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AWS Cloud service considerations for designing multi-tenant SaaS solutions



An increasing number of software as a service (SaaS) providers are considering the move from single to multi-tenant to utilize resources more efficiently and reduce operational costs. This blog aims to inform customers of considerations when evaluating a transformation to multi-tenancy in the Amazon Web Services (AWS) Cloud. You’ll find valuable information on how to optimize your cloud-based SaaS design to reduce operating expenses, increase resiliency, and offer a high-performing experience for your customers.

Single versus multi-tenancy

In a multi-tenant architecture, resources like compute, storage, and databases can be shared among independent tenants. In contrast, a single-tenant architecture allocates exclusive resources to each tenant.

Let’s consider a SaaS product that needs to support many customers, each with their own independent deployed website. Using a single-tenant model (see Figure 1), the SaaS provider may opt to utilize a dedicated AWS account to host each tenant’s workloads. To contain their respective workloads, each tenant would have their own Amazon Elastic Compute Cloud (Amazon EC2) instances organized within an Auto Scaling group. Access to the applications running in these EC2 instances would be done via an Application Load Balancer (ALB). Each tenant would be allocated their own database environment using Amazon Relational Database Service (RDS). The website’s storage (consisting of PHP, JavaScript, CSS, and HTML files) would be provided by Amazon Elastic Block Store (EBS) volumes attached to the EC2 instances. The SaaS provider would have a control plane AWS account used to create and modify these tenant-specific accounts.

Single-tenant configuration

Figure 1. Single-tenant configuration

To transition to a multi-tenant pattern, the SaaS provider can use containerization to package each website, and a container orchestrator to deploy the websites across shared compute nodes (EC2 instances). Kubernetes can be employed as a container orchestrator, and a website would then be represented by a Kubernetes deployment and its associated pods. A Kubernetes namespace would serve as the logical encapsulation of the tenant-specific resources, as each tenant would be mapped to one Kubernetes namespace. The Kubernetes HorizontalPodAutoscaler can be utilized for autoscaling purposes, dynamically adjusting the number of replicas in the deployment on a given namespace based on workload demands.

When additional compute resources are required, tools such as the Cluster Autoscaler, or Karpenter, can dynamically add more EC2 instances to the shared Kubernetes Cluster. An ALB can be reused by multiple tenants to route traffic to the appropriate pods. For RDS, SaaS providers can use tenant-specific database schemas to separate tenant data. For static data, Amazon Elastic File System (EFS) and tenant-specific directories can be employed. The SaaS provider would still have a control plane AWS account that would now interact with the Kubernetes and AWS APIs to create and update tenant-specific resources.

This transition to a multi-tenant design utilizing Kubernetes, Amazon Elastic Kubernetes Service (EKS), and other managed services offers numerous advantages. It enables efficient resource utilization by leveraging containerization and auto-scaling capabilities, reducing costs, and optimizing performance (see Figure 2).

Multi-tenant configuration

Figure 2. Multi-tenant configuration

EKS cluster sizing and customer segmentation considerations in multi-tenancy designs

A high concentration of SaaS tenants hosted within the same system results in a large “blast radius.” This means a failure within the system has the potential to impact all resident tenants. This situation can lead to downtime for multiple tenants at once. To address this problem, SaaS providers are encouraged to partition their customers amongst multiple AWS accounts, each with their own deployments of this multi-tenant architecture. The number of tenants that can be present in a single cluster is a determination that can only be made by the SaaS provider after weighing the risks. Compare the shared fate of some subset of their customers, against the possible efficiency benefits of a multi-tenant architecture.

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EKS security

SaaS providers must evaluate whether it’s appropriate for them to make use of containers as a workload isolation boundary. This is of particular importance in multi-tenant Kubernetes architectures, given that containers running on a single Amazon EC2 instance will share the underlying Linux kernel. Security vulnerabilities place this shared resource (the EC2 instance) at risk from attack vectors from the host Linux instance. Risk is elevated when any container running in a Kubernetes Pod cluster initiates untrusted code. This risk is heightened if SaaS providers permit tenants to “bring their code”. Kubernetes is a single tenant orchestrator, but with a multi-tenant approach to SaaS architectures, a single instance of the Amazon EKS control plane will be shared among all the workloads running within a cluster. Amazon EKS considers the cluster as the hard isolation security boundary. Every Amazon EKS managed Kubernetes cluster is isolated in a dedicated single-tenant Amazon VPC. At present, hard multi-tenancy can only be implemented by provisioning a unique cluster for each tenant.

EFS considerations

A SaaS provider may consider EFS as the storage solution for the static content of the multiple tenants. This provides them with a straightforward, serverless, and elastic file system. Directories may be used to separate the content for each tenant. While this approach of creating tenant-specific directories in EFS provides many benefits, there may be challenges harvesting per-tenant utilization and performance metrics. This can result in operational challenges for providers that need to granularly meter per-tenant usage of resources. Consequently, noisy neighbors will be difficult to identify and remediate. To resolve this, SaaS providers should consider building a custom solution to monitor the individual tenants in the multi-tenant file system by leveraging storage and throughput/IOPS metrics.

RDS considerations

Multi-tenant workloads, where data for multiple customers or end users is consolidated in the same RDS database cluster, can present operational challenges regarding per-tenant observability. Both MySQL Community Edition and open-source PostgreSQL have limited ability to provide per-tenant observability and resource governance. AWS customers operating multi-tenant workloads often use a combination of ‘database’ or ‘schema’ and ‘database user’ accounts as substitutes. AWS customers should use alternate mechanisms to establish a mapping between a tenant and these substitutes. This will give you the ability to process raw observability data from the database engine externally. You can then map these substitutes back to tenants, and distinguish tenants in the observability data.

Conclusion

In this blog, we’ve shown what to consider when moving to a multi-tenancy SaaS solution in the AWS Cloud, how to optimize your cloud-based SaaS design, and some challenges and remediations. Invest effort early in your SaaS design strategy to explore your customer requirements for tenancy. Work backwards from your SaaS tenants end goals. What level of computing performance do they require? What are the required cyber security features? How will you, as the SaaS provider, monitor and operate your platform with the target tenancy configuration? Your respective AWS account team is highly qualified to advise on these design decisions. Take advantage of reviewing and improving your design using the AWS Well-Architected Framework. The tenancy design process should be followed by extensive prototyping to validate functionality before production rollout.

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//Last UPDATE ON 18/09
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