1. IMDGs An essential part of your architecture

2. About me romnan_shramkov@epam.com

3. What is IMDG? In short: it’s performance and scalability enabling solution

4. Whatis.com An in-memory data grid (IMDG) is a data structure that resides entirely in RAM (random access memory), and is distributed among multiple servers.

5. Cyber Monday

6. Solution Cache Low latency NoSQL Scalability Fault tolerance Data management

7. Grid Solution Grid Low latency Fault tolerance Data management Elasticity ACID transactions

8. Cache Key-value storage which works with domain objects, may support a document API Eviction and invalidation policies Read and write strategies: read through, write through, read-ahead, write behind, Change Data Capture Local cache and Local view Date pre-load, recovery from disk during cold start and after simultaneous node failure

9. Data Query language, indexes parallel query and "map/reduce"

10. Clients & API API and client library for different programming languages Transparent proxy, grid Pluggable connectors for databases JDBC, JMS, Memcached connectivity

11. Infrastructure Easy clustering, zero time deployment Monitoring, management and Self healing Configurable topology with Sync/Async Backups SLA based elastic deployments Security for connecting a node to space and client to space

12. Tool for In-Memory

13. SOA is not scalable

14. Processing Task Execution, Processing Grid and (Massive) Parallel Executions Remote Services, Collocated Execution Complex Event Processing Pooling Container Notify Container

15. Case Study

16. Authorization Server Three steps: Validate digital signature using stored Access Token Validate message nonce uniqueness for the last 15 minutes Validate URL access by checking of all ACLs configured for the client 16

17. Challanges 50 ms SLA Strong Consistency Protect any requests to any service Durable

18. Architecture with Cache 18

19. Architecture with Grid All elements of the architecture are fully provided by GigaSpaces XAP platform 19

20. Performance Architecture App Servers, nodes Spaces / Memcached, nodes Users Throughput, rq/s Average, ms Median, ms 90% Line, ms 1 Node (Users ratio 3.75, Throughput ratio 3.57) Grid1145579.9341 47 Cache1012162.70343045 6 Nodes (Users ratio 1.81, Throughput ratio 2.32) Grid661362,406.97322453 Cache42751,037.15363154 20

21. Scalability 21

22. Areas Low latency applications Big Data 3 V (Verity, Volume, Velocity) Real time big data analysis (Fast Data) Stream processing Complex Event Processing