Service Virtualization Tools

What Are Service Virtualization Tools?

Service virtualization tools provide teams with the ability to test an entire system even when some of its components might still be in development. Let’s explore the many attributes of service virtualization (SV) and compare the best tools that the industry offers.

Why Is Service Virtualization Important

Service virtualization is a method that development teams use to simulate the behavior of an application’s components. These components can be APIs, databases, networks, devices, and more.

Development teams use service virtualization because some components of the project might not be available for testing purposes when needed. Here are some reasons why components might not be ready.

• Developers are still building them.
• Problematic to set up or access.
• Hard to configure or provision in a testing environment.
• Third parties may own the components or charge a fee to access them.
• Only available for testing purposes at times that are inconvenient or in a limited capacity.
• Different teams may need them at the same time, each with various data setups and other necessities.
• Testers may find they’re restricted or expensive to use for performance and load testing.

By simulating downstream dependencies, development teams can get past obstacles such as these, with the teams swapping actual functionality for simulated responses and behavior. When used properly, service virtualization compels the system to behave exactly like it would if the component was complete and available.

Service virtualization acts like a flight simulator for applications. Testers test for deficiencies during development helping teams address potential problems so the plane doesn’t crash.

Benefits of Service Virtualization

Using SV saves money, time, frustration, and headache. Development doesn’t halt while team members wait for finished components from other areas. This is because service virtualization provides teams with ubiquitous access to precisely emulated test environments. Thus, teams avoid any “us vs. them” conflicts. Other benefits include improved testing accuracy and quicker time to market.

Service Virtualization Tools & What They Do

In addition to simulating the real behavior of the system’s components, SV tools can also duplicate nonfunctional parts of the system such as slow response times and connections.

SV tools can incorporate complex request matches, which allows the test to provide different responses for various request types. Some virtual services give a group of stubbed responses for the request criteria that testers provide, and then send all other requests to an operating backend system. Others simulate the behavior of the system when the SV constructs parts of the response based on request attributes and data.

Here are more helpful features:

• SV deploys a digital twin of your test environment to use as a sandbox for partner development or as a virtual endpoint for internal testing.
• Developers capture traffic using an SV platform to create virtual assets, as opposed to building the interactive pattern from scratch.
• SV supports various protocols, like HTTP, MQ, TCP, and many more.
• SV tools often feature user interfaces that allow non-developers to use the tools without having to understand the project’s details.

Steps Before Choosing a Service Virtualization Tool

Before teams start investing time, money, and effort into SV, doing some research and prep is advantageous.

1. Make an appropriate analysis of test cases.
2. Identify test data.
3. Determine target load, where appropriate.

To realize the full value of service virtualization, it’s important to ensure that the tool meets and supports your team’s testing needs. Otherwise, it will become too complex and too expensive to maintain.

9 Capabilities That Make SV Tools Easy to Use

Here are nine capabilities to consider in a tool that might make service virtualization easier for your team to use.

1 – Scriptless Functionalities

Dev teams should be able to build virtual services without having to write any code. Instead, a visual tooling system is ideal. Usually, the person who needs a virtual service is a tester, who has less firsthand technical details about how the services were implemented.

2 – Rapid Virtual Service Creation Prior to Real Service Availability

Leveraging virtual services as prototypes before the real service is available is highly advantageous. With this feature, teams can create interfaces for dependent components of the application before they’re ready.

3 – Intelligent Response Correlation

This means that the service virtualization tool can respond differently based on the requests that come in. Different types of response correlation to consider include:

• Deployment protocol
• Message correlation
• Data source correlation

4 – Data-Driven Responses

Data-driven responses give teams the flexibility to create logic in an abstracted way. They can connect virtual services to data sources like Excel, CSV, tabular, hierarchical, and live databases for real-time data lookups.

5 – Ability to Reuse Services

Dev teams can work together to define core, common, or shared services, and then reuse those templates and logic in other virtual services multiple times.

6 – A Custom Extensibility Framework

Having the ability to use scripts but not be limited to a single language is helpful if you need to write code to accomplish tasks like generating a proprietary token or unique identifier.

7 – Support for Authentication & Security

With this type of support, your team can validate incoming transport layer security, such as SSL certificates, and interact with the live services during recording, which could be governed by authentication mechanisms like OAuth, Basic Auth, Digest, Kerberos, NTLM, and more.

8 – Configurable Performance Environments

Enabling performance testing enables teams to do earlier stage performance testing and reduces exclusive reliance on full testing environments. Teams can laser-focus on specific component SLAs by using virtual services to emulate out of scope dependencies. They can create performance environments by surrounding the application with virtual services.

9 – Support for Clustering & Scaling

As your performance team adopts service virtualization and general usage increases, you’ll need a tool that enables scaling, which can manifest in two forms: high throughput and fault tolerance. To support scaling, you’ll want a tool that can be clustered behind a load balancer so that you can distribute the load given to your virtualization infrastructure appropriately. You’ll also want a tool that can maintain asset parity as you modify different virtual services on individual nodes.

More SV Tool Capabilities to Consider

Capabilities associated with optimizing workflows, automation, support for management and maintenance, and supported technologies are important to consider in your search for the best service virtualization tool. Learn more here.

Best Service Virtualization Tools

We compare the features, benefits, and capabilities of the top service virtualization commercial tools.