Category: Customer Solutions

In this post, you will learn how CRED built an automated orchestration framework around Amazon RDS blue/green deployments. The framework performs engine upgrades, instance scaling, storage optimization, and Change Data Capture (CDC) pipeline migration across their entire fleet. This approach achieved zero data loss incidents and zero production incidents.

In this post, we share how Securonix migrated hundreds of Amazon ElastiCache clusters from Redis OSS to Valkey, achieving a 20% reduction in caching costs. This amounts to over $100,000 in annualized savings. The migration also improved CPU utilization and overall throughput across Securonix’s global SIEM platform, which processes hundreds of terabyte data volumes daily for enterprise security teams worldwide.

Managing massive data volumes at scale presents significant operational challenges. At Similarweb we faced these challenges with Apache HBase and found a solution in Amazon DynamoDB. Similarweb is a digital intelligence platform that provides AI-powered insights into website traffic, app usage, and market trends to help businesses benchmark competitors and optimize growth strategies. We faced growing scalability and operational complexity issues with our existing Apache HBase infrastructure, which prompted us to explore more flexible and efficient alternatives. This post walks you through our journey migrating our data storage from Apache HBase to DynamoDB. We discuss the technical challenges, migration approach, data modeling strategies, cost optimization techniques, and key benefits achieved along the way.

Amazon receives millions of visits every day, and earning each customer’s trust visit after visit is the foundation that the store is built on. A meaningful part of that trust comes down to whether the recommendations we surface feel relevant and whether they reflect what the customer actually cares about in the moment. In this post, we describe an architecture that makes it achievable. Amazon SageMaker hosts a sentence transformer model on a managed endpoint and turns customer query text into dense semantic vectors. Valkey is an open source, in-memory data store with built-in vector search. It’s available on AWS through Amazon ElastiCache and Amazon MemoryDB. In our architecture, we use Amazon-managed Valkey to store the product catalog as a vector index.

In this post we demonstrate how Nine Entertainment achieved a 98% cost reduction by migrating to Amazon ElastiCache Serverless for Valkey while improving scalability and eliminating manual intervention during peak events.

In this post, you learn how HotelTrader reduced inter-availability zone data transfer costs by 95% and improved average latency by 49% by migrating from the Redis Lettuce client to Valkey GLIDE on Amazon ElastiCache. The post walks through how HotelTrader identified hidden cross-AZ data transfer costs in their multi-AZ ElastiCache cluster, implemented Valkey GLIDE’s AZ-affinity read strategy to route requests to local replicas, optimized throughput with request batching, and executed a zero-downtime migration using A/B testing over 15 days.

In this post, we show you how Kajabi navigated complex Aurora PostgreSQL database upgrades and achieved an 80.53% cost reduction through strategic planning and technical execution. You’ll discover their hybrid approach combining Amazon Aurora blue/green deployments with PostgreSQL native replication. You’ll also learn about their implementation of Aurora I/O-Optimized storage and the key lessons from their journey. Whether you’re managing large-scale databases or planning your own upgrade path, Kajabi’s experience offers valuable insights. You’ll see how to balance performance requirements with cost optimization while maintaining continuous availability.

In this post, we share Ring’s billion-scale semantic video search on Amazon RDS for PostgreSQL with pgvector architectural decisions vs alternatives, cost-performance-scale challenges, key lessons, and future directions. The Ring team designed for global scale their vector search architecture to support millions of customers with vector embeddings, the key technology for numerical representations of visual content generated by an AI model. By converting video frames into vectors-arrays of numbers that capture what’s happening (visual content) in each frame – Ring can store these representations in a database and search them using similarity search. When you type “package delivery,” the system converts that text into a vector and finds the video frames whose vectors are most similar-delivering relevant results in under 2 seconds.

In this post, we provide a guide to migrating from Redis OSS to ElastiCache for Valkey, incorporating different migration strategies and AWS best practices. Additionally, we highlight a customer’s successful migration to Valkey, which maintained their robust performance standards while achieving a 20% reduction in ElastiCache cluster costs.

Dutchie, a leading technology platform serving the cannabis industry, manages critical operations for thousands of dispensaries across multiple states, processing millions of transactions annually. In this post, we explore how Dutchie successfully navigated the challenges of migrating mission-critical workloads to Amazon RDS for SQL Server in preparation for 4/20 week in 2025.