Our Lessons Learned Building a Backend-as-a-Service A Technical Deep Dive Felix Gessert [email protected] 09.05.2017, Netlight @baqendcom Web Application Needs Non-Functional Requirements Modern“Over design 30 percent of web Fast Page Loads development teams deliver projects Engaginglate UX or over-budget.” Automatic scalability Survey by New Bamboo Fast time-to-market High availability Common Web Architektures The 3-Tier Stack Blocks delivery of website Must ensure Subject to latency high availability Render Data HTML, CSS, JS, ... User Action Update Client Requires business Server Database logic in the server Needs to be scalable Common Web Architektures Problem: • User Management The 2-Tier Stack • Access Control • Server-side Business Logic Progressive client- • Latency and scalability still an side rendering issue Still latency-critical Render Database-as-a-service Client Cloud DB HTML, CSS, JS Data Update Client-side business logic Angular React Vue.js DynamoDB Elasticache MongoDB Common Web Architektures The 2-Tier Stack Business Logic Browser HTML, CSS, JS Static Data Website Files Update Cloud APIs (e.g. comments) Angular React Vue.js DynamoDB Elasticache MongoDB The Serverless Paradigm Backend-as-a-Service FaaS and BaaS Many different services Function-as-a-Service and APIs (AWS Lambda) Authentication Scalable code excution Private DB Gateway Business Code Cloud DB Notifications Backend-as-a-Service Overview Must be fast, scalable and highly available Unified API and docs Reusable features Backend-as-a-Service BAAS OVERVIEW How Backend-as-a- Service works Backend-as-a-Service Feature Sets API for application features Data Real- Query, Backend Users, File Access Storage Time Search Code OAuth Storage Control Hosting and Delivery REST API and JS SDK Frontend GET /app.html GET /js/main-34da93.js GET /css/main-9ad7ca3.css Compatible with: GET /app.html GET /js/main-34da93.js GET /css/main-9ad7ca3.css dash Frontend GET /app.html GET /js/main-34da93.js GET /css/main-9ad7ca3.css db.Page.load('main') .done(...); db.Page.find() .descending('published') .limit(3) .resultList(...); GET /img/pic005.jpg GET /img/pic017.jpg GET /img/pic022.jpg Backend-as-a-Service Comparison of Service Models Backend-as-a-Service Platform-as-a-Service Infrastructure-as-a-Service • Fast time-to-market • Full control of backend • High flexibility and full control • Low maintenance • Tools for deployment • Build software from scratch • Often limited in and maintenance • High maintenance overhead expressiveness,, scalabilityscalability • Limited in platform or performance control Presentation is loading The Latency Problem Average: 9,3s Loading… -20% Traffic -9% Besucher -1% Umsatz Performance affects many Business KPIs ...what causes slow page loads? State of the Art Two Bottlenecks: Latency and Processing High Latency Processing Overhead Network Bandwidth vs. Latency I. Grigorik, High performance browser networking. O’Reilly Media, 2013. Netzwerk Bandbreite vs. Latenz 2× Bandwidth = Same Load Time ½ Latency ≈ ½ Load Time STATE OF THE ART How to improve web performance? https://www.ampproject.org What Others Do: AMP /docs/reference/spec.html Google‘s Accelerated Mobile Pages How AMP works: • Stripped down HTML + AMP tags (e.g. img) rendered asynchronously by AMP runtime • CSS must be inlined + <50 KB + • No custom JS (except in iframes) • Only static sizes no repaints • Cached in Google CDN, as long as it is crawled the next time only suited for static media, e.g. news How to apply these techniques for any website? Solution: Global Caching Fresh Data From Distributed Web Caches Low Latency Less Processing New Caching Algorithms Solve Consistency Problem 0 1 1 0 1 0 0 1 New Caching Algorithms Solve Consistency Problem F. Gessert, S. Friedrich, W. Wingerath, M. Schaarschmidt, und N. Ritter, F. Gessert, F. Bücklers, und N. Ritter, „ORESTES: a Scalable Database-as-a-Service „Towards a Scalable and Unified REST API for Cloud Data Stores“, in 44. Architecture for Low Latency“, in CloudDB 2014, 2014. Jahrestagung der GI, Bd. 232, S. 723–734. F. Gessert, M. Schaarschmidt, W. Wingerath, S. Friedrich, und N. Ritter, „The F. Gessert und F. Bücklers, „ORESTES: ein System für horizontal skalierbaren Zugriff auf Cache Sketch: Revisiting Expiration-based Caching in the Age of Cloud Data Cloud-Datenbanken“, in Informatiktage 2013, 2013. Management“, in BTW 2015. 7 Year F. Gessert und F. Bücklers, Performanz- und Reaktivitätssteigerung von OODBMS F. Gessert und F. Bücklers, Kohärentes Web-Caching von Datenbankobjekten im vermittels der Web-Caching-Hierarchie. Bachelorarbeit, 2010. 0 1 1 0 1 0 0 1CloudResearch Computing. Masterarbeit & 2012. Development M. Schaarschmidt, F. Gessert, und N. Ritter, „Towards Automated Polyglot W. Wingerath, S. Friedrich, und F. Gessert, „Who Watches the Watchmen? On Persistence“, in BTW 2015. the Lack of Validation in NoSQL Benchmarking“, in BTW 2015. S. Friedrich, W. Wingerath, F. Gessert, und N. Ritter, „NoSQL OLTP Benchmarking: A F. Gessert, „Skalierbare NoSQL- und Cloud-Datenbanken in Forschung und Survey“, in 44. Jahrestagung der Gesellschaft für Informatik, 2014, Bd. 232, S. 693– Praxis“, BTW 2015 704. F. Gessert, N. Ritter „Scalable Data Management: NoSQL Data Stores in W. Wingerath, F. Gessert, S. Friedrich, N. Ritter „Real-time stream processing for Big Research and Practice“, 32nd IEEE International Conference on Data Data“, Big Data Analytics it - Information Technology, 2016 Engineering, ICDE, 2016 F. Gessert, W. Wingerath, S. Friedrich, N. Ritter “NoSQL Database Systems: A Survey F. Gessert, N. Ritter „Polyglot Persistence“, Datenbank Spektrum, 2016. and Decision Guidance”, Computer Science - Research and Development, 2016 Parse Baqend Kinvey 2.6 s 0.3 s 3.9 s Typical Speedup: 15x T R Y T H I S Impact of Global Caching benchmark.baqend.com Baqend 0,3s 2,1s 1,8s Baqend 2,6s 0,3s Baqend 0,2s 1,6s Azure 1,5s 4,2s 0,8s 1,9s Parse 1,6s 3,2s Firebase 2,7s Frankfurt 5,3s Kinvey 3,8s 6,6s Apiomat 4,4s Tokyo California Baqend 0,3s 6,3s 4,7s 6,5s 10,0s 9,3s Sydney THINKS USE CASE How do these techniques work for a high-traffic shop? Performance Case Study Thinks Online-Shop Shop < 1 Second Page Loads Concurrent Expected: Users • 3,5 Mio. TV Viewers • 4 Weeks for Development & Tests 7.8% 3% • >300K Visitors Conversion Server Rate Usage High Cache Hit Peak Load of over Rate: 99% 20.000 requests per second Logo in TV screen: sudden spike At high load micro- caching is very effective >3.2 Gigabit/s How does this work? Dynamic Caching in Detail Has Time-to-Live (expiration) purge(obj) 푘 False-Positive 푘푛 Hash- 푛 − 푘 = ln 2 ⋅ ( ) Rate: 푓 ≈ 1 − 푒 푚 Functions: 푚 With 20.000 entries and a 5% false positive rate: 11 Kbyte Browser CDN Cache Consistency: Δ-Atomicity, Read-Your-Writes, Monotonic Reads, Monotonic Writes, Causal Consistency hashA(oid) hashB(oid) hashA(oid) hashB(oid) Flat(Counting Bloomfilter) 0 1 1 1 1 0 32 1 4 10 Our Network Optimizations In Baqend SSL SSL Fast Persistent Connections Handshake Client CDN Server - Early SSL Termination - Caching at Internet Exchange Points - OCSP Stapling - Backend Failover & Stale-on-error - Session Resumption - Automatic Skalierung - Warm Backend-Connections - DDOS Protection HTTP/2: Why HTTP/2? • Multiplexing over 1 TCP connection (no head-of-line blocking) Typical Improvements • Request Pipelining • Server Push • Header Compression HTTP HTTPS 3,22s 4,03s HTTP HTTPS with CDN with CDN and h2 0,44s 0,35s SCALING A BAAS How to achieve scalability? Backend Performance Best Practices Load Balancer Application Server Database Load Balancing Stateless Sessions Horizontally scalable Auto-scaling Minimize shared state databases (e.g. “NoSQL”) Failover Efficient Code & IO Replication Sharding Failover Backend Architecture Baqend Cloud Backend-as-a-Service API: AccessInclusion throughof allHTTP Web CachesData, Queries, UserScalable Login,Databases etc. Content-Delivery- Network Backend Architecture Baqend Cloud CDN Baqend Cloud on on Content-Delivery- Network Client Route 53 SSL DNS HTTP/2 Websockets HA Proxy Varnish Baqend DB Client Data Updates Metadata Files ELB ElastiCache S3 Storage Logging Updates Updated Query Storm Query Matching Pub/Sub Pub/Sub Management and Orchestration Server Manager Swarm Nimbus Zookeeper Overview Optimizations Consistent Browser Caching HTTP/2 & SSL Fast CDN-Invalidations APIs for SPAs High Availability Automatic Scaling DDoS Protection Other Optimizations Scale & Optimize Images Load Javascript async. Minify JS & CSS Use Resource Hints BAQEND OVERVIEW How do I use Baqend? Including Baqend Getting Started <script src="https://www.baqend.com/js- sdk/latest/baqend.min.js"></script> Loads the JS SDK including the Bloom filter logic DB.connect('my-app'); Connects to the backend & loads the Bloom filter DB.News.load('2dsfhj3902h3c').then(myCB); DB.Todo.find() .notEqual('done', true) .resultList(myCB); Load & query data using the Bloom Try this: www.baqend.com/tutorial.htmlfilter + Browser Cache Development On Baqend Dashboard CLI REST & SDK Create Schema, Config- Develop, deploy and test Website logic: load site, get urations, Browse Data, etc. frontend und backend Code data, login, etc. IN DEPTH How are the Baqend BaaS APIs used? Baqend JS SDK For Web & Hybrid Browser Node.js Ionic & Cordova React Native • Completely ES6- and TypeScript-compatible • Support for Maps, Sets, Arrays • Models can be ES6-classes • Promise-based • Abstracts from Caching logic, intelligent Object-Identity • Powerful Query-Builder • Automatic Change- and Dependency-Tracking Data Modelling