Category: Serverless

Organizations require systems and mechanisms in place to gather and analyze large amounts of data as it is created, in order to get insights and respond in real time. Stream processing data technologies enable organizations to ingest data as it is created, process it, and analyze it as soon as it is accessible. In this […]

In this post, we discuss an automotive manufacturing information management use case where we store information about components within a vehicle as well as the hierarchy between each of the components. For our automotive use case, we use Amazon DynamoDB to deliver transactional queries, such as component attribute lookups. We will also show you how to use DynamoDB for larger responses such as a recursive query for all the components in a vehicle. While recursive object relationships can be represented in graph databases and possibly traditional RDBMS (with complex joins), these deeper queries can also be represented in DynamoDB.

January 2024: This post was reviewed and updated for accuracy. When Amazon Aurora Serverless v1 came out, it was one of the most exciting new features of 2018. The ability to have a relational database without having to worry about paying for idle compute, and without having a poor user experience due to periods of […]

In this post, you learn about Aurora Serverless v2 databases and factors to consider when replacing provisioned instances with Aurora Serverless v2 instances. Amazon Aurora Serverless allows you to use Amazon Aurora MySQL-Compatible Edition and Amazon Aurora PostgreSQL-Compatible Edition without worrying about the management of the compute for your application database. Many organizations today are […]

Amazon Aurora Serverless is an on-demand, auto scaling configuration for Aurora. It scales the capacity up or down based on your application’s needs. It enables you to run your database in the cloud without managing any database capacity. Aurora Serverless v2 supports Amazon Aurora Global Database , Multi AZ, AWS Identity and Access Management (IAM) […]

Message queues allow different parts of a system to communicate and process operations asynchronously. Amazon Simple Queue Service (Amazon SQS) is a fully managed message queueing service that offers two types of message queues: standard queues and first-in-first-out (FIFO) queues. For some applications, such as a call center application, you need message filtering along with […]

The business problem of real-time data aggregation is faced by customers in various industries like manufacturing, retail, gaming, utilities, and financial services. In a previous post, we discussed an example from the banking industry: real-time trade risk aggregation. Typically, financial institutions associate every trade that is performed on the trading floor with a risk value […]

The collection, aggregation, and reporting of large volumes of data in near real time is a challenge faced by customers from many different industries, like manufacturing, retail, gaming, utilities, and financial services. In this post, we present a serverless aggregation pipeline in AWS. We start by defining the business problem, introduce a serverless architecture for […]

January 2024: This post was reviewed and updated for accuracy. Storing user names and passwords directly in applications is not a best practice. Saving credentials as plaintext should never occur in a secure application. As a solution, AWS Identity and Access Management (IAM) policies can assign permissions that determine who is allowed to manage Amazon […]

Amazon Aurora Serverless is an on-demand, automatically scaling configuration for Amazon Aurora (MySQL-compatible edition). The database automatically starts up, shuts down, and scales capacity based on your application’s needs. It enables you to run your database in the cloud without managing any database instances. It’s a simple, cost-effective option for infrequent, intermittent, or unpredictable workloads. Recently, AWS announced […]