Category: SaaS

In this series of posts, we walk through the process of creating a DynamoDB data model using an example multi-tenant application, a customer issue tracking service. The goal of this series is to explore areas that are important for decision-making and provide insights into the influences to help you plan your data model for a multi-tenant application. In this last part of the series, we explore how to validate the chosen data model from both a performance and a security perspective. Additionally, we cover how to extend the data model as new access patterns and requirements arise.

In this series of posts, we walk through the process of creating a DynamoDB data model using an example multi-tenant application, a customer issue tracking service. The goal of this series is to explore areas that are important for decision-making and provide insights into the influences to help you plan your data model for a multi-tenant application. In this post, we continue the design process, selecting a partition key design and creating our data schema. We also show how to implement the access patterns using the AWS Command Line Interface (AWS CLI).

In this series of posts, we walk through the process of creating a DynamoDB data model using an example multi-tenant application, a customer issue tracking service. The goal of this series is to explore areas that are important for decision-making and provide insights into the influences to help you plan your data model for a multi-tenant application. In this post, we define the access patterns and decide on the table design.

In this post we introduce a solution that addresses a common challenge faced by many customers: managing costs in multi-tenant applications, particularly for shared databases in Amazon Relational Database Service (Amazon RDS) and Amazon Aurora. This solution uses Amazon RDS Performance Insights and AWS Cost and Usage Reports (CUR) to addresses this challenge. This allows for efficient grouping of tenants within the same RDS or Aurora instances, while helping you implement accurate chargeback models, optimize resource-intensive workloads, and make data-driven decisions for capacity planning.

In this post, we explore approaches that address operating Amazon Neptune in a multi-tenant SaaS environment, as well as the considerations that may influence how and when to apply these strategies depending on your tenant needs.

This post is a continuation of our series on scaling your relational database for software as a service (SaaS). SaaS providers commonly use relational databases, such as Amazon Relational Database Service (Amazon RDS) and Amazon Aurora, in their solutions. In Part 1, we looked at some common ways to scale or optimize your relational database […]

One of the challenges that software as a service (SaaS) providers face as their business grows is how to maintain their tenants’ experience. This includes ensuring acceptable performance and response times as the tenant base grows. Relational databases, such as Amazon Relational Database Service (Amazon RDS) and Amazon Aurora, are commonly used by SaaS providers. […]