e-Commerce web app Architecture and Scalability

1. e-Commerce web app Architecture and
Scalability

2. So, what’s in an E-Commerce Store?
Slide 2
Catalogs
State
Discounts
Inventory
Fulfillment
Social Integration
Payment
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Analytics
Cross-sell
Content
Search
Seasonality
00000
Ads
Personalization
Cust. Service

3. Conceptual View
Slide 3

4. Application View
Slide 4
IntegrationMiddleware

5. The Key to Scalability…
Slide 5
•Ability of a system to handle or be enlarged to handle growing amounts of work
gracefully
… is to understand what it is
•Identify bottlenecks, and mitigate
•Identify load sources, and minimize
… is to keep principles simple
•“How scalable do you want it?” (Do you have the NFRs?)
… is to understand what’s expected
•If my look-to-book ratio is 90:10, can I scale differently?
•Do I always need to depend on the scalability of my partners?
•Do all of my subsystems need to scale equally?
•If my load is seasonal, should I be safe and overprovision?
… is to exploit system characteristics

6. IntegrationMiddleware
So what’s Different?
Slide 6
Lots of integration –
and dependencies
Combo of content
and Data
Complicated rules
spanning entities
Rich and useful data
to be analyzed and
mined
The breadwinner!
Many different
channels – and loadLots of these guys
(hopefully!)
Some typical usage
patterns
Lots of potential plus
lots of load

7. Mapping to Scalability Considerations
Multiple channels
User behavior
Social Content
Slide 7
Content + Data
Rules and analytics
Integration – and dependencies

8. Scalability Strategies: Multiple Channels
• Scale out
• Minimize state for better load balancing, and to reduce memory footprint
• Use CDNs to farm out traffic to other sites, or consider A/A DC’s
• Exploit client capability, and minimize traffic
• Leverage device profile to serve appropriate content
• Scale out
• Minimize state for better load balancing, and to reduce memory footprint
• Use CDNs to farm out traffic to other sites, or consider A/A DC’s
• Exploit client capability, and minimize traffic
• Leverage device profile to serve appropriate content
Frontends
• Use lightweight protocols
• Split between presentation services and interface services and choose
granularity
• Use lightweight protocols
• Split between presentation services and interface services and choose
granularity
Services
Slide 8

9. Scalability Strategies: Content, Social Traffic
• Content and data scale differently – so scale them independently
• Mash up content, UGC, and catalog data in a portal
• Leverage CMS’ caching as far as possible
• Consider publishing static HTML
• Organize CMS structures appropriately
• Use CDNs or servers appropriate to the purpose
• Content and data scale differently – so scale them independently
• Mash up content, UGC, and catalog data in a portal
• Leverage CMS’ caching as far as possible
• Consider publishing static HTML
• Organize CMS structures appropriately
• Use CDNs or servers appropriate to the purpose
Content
• Separate onto other servers
• Leverage existing social network platforms
• Separate onto other servers
• Leverage existing social network platforms
UGC
Slide 9

10. Scalability Strategies: User Behavior
Slide 10
•Separate reads and writes; scale out read nodes using replication / master-slave, …
•Split functionality between database instances
•Use sharding (carefully) to partition and scale out writes
•Choose optimistic reads (carefully) to minimize locks
•Separate reads and writes; scale out read nodes using replication / master-slave, …
•Split functionality between database instances
•Use sharding (carefully) to partition and scale out writes
•Choose optimistic reads (carefully) to minimize locks
Data
•A fair bit of data changes slowly – cache aggressively: catalogs, content, …
•Try and cache inventory levels as well, based on thresholds
•A fair bit of data changes slowly – cache aggressively: catalogs, content, …
•Try and cache inventory levels as well, based on thresholds
Minimize I/O
•Create private clouds or leverage public / hybrid clouds•Create private clouds or leverage public / hybrid clouds
Elasticity

11. Scalability Strategies: Rules and Analytics
Slide 11
• Classify into cross-sell rules, transaction processing rules
• Cross-sell rules more heavily used, use more data
• Pre-compute results - not everything needs to be real-time
• Reduce target datasets - not everything is against the universe
• Classify into cross-sell rules, transaction processing rules
• Cross-sell rules more heavily used, use more data
• Pre-compute results - not everything needs to be real-time
• Reduce target datasets - not everything is against the universe
Rules
• Separate analytics from transactional systems
• Run them off of their own instance
• Separate analytics from transactional systems
• Run them off of their own instance
Analytics

12. Scalability Strategies: Integration
Slide 12
• Use synchronous calls only when needed (for example, payments)
• Use queuing for durability and throttling
• Have a fallback mechanism:
• Last day’s inventory in case the inventory system isn’t coping
• Backend payment if payment gateway isn’t coping
• Consider batch mode integration vs. real-time always
• Use synchronous calls only when needed (for example, payments)
• Use queuing for durability and throttling
• Have a fallback mechanism:
• Last day’s inventory in case the inventory system isn’t coping
• Backend payment if payment gateway isn’t coping
• Consider batch mode integration vs. real-time always
Dependencies

13. Strategies for Commerce Engines
Use products (commercial | open source) for commerce, content,
search, etc.
Choose taxonomy and design carefully
Catalogs, virtual catalogs, materialized catalogs, catalog sets, page
snapshots, …
Content taxonomy
Cache appropriately
Content caching at browser, CDN, CMS, commerce engine, …
Commerce caching for catalogs, ad rules, pricing and inventory, …
Scale appropriately
Consider data volumes (catalog sizes, user base, …) for sharding or
partitioning
Follow vendor best practices for scaling
Slide 13

14. General Scalability Strategies
 Use statelessness to scale better
 Choose shared-nothing models to scale best
 Choose shared-(something) or externalized state models with due considerations
 Reduce HTTP requests and payload
 Use techniques like file versioning, sprites, inline images, compression, …
 Be asynchronous where possible
 When calling backend systems, for example
 Choose faster (or lesser) I/O to minimize latency
 Cache aggressively
 Use faster I/O where possible
 Keep data small and archive aggressively to scale I/O and DBs
 Keep data close helps use network better and to reduce latency
 Write good code!
Slide 14

15. In Summary
Know what you are looking to achieve
NFRs, business outlook
Exploit usage characteristics
Read/write ratios, acceptable lags, functional separation
Design for scale
Statelessness, service granularity, protocols
Reduce load
Pre-compute data, cache aggressively, offload
Identify subsystem scalability needs
Scale what’s needed, not everything
Leverage others!
Product capabilities, CDNs, cloud providers, social networking platforms
Slide 15