The Power of Event Driven Caches (Brendan Powers, Bloomberg L.P) Kafka Summit London 2019

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The Power of Event-Driven
Caches
Why caching is hard, and what you can do about it.
Kafka Summit London
May 13, 2019
Brendan Powers
Software Engineer
@brendan0powers

Who am I?

There are only two hard things in Computer Science:
cache invalidation and naming things.
-- Phil Karlton

Database Access
App DB

Cache Access Patterns
App
Cache
DB

“Thundering Herd” Problem
DBApp
Cache

DB

Concurrency
App App
?
Cache

Is the Data in My Cache Valid?
DBApp
Cache
???

Is the Data in My Cache Valid?
?? ?

Your Database is the Source of Truth
DB

Push Writes to the DB into the Cache
Cache
DB

Revised Architecture Diagram
Cache
App DB

Cache Instances are Consistent
DB
Cache
Cache
Cache

How do I get Change Notification from my DB?
Cach
e DB

Dual Writes
App
DB
Cache Kafka

Keep the Number of Write Paths Small
!
DB
Cache Kafka

Dealing With Partial Write Failure
DB
App
Cache Kafka

Change Data Capture (CDC)
DB App
Write Log

Change Data Capture (CDC)
DB
Write LogCache Kafka
App

Why Kafka?
● Durable
● Scalable
● Debuggable

Kafka’s Topic Offset Tracking
98765
DB
Cache
4321

Too Complicated?
Cache
App DB

Too Complicated?
DB
Cache
App

Recent Writes
User 1User 2User 1User 3User 2

Kafka Never Forgets...
. . . User 1User 2User 1User 3User 2

User 1User 2User 1User 3User 2

User 1
User 2
User 1
User 3User 2

User 1
User 2
User 1
User 3
User 2

User 2
User 1
User 3
User 2

User 1
User 3
User 2

User 1User 3User 2

Full Records
User 1{
“Id”: 492343,
“name”: “User 1”,
“Date_joined”, “05/05/1995”,
…...
}
User 2

DB

Cache

Cache
DB

Simplifying Our Design
DB
Cache
App

Simplifying Our Design
Cache
App DB

Fault Tolerant
Cache
App

Scale Independence
DB
Cache
Cache
Cache Cache
Cache

More Sleep, Less Phone Calls
App
Cache
DB

When to Use This Technique
● When your cache needs to be up to date
● When latency is very important
● When you need to give clients flexibility in their caching strategy

When NOT to Use This Technique
● When your data rarely changes
● When you data size is very large (100s of GB or TB)

How?
Cache
?

Store the Kafka Topic in a Hash Table
[ ]Cache

In RAM Inside Your Application
[ ]Cache

Too Big for RAM? Store it on Disk
App
[ ]Cache

A Cache in Every Instance
[ ]Cache
[ ]Cache
[ ]Cache

Out of Process Cache
App App App
[ ]Cache

[ ]Cache

CACHE!

Shard Your Data
A-I J-R S-Z
[ ]Cache
[ ]Cache
[ ]Cache

How Does the Application Find its Data?
App
[ ]Cache
[ ]Cache
[ ]Cache

Questions?

Kafka Connectors
● Debezium
● JDBC
● Dedicated connectors for MS SQL, Oracle, etc.

Will My Data Fit in RAM?
● How much RAM do you have?
● How big are your records?
● Do you have to cache the entire record?

Caches can Forward Requests
[ ]Cache
[ ]Cache
[ ]Cache
App

Use a Proxy
AppProxy
[ ]Cache
[ ]Cache
[ ]Cache

[ ]

[ ]
[ ] [ ]

[ ]
[ ] [ ]
?

[ ]
[ ]
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The Power of Event Driven Caches (Brendan Powers, Bloomberg L.P) Kafka Summit London 2019

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