API Optimization Tale: Monitor, Fix and Deploy (on Friday). GopherCon Europe 2023

https://gophercon.eu/schedule/#session-4

1. API OPTIMISATION TALE: API OPTIMISATION TALE: MONITOR, FIX MONITOR, FIX AND DEPLOY AND DEPLOY (ON FRIDAY) (ON FRIDAY) MACIEK RZĄSA · CHATTERMILL MACIEK RZĄSA · CHATTERMILL Photo by from STpcsDG @MJRZASA @MJRZASA Miguel Á. Padriñán Pixabay
2. FRIDAY FRIDAY 16:03 16:03
3. Photo by on Max Baskakov Unsplash
5. © Photo by Natalia Rząsa
6. Photo by on Fabius Leibrock Unsplash
8. EXTRACTION EXTRACTION
9. FROM FROM TO TO EXTRACTION EXTRACTION class Product < ApplicationRecord has_many :billing_records end class BillingRecord < ApplicationRecord belongs_to :product end class Product < ApplicationRecord def billing_records @billing_records ||= ::Billing::QueryService .billing_records_for_products(self) end end class BillingRecord def product @product ||= Product.find(product_id) end end
10. EXTRACTION EXTRACTION
11. MONITOR MONITOR wait for it FIX: OPTIMISE FIX: OPTIMISE wait for it DEPLOY DEPLOY CI checks easy & reliable rollback safe env with a fallback feature flags .
12. EXTRACTION: FIRST ATTEMPT EXTRACTION: FIRST ATTEMPT
13. EXTRACTION: GRAPHQL EXTRACTION: GRAPHQL
14. standard errors (Rollbar/Sentry) performance (NewRelic) custom request instrumentation (Kibana) method name arguments stacktrace response time (elapsed) error EXTRACTION: MONITORING EXTRACTION: MONITORING { "payload": { "method": "records_for_product", "arguments": "[[\"gid://platform/Product/12345\"]]", "stacktrace": "[ \"app/models/product.rb:123\", \"app/services/sell_product.rb:43\" ]", "elapsed": 1.128494586795568, "error": null } }
15. MONITOR MONITOR standard stack (Rollbar/NewRelic) custom request instrumentation FIX: OPTIMISE FIX: OPTIMISE wait for it DEPLOY DEPLOY CI checks easy & reliable rollback safe env with a fallback feature flags .
16. OPTIMISE OPTIMISE
17. FLOOD OF REQUESTS FLOOD OF REQUESTS PROBLEM: SINGLE VIEW/JOB INITIATES PROBLEM: SINGLE VIEW/JOB INITIATES MANY BILLING REQUESTS MANY BILLING REQUESTS HOW MANY? THOUSANDS! HOW MANY? THOUSANDS!
18. INITIAL INITIAL OPTIMISED OPTIMISED FLOOD OF REQUESTS FLOOD OF REQUESTS def perform(*) products = Product.eligible products.find_in_batches.each do |product| # one billing request per call DoBusinessLogic.call(product) end end class DoBusinessLogic def call(product) product.billing_records.each {} end end class Product < ApplicationRecord def billing_records @billing_records ||= ::Billing::QueryService .billing_records_for_products(self) end end def perform(*) products = Product.eligible products.find_in_batches do |batch| # one billing request per batch cache_billing_records(batch).each do |p| # no billing requests DoBusinessLogic.call(p) end end end def cache_billing_records(products) indexed_records = ::Billing::QueryService .billing_records_for_products( *products ) .group_by(&:product_gid) products.each do |product| product.cache_billing_records!( indexed_records[product.gid].to_a ) end end
19. FLOOD OF FLOOD OF REQUESTS? REQUESTS? PRELOAD, PRELOAD, CACHE, CACHE, (HASH-)JOIN (HASH-)JOIN ◀ Ulf Michael Widenius, MySQL. Image source: wikipedia.org
20. FREQUENTLY NEEDED DATA FREQUENTLY NEEDED DATA PROBLEM: SINGLE FIELD WAS FREQUENTLY USED PROBLEM: SINGLE FIELD WAS FREQUENTLY USED (~1K HITS PER DAY) (~1K HITS PER DAY)
21. PLAN PLAN add field to kafka build a read model backfill the data start using the read model remove billing query SOLUTION SOLUTION find that date in local DB verify if it's really the same date use it and remove billing query FREQUENTLY NEEDED DATA FREQUENTLY NEEDED DATA # 1k billing hits per day ::Billing::QueryService .first_successful_record_created_at(client) &.in_time_zone&.to_date # one local DB query client .products.successful .minimum(:start_date)
22. DATA NEEDED DATA NEEDED FREQUENTLY? FREQUENTLY? USE THE USE THE DOMAIN, LUKE! DOMAIN, LUKE! ◀ Image source: starwars.fandom.com
23. DATA FLOOD DATA FLOOD PROBLEM: GENERIC QUERIES PROBLEM: GENERIC QUERIES FETCHING ALL THE DATA THAT MIGHT BE NEEDED FETCHING ALL THE DATA THAT MIGHT BE NEEDED
24. DATA FLOOD DATA FLOOD # REST response { "gid": "gid://..." "clientGid": "gid://..." "productGid": "gid://..." "availability": true "pending": false "frequency": "weekly" "startDate": "2020-08-21" "endDate": "2020-10-28" # ... # 36 fields total # loading 3-4 associations } def billing_records_for_products(*products) fetch_billing_records( filter: {products: products} ).select(&:accessible?) end query($filter: RecordFilter!) { cycles(filter: $filter) { nodes { gid productGid pending frequency } } } def billing_records_for_products(*products) fetch_billing_records( filter: { products: products, accessible: true } ) end
25. Photo by on Erik-Jan Leusink Unsplash
26. WHAT COULD POSSIBLY GO WRONG? WHAT COULD POSSIBLY GO WRONG?
27. WHAT COULD POSSIBLY GO WRONG? WHAT COULD POSSIBLY GO WRONG? ROOT CAUSE ROOT CAUSE FIX FIX # REST client get('/records', **params.slice(:product_gids)) # DB query in billing def billing_records(product_gids: nil, gids: nil, client_gid: nil) scope = ::BillingRecord scope = scope.where(product_gid: product_gids) if product_gids scope = scope.where(gid: gids) if gids scope = scope.where(client_gid: client_gid) if client_gid scope.all end def billing_records(product_gids: nil, gids: nil, client_gid: nil) return [] if [product_gids, gids, client_gid].all?(&:blank?) # ... end
28. DATA FLOOD? DATA FLOOD? QUERY QUERY CUSTOMISATION & CUSTOMISATION & UNDERFETCHING UNDERFETCHING FILTERING ON THE FILTERING ON THE SERVER SIDE SERVER SIDE
29. TIP? TIP? ALWAYS TEST ALWAYS TEST MANUALLY. MANUALLY. ALWAYS. ALWAYS.
30. 429 TOO MANY REQUESTS 429 TOO MANY REQUESTS PROBLEM: SPIKE OF REQUESTS PROBLEM: SPIKE OF REQUESTS EVERY SUNDAY EVENING EVERY SUNDAY EVENING
31. PROBLEM PROBLEM WEEK1. WEEK1. SOLUTION: PRELOADING SOLUTION: PRELOADING WEEK2. PROPER SOLUTION: JITTER WEEK2. PROPER SOLUTION: JITTER WEEK3. FINAL PROPER SOLUTION WEEK3. FINAL PROPER SOLUTION WEEK4. REALLY FINAL PROPER WEEK4. REALLY FINAL PROPER SOLUTION: RATE LIMITING SOLUTION: RATE LIMITING 429 TOO MANY REQUESTS 429 TOO MANY REQUESTS # scheduling at talent's 5 PM on Sunday eligible_products.each do |p| WeeklyReminder.schedule( product, day: :sunday, time: '17:00' ) end eligible_products.find_in_batches do |batch| with_billing_records_preloaded(batch) do batch.each do |product| WeeklyReminder.schedule( product, day: :sunday, time: '17:00' ) end end end # class WeeklyReminder def scheduling_time(*) super + (SecureRandom.rand * 120 - 60).seconds end # class AnotherWeeklyReminder def scheduling_time(*) super + (SecureRandom.rand * 120 - 60).seconds end Sidekiq::Limiter.window( 'weekly-reminder', RATE_LIMIT_COUNT, RATE_LIMIT_INTERVAL, wait_timeout: 2 )
32. 429 TOO MANY 429 TOO MANY REQUESTS? REQUESTS? I DON'T ALWAYS TEST ON I DON'T ALWAYS TEST ON PRODUCTION PRODUCTION BUT WHEN I DO, I RUN BUT WHEN I DO, I RUN TESTS ON FRIDAY TESTS ON FRIDAY
33. MONITOR MONITOR standard stack (Rollbar/NewRelic) custom request instrumentation FIX: OPTIMISE FIX: OPTIMISE preloading to avoid N+1 server-side filtering using local data underfetching spreading the load DEPLOY DEPLOY CI checks easy & reliable rollback safe env with a fallback feature flags . NIHIL NOVI SUB SOLE NIHIL NOVI SUB SOLE
34. FAIL OFTEN SO FAIL OFTEN SO YOU CAN YOU CAN SUCCEED SUCCEED SOONER SOONER Tom Kelley Photo: snikologiannis/Flickr; http://ow.ly/CHwhd
35. Maciek Rząsa  @mjrzasa MACIEK MACIEK RZĄSA RZĄSA Q&A Q&A fFnc,tFnr  @mjrzasa