Client-Facing Web E-Trading Platforms

Client-Facing Web E-Trading Platforms
A Leading Fortune 100 Company 1.2.2011

About the Project
Web-based Delivery
Browser-based rich internet application
Some state shared between the client and the server
Latency tolerance is very low with streaming prices and trading
Multiple Stakeholders
Several business units with different priorities and interests
Existing applications that need to be integrated
Downstream System Timelines
Release/Change management windows of downstream systems
Aggressive delivery schedule
2

Existing Architecture
Web E-Trading Platform
Largely an integration project with the actual trading systems
Differing downstream dependencies
Differing downstream performance characteristics
Not a Typical Web-Application
Many non-request-driven event flows
Caching difficult as data can change in multiple ways
Not every downstream system is designed for end-user responsiveness
3

4
High Level Initial Architecture

5
High Level Initial Architecture –FULL SCREEN

Technical Challenges, Part 1
Middle Tier to reach Trading Systems
Many point-to-point (p2p) connections
Shared message bus to notify components of changes
Distributed nature involves high translation overhead
Distributed transactions required over many p2pconnections
Very distributed management of shared data
Low tolerance for system latency
Inter-tangled SDLCs of various teams
6

7
Technical Challenges, Part 2
Challenges
Large number of non-request handling processes/moving parts
High DB/downstream connection count
DB Latency and scalability, pessimistic locking, etc.
Performance bound to downstream systems
Inconsistent data/state in various systems without constant event broadcast
Inter-dependency of development groups
Management tools require too much awareness of infrastructure.
Too many ptp connections
over reliance on shared message bus

8
Scalability Examples, Part 1
Account Management Tool
Change data
Invalidate caches
Send notifications to users
All done by the tool

9
Data Maintenance Jobs
Change data in local DB
Notify other processes
Stream updates to users
All done by the job

10
High Level Arch. incorporating XAP

11
High Level Arch. incorporating XAP –FULL SCREEN

Benefits of incorporating XAP, Part 1
A home for non-web traffic
Processing Units house downstream system event reactors.
Transactionally handle downstream events alongside the golden source of application data
Emit events to the web event bus if and when necessary
Consistent Admin API for monitoring services in the grid
Real-time self-updating cache
Local Cache/Views eliminate out-of-web process lookups when necessary.
Moves the RDBMS off the critical path to the recovery path
The Space becomes a Primary data source for web tier
12

Benefits of incorporating XAP, Part 2
More than a cache: A platform and API
Not only for the data – also a giant distributed spring context
Space Remotedinterfaces, Polling Containers, and the standard partitioned data grid.
Scalability built-in with configurable SLA’s
Optional elastic capacity capabilities are available.
Deployment Independence
Functional units deployed as Processing Units
Contracts between Web Services and UI, and Web Layer and GS via Space Remoting
Hot redeployment of units without downtime.
Intra-platform dependencies abstracted to Space URLs
13

Scalability Examples Revisited, Part 1
Account Management Tool
Space Remoting Calls
Caches notified by space
Simple admin API
Tool is a user of the Admin API
14

15
Data Maintenance Jobs
Listening from the Space
Changing space data inside a transaction
Consistent data modification pattern
Easy failover to a backup node.

Summary
Before
Distributed modification of Shared Data
Varying SLA’s of downstream systems
Too many moving parts needed attending to when making data changes
RDBMS overloaded by being on the critical path with too many processes
After
A platform for deploying distributed event driven architecture
Databases moved to the recovery path
Benefits to the SDLC with each PU being a differently released context
Inbuilt resilience and scalability with configurable partitioning and failover
Delivering a true platform ecosystem
16

17
Wrap-up
Q&A

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Client-Facing Web E-Trading Platforms

by Nati Shalom on Feb 10, 2011

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Client-Facing Web E-Trading Platforms Presentation Transcript