GigaSpaces HA
Upcoming SlideShare
Loading in...5
×
 

Like this? Share it with your network

Share

GigaSpaces HA

on

  • 410 views

GigaSpaces clustering

GigaSpaces clustering

Statistics

Views

Total Views
410
Views on SlideShare
409
Embed Views
1

Actions

Likes
0
Downloads
4
Comments
0

1 Embed 1

https://www.linkedin.com 1

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

GigaSpaces HA Presentation Transcript

  • 1. GigaSpacesClustering
  • 2. Today’s Reality – Tier Based Architecture Separate technology implementation Separate technology implementation bottlenecks bottlenecks Separate technology implementation Bottlenecks in all areas where state is stored, architecture can’t scale linearly!
  • 3. Traditional Architecture - path to complexity…A Auction ServiceB Bid Service Auction Bid Trade InfoT Trade Service A B T I I Process Service Bid Service Service Service Bid Result ResultI Info Service Bid Validate Process Accepted TradeT Timer Service Place bid Bidder Get Bid Result Auction Timer Owner T Service
  • 4. Traditional Architecture - path to complexity…A Auction ServiceB Bid ServiceT Trade Service A B T II Info ServiceT Timer Service Business tier Bidder Auction Owner Back-up Separate failover strategy and implementation for each tier Redundancy doubles network traffic Bottlenecks are created Back-up Latency is increased
  • 5. Do you see the Problem?Scalability is not linear Business tierScalability management B nightmare I A B T Bidder Auction Owner Back-up Back-up Back-up Back-up
  • 6. The SolutionGigaSpaces Elastic Application Server
  • 7. Step 1 – Create a Processing UnitA Auction ServiceB Bid Service B T I AT Trade ServiceI Info Service Processing UnitT Timer Service Business tier Bidder Auction Owner Single model for design, deployment and management No integration effort Manage data in memory Collapse the tiers Collocate the services
  • 8. Step 2 – Async PersistencyA Auction ServiceB Bid Service B T I AT Trade Service Place BidI Info ServiceT Timer Service Processing Unit Validate Bidder Process Bid Auction Owner Get Bid Process Trade Results Process Results Persist for Compliance & Collocation of data, messaging Reporting purposes: and services in memory: - Storing State  Minimum Latency (no - Register Orders network hops) - etc.  Maximum Throughput
  • 9. Step 3 – Resiliency SLA Driven Backup Container B T I B T I A A Processing Unit Single, built-in failover/redundancy investment strategy Fewer points of failure Automated SLA driven failover/redundancy mechanism Continuous High Availability
  • 10. Step 3 – Resiliency SLA Driven Primary Backup Backup Container Processing Unit Single, built-in failover/redundancy investment strategy Fewer integration points mean fewer chances for failure Automated SLA driven failover/redundancy mechanism Continuous Availability Self Healing Capability
  • 11. Step 4 – Scale Backup Backup B T I B T I B T I B T I A A A A Processing Unit Write Once Scale Anywhere: Linear scalability Single monitoring and management engine Automated, SLA-Driven deployment and management - Scaling policy, System requirements, Space cluster topology
  • 12. Step 5 – Auto Scale Out
  • 13. The Processing Unit – Scalability UnitSingle Processing Unit Processing Unit - Scaled Involves Config Change No code changes!
  • 14. The Processing Unit – High-Availability Unit Primary - Processing Unit Backup - Processing Unit Business logic – Active mode Business logic – Standby mode Sync Replication
  • 15. The Processing Unit - Database Integration Primary - Processing Unit Backup - Processing Unit Business logic – Active mode Business logic – Standby mode Sync Replication Async Async Replication Replication Initial Load Mirror Process ORM
  • 16. ThankYou!