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Unraveling the Complexities of Cost Per Tenant in SaaS

Unraveling the Complexities of Cost Per Tenant in SaaS

As a SaaS builder, one of the most pressing challenges you often face is accurately attributing costs to each tenant in your multi-tenant environment. Achieving precise cost attribution is crucial for various reasons, including understanding your cost of goods sold, optimizing pricing models, improving profitability, and gaining deep insights into your unit economics. However, there is no magic bullet solution to tackle this complex problem.

Anthony McClure
Amazon Employee
Published Oct 30, 2024
In the latest episode of "Building SaaS on AWS," our experts dive deep into this crucial topic, unveiling a comprehensive workshop that guides you through the process of attributing costs per tenant in your SaaS solution. Whether you're just starting to design and build multi-tenant applications or you're an experienced SaaS provider looking to optimize your existing solutions, this episode is an invaluable resource.
Throughout the show, our experts break down the problem statement and introduce key concepts that are essential for understanding the nuances of cost attribution in a SaaS environment. They explain the distinctions between the application plane and the control plane, as well as the differences between the silo model and the pooled model of tenant isolation. While attributing costs in a silo model is relatively straightforward using cost allocation tags, the real challenge lies in the pooled model, where tenants share resources.
To address this challenge, the workshop presents a systematic approach that involves making your shared resources tenant-aware. By injecting tenant context into your microservices and capturing relevant metrics, you can aggregate tenant usage data and apportion costs accordingly. The episode walks you through code examples that demonstrate how to extract tenant identifiers from JSON Web Tokens (JWT) and incorporate them into various AWS services, including AWS Lambda, Amazon API Gateway, Amazon DynamoDB, and Amazon ECS.
One of the key highlights is the use of AWS Lambda Extensions, which allow you to tap into the telemetry API and combine platform telemetry with function logs to generate tenant-aware platform reports. This approach enables you to capture fine-grained usage metrics, such as billing duration and maximum memory usage, on a per-tenant basis.
The workshop also covers strategies for attributing costs in containerized environments, where tenants share resources like Amazon ECS and Amazon Aurora PostgreSQL. By leveraging techniques like database user per tenant and Amazon RDS Performance Insights, you can associate database load and query statistics with individual tenants, providing you with a comprehensive view of your resource consumption.
But the workshop doesn't stop there. It also demonstrates how to visualize and analyze your cost per tenant data using powerful tools like Amazon Athena and Amazon QuickSight. By integrating with AWS's Cost and Usage Reports and leveraging the Cloud Intelligence Dashboards, you can create insightful visualizations that break down your overall AWS costs by tenant, service, and feature. These visualizations can be instrumental in driving informed decision-making, optimizing your pricing strategies, and improving your overall profitability.
Whether you're a seasoned SaaS builder or just embarking on your journey, this episode of "Building SaaS on AWS" is a must-watch. It not only equips you with the knowledge and tools to tackle the cost per tenant challenge but also serves as a valuable resource for understanding the intricacies of building and operating multi-tenant SaaS solutions on AWS.
Don't miss out on this invaluable opportunity to level up your SaaS game. Head over to the Video on Demand recording at https://youtu.be/OfwHIFNhYQ8 and immerse yourself in the wealth of knowledge shared by our AWS experts. Unlock the secrets of cost per tenant attribution and take your SaaS solution to new heights of efficiency and profitability.
 

Any opinions in this post are those of the individual author and may not reflect the opinions of AWS.

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