@riferrei | #oraclecodeone | @CONFLUENTINC Keep your caches hot with apache kafka® and the connector api [dev1346] @riferrei | @oraclecodeone | @CONFLUENTINC

KS19Meetup. CONFLUENT COMMUNITY DISCOUNT CODE 25% OFF*

About Us: ● Ricardo Ferreira ❑ Developer Advocate @ Confluent ❑ Ex-Oracle, Red Hat, IONA Tech ❑ [email protected] ❑ https://riferrei.net ● Alexa (amazon echo) ❑ The voice behind Amazon ❑ Ex-Raspberry Pi, Arduino ❑ She is a female in character! @riferrei @alexa99

@riferrei | @oraclecodeone | @CONFLUENTINC Data is only useful if it is fresh and contextual

Airbag systems are made out of three key components: ● The bag itself ● The sensors which detects when there is a collision probability based on speed ● The inflation system, which does combine the chemical compounds (sodium azide and potassium nitrate) to make gas to inflate the bag What if the airbag deploys 30 seconds after the collision?

@riferrei | @oraclecodeone | @CONFLUENTINC Caches are great to keep data fresh

Apis need to access large amounts data freely and easily ● Data should never be the scarce resource of apis ● Latency should be kept as minimal as possible ● Data should not be static: keep data always updated ● Find ways to handle large amounts of data easily Cache API Read Write Read Write

Caches can be built-in or distributed caches Cache API Built-in Caches Cache API Distributed Caches Cache Cache Read Write Read Write ● If data can fit into the api memory space, use built-in ● Use distributed caches for large amounts of data ● Some cache implementations provide both options ● For distributed caches, make sure to use one that has o(1) retrieval time

@riferrei | @oraclecodeone | @CONFLUENTINC Why apache kafka?

10 01 Messaging done right 02 Stream processing 03 Persistent storage @riferrei | @oraclecodeone | @CONFLUENTINC

Time for fun

@riferrei | @oraclecodeone | @CONFLUENTINC

@riferrei | @oraclecodeone | @CONFLUENTINC Caching patterns

Caching pattern: refresh ahead ● Proactively keep the cache updated with the last state ● Keep the entries always in- sync for better consistency ● Ideal for latency sensitive use cases such as apis ● Ideal for when the data is costly to get from backend ● It may need data loading Kafka Connect Cache Kafka Connect API

Caching pattern: refresh ahead/adapt ● Proactively keep the cache updated with the last state ● Keep the entries always in- sync for better consistency ● Ideal for latency sensitive use cases such as apis ● Ideal for when the data is costly to get from backend ● It may need data loading Kafka Connect Cache Kafka Connect Transform and adapt records before delivery Schema Registry for canonical models API

Caching pattern: write behind ● Removes i/o pressure from the api, allowing scalability ● True horizontal scalability ● Ensures event ordering and persistence (replayability) ● Minimizes database code complexity from the api ● Handles database failures beautifully via replication Kafka Connect Cache Kafka Connect API

Caching pattern: write behind/adapt ● Removes i/o pressure from the api, allowing scalability ● True horizontal scalability ● Ensures event ordering and persistence (replayability) ● Minimizes database code complexity from the api ● Handles database failures beautifully via replication Kafka Connect Cache Kafka Connect Transform and adapt records before delivery API Schema Registry for canonical models

Caching pattern: event federation ● Replicates data across regions across the globe ● Keep multiple regions in-sync ● Great to improve rto / rpo ● Handles network slowness ● While keeping disparate clusters in-sync, it also allows the caches to be global as well Confluent Replicator

@riferrei | @oraclecodeone | @CONFLUENTINC Kafka connect implementation strategies

Kafka connectors for popular caches ● Connector for redis and is available on confluent hub ● Connector for Memcached is available on confluent hub ● Connector for gridgain and apache ignite are available ● Connector for infinispan is available for red hat users Kafka Connect Kafka Connect Kafka Connect Kafka Connect

some caches may need different strategies ● Oracle provides hotcache for golden gate and coherence ● Hazelcast has the jet sdk which supports connect ● Pivotal gemfire and apache geode has the spring data ● Good news: you can always write your own connectors using the connector api Golden gate Hazelcast Jet Spring data Connect Framework Any Cache

Want to convert your database to streams? ● Meet debezium: a plataform to perform database cdc ● Works in a log level, which means true cdc behavior for your projects ● Open-source and maintained by red hat. Has a broad set of connectors available ● It is built on kafka connect

@riferrei | #oraclecodeone | @CONFLUENTINC

No content