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Basics of SaaS testing, challenges and strategies
With the software-as-a-service model, QA professionals must address particular test challenges and criteria. Let's look at those SaaS issues and the strategies to navigate them.
As SaaS grows in popularity and usefulness across organizations, the testing community can also expect an uptick in SaaS testing opportunities. Gartner estimates that SaaS spending eclipsed the $100 million mark in 2020 and will continue to grow exponentially in the coming years.
The SaaS method of delivery has many complex testing implications. Teams will need to develop a test strategy with the understanding that SaaS refers to the method through which the software is delivered rather than a type of application -- i.e., understand that SaaS apps differ from installing software on premises.
SaaS testing validates SaaS applications based on business workflows along with configurations, data, integrations and nonfunctional requirements. Effective SaaS testing begins early in the software development lifecycle and has a wider scope, especially in the nonfunctional areas. Additionally, teams will continue to test as the vendor pushes upgrades and patches.
SaaS testing challenges
The potential challenges of SaaS testing can be broken down into two distinct categories:
- challenges related to the software itself
- challenges related to the delivery model
Since SaaS applications are commercial off-the-shelf, the code base is the same for all users. As a result, it leaves testing teams little to no visibility into the vendor's product development and testing. Testers also have no access to the codebase.
So at this juncture, testing must focus on configurations and customizations, the latter of which can be difficult to maintain. Teams will need to coordinate configurations and integrations between the vendor and internal development team, including potentially hard-to-integrate legacy applications.
Delivery model challenges include the extensive undertaking of nonfunctional testing and validating multi-tenancy. These tests must address security, especially with roles and permissions. Also, because the vendor remains in control of upgrades, another delivery model challenge will be possible frequent regression testing.
Both elements of SaaS testing require the team to pay attention to data flows and all types of nonfunctional testing.
How to develop an effective SaaS testing strategy
These three elements make up the basis of a successful SaaS test strategy:
- Application: business workflows and end-to-end integrations, data integrity and security, access roles and permissions and nonfunctional requirements.
- Network: network bandwidth to ensure accurate and secure data transfer between the SaaS application and the client network.
- Infrastructure: disaster recovery and availability and reliability of the SaaS application to the subscriber as well as regulatory compliance.
Functional testing
When the team approaches functional testing for the application, the focus shouldn't be on the core functionality, but more on business processes based on configurations and customizations.
Data testing requires teams validate that data migrated to the SaaS application matches the current application, including both static data migration and data transformation, and the states of the data in the integrations. These integration tests involve validating the interfaces between the SaaS application and organization's legacy applications, which require a full end-to-end systems test.
Nonfunctional testing
A nonfunctional testing strategy must test various criteria, including:
- load
- stability
- reliability
- security
- interoperability
- scalability
Other important nonfunctional areas to include in the testing strategy are:
- network bandwidth
- disaster recovery
- reliability
- availability
- mobile testing
- data security
Testing these areas is important because these qualities confirm that the infrastructure meets the application specifications.
Finally, it's important to include a regression test strategy for continuous upgrades from the vendor. This strategy should include an automated regression suite that focuses on analysis of the changes, selecting regression test cases and execution of both functional and nonfunctional test cases.
