![]() A database instance can either be a provisioned instance, db.t4g.medium for example, or a serverless instance. Next, you add database instances to the cluster. ![]() You start by creating an Aurora cluster to configure and provision the storage layer. Luckily, AWS addressed both criticisms.Īurora Serverless v2 comes with support for multi-AZ and read replication. Also, the missing support for read replicas was a bummer. When reviewing Aurora Serverless v1, I could not believe AWS offered a database service that does not span multiple availability zones. In summary, Aurora Serverless brings a relational database closer to DynamoDB’s pay-per-request pricing model. Think about the enormous cost savings for workloads with high load peaks and significant idle periods. That’s a game-changer because you no longer need to provision database machines based on load peaks. The CPU and memory capacity automatically adapts to the current workload in the background without causing downtime. With Aurora Serverless, you can vertically scale a database machine. However, doing so causes a short downtime. The other option is to scale vertically by switching to a database machine with more CPU and memory. However, that works when scaling capacity for read requests only. Also, the storage layer replicates among availability zones.īut how to scale compute capacity of a relational database? One option is to add additional machines to the cluster, acting as read replicas. No more need to provision storage upfront. With Aurora, AWS provides a scalable and highly available storage layer for relational databases. Scaling relational databases was complicated. Reason enough to take a closer look at the new service.īefore we start, let me explain why Aurora Serverless is a big deal.ĭo you prefer listening to a podcast episode over reading a blog post? Here you go! Why is Aurora Serverless a big deal? Four years later, AWS is making a fresh start with Aurora Serverless v2. ![]() Therefore, I used Aurora Serverless in exceptional cases only. Unfortunately, the innovative service never achieved a breakthrough. Even after Aurora Serverless became a generally available service in August 2018, it missed important features like multi-AZ deployments and read replication. I was excited when AWS announced Aurora Serverless at re:Invent 2017.
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