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Confluent, an AWS ISV Partner with Data & Analytics Competency and Service Ready designations in Amazon Redshift, AWS PrivateLink, and AWS Outposts, offers a platform for managing real-time data streams. Founded by the creators of Apache Kafka, Confluent enables organizations to handle data in motion seamlessly across on-premises environments and AWS.
In this article, we will explore how a logistics and inventory system can achieve microsecond read performance through the combined power of Amazon ElastiCache for Redis and durable streaming with Confluent Cloud Kafka. This approach can be adapted for various streaming applications, particularly those requiring asynchronous low-latency reads. For instance, while Apache Kafka can consume records in approximately 20-30ms (for a 1 KB JSON), ElastiCache can perform read operations in just 0.352-0.713ms, making it, on average, 47 times faster than Kafka.
We will illustrate a scenario aimed at reducing an e-commerce website’s page load time to half a second or less. In such instances, minimizing every millisecond is crucial. Amazon ElastiCache ensures rapid data retrieval, while Confluent guarantees data persistence.
Solution Overview
Amazon ElastiCache is a fully managed, scalable in-memory data store that delivers sub-millisecond latency. It supports two widely used data store engines: Memcached and Redis, with Redis being the preferred choice due to its ease of use, high availability, and support for advanced data structures.
Confluent Cloud is a robust, secure event streaming platform built on Apache Kafka. It allows both developers and operators to concentrate on application building rather than cluster management, offering fully managed Kafka services alongside additional tools for seamless integration.
As shown in Figure 1, users interact with various microservices via Amazon API Gateway, including an inventory service that utilizes ElastiCache for Redis to cache inventory and product detail lookups. The cache updates in near-real-time through a Confluent sink connector that monitors changes to topics within Confluent Cloud.
Building Blocks
Apache Kafka serves as an open-source platform for distributed event streaming, enabling organizations to create high-performance data pipelines and mission-critical applications. Confluent enhances Kafka’s capabilities through elastic scaling and offers two primary products:
- Confluent Platform: An enterprise-ready distribution of Apache Kafka.
- Confluent Cloud: A fully managed SaaS solution for Apache Kafka.
As a cloud-native service, Confluent Cloud provides a serverless experience with self-service provisioning, elastic scaling, and usage-based billing. Security features protect data, and the service’s reliability is supported by an enterprise-grade uptime SLA.
Many users leverage Amazon ElastiCache for caching purposes due to its simplicity as a key-value store. ElastiCache offers a high-performance, resizable, cost-effective in-memory solution, alleviating the complexities of distributing cache environments. It supports multiple built-in data structures, replication, eviction policies, and automatic failover for enhanced resiliency.
In this setup, caching can be implemented using Redis STRINGS in a key-value schema to minimize read latency from Kafka.
Motivation
In our example, a development team at a fictional company recently deployed a new inventory management and logistics system using Confluent Cloud on AWS. When new inventory arrives, it triggers events that publish messages to various Kafka topics, including the inventory topic. Multiple microservices subscribe to these Kafka topics based on their designated functionalities.
The e-commerce frontend relies on the inventory microservice to fetch product descriptions as customers browse pages, making page load times a critical performance metric. To address latency issues, the team considered adding a caching layer.
Investigation
The development team initially explored Apache Kafka Streams and Confluent’s ksqlDB to meet low latency requirements. However, they opted for a solution that aligned better with their expertise. The operations team sought a simplified method to integrate Kafka events into a familiar caching system. Ultimately, they turned to Amazon ElastiCache for Redis to minimize operational burdens but realized they needed a key component.
After researching Confluent’s connectors, they discovered the Confluent Redis sink connector, which enables them to observe the inventory Kafka topic in Confluent Cloud and sync those events to their Amazon ElastiCache cluster. This integration allows the e-commerce team to retrieve product details in under a millisecond, meeting their page load requirements. They found that the connector updates the cache in less than 30ms, ensuring customers always access data in near-real-time.
Solution
With all components finally integrated, the team established a real-time inventory system using fully managed Confluent Cloud while significantly enhancing e-commerce website inventory data reads through Amazon ElastiCache. Ultimately, the team learned about advanced access patterns in Redis that could optimize customer experiences and additional benefits beyond performance and scalability gained from using ElastiCache for Redis. Furthermore, they found that the flexibility of various data structures opened up new possibilities, such as real-time scoring systems utilizing SORTED SETS.
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