Kevin McGehee

This session delves into the intricacies of Amazon ElastiCache data modeling using the purpose-built Valkey data types to optimize application performance and scalability.

Modern algorithmic trading platforms deploy fleets of specialized AI agents, including market analysts, risk assessors, order executors, and compliance monitors, that must coordinate in real time without conflict.

Semantic caching uses vector similarity search to retrieve cached LLM responses for semantically equivalent queries, reducing inference latency and cost in agentic AI architectures.

LLM inference depends on limited GPU memory, and a KV cache lets agentic AI applications reuse computed intermediate states across prompts to reduce latency and costs.

This session delves into the intricacies of Amazon ElastiCache data modeling using the purpose-built Valkey data types to optimize application performance and scalability.

Caching can dramatically improve the performance of your application, and the cache can often become a critical component of data architecture. In this chalk talk, learn how to build a highly available Amazon ElastiCache solution.

In this builders' session, you will create a high-performance, real-time, geospatial alerting pipeline using Amazon ElastiCache for Valkey. This architecture pattern is tailored for dynamic applications like ridesharing, logistics, and fleet management.

This session delves into the intricacies of Amazon ElastiCache data modeling using the purpose-built Valkey data types to optimize application performance and scalability.

Imagine a world where every customer call is answered instantly, issues are resolved swiftly without any human intervention, and the entire experience feels personal and seamless.

Amazon MemoryDB for Redis provides in-memory performance while using a highly available, distributed transaction log to help ensure data is persisted across multiple Availability Zones.

Developers building applications that require high performance on a massive scale use microservices because they are easier to deploy, manage, and scale. These developers often use Redis, Stack Overflow’s “most loved” database for five consecutive years, because it’s lightning-fast and offers flexible data structures to quickly build applications.

The Amazon ElastiCache team has been hard at work innovating on your behalf. In this session, learn about the work the team did in 2020 to make sure that ElastiCache cloud service is cost-effective and provides exceptional performance for Redis and Memcached.

With the explosive growth of business-critical, real-time applications built on Redis, availability, scalability, and security have become top considerations. Learn best practices for setting up your Amazon ElastiCache for success with online scaling, high availability across multiple Availability Zones, and security configurations from our fully managed service.

We have seen our customers follow an adoption curve with Redis. Initially used to accelerate database access, Redis quickly becomes a repository for valuable business information.