Author: Tod Golding

Building multi-tenant systems can represent a major effort for some teams. This post focuses on introducing strategies that allow developers to write their day-to-day code without having to think about how tenancy might influence their implementation. AWS Lambda Layers allow SaaS architects to centralize tenant-aware libraries without impacting the size or load-time of your application’s functions.

With Amazon Keyspaces, AWS has enabled SaaS providers to run their Apache Cassandra workloads using a fully managed, serverless offering. This option allows you to leverage the strengths of Cassandra while getting all of the scale, cost, reliability, and operational efficiency that comes with a managed model. Learn how Amazon Keyspaces can be used to store data in a multi-tenant architecture and review common models for partitioning each tenant’s data.

The AWS SaaS Factory team had the chance to work with Ridgeline, a privately funded fintech startup determined to modernize investment management software, and help build their purpose-built enterprise platform on AWS. We speak with Chris Petrunik, Director of Engineering at Ridgeline, to learn how their platform works and what advice they have for other businesses building SaaS solutions on AWS.

Tenant isolation is fundamental to the design and development of SaaS systems, enabling providers to reassure customers their resources cannot be accessed by other tenants. While the importance of isolation is well understood, the strategies for realizing a robust isolation model vary significantly. Learn how our new SaaS Tenant Isolation Strategies whitepaper assembles a collection of best practices and considerations that often shape your approach to implementing isolation in a SaaS environment.

With the introduction of Amazon Aurora Serverless (currently in preview), SaaS providers are now equipped with a model to bring the scale and cost efficiency of serverless computing directly to storage partitioning models of SaaS solutions. We take a closer look at how Aurora Serverless works and how it influences your approach to storage partitioning in SaaS environments. The goal here is to highlight the implications of the serverless storage model, identifying key areas that will be of particular interest to SaaS developers.

We are excited to introduce AWS SaaS Factory to help accelerate and guide the adoption of a Software-as-a-Service (SaaS) delivery model on AWS. The program offers a comprehensive set of business and technical best practices, as well as engagement opportunities that empower and support ISVs building SaaS offerings on AWS. The focus is on helping customers and APN Partners at all stages of the SaaS on AWS journey.

As SaaS organizations grow and begin to extend their global reach, they must consider how their larger geographic footprint will shape and influence the architecture of their systems. Operations, deployment, agility, security, and scale all can be impacted by the move to a geographically distributed SaaS model. The more complexity that is added to a system’s operational and deployment profile, the more challenging it becomes to maintain the agility goals that are often associated SaaS delivery models.

Networking is often viewed as a foundational element of a system’s architecture. The reality is there are plenty of scenarios where the networking footprint of a SaaS application can influence the functionality, extensibility, and management profile of your SaaS environment. While there are plenty of creative ways developers leverage AWS networking constructs to refine SaaS solutions, the introduction of AWS PrivateLink adds new opportunities in the SaaS networking landscape.

SaaS solutions often present architects with a diverse mix of scaling and optimization requirements. With SaaS, your application’s architecture must accommodate a continually shifting landscape of customers and load profiles. The number of customers in the system and their usage patterns can change dramatically on a daily—or even hourly—basis. These dynamics make it challenging for SaaS architects to identify a model that can efficiently anticipate and respond to these variations.

In traditional single-tenant environments, calculating and aggregating infrastructure costs is a pretty straightforward exercise. Typically, each application or customer has its own collection of dedicated resources and tallying the costs is simply a matter of categorizing and summing those costs. However, in multi-tenant SaaS environments, this becomes a much more challenging problem. With SaaS, tenants often share some or all of a system’s infrastructure resources.