October 2021 Summaries

Next.js Edge functions, recently announced by the Vercel team, enable developers to execute code globally at locations closest to users, reducing latency and eliminating cold starts through the use of V8 Isolates. These functions are akin to serverless functions run on CDN infrastructure, offering significant performance improvements for applications with global reach. The process of getting started with Next.js Edge involves creating a Next.js application, setting up a Redis database using Upstash, and developing an edge function to deliver location-based custom greetings. The application, once deployed to Vercel, demonstrates the ability to serve personalized content with low latency by fetching data from the nearest server. Upstash Redis enhances this functionality by providing a globally optimized data service tailored for edge functions, helping developers build fast and responsive applications.

Upstash embarked on its mission to be an optimal database for AWS Lambda functions, but it identified an opportunity to serve Cloudflare Workers, which offer global low-latency execution but lack stateful data management. To solve this, Upstash developed solutions like a REST API tailored for Cloudflare Workers and edge caching, which significantly improved performance by caching Redis® REST responses at edge locations. However, edge caching presented limitations like stale data and support only for REST API, prompting Upstash to introduce a Global Database solution that replicates data across multiple AWS regions, offering eventual consistency without cache-invalidation issues and making it a suitable option for both read and write operations. Upstash's Global Database is designed to minimize read latencies while edge caching is recommended for cases where caching is sufficient, with the possibility of combining both solutions for optimal performance. Looking ahead, Upstash plans to enhance its architecture for low-latency writes and expand its capabilities by introducing Kafka support to facilitate use cases such as clickstream analysis and serverless function logging.

Upstash has launched a Global Database designed to optimize low-latency read operations for serverless and edge computing environments by deploying replicas across multiple global regions. This database utilizes a single leader replication model where a leader replica processes write requests and propagates them to backup replicas, with a gossip-based communication protocol managing cluster membership and failure detection. Although this setup provides weak consistency and may result in stale reads, it enhances read scalability by allowing any replica to handle read requests. The system employs a last-write-wins algorithm to resolve conflicts arising from network partitions, and learner replicas, which are read-only and unsuitable for leadership, are used to expand edge locations without causing write conflicts. Currently, the focus is on minimizing read latency rather than handling write-heavy loads, with plans to improve write latency and expand the number of regions in response to user feedback.