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Allowing tenants to upload their own code increases the risk of application failure, because you have less control over the code that is running in the application. Many Software as a Service (SaaS) systems apply limits to this. Most simply disallow it. Allowing tenants to upload code or scripts also increases the security risks associated with the application.
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The security considerations just described apply to both Windows Azure storage and SQL Azure technology platform. However, they each have a different billing model. Usage of Windows Azure storage is billed by the amount of storage used and by the number of storage transactions, so from a cost perspective it doesn t matter how many separate storage accounts or containers you have. SQL Azure is billed based on the number of databases you have, so it makes sense from a cost perspective to have as many tenants as possible sharing each instance. Data Architecture Extensibility There are a number of ways that you can design your data storage to enable tenants to extend the data model to include their own custom data. These approaches range from each tenant having a separate schema, to providing a set of pre-defined custom columns, to more flexible schemas that enable a tenant to add an arbitrary number of custom fields to a table. If you use SQL Azure, much of the application s complexity will result from having to work within the constraints of fixed data schemas. If you are using Windows Azure table storage, the complexity will arise from working with variable schemas. Windows Azure table storage allows records in the same table to have completely different structures, which allows for a great deal of flexibility at the cost of more complexity in the code. Custom extensions to the application s data model should not require changes to application code. To enable the application s business logic and presentation logic to integrate with the data model extensions, you will require either a set of configuration files that describe the extensions or code that can dynamically discover the extensions. Data Architecture Scalability If you can partition your data horizontally, you will be able to scale out your data storage. In the case of SQL Azure, if you decide that you need to scale out, you should be able to move all of an individual tenant s data to a new SQL Azure instance. Note: Partitioning data horizontally, also known as sharding, implies taking some of the records in a table and moving them to a new table. Partitioning data vertically implies taking some fields from every row and placing them in a different table. For a discussion of partitioning strategies in SQL Azure, see the paper, SQL Azure Considerations Guide; you can download it at http://wag.codeplex.com.
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Microsoft SharePoint is an example of an application with a fixed schema database that is made to look extremely flexible. You are billed for SQL Azure based on the number of databases you have, and the size of the databases. If you transfer data in and out of SQL Azure from within the same data center, there s no data transfer cost, but if you transfer data in and out of SQL Azure from outside the data center, you ll be charged for the data transfer.
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The key factor that determines the scalability of Windows Azure table storage is the choice of partition key. All queries should include the partition key to avoid scanning multiple partitions. For more information, see Phase 2: Automating Deployment and Using Windows Azure Storage of Windows Azure Architecture Guide, Part 1, Moving Applications to the Cloud; it is available at http://msdn.microsoft.com/ en-us/library/ff728592.aspx. Your billing and cost model may affect your choice of single-tenant or multi-tenant architecture. Billing Customers For an application deployed to Windows Azure, Microsoft will bill you each month for the services (compute, storage, transactions, and so on) that each of your Windows Azure accounts consumes. If you are selling a service to your customers, like the Tailspin Surveys application, you need to bill your customers for the service. One approach to billing is to use a pay-per-use plan. With this approach, you need to monitor the resources used by each of your customers, calculate the cost of those resources, and apply a markup to ensure you make a profit. If you use a single-tenant architecture and create a separate Windows Azure account for each of your customers, it s easy to determine how much an individual customer is costing in terms of compute time, storage, and so on, and then to bill the customer appropriately. However, for a single-tenant instance running in a separate Windows Azure account, some costs will effectively be fixed; for example, paying for a 24x7 compute instance, or a SQL Azure instance, may make the starting cost too high for small customers. With a multi-tenant architecture, you can share the fixed costs between tenants, but calculating the costs per tenant is not so straightforward and you will have to add some additional code to your application to meter each tenant s application usage. Furthermore, customers will want some way of tracking their costs, so you will need to be transparent about how the costs are calculated and provide access to the captured usage data. It is difficult to predict exactly what usage an individual subscriber will make of the service; for the Surveys application, Tailspin cannot predict how many surveys a subscriber will create or how many survey answers the subscriber will receive in a specified period. If Tailspin adopts a billing model that offers the Surveys service for a fixed monthly fee, the profit margin will vary between subscribers (and could even be negative in some cases). By making Surveys a multitenant application, Tailspin can smooth out the differences in usage patterns between subscribers, making it much easier to predict costs
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