In an ideal software development life cycle (SDLC), developers and testers simultaneously work together towards making an end-to-end software product. However, in reality, a developer, tester, or a dependent team‘s productivity might not be in sync. This could be due to a team’s failure to complete its task due to some dependencies. Productivity and team collaboration started improving after the introduction of Agile and DevOps methodologies. However, team collaboration issue and time lag became a common emerging problem while scaling your SDLC. Such time lag between the teams often acted as a threat to a project’s productivity cycle. Eventually, organizations started opting for service virtualization to mend these productivity gaps by speeding up the dependent task completion rate.
Let us assume a scenario to understand service virtualization. Let us say a testing team is waiting for a code release that is pending with a developer team. Whereas the developer team is waiting for API related information from another team.
In short, the tester cannot do any work until API information is available to the developer.
A solution to the above scenario would be to opt for service virtualization. It usually offers a realistic virtual environment by mimicking any unavailable service and components. It can also help with realistic API simulation. In this discussed scenario, once the API simulation is done, the virtual API component would be available to the development team, which would decrease teams’ dependency time.
Thus, it helps the dependent teams with their task completion by simulating a component even before that component is developed or is unavailable due to some reasons.
Benefits of Service Virtualization
As per a Gartner survey conducted among 500+ organizations, the highlighted benefits were:
- Increase in test rates
- Reduction in test cycles by nearly 50%
- Reduction in system defects by 40%
In a complex testing environment, virtualization can help with:
- Better collaboration and reuse.
- Flexible virtual service creation.
- Thorough testing of business logic.
- Continuous testing.
- Strong component integration.
- Reduced time and project cost.
How Does it Work?
Service virtualization is implemented based on project type. For example, in a DevOps environment its implementation is as follows:
- Listener captures traffic, fetch the data from log files, sample data between the test and dependent application.
- The solution performs correlation and evaluation of the above-captured data and creates a virtual service.
- Finally, the virtual services with all characteristics of an unavailable service get deployed.
When we talk about virtual services, you may think about stub or mock services. But it is interesting to note both are built for different purposes. Let us have a look at those differences.
Stub Vs Service Virtualization
Stubs are usually fake software that imitates specific real-life software behavioral response, and they are used for testing. Stubs are content-specific.
In short, stubs help with class level simulation. Whereas service virtualization covers a large network spectrum simulation.
Service Virtualization is more than just imitation software.
Steps Before Choosing Service Virtualization
If you are interested to opt for service virtualization and wondering about the prerequisites, there are no such hard and fast prerequisites to follow. However, following a few of the prerequisites can make your journey a smoother experience.
So, the optional pre-requisite before opting for virtualization is:
- Discussing with the dev team about technical feasibility:
As in every project, mostly a dev team handles all the technical development tasks hence it might be beneficial to sit and discuss feasibility with them or related team members.
- Identify a relevant service virtualization tool:
After the feasibility discussion with the dev team, then the next step would be selecting tools. It is recommended to define the objectives, brainstorm on options, create a short-list, perform an evaluation, and then select the tool that you think would provide an optimal solution and excellent project feasibility.
- Decide between commercial or open-source service virtualization tool:
Most of the time comparing open source and commercial product could be a moot point as finding out the better alternative is an ongoing debate. Of course, both have their pros and cons. Do not feel overwhelmed and select the right tool as per your budget, project transparency, project feasibility and training costs.
- Proof of concept (POC):
POC helps with an understanding of Service Virtualization implementation feasibility.
All the above prerequisites might help you achieve an optimal implementation with a harmonious balance between project cost, quality, and scheduling.
Popular Service Virtualization Use Cases
Across the entire technology landscape, Service Virtualization has a wide variety of use cases. It can be used right from training an environment, data management to performance testing and so on.
Let us have a look at some of the use cases
Usually, a training environment would have:
- Restricted access to the stored information.
- Tight backend access.
- Lack of data set availability.
Service Virtualization can simplify the testing environment by mirroring production and backend services. It easily carries all these mirroring activities without any additional hardware spend.
Sometimes maintaining a live performance environment can become a challenging task because of several external dependencies and response time lag.
Service virtualization allows performance testing in a more integrated way by mimicking the external absent dependencies and reducing the response time to a manageable level.
Management of test data:
Mostly in a distributed system, there comes a need for test data creation and synchronization. The whole test data creation and synchronization process might consume a lot of time and effort.
Service virtualization helps Quality Assurance and development team to automate test data response with the ease of data capture, and virtualized data set.
Third-party application integration:
There may be a possibility of third-party application unavailability, which might lead to a production environment halt.
Service virtualization can help mimic the accurate behavior of third-party systems in a timely fashion. That helps with proper system synchronization and system behavior, even without waiting for third-party services.
Containing a test environment:
Sharing test environment variables can raise several issues. Some issues may include test environment redundancy, dependency, and inconsistencies. These inconsistencies can become detrimental to the software development life cycle.
In case of any test environment modification, the service virtualization changes its environment to reflect the modification accurately.
Service Virtualization is carried out by various open and commercial software tools. Each of those tools has its benefits. Please refer to the 10 Best Service Virtualization tools in 2021 article for more information.
As per Coleman Parker’s survey, according to the participated developer team, service virtualization might bring the following positive changes in an SDLC workplace:
- Expected 80% increase in customer satisfaction.
- Possible 77% in the project cost reduction.
- 73% increase in market reputation improvement.
Service virtualization is a powerful tool that can be used in any Agile, DevOps environment and even during any stage of SDLC. It aligns all the team’s work effort in producing a fast and much more reliable product. It helps with:
- Test environment and simulation.
- External and internal system access.
- Reducing team interdependency.
- Data recording and evaluation.
If you are still not sure about service virtualization, reach out to our team and we would love to help you out with an optimized solution.