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e-Commerce web app Architecture and Scalability

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Aryashree Pritikrishna
Aryashree Pritikrishna

This document discusses strategies for scaling e-commerce web applications. It begins by describing common components of e-commerce stores like catalogs, inventory, payments, and analytics. It then discusses keeping principles simple, understanding expected usage, and exploiting system characteristics for scalability. Specific strategies addressed include scaling multiple channels, content and social traffic, user behavior patterns, integration dependencies, and rules/analytics systems. The document emphasizes statelessness, reducing load, caching, separating concerns, and leveraging existing scalable systems.

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e-Commerce web app Architecture and Scalability
So, what’s in an E-Commerce Store? Slide 2 Catalogs State Discounts Inventory Fulfillment Social Integration Payment Note: This image is for illustrative purposes only. MindTree does not recommend or associate itself with either this site, or the products displayed here. Any copyrights belong to their respective owners Analytics Cross-sell Content Search Seasonality 00000 Ads Personalization Cust. Service
Conceptual View Slide 3
Application View Slide 4 IntegrationMiddleware
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
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
Mapping to Scalability Considerations Multiple channels User behavior Social Content Slide 7 Content + Data Rules and analytics Integration – and dependencies
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
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
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
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
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
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
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
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

More Related Content

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 Note: This image is for illustrative purposes only. MindTree does not recommend or associate itself with either this site, or the products displayed here. Any copyrights belong to their respective owners Analytics Cross-sell Content Search Seasonality 00000 Ads Personalization Cust. Service
  • 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