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Next Generation Enterprise Architecture

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Apache Mesos, Apache Hadoop, Apache Spark + Custom Enterprise Applications: This stack combined is greater than the sum of each of the pieces of this stack. Mesos can manage resources across an entire data center, Hadoop provides a distributed data store and scalable data processing, and Spark delivers great in-memory and disk-based performance of data processing as well as streaming capabilities. Couple all of that with custom enterprise applications, and the data center turns into a well-oiled machine. When combined, this software stack delivers unlimited flexibility for the entire data center.

Jim Scott, Director of Architecture and Enterprise Strategy | Strata + Hadoop World | Barcelona, Spain, November 2014

Published in: Data & Analytics
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Next Generation Enterprise Architecture

  1. 1. The Next Generation Enterprise Architecture © 2014 MapR Techno©lo 2g0ie1s4 MapR Technologies 1 Resistance is Futile:
  2. 2. © 2014 MapR Technologies 2 Agenda • Current State – History – Moving Forward • The Next Enterprise Architecture • Business Implications • Concrete Implementations
  3. 3. © 2014 © 201 M4 aMpaRp RTe Tcehcnhonloogloiegsies 3 Current State
  4. 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. 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. 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. 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. 8. The Next “Last” Enterprise Architecture © 2014 © 201 M4 aMpaRp RTe Tcehcnhonloogloiegsies 8
  9. 9. The Next Generation Enterprise Architecture Enterprise Applications Global Resource Management © 2014 MapR Technologies 9 • 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
  10. 10. © 2014 MapR Technologies 10 Technologies That Work Web Servers Business Applications Enterprise Applications Global Resource Management Mesos + YARN Distributed File System MapR-FS S3 HDFS
  11. 11. We Will Call This Architecture… © 2014 MapR Technologies 11
  12. 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. 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. 14. © 2014 MapR Technologies 14 Zeta Architecture at Google HTTP Servers Enterprise Applications Global Resource Management Borg & Omega Distributed File System GoogleFS GMail
  15. 15. © 2014 © 201 M4 aMpaRp RTe Tcehcnhonloogloiegsies 15 Concrete Implementations
  16. 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. 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. 18. © 2014 MapR Technologies 18 Advertising Platform
  19. 19. © 2014 MapR Technologies 19 Advertising Platform - Simplified
  20. 20. © 2014 MapR Technologies 20 Advertising Platform on Zeta
  21. 21. © 2014 © 201 M4 aMpaRp RTe Tcehcnhonloogloiegsies 21 Business Implications
  22. 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. 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. 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. 25. Production Research © 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 Datacenter 1 Datacenter 2 WAN EC2
  26. 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. 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. 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. 29. Go Forth and Implement the Zeta Architecture © 2014 MapR Technologies 29
  30. 30. © 2014 MapR Technologies 30 Q & A Engage with us! @kingmesal maprtech jscott@mapr.com MapR maprtech mapr-technologies

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