It can now support enterprises with thousands of applications that want to manage database capacity across the board, including multi-tenant environments supporting different customers. So, why is v2 important? Are customers in need of increased capabilities at a lower cost rate, or increased speeds, or better controls? It’s actually all of the above! While v2 provides the full breadth of Aurora’s capabilities, the exciting news is that it will scale to hundreds of thousands of transactions in a fraction of a second, delivering up to 90% cost savings compared to provisioning for peak capacity. Source: Future-proofing your database workloads with Aurora Serverless When Aurora Serverless adds new resources to the Aurora DB cluster, it uses the router fleet to switch active client connections to the new resources. The underpinnings of what the serverless aspects bring to bear in Aurora are seen in the following diagram.įigure 1: Shows how Aurora manages the warm pool of resources in an AWS Region to minimize scaling time. We help them by taking the Aurora Serverless route while modernizing their overall solution. Our ad content and consumer influencer customers have been trying to get ahead of the curve and started asking about better ways to cost-optimize their Aurora clusters. Development and test databases. Databases can automatically shut down when not in use and start much more quickly.Variable, infrequently used applications. No need to provision for peak capacity - you only pay for the database resources you consume.The highly popular Aurora Serverless v1 is ideal for use cases such as: And, of course, you pay only for what you use. Since it’s a fully managed service, you’ll save time because Aurora Serverless handles updating, upgrading, and provisioning for you. It automatically starts up, shuts down, and scales capacity based on your application’s needs, eliminating manual database management. With these tremendous capabilities and thousands of customers, Aurora Serverless stitches together an on-demand, cost-effective option for infrequent, intermittent, or unpredictable workloads. The database management and administration features are derived from Amazon RDS. With some workloads, Aurora provides up to five times better performance than MySQL and up to three times the throughput of PostgreSQL without requiring changes to most of your existing applications. Aurora and Aurora Serverless overviewĪurora is a fully managed MySQL and PostgreSQL-compatible relational database engine. Then I’ll describe how v2 can help future-proof your database workloads. In this blog, I’ll begin with a brief overview of Aurora and Aurora Serverless. The Aurora Serverless v2 preview can easily be accessed by filling out the following form: On December 1 at AWS re:Invent 2020, AWS announced Amazon Aurora Serverless v2 availability in preview for the MySQL 5.7-compatible edition of Amazon Aurora (Aurora). Make sure PG Server is running and then run the Docker cmd: docker run -d -rm -it -name my-data-api -p 8080:80 -e ENGINE=PostgreSQLJDBC -e POSTGRES_HOST= Kireet Kokala, VP Big Data & Analytics at nClouds If you run a local DB and want to develop locally the options.endpoint to run locally works great with the Docker container koxudaxi/local-data-api. ResourceArn: _AURORA_DATA_API_ARN || '',ĭatabase: _AURORA_DATA_API_DB || '', SecretArn: _AURORA_DATA_API_SECRET_ARN || '', const dataApiClient = require('data-api-client') Or to use a "wrapper" package which we opted for with the data-api-client. Somewhat old question but the answer is to either use the AWS.RDSDataService() from the AWS SDK.
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