Building low latency apps with a serverless architecture and in-memory data I AWS Dev Day 2018
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The document discusses building low-latency applications using serverless architecture and in-memory data technologies. It highlights the features and advantages of various Amazon services, including DynamoDB, ElastiCache, and Neptune, emphasizing fast performance, scalability, and reduced latency. Additionally, it addresses challenges in managing highly connected data and the benefits of a polyglot persistence approach.
![© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Chat apps powered by ElastiCache
https://aws.amazon.com/blogs/database/amazon-elasticache-utilizing-redis-geospatial-capabilities/
Clients
Chat apps
Application Load
Balancer
WebSockets
Amazon
ElastiCache
Redis
PubSub Server
persistent
connections
Elastic
Beanstalk
SUBSCRIBE chat_channel:114
PUBLISH chat_channel:114 "Hello all"
>> ["message", "chat_channel:114", "Hello all"]
UNSUBSCRIBE chat_channel:114](https://image.slidesharecdn.com/4-180424071345/85/Building-low-latency-apps-with-a-serverless-architecture-and-in-memory-data-I-AWS-Dev-Day-2018-32-320.jpg)
Building low latency apps with a serverless architecture and in-memory data I AWS Dev Day 2018
- 1. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Building low latency apps with a serverless architecture and in-memory data Darin Briskman | April 2018 [email protected]
- 2. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Things with purpose
- 3. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Non-Relational Powers New Architectures
- 4. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Traditional application characteristics HR Payroll CRM ERP … Users 100s-1000s Data volume GB-TB Locality HQ Performance Seconds Request Rate Tens of thousands Access Internal servers, PCs Scale Up Economics Pay up front Developer Access days/weeks/months
- 5. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Cloud application characteristics Key-valueRelational Document Graph ; Users 1M+ Data volume TB-PB-EB Locality Global Performance Milliseconds-Microseconds Request Rate Millions Access Mobile, IoT, Devices Scale Up-Out-In Economics Pay as you go Developer access Instant API access
- 6. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Database characteristics Referential integrity with strong consistency, transactions, and hardened scale GraphKey-value Document ; Relational Low-latency, key-based queries with high throughput and fast ingestion of data Indexing and storing documents with support for query on any property Creating and navigating relations between data easily and quickly Complex query support via SQL Simple query methods with filters Simple query with filters, projections, and aggregates Easily express queries in terms of relations
- 7. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Polyglot persistence Different data technologies for different data needs • Within an application • Across an organization • Spanning multiple organizations Loose coupling sets you free • Services communicate through queues • Non-relational databases make excellent queues
- 8. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. The New De-Normal
- 9. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Different approaches for highly connected data Purpose-built for a business process Purpose-built to answer questions about relationships
- 10. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon DynamoDB F a s t a n d f l e x i b l e N o S Q L d a t a b a s e s e r v i c e f o r a n y s c a l e Fast, consistent performanceHighly scalable Fully managed Business critical reliability Consistent single-digit millisecond latency; DAX in-memory performance reduces response times to microseconds Auto-scaling to hundreds of terabytes of data that serve millions of requests per second Automatic provisioning, infrastructure management, scaling, and configuration with zero downtime Data is replicated across fault tolerant availability zones, with fine-grained access control
- 11. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. VPC Endpoints April 2017 Auto Scaling June 2017 DynamoDB Accelerator (DAX) April 2017 Time to Live (TTL) February 2017 GlobalTables (GA) N E W ! On-demand Backup (GA) N E W ! Amazon DynamoDB D e l i v e r i n g o n c u s t o m e r n e e d s Encryption at rest (Coming Soon) N E W !
- 12. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. DynamoDB Global Tables ( G A ) F i r s t f u l l y m a n a g e d , m u l t i - m a s t e r, m u l t i - r e g i o n d a t a b a s e Build high performance, globally distributed applications Low latency reads and writes to locally available tables Disaster proof with multi-region redundancy Easy to set up and no application re-writes required Globally dispersed users Replica (N. America) Replica (Europe) Replica (Asia) Global App Global Table
- 13. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon DynamoDB – Backup and Restore F i r s t N o S Q L d a t a b a s e t o a u t o m a t e o n - d e m a n d a n d c o n t i n u o u s b a c k u p s Point in time restore for short-term retention and data corruption protection (coming soon) Back up hundreds of TB instantaneously with NO performance impact On-demand backups for long-term data archival and compliance (GA)
- 14. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon DynamoDB E n c r y p t i o n @ r e s t ( c o m i n g s o o n ) Server-side encryption Supports compliance certifications No application code rewrites
- 15. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Elasticsearch Service L o g a n a l y t i c s , c l i c k s t r e a m a n a l y t i c s , f u l l - t e x t s e a r c h Easy to Use Fully managed. Single click topologies. Open & Integrated Elasticsearch APIs & Kibana. AWS Integrated. Secure VPC. IAM. Scalable & Available 100 Nodes. 150 TB. Multi-AZ.
- 16. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Elasticsearch Service: What’s new 100 nodes 150TB February 2017 VPC Slow Logs October 2017April 2017 Elasticsearch 5 January 2017 1 Petabyte I3 Instances (coming soon) N E W ! Encryption at rest (coming soon) N E W ! Elasticsearch 6 (coming soon) N E W ! C4, M4, R4 1.5TB Storage
- 17. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon ElastiCache Extreme Performance Secure & hardened Easily scalable Highly available & reliable In-memory data store and cache using optimized stack to deliver sub- millisecond response times VPC for cluster isolation, encryption at rest/transit, and HIPAA compliance Read scaling with replicas. Write and memory scaling with sharding. Non disruptive scaling Multi-AZ with automatic failover Managed, in-memory data store service Redis or Memcached to power real-time apps with sub-millisecond latency
- 18. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Memcached 1.4.34 April 2017 Online cluster resizing Redis Cluster aware backup/restore March 2017 HIPAA Eligibility N E W ! Amazon ElastiCache D e l i v e r i n g o n c u s t o m e r n e e d s Encryption In Transit,At Rest, and RedisAUTH N E W ! N E W ! Redis test failover April 2017
- 19. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Highly connected data Social News Feed Restaurant Recommendations Retail Fraud Detection
- 20. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Too expensive Difficult to maintain high availability Difficult to scale Limited support for open standards $ Existing Graph DatabasesRelational Databases Inefficient graph processingUnnatural for querying graph Rigid schema inflexible for changing graphs Challenges building apps with highly connected data
- 21. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Neptune F u l l y m a n a g e d g r a p h d a t a b a s e (public preview today) Fast & Scalable Reliable Open Store billions of relationships and query with milliseconds latency Six replicas of your data across three AZs with full backup and restore Build powerful queries easily with Gremlin and SPARQL SupportsApache TinkerPop &W3C RDF graph models Gremlin SPARQL Easy
- 22. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Request rate High Low Latency Low High Structure Low High Data volume Low High Amazon RDS Amazon S3 Amazon Glacier Amazon CloudSearch and Amazon Elasticsearch Service Amazon DynamoDB Amazon ElastiCache and Amazon DynamoDB Accelerator (DAX) HDFS
- 23. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Powerful ~200 commands + Lua scripting In-memory data structure server Utility data structures Strings, lists, hashes, sets, sorted sets, bitmaps, and HyperLogLogs Simple Atomic operations supports transactions Ridiculously fast! <1 ms latency for most commands Highly available replication Persistence Open source What is Redis?
- 24. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Caching Clients Amazon ElastiCache Redis Amazon DynamoDB Elastic Load Balancing Amazon EC2 Amazon RDS write-through reads/ writes DDB streams mysql.lambda_async reads/ writes Amazon S3 reads/writes Object data Unstructured data Relational data
- 25. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Caching NoSQL Amazon EC2 reads/ writes reads MongoDB Cluster Cassandra Cluster Smaller NoSQL DB clusters needed = lower costs Faster data retrieval = better performance Elasticsearch Cluster Clients
- 26. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon EC2 reads/ writes Amazon ElastiCache Redis reads MongoDB Cluster DBObject doc = collection.findOne(); Cache serialized DBObject in Redis (good) Cache rows in Redis hash (faster/more efficient) Cassandra Cluster Amazon ElastiCache Redis Amazon EC2 reads/ writes reads ResultSet rs = session.execute(stmt); Cache serialized ResultSet in Redis (good) Cache rows in Redis hash (faster/more efficient) Smaller NoSQL DB clusters needed = lower costs Faster data retrieval = better performance Caching NoSQL databases with Amazon ElastiCache
- 27. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Kinesis Analytics Amazon Kinesis Streams Amazon Kinesis Streams Amazon ElastiCache (Redis) cleansed stream Streaming data enrichment/processing Datasources raw stream Subscribers AWS Lambda function 1 Continualdata filtering/enrichment Real-time pub/sub AWS Lambda function 2
- 28. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Big data architectures using Redis Amazon Kinesis DataSources AWS Lambda Apache Storm on EMR Spark Streaming on Amazon EMR Amazon Kinesis app Amazon EC2 AWS IoT Amazon ElastiCache Collect Store Process Amazon S3 Apache Kafka AWS Lambda Custom app Spark on Amazon EMR Analyze
- 29. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Rules Engine Amazon ElastiCache Redis AWS Lambda Direct integration LambdaSNS SQS S3 KinesisDDB AWS IoT devices AWS IoT Sensor store IoT powered by ElastiCache
- 30. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Mobile apps powered by ElastiCache Amazon API Gateway AWS Lambda Amazon ElastiCache Redis GEOADD GEORADIUS Search points of interest Update points of interest https://aws.amazon.com/blogs/database/amazon-elasticache-utilizing-redis-geospatial-capabilities/ Amazon DynamoDB DDB streams Amazon EC2
- 31. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Ad tech powered by ElastiCache Clients Advertisers https://aws.amazon.com/caching/database-caching/ Ad network Ad slot Consumer Ad slot publishers Ad placement (websites/apps) Amazon ElastiCache Redis <40 ms Clickstream (shopping events) User visits page Publisher places ad slot for auction Ad network calls for bidsBidders respond with bids Winners bid ad displayed
- 32. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Chat apps powered by ElastiCache https://aws.amazon.com/blogs/database/amazon-elasticache-utilizing-redis-geospatial-capabilities/ Clients Chat apps Application Load Balancer WebSockets Amazon ElastiCache Redis PubSub Server persistent connections Elastic Beanstalk SUBSCRIBE chat_channel:114 PUBLISH chat_channel:114 "Hello all" >> ["message", "chat_channel:114", "Hello all"] UNSUBSCRIBE chat_channel:114
- 33. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. • Very popular for gaming apps that need uniqueness and ordering • Easy with Redis sorted sets ZADD "leaderboard" 1201 "Gollum” ZADD "leaderboard" 963 "Sauron" ZADD "leaderboard" 1092 "Bilbo" ZADD "leaderboard" 1383 "Frodo” ZREVRANGE "leaderboard" 0 -1 1) "Frodo" 2) "Gollum" 3) "Bilbo" 4) "Sauron” ZREVRANK "leaderboard" "Sauron" (integer) 3 Gaming—real-time leaderboards
- 34. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Ex: throttling requests to anAPI uses Redis counters ELB Externally facing API Reference: http://redis.io/commands/INCR FUNCTION LIMIT_API_CALL(APIaccesskey) limit = HGET(APIaccesskey, “limit”) time = CURRENT_UNIX_TIME() keyname = APIaccesskey + ":” + time count = GET(keyname) IF current != NULL && count > limit THEN ERROR ”API request limit exceeded" ELSE MULTI INCR(keyname) EXPIRE(keyname,10) EXEC PERFORM_API_CALL() END Rate limiting
- 35. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon ElastiCache µs is the new ms
- 36. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Thank you! … and thanks to our sponsors!
Editor's Notes
- #23: If we were to categorize data stores into a temperature gauge, we’d see characteristics that really tailor to different data services…