Service virtualization: An introductory guide

What is service virtualization?

Service virtualization is a simulation technology that lets testers automatically execute tests even when an application’s dependent system components can’t be easily accessed or configured for testing. By simulating these dependencies, service virtualization technologies ensure that tests will be based on appropriate dependency behavior and data, each and every time the test is run.

Service virtualization is typically used when a test needs to interact with dependent system components that are:

• Unreliable, evolving, or not yet finished
• Outside the scope of the tester’s control or operated by another company or division
• Available for testing only at inconvenient times or in limited capacities
• Difficult to provision or to configure in a testing environment
• Too restricted or too costly to use for automated regression testing
• Simultaneously required by multiple testers using different test data setups and other requirements

Mocking vs. service virtualization

With the rise of API-driven architectures, the distinction between mocking and service virtualization has become somewhat blurred. Here are the key differences.

Key components of service virtualization

1. Physical machine (server/computer)

This is your host. It provides the core hardware resources (CPU, memory, storage, and network) supporting virtualization.

2. Virtual machine (VM)

This software-based emulation of the physical computer runs the operating system and applications. Your virtual machine only shares your host’s hardware resources but operates independently of it.

3. Hypervisor

A hypervisor is the software layer that manages and allocates resources between the host machine and your virtual machines.

When to use service virtualization

Service virtualization can be an invaluable tool in specific situations.

Assistance with negative testing

Negative tests evaluate an application’s performance when unexpected data is input or when unforeseen conditions are present. Because it’s often impossible to replicate these conditions or input in a live environment, testers can use service virtualization to identify and fix potential problems.

Simulating specific behavior

Some applications are built with specific behavior that’s difficult to replicate and manipulate in production environments. Service virtualization allows testers to re-create this behavior easily to accelerate the speed of software testing.

Facilitating automated testing

Automated testing requires all dependent systems to be available with the appropriate configuration, functionality, and test data at any time a test is run. Service virtualization makes it possible to accurately recreate these dependencies, enabling testing to proceed as needed.

Use cases for service virtualization

Agile development and CI/CD pipelines

Service virtualization enhances productivity by removing dependencies on unavailable external systems. This allows your team to work in parallel and simulate expected responses. Thus enabling faster iterations within your agile environments.

API development

Virtualizing APIs allows teams to test and integrate even before implementation. This allows your team to get early feedback, facilitates collaboration across teams, and ensures compatibility while reducing delays in the development process.

Implementation strategies for service virtualization

1. Leverage simulation for robust risk testing

You can leverage service virtualization to stimulate your network variability, performance degradation, and security vulnerabilities. This will allow you to get more than what traditional testing can offer you, especially when you can’t access the real system and simulate how it performs under stress.

2. Know and prioritize dependencies

Map out all dependent systems for your application, assess their configuration complexity and cost of access, and determine expert availability. Virtualization offers a faster, leaner alternative for legacy systems where the availability of domain experts is critical or slow to access.

3. Empower your teams to self-provision environments

One key benefit of service virtualization is reducing operational overhead by enabling teams to provision their test environments. By removing the dependency on a centralized environment, your team can iterate faster.

4. Balance cost and realism

While testing against the most realistic environments is ideal, you need to consider the cost. Simulated services can reduce infrastructure costs, system access fees, and the burden of maintaining large test environments. Thus, only explore service virtualization to get the most value from your investment.
Virtualization offers a faster, leaner alternative for legacy systems where the availability of domain experts is critical or slow to access.

Virtualization offers a faster, leaner alternative for legacy systems where the availability of domain experts is critical or slow to access.

Types of tests for service virtualization

Service virtualization can play a role in many types of software testing.

1. Application testing – use service virtualization to stress test individual components of applications
2. Component testing – testers can isolate application components earlier in the SDLC
3. Mainframe testing – eliminate testing constraints for development of mainframe applications
4. Chaos testing – service virtualization can enable negative testing scenarios that are difficult to replicate in live production
5. Third-party API testing – using service virtualization allows testers to remove access constraints and reduce costs

Benefits of service virtualization

1. Eliminate delays

Service virtualization enables testers to test highly interconnected systems at any time without needing to wait for access to dependent components that are not yet implemented, that are still evolving, or that are under the control of a third party. By enabling multiple testing teams to test systems simultaneously, service virtualization helps accelerate testing and development timelines.

2. Test earlier

With the ability to start testing whenever an application is ready, testers can expose defects earlier in the software development lifecycle when they are easier, faster, and cheaper to fix.

3. Minimize costs

Many modern applications are dependent on third-party services that charge a fee every time the service is used or accessed. By simulating the behavior of these services, service virtualization allows tests to be executed and incorporated into continuous integration without worrying about having to pay exorbitant, recurring service fees.

Challenges and limitations of service virtualization

1. Cost and effort

As much as service virtualization reduces testing dependencies, setting up, maintaining, and implementing the infrastructure can be complex, not cheap, and require significant time and resources. When all of this is considered, the cost and effort can sometimes outweigh the benefits.

2. Limited support for protocols and technologies

Service virtualization doesn’t always support every protocol and technology. Thus, if your infrastructure relies on these specialized protocols or proprietary technologies, it would be challenging to stimulate backend services and systems to test your workflows.

Best practices for service virtualization

1. Understand your dependencies

You must identify the critical component your system relies on. This will help you know what is unavailable or hard to control in test setups. It will also help you decide what you should virtualize, accelerate your testing, and reduce the test environment constraints you will face. Once you know this, knowing the requirements will come naturally.

2. Define objectives and assess the landscape

What are your goals for exploring service virtualization? Analyze your current development and test environment for its needs and any bottlenecks. This will help you achieve your project goal.

3. Pick simplicity

Avoid overengineering your virtual services, as this will ensure they align with your project’s objectives, are reusable, and are relevant. Thus, it is important to virtualize only the behaviors required by your test cases and let your test plan guide which transactions to simulate.

4. Choose the right tool

Pick a tool that complements your team’s and environment’s technical stack. Research the tool’s integration capabilities with existing infrastructure, features, vendor support, scalability, and performance. Choosing the wrong tool can be expensive and cause issues.

5. Run a Proof of Concept (PoC)

Pick a tool that complements it. Before committing to a tool or strategy, run a small, targeted PoC to stimulate a few core behaviors to validate the value and feasibility of service virtualization. This will clear any doubt, verify your assumptions, demonstrate ROI early, and guide how best to adopt it.

Virtualization vs. server virtualization

While the benefits of service virtualization might be pretty straightforward, it is important to know the difference between service virtualization and other forms of virtualization, as they are all different.

Gateway vs. virtual service

Gateways and virtual services are essential building blocks for simulating realistic traffic flows, even when testing. On the one hand, service virtualization focuses on simulating backend behavior. On the other hand, gateways and virtual services define how traffic reaches and interacts with your services. However, as similar as they sound, there are some differences between them:

Tricentis Tosca Service Virtualization

Tricentis dramatically accelerates software delivery by taking a new and fundamentally different approach to software testing . Our solutions are totally automated, fully codeless, and intelligently driven by AI. By addressing the needs of Agile development and complex enterprise apps, Tricentis increases software delivery speed, reduces costs, accelerates cloud migration, and improves the quality of each iteration.

Tricentis Tosca’s Service Virtualization (SV) enables you to simulate the behavior of dependent systems, components, and services that might be unavailable, costly to deploy, or not yet built. This removes one of the major sources of testing delays, enabling automated tests to run at any time. With Tosca’s SV, you drastically accelerate your end-to-end testing while reducing testing costs and catching 60-90% more defects in the development lifecycle.

Tricentis dramatically accelerates software delivery by taking a new and fundamentally different approach to software testing.

Tosca SV works by recording messages exchanged between the software being tested and its constrained dependencies, automatically learning the expected interactions by “listening in” on these messages. Its model-based approach enables users with limited expertise to quickly create and run reliable virtualized environments for more than 100 technologies and protocols.

Tosca SV automatically flags messages that are improperly formed or sent in the incorrect order, eliminating the need to manually check thousands or millions of messages.

Along with Tosca SV, Tricentis offers a suite of testing solutions from unified test management, end-to-end testing, data integrity testing, app-native testing, performance, and load testing, including smart impact analysis. It even supports every flavor and type of testing, from black box testing, white box testing, exploratory testing, regression testing, and chaos engineering.