 Benefits of Multi-Temperature Data Management for Data Analytics3 Benefits of Multi-Temperature Data Management for Data Analytics
3 Benefits of Multi-Temperature Data Management for Data AnalyticsMapR Technologies
 
Evolving from RDBMS to NoSQL + SQL
Evolving from RDBMS to NoSQL + SQLEvolving from RDBMS to NoSQL + SQL
Evolving from RDBMS to NoSQL + SQLMapR Technologies
 
Evolving Beyond the Data Lake: A Story of Wind and Rain
Evolving Beyond the Data Lake: A Story of Wind and RainEvolving Beyond the Data Lake: A Story of Wind and Rain
Evolving Beyond the Data Lake: A Story of Wind and RainMapR Technologies
 
Open Source Innovations in the MapR Ecosystem Pack 2.0
Open Source Innovations in the MapR Ecosystem Pack 2.0Open Source Innovations in the MapR Ecosystem Pack 2.0
Open Source Innovations in the MapR Ecosystem Pack 2.0MapR Technologies
 

More from MapR Technologies (20)

Converging your data landscape
Converging your data landscapeConverging your data landscape
Converging your data landscape
 
ML Workshop 2: Machine Learning Model Comparison & Evaluation
ML Workshop 2: Machine Learning Model Comparison & EvaluationML Workshop 2: Machine Learning Model Comparison & Evaluation
ML Workshop 2: Machine Learning Model Comparison & Evaluation
 
Self-Service Data Science for Leveraging ML & AI on All of Your Data
Self-Service Data Science for Leveraging ML & AI on All of Your DataSelf-Service Data Science for Leveraging ML & AI on All of Your Data
Self-Service Data Science for Leveraging ML & AI on All of Your Data
 
Enabling Real-Time Business with Change Data Capture
Enabling Real-Time Business with Change Data CaptureEnabling Real-Time Business with Change Data Capture
Enabling Real-Time Business with Change Data Capture
 
Machine Learning for Chickens, Autonomous Driving and a 3-year-old Who Won’t ...
Machine Learning for Chickens, Autonomous Driving and a 3-year-old Who Won’t ...Machine Learning for Chickens, Autonomous Driving and a 3-year-old Who Won’t ...
Machine Learning for Chickens, Autonomous Driving and a 3-year-old Who Won’t ...
 
ML Workshop 1: A New Architecture for Machine Learning Logistics
ML Workshop 1: A New Architecture for Machine Learning LogisticsML Workshop 1: A New Architecture for Machine Learning Logistics
ML Workshop 1: A New Architecture for Machine Learning Logistics
 
Machine Learning Success: The Key to Easier Model Management
Machine Learning Success: The Key to Easier Model ManagementMachine Learning Success: The Key to Easier Model Management
Machine Learning Success: The Key to Easier Model Management
 
Data Warehouse Modernization: Accelerating Time-To-Action
Data Warehouse Modernization: Accelerating Time-To-Action Data Warehouse Modernization: Accelerating Time-To-Action
Data Warehouse Modernization: Accelerating Time-To-Action
 
Live Tutorial – Streaming Real-Time Events Using Apache APIs
Live Tutorial – Streaming Real-Time Events Using Apache APIsLive Tutorial – Streaming Real-Time Events Using Apache APIs
Live Tutorial – Streaming Real-Time Events Using Apache APIs
 
Bringing Structure, Scalability, and Services to Cloud-Scale Storage
Bringing Structure, Scalability, and Services to Cloud-Scale StorageBringing Structure, Scalability, and Services to Cloud-Scale Storage
Bringing Structure, Scalability, and Services to Cloud-Scale Storage
 
Live Machine Learning Tutorial: Churn Prediction
Live Machine Learning Tutorial: Churn PredictionLive Machine Learning Tutorial: Churn Prediction
Live Machine Learning Tutorial: Churn Prediction
 
An Introduction to the MapR Converged Data Platform
An Introduction to the MapR Converged Data PlatformAn Introduction to the MapR Converged Data Platform
An Introduction to the MapR Converged Data Platform
 
How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...
How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...
How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...
 
Best Practices for Data Convergence in Healthcare
Best Practices for Data Convergence in HealthcareBest Practices for Data Convergence in Healthcare
Best Practices for Data Convergence in Healthcare
 
Geo-Distributed Big Data and Analytics
Geo-Distributed Big Data and AnalyticsGeo-Distributed Big Data and Analytics
Geo-Distributed Big Data and Analytics
 
MapR Product Update - Spring 2017
MapR Product Update - Spring 2017MapR Product Update - Spring 2017
MapR Product Update - Spring 2017
 
3 Benefits of Multi-Temperature Data Management for Data Analytics
3 Benefits of Multi-Temperature Data Management for Data Analytics3 Benefits of Multi-Temperature Data Management for Data Analytics
3 Benefits of Multi-Temperature Data Management for Data Analytics
 
Evolving from RDBMS to NoSQL + SQL
Evolving from RDBMS to NoSQL + SQLEvolving from RDBMS to NoSQL + SQL
Evolving from RDBMS to NoSQL + SQL
 
Evolving Beyond the Data Lake: A Story of Wind and Rain
Evolving Beyond the Data Lake: A Story of Wind and RainEvolving Beyond the Data Lake: A Story of Wind and Rain
Evolving Beyond the Data Lake: A Story of Wind and Rain
 
Open Source Innovations in the MapR Ecosystem Pack 2.0
Open Source Innovations in the MapR Ecosystem Pack 2.0Open Source Innovations in the MapR Ecosystem Pack 2.0
Open Source Innovations in the MapR Ecosystem Pack 2.0
 

Recently uploaded

Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 
Benefits Of Flutter Compared To Other Frameworks
Benefits Of Flutter Compared To Other FrameworksBenefits Of Flutter Compared To Other Frameworks
Benefits Of Flutter Compared To Other FrameworksSoftradix Technologies
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationSafe Software
 
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024BookNet Canada
 
Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Allon Mureinik
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationSafe Software
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticscarlostorres15106
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationMichael W. Hawkins
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxKatpro Technologies
 
Understanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitectureUnderstanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitecturePixlogix Infotech
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsEnterprise Knowledge
 
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | DelhiFULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhisoniya singh
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsMemoori
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 3652toLead Limited
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Paola De la Torre
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsMark Billinghurst
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Alan Dix
 

Recently uploaded (20)

Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
Benefits Of Flutter Compared To Other Frameworks
Benefits Of Flutter Compared To Other FrameworksBenefits Of Flutter Compared To Other Frameworks
Benefits Of Flutter Compared To Other Frameworks
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
 
Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
 
Understanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitectureUnderstanding the Laravel MVC Architecture
Understanding the Laravel MVC Architecture
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI Solutions
 
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | DelhiFULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial Buildings
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR Systems
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
 

Zeta Architecture Overview

  • 1. ® © 2014 MapR Technologies 1 ® © 2014 MapR Technologies Zeta Architecture Jim Scott – Director, Enterprise Strategy & Architecture Houston - March 25, 2015
  • 2. ® © 2014 MapR Technologies 2 Agenda •  Current State –  History –  Moving Forward •  The Next Enterprise Architecture •  Business Implications •  Concrete Implementations
  • 3. ® © 2014 MapR Technologies 3© 2014 MapR Technologies ® Current State
  • 4. ® © 2014 MapR Technologies 4 Study History to Prepare for the Future •  A data center was built •  The servers were statically partitioned •  If we want to break the cycle we have to break the partitions and become dynamic
  • 5. ® © 2014 MapR Technologies 5 Understanding the Why’s •  Isolation of resources –  Assists in troubleshooting –  Prevents the analytics team from impacting production •  Maximum throughput of an application –  Guaranteed volume (maximum): compute, memory and storage •  Business Continuity –  We know exactly what is backed up, when, and where –  Difficult to perfect and to test
  • 6. ® © 2014 MapR Technologies 6 Issues with Isolated Workloads •  Segregated servers lead to under utilized hardware –  Wasted capacity and energy •  Complicated processes to move data to the required processing servers –  Operational impact, including extra monitoring –  Time delays moving data (not real-time) –  Troubleshooting time when there are issues •  Difficult to thoroughly test DEV vs. QA vs. Production –  Environments have different shapes and sizes –  They will not have identical configurations
  • 7. ® © 2014 MapR Technologies 7 Goals Moving Forward •  Leverage all existing hardware •  Create isolation in a different way •  Improve production operational processes •  Fix process of moving from DEV to QA to Production •  Support real-time business continuity
  • 8. ® © 2014 MapR Technologies 8© 2014 MapR Technologies ® The Next “Last” Enterprise Architecture
  • 9. ® © 2014 MapR Technologies 9 The Next Generation Enterprise Architecture •  Dynamic compute resources •  Common storage platform •  Real-time application support •  Flexible programming models •  Deployment management •  Solution based approach •  Applications to operate a business * This is a pluggable architecture Distributed File System Enterprise Applications Global Resource Management
  • 10. ® © 2014 MapR Technologies 10 Technologies That Work Global Resource Management Distributed File System Enterprise Applications Mesos + Myriad YARN MapR-FS HDFSS3 Web Servers Business Applications
  • 11. ® © 2014 MapR Technologies 11 We Will Call This Architecture…
  • 12. ® © 2014 MapR Technologies 12 What’s in a Name •  The letter Z is the last letter in the English alphabet, but Zeta is not the last letter of the Greek alphabet –  But this is the last generalized architecture you will need. •  Sixth letter of the Greek alphabet –  Hexagon represents the 6 surrounding pieces •  Zeta represents the number 7 –  7 total components in this architecture –  Components work with a global resource manager
  • 13. ® © 2014 MapR Technologies 13 Origin Story of the Zeta Architecture •  Cultivated by Jim Scott –  Created the pretty diagrams –  Put a nice name on it –  Documented the concepts •  Not really a new concept –  Google pretty much pioneered these technology concepts –  They have never really discussed it cohesively in this way
  • 14. ® © 2014 MapR Technologies 14 Zeta Architecture at Google Global Resource Management Distributed File System Enterprise Applications Borg & Omega GoogleFS HTTP Servers GMail
  • 15. ® © 2014 MapR Technologies 15© 2014 MapR Technologies ® Concrete Implementations
  • 16. ® © 2014 MapR Technologies 16 Web Server Logs •  Web server generates logs •  Land on local disk –  Logs periodically rotated •  Shipped to other servers •  Run jobs on logs
  • 17. ® © 2014 MapR Technologies 17 Web Server Logs •  Web server generates logs •  Land on DFS –  Logs still rotate –  Logs now tolerant of a server failure prior to rotation –  Logs are instantaneously available for computation •  Run jobs on logs –  Data locality
  • 18. ® © 2014 MapR Technologies 18 Advertising Platform
  • 19. ® © 2014 MapR Technologies 19 Advertising Platform - Simplified
  • 20. ® © 2014 MapR Technologies 20 Advertising Platform on Zeta
  • 21. ® © 2014 MapR Technologies 21© 2014 MapR Technologies ® Business Implications
  • 22. ® © 2014 MapR Technologies 22 Integration of Existing Systems •  Use standards like NFS to connect existing systems •  Pluggable security models fit into your companies current standards •  Not everything works well in this model –  Oracle, DB2, SQL Server, PostgreSQL, MySQL •  They tend to not support being resource managed, containers or other DFS •  Applications in this architecture can still use them •  If they start supporting these technologies then things change ®
  • 23. ® © 2014 MapR Technologies 23 Rethink the Data Center •  All Servers –  Run Mesos –  Participate in the Distributed File System •  Dynamic Allocation of Resources –  Spin up more web servers –  Custom Business Applications –  Big Data Analytics •  Data Locality –  No more shipping data –  Store and process the data where it was created
  • 24. ® © 2014 MapR Technologies 24 Simplified Architecture •  Less moving parts –  Less things to go wrong •  Better resource utilization –  Scale any application up or down on demand •  Common deployment model (new isolation model) –  Repeatability between environments (dev, qa, production) •  Shared file system –  Get at the data anywhere in the cluster –  Simplifies business continuity
  • 25. ® © 2014 MapR Technologies 25 Business Continuity •  Resilience –  Redundancy –  High Availability –  Spare Capacity •  Recovery –  Snapshots –  Disaster Recovery •  Contingency –  Protect against the unforeseen –  Multisite Capability Production WAN Production Research Datacenter  1   Datacenter  2   WAN EC2
  • 26. ® © 2014 MapR Technologies 26 Platform-wide Security and Compliance •  Authentication, Authorization, Auditing –  Users and jobs –  All tiers •  Data protection –  Wire-level encryption between servers –  Masking •  Regulatory Compliance –  Automatic expiration of “old” data –  Data locality supported by distributed file system
  • 27. ® © 2014 MapR Technologies 27 Net Benefit •  Reduced operating expenses (OPEX) –  Better utilization of available capacity and data center space •  Reduced capital expenses (CAPEX) –  Less total hardware needed •  Improves time to market –  Streamlined deployments –  Environments become consistent and predictable •  Delivers a competitive advantage –  Via platform scaling –  Performance improvements
  • 28. ® © 2014 MapR Technologies 28 Recap •  Saves valuable time and money •  Enables stronger business continuity capabilities •  Google has been doing this for years –  Real-time is the crux of everything Google does •  Time for the rest of us to operate at Google scale –  The technologies are there and they play together nicely –  Process changes must occur internally to achieve this architecture •  This approach will become the “traditional” way of thinking –  Don’t get beat to it by your competitors
  • 29. ® © 2014 MapR Technologies 29 Go Forth and Implement the Zeta Architecture
  • 30. ® © 2014 MapR Technologies 30 $50M$50Min Free Training www.mapr.com/odt
  • 31. ® © 2014 MapR Technologies 31 Q&A @kingmesal maprtech jscott@mapr.com Engage with us! MapR maprtech mapr-technologies

Editor's Notes

  1. Static partitioning was used to create isolation. This enabled people to know that when a problem occurred what was causing the issue. This is something containers can fix. Additionally, when we statically partition, we cannot fully leverage all the resources for all the most important work. Most server types are busy at different times of day, or can be. Which work is the most important? Whichever is deemed the most important now!
  2. The problem with this business continuity story is that you are still limited to generally scheduled backups and not real-time.
  3. Pluggable, because we need an architecture that platforms can be modeled after. If we have to rethink an enterprise architecture every time the next greatest thing comes out we end up redoing a lot of work.
  4. These technology concepts are now mature enough that they will stick around and the specific implementation is flexible.
  5. NOTE: The solution architecture can integrate remote platforms and is a conceptual model and thus isn’t necessarily managed by a global resource manager
  6. “Google is living a few years in the future and sends the rest of us messages” –Doug Cutting, Hadoop Founder
  7. Server crashes before a file is rolled and the data is lost.
  8. Leveraging the distributed file system means that the data is NOT lost. Scales without the pain of figuring out how to move that data, the platform handles it for you. From the solution architecture perspective this is likely going to be utilized in monitoring the operations of an environment, or perhaps revenue management.
  9. These parts are expensive. They are difficult to test because production is often drastically different from dev and qa.
  10. NOTE: The billing database is an external entity, likely an RDBMS and is still a part of the solution architecture to deliver the business objectives
  11. As pointed out in the advertising example. The billing system is still in an RDBMS. It still integrates via the solution architecture, but the RDBMS is not running on this platform architecture.
  12. The benefits are plentiful They rely heavily on Borg and Omega They perform 2 billion container deployments per week
  13. Follow me on twitter to get updates for documentation on the Zeta Architecture