BlazeMeter Mock Services
February 26, 2024

Above & Beyond: BlazeMeter Mock Services

Announcements
Service Virtualization

For years, service virtualization had been the go-to simulation tool for user behavior, system data, and software performance. It was, at the time, an effective way to increase testing velocity and reduce the high costs associated with real and live systems.

But, like every iteration of technology, it has grown outdated, cumbersome, and expensive in its own right.

In that time, BlazeMeter has continued to push past the growing detractions of service virtualization with its ever-expanding mock services offerings. Our commitment to investment and expansion of mock services has continued to keep us atop the mock services competition in the industry.

In this blog, we will break down BlazeMeter Mock Services, showing the wide-ranging and effective capabilities that we have to offer. We will also highlight examples of how you can execute BlazeMeter Mock Services in your own environment. By the end, you will be wondering why you have stayed with your legacy service virtualization this long!

What Are Mock Services?

Mock services are a simulation of real web services. Mock services are designed to replicate live services that are unavailable, such as system data, user behavior, and software performance. Testing teams can leverage this tool to save time, money, and other valuable resources. 

The benefits of mock services include drastic reduction in cost, the ability to use the tools both on-prem and in the cloud, simple setup and maintenance, and their ability to aid in shift-left testing.

Breaking Down BlazeMeter Mock Services

For many legacy service virtualization tools and other mock services offerings, the capabilities to truly do everything that a tester needs to execute a great test can be quite limited.

That is not the case with BlazeMeter Mock Services. Take a look below at all the effective ways BlazeMeter can make the lives of testers easier and examples of how they can be executed.

Chaining of Requests in Processing Actions

Users can leverage seamless integration of multiple processing actions within a transaction — enabling the output of one action to be used as the input for subsequent actions. This feature streamlines complex automated testing scenarios, improving accuracy and efficiency.

Example: Sequential API calls within a transaction utilize the output of the preceding call, allowing a user to validate an entire user journey from login to transaction completion.

Dynamic Response Status Code Mapping Using Script

Configurable response status codes based on evaluated expressions allow for dynamic adaptation of response codes based on transaction outcomes. This feature provides nuanced testing capabilities by simulating various server responses.

Example: Customizing mock service responses to mimic server behavior under different conditions, such as location-based or input-specific scenarios.

Import & Export Actions to Support Processing Actions

Backing up and restoring all service-related assets via export/import enables users to maintain service continuity and quickly recover from data loss. Now there is a robust solution for service management and disaster recovery.

Example: Regular backups of service configurations allow for quick restoration, ensuring minimal downtime in testing workflows.

SSL Alias Configuration

Alias and password specification for SSL certificates within keystores simplifies the process of selecting the appropriate certificate for secure calls. This enhances the security and ease of SSL communication in service integrations.

Example: Users can quickly identify and utilize the correct SSL certificate by its alias when setting up secure communications with third-party services.

Conditional Routing Logic Using Processing Action

Conditional execution of processing actions based on specific criteria allows for targeted and efficient processing action triggers. Now more complex situations are enabled by improved logic flow of mock services.  

Example: Conditional logic ensures that only relevant processing actions are triggered, such as validating payment information only if a transaction request includes a payment method.

Configurable Data Profiles for Mocks

Environment-specific data profiles managed via the Configurations tab facilitate easy transitions between different testing environments without hardcoding. Streamline your configuration management and reduce setup time across environments.

Example: A mock service can be configured to use environment-specific parameters, such as API endpoints or authentication credentials, selected at runtime based on the testing stage.

Marking Optional Parameters in Request Matchers

Users are given the option to designate request parameters as optional within matchers, which provides greater flexibility and simplicity in request matching. This reduces the need for numerous matchers and accommodates request variability.

Example: Matching a diverse set of requests with varying parameters without the need for exhaustive matcher configurations.

Proxy Configuration for External Calls

Users can specify proxy servers for external calls made by mock services — ensuring external calls comply with specific network routing protocols. Now you can leverage seamless integration of mock services within complex network architectures.

Example: Testing applications that require external service calls through a designated corporate proxy to ensure security and network compliance.

XML Node Attribute Selection for XPath Matching

Parse and utilize XML node attributes for XPath matching to extend the matching precision to attribute-level detail within XML data. This provides enhanced control and accuracy in XML-based mock service responses.

Example: Accurate matching and validation of XML responses that include specific attribute values, ensuring the mock service behaves as expected in scenarios where XML attributes carry significant information.

CDATA Matching & Parsing

Parse CDATA within XML requests for accurate matching. This enables handling and validation of XML requests containing CDATA sections, which ensures comprehensive testing of XML-based communications that include CDATA.

Example: Validating complex XML structures that utilize CDATA to encapsulate data, ensuring the mock service can accurately process and respond to such requests.

Looping Through Datasets in Mock Services

Loop through multiple rows of data in datasets to enable dynamic responses based on varied test data. Users then have more comprehensive and thorough testing scenarios, as each request can receive multiple rows of response from the dataset, which enhances the ability to test applications under different conditions and with various data inputs without manual intervention.

Example: When testing a service that returns a response with multiple entires, mock services can cycle through different user data with each request and validate the service's ability to handle diverse information.

Bottom Line

Let your mock services do more for you.

Don’t limit yourself to legacy technology while searching for a modern solution. The better and more up to date your testing toolkit is, the better your tests and — by extension — your app will be.

BlazeMeter Mock Services are the most comprehensive tool on the market for eliminating environment dependencies. Our industry-leading offerings are a direct result of our commitment to the tester and continuous innovation of testing functionality. Your success is our success.

Unlock unrivaled mock services with BlazeMeter by getting started testing for FREE today!

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