AWS Partner Network (APN) Blog
Author: Anubhav Sharma
Anubhav Sharma is a Principal Solutions Architect at AWS with over 2 decades of experience in coding and architecting business-critical applications. Known for his strong desire to learn and innovate, Anubhav has spent the past 6 years at AWS working closely with multiple independent software vendors (ISVs) and enterprises. He specializes in guiding these companies through their journey of building, deploying, and operating SaaS solutions on AWS.
Reimagining Vector Databases for the Generative AI Era with Pinecone Serverless on AWS
Pinecone has developed a novel serverless vector database architecture optimized for AI workloads like retrieval-augmented generation. Built on AWS, it decouples storage and compute and enables efficient intermittent querying of large datasets. This provides elasticity, fresher data, and major cost savings over traditional architectures. Pinecone serverless removes bottlenecks to building more knowledgeable AI applications economically at scale on AWS.
Building a Multi-Tenant SaaS Solution Using AWS Serverless Services
The move to a SaaS delivery model is accompanied by a desire to maximize cost and operational efficiency. This can be especially challenging in a multi-tenant environment where the activity of tenants can be difficult to predict. In this post, AWS experts look into a reference solution that provides an end-to-end view of a functional multi-tenant serverless SaaS environment. The goal is to explore the architecture and design considerations that went into creating this reference solution.
Capturing and Visualizing Multi-Tenant Metrics Inside a SaaS Application on AWS
As a SaaS provider, it’s essential to have a clear picture of how tenants are exercising your system. Being able to model the functional and operational profile of tenants and tenant tiers is critical to evolving the business and technical strategies of a SaaS organization. Learn about the role metrics play within a SaaS-based application, and dive deep into a solution that provides all of the infrastructure that will support the ingestion, aggregation, and analysis of SaaS metric data.
Partitioning Pooled Multi-Tenant SaaS Data with Amazon DynamoDB
As you design, develop, and build SaaS solutions on AWS, you must think about how you want to partition the data that belongs to each of your customers (tenants). In this post, experts from AWS SaaS Factory focus on what it means to implement the pooled model with Amazon DynamoDB. We’ll outline basic strategies to partition and isolate data by tenant, and illustrate common techniques you can use to avoid the “hot” partition problem that’s often associated with partitioning tenant data in a pooled model.
In-Depth Strategies for Building a Scalable, Multi-Tenant SaaS Solution with Amazon Redshift
Software-as-a-Service (SaaS) presents developers and architects with a unique set of challenges. One essential decision you’ll have to make is how to partition data for each tenant of your system. Learn how to harness Amazon Redshift to build a scalable, multi-tenant SaaS solution on AWS. This post explores trategies that are commonly used to partition and isolate tenant data in a SaaS environment, and how to apply them in Amazon Redshift.