integrating amazon elasticache into your database stack - aws may 2016 webinar series

© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.

Dan Zamansky, Senior Product Manager

May 26, 2016

AWS Webinar SeriesIntegrating Amazon ElastiCache into Your Database Stack

Learning Objectives

• Understand key Amazon ElastiCache features

• Learn how to set up Amazon ElastiCache and how to integrate it into your database stack

• Explore sample use cases, best practices, and tips on using Amazon ElastiCache to speed up your application by reducing database latencies and increasing throughput

Modern Applications Require Real-Time PerformanceWe live in a connected world (IoT)

• Phones, Tablets, Cars, Air Conditioners, ToastersExperiences are increasingly contextualApps need to provide real-time responsesDatabase performance is frequently the bottleneckLoad is spikey and unpredictable

Businesses Need To Be Ready For Success!

What is ElastiCache?

AWS Database Services

Compute Storage

AWS Global Infrastructure

Database

Application Services

Deployment & Administration

Networking

Performance Optimized In-Memory Key-Value Store in the Cloud

Amazon RDS

Amazon DynamoDB Amazon Redshift

Amazon ElastiCache

Fully managed service = Automated Operations

In-Memory datastore self-hosted on Amazon EC2

Amazon ElastiCache

In-Memory Key-Value Store

High-performance

Redis and Memcached

Fully managed; Zero admin

Highly Available and Reliable

Hardened by Amazon

AmazonElastiCache

AmazonRDS

Amazon S3

Request RateHigh Low

LatencyLow High

Data VolumeLow High

AmazonGlacier

AmazonCloudSearch

Stru

ctur

eLow

High

AmazonDynamoDB

AmazonElastiCache

HDFS

ElastiCache - Customer Value

Extreme Performance

Sub-millisecond access latencies

Engineered for Cloud Scale

Open Source Compatible

Compatible with Redis and

Memcached

Existing code will work when you

update node end points

Fully Managed

Automates tasks such as failed node

replacement, software patching,

upgrades and backups

CloudWatch enables you to monitor cache performance

metrics

Secure and Hardened

Supports Amazon VPC and IAM for secure and fine grained access.

Monitors your nodes and applies security patches when necessary

Highly Available and

Scalable

Multi-AZ with automatic failover to

a read replica, no human intervention

required.

Easily scale your Redis (vertically) and Memcached

(horizontally) environments

Cost Effective

Pay as low as 17 cents per hour. Get

started with 750 free hours per

month of a micro node for a year.

No cross availability zone data transfer

costs.

Memcached

Slab allocator

In-memory key-value datastore very popular as a caching solution

Supports strings, objects

Multi-threaded

Insanely fast!

Very established

No persistence

Patterns for sharding

Redis – the in-memory king

Powerful ~200 commands

In-memory data structure server

Utility data structuresstrings, lists, hashes, sets, sorted sets, bitmaps & HyperLogLogs

Simple

Atomic operationssupports transactionshas ACID properties

Ridiculously fast!<1ms latency for most commands

Highly Available

Persistentsnapshots or append-only log

Open Source

Why Memcached and Redis?

Source: http://db-engines.com/en/ranking/key-value+store

Deploying ElastiCache for

ElastiCache with Redis - Development

Region

Availability Zone A Availability Zone B

Auto Scaling group

ElastiCache cluster

Nope

Prim

ary


Rep

lica

Rep

lica

writesUse Primary Endpoint

readsUse Read Replicas

Auto-Failover Chooses replica with

lowest replication lag DNS endpoint is same

Snapshots

ElastiCache for Redis Multi-AZ

ElastiCache for Redis



Automatic Failover to a read replica in case of primary node failure

ElastiCacheAutomatessnapshots for persistence

ElastiCache with Redis Multi-AZ

Region


Auto Scaling group

ElastiCache cluster

Redis – Read/Write Connections

Create Snapshot

Restore Snapshot

Key Use Patterns

Use Case #1 - Caching

Elastic LoadBalancing EC2 App

InstancesRDS MySQL DB Instance

ElastiCache

Database Writes

App Reads

ClientsCacheUpdates

Database Reads

Amazon ElastiCache

Eliminate database hotspots

Predictable Performance

Cut Load on Backend

Increase Read Throughput

Reduce App Latency

Caching Will Make Your Database More Efficient

Reduce Database Cost

Common Caching Technique #1 – Lazy Caching:

Adding Caching to Your Application is Easy

Common Caching Technique #2 – Write-back caching:

Adding Caching to Your Application is Easy

Not if I destroy it

first!It’s

mine!

Very popular for gaming appsNeed uniqueness + orderingEasy with Redis Sorted Sets

ZADD "leaderboard" 1201 "Gollum”ZADD "leaderboard" 963 "Sauron"ZADD "leaderboard" 1092 "Bilbo"ZADD "leaderboard" 1383 "Frodo”

ZREVRANGE "leaderboard" 0 -11) "Frodo"2) "Gollum"3) "Bilbo"4) "Sauron”

ZREVRANK "leaderboard" "Sauron"(integer) 3

Use Case 2 - Real-time Leaderboard

Use Case 3 - Chat and Messaging

• PUBLISH and SUBSCRIBE Redis commands• Game or Mobile chat, real-time comment streams• Server intercommunication

SUBSCRIBE chat_channel:114PUBLISH chat_channel:114 "Hello all">> ["message", "chat_channel:114", "Hello all"]UNSUBSCRIBE chat_channel:114

• Popular for recommendation engines and message board ranking• Redis counters – increment likes/dislikes• Redis hashes – list of everyone’s ratings• Process with algorithm like Slope One or Jaccardian similarity• Ruby example - https://github.com/davidcelis/recommendable

Use Case 4 – Ratings

INCR item:38927:likesHSET item:38927:ratings "Susan" 1

INCR item:38927:dislikesHSET item:38927:ratings "Tommy" -1

https://github.com/davidcelis/recommendable

Ex: Throttling requests to an APILeverages 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 + ":” + timecount = 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

Use Case 5 - Rate Limiting

Tune It Up!

AmazonCloudWatch

Alarms

Monitoring with CloudWatch

• Easily Accessible via the ElastiCache console

• Track health of your nodes

• Set alarms to act when need to address running into limitations

Key ElastiCache CloudWatch Metrics

• CPUUtilization• Memcached – up to 90% ok• Redis – divide by cores (ex: 90% / 4 = 22.5%)

• SwapUsage low• Evictions low• CacheMisses / CacheHits Ratio low• CurrConnections stable

Common Issues

Thundering Herd

Causes• Cold cache – app startup• Adding / removing nodes• Cache key expiration (TTL)• Out of cache memory

Large # of cache misses Spike in database load

Mitigations• Script to populate cache• Gradually scale nodes• Randomize TTL values• Monitor cache evictions

1. Forks main Redis process2. Writes backup to disk from child process3. Continues to accept traffic on main process4. Any key update causes a copy-on-write5. Potentially DOUBLES memory usage by Redis

Swapping During Redis Backup (BGSAVE)

Reduce memory allocated to Redis• Set reserved-memory field in parameter groups • Decreases node memory available for app

Use larger cache node type• More expensive• But no data eviction

Write-heavy apps need extra memory http://bit.ly/elasticache-bgsave

Swapping During Redis Backup – Mitigations

http://bit.ly/elasticache-bgsave

http://bit.ly/elasticache-bgsave

Redis reserved-memory Parameter

Recap

• In-memory data store can help address the most demanding application requirements, as well as protect from impact of spikes in app access.

• ElastiCache is a reliable, secure and fully-managed, performance-optimized in-memory data structure service.

• Use Multi-AZ with automatic failover for production workloads.

• Redis provides powerful capabilities for a variety of in-memory use cases

• For much more detail on setting up and using ElastiCache please see our whitepaper (google “ElastiCache whitepaper”)

Free tier: 750 hours of Micro Cache Node per Month

Pay as little as $0.017 per hour thereafterfor a T2.micro node

You can get started for free

Thank you!

integrating amazon elasticache into your database stack - aws may 2016 webinar series

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