BlazeMeter ensures delivery of high-performance software by enabling DevOps teams to quickly and easily run open-source-based performance tests against any mobile app, website or API at massive scale to validate performance at every stage of software delivery.
The rapidly growing BlazeMeter community has more than 100,000 developers and includes prominent global brands such as Adobe, Atlassian, Gap, NBC Universal, Pfizer and Walmart as customers. Founded in 2011, the company is headquartered in Palo Alto, Calif., with its research and development in Tel Aviv.
SmartBear LoadNinja is a cloud-based next-generation tool designed to develop and implement automated load tests for web services and web applications. LoadNinja helps organizations test their web server’s performance during tremendous load and will determine scalability and define overall dynamics.
Load testing is integral in today's aggressive marketplace so that organizations can quickly and easily determine how their web servers will operate during extreme load (requests). LoadNinja intuitively creates load tests using automation developed by documenting past interactions over web pages and reproduces these interactions with hundreds of virtual users (VUs) simultaneously. These tests help organizations fully comprehend what load their websites, pages, etc, can successfully sustain without interruption or downtime.
LoadNinja provides various metrics, such as CPU usage and traffic generated during each test run. LoadNinja integrates well with many of today’s popular browsers and web servers.
LoadNinja Testing - How it works:
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Develop a UI or API test scenario: These are single-instance tests. Each test is representative of an actual application usage process, such as updating client information, making or tracking an order, etc. A UI test replicates the actions of one user on the tested website. An API test replicates the behavior of one client application. Organizations will run these tests numerous times to replicate tremendous load on the specified web application being tested.
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Load testing scenario: This is the example of an organization’s load test. The scenario will integrate one of many single-instance tests, designate the number of virtual users (VUs), advance load parameters, and other specific metrics.
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Work the scenario: LoadNinja processes the load tests in the cloud and provides cloud machines automatically for the entirety of the test. During a UI test, each VU utilizes a real browser to conduct a test action to interact with the organization's web applications appropriately mimicking real user responses, including “think times” and experiencing client-side scripts. Throughout the entire process, LoadNinja will create real-time charts so that organizations are able to best monitor test metrics and the overall wellbeing of the application.
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Study the results: Once the test is finished, LoadNinja will create a report detailing all the critical performance metrics gathered during the test. This report will give a good determination of an organization’s server capabilities and if it meets the established SLA.
Top Features:
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Real-life load tests, simulated real user actions: LoadNinja will document real user actions on the site to be tested, then replicate those actions with the assistance of hundreds or even thousands of virtual users. This ensures load tests are as close to real-life processes as possible. LoadNinja does not just test one URL of a website; it replicates the entire user experience. This is one feature that differentiates LoadNinja from most other solutions in the marketplace.
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Real browsers, real user replication: LoadNInja replays the documented traffic from real browsers. Every VU utilizes its own browser; there is no overlapping. LoadNinja precisely replicates each user action. Whatever code or script is used, it will be completely tested for every page.
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Develop tests quickly and easily: Organizations are able to quickly develop UI tests by documenting user actions in the embedded browser. API tests can be developed using the embedded request editor. There is no coding, downloading, or installation of browser plugins necessary.
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Scales easily: LoadNinja is a cloud solution; there is no need to designate drive space or add extra “agent” devices to save recorded scripts or test results. LoadNinja does it all intuitively and automatically in the cloud. Organizations simply choose the determined amount of VUs desired to replicate, and begin. It’s that simple!
Tricentis NeoLoad is a performance testing tool that provides developers and testers with automatic test design, test maintenance, realistic simulation of user behavior, fast root cause analysis, and built-in integrations with the entire SDLC toolchain. With NeoLoad’s plugins, teams can reuse and share test assets and results from functional testing tools, analytics, metrics, and APM tools in order to catch performance issues early. With NeoLoad’s full tech stack support, users can test the range of mobile, web, and desktop apps.
Tricentis NeoLoad Features
Tricentis NeoLoad has many valuable key features. Some of the most useful ones include:
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Supports API technologies
- Assisted design with Swagger/Open API import and highly efficient extractors for quick test design and fewer errors in scripting.
- Ability to test as code or GUI-based productivity.
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Automated testing of API performance
- CI/CD automated API testing, dynamic load generation infrastructure, and auto pass/fail based on SLAs.
- Real-time test results for fast dev feedback loop if bottleneck is found.
- Non-regression API performance trends.
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API-based applications
- Ability to test stand-alone APIs or APIs within end-to-end tests. Same platform, same skills.
- Dev, PO, QA, Ops share a common view of API performance.
- Confidence in API and application speed and reliability.
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Design tests faster and update automatically
- Assisted design using wizards and automatic parameter handling.
- Reuse functional scripts and/or convert LoadRunner scripts to NeoLoad performance tests.
- Update system-level scripts quicker with automatic user path updates.
- Easy to reuse and maintain.
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Realistic user simulation
- Simulate any business case.
- Scale load tests with up to millions of virtual users.
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Bottleneck identification
- Real-time test analysis.
- Pass/fail based on SLA.
- Root cause analysis.
Tricentis NeoLoad Benefits
There are many benefits to implementing Tricentis NeoLoad. Some of the biggest advantages the solution offers include:
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Automate API testing within CI pipelines: Design, maintain, and run performance tests. Analyze results within continuous integration pipelines.
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Accelerate end-to-end app testing: Create test scripts fast for complex applications using a graphical user interface without the complexity of scripting new and updated tests.
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Find performance bottlenecks fast: Compare SLAs to server-level statistics to measure how an application is performing. See overall analysis of behavior or an analysis of the data flow to a particular user path.
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Manage across the enterprise: Collaborate across QA, operations, dev, and business teams to define SLAs and review results. Share test results and manage test infrastructure. Schedule and share resources across teams and apps.
Reviews from Real Users
Tricentis NeoLoad stands out among its competitors for a number of reasons. Some of these include its price, its user-friendly UX, its API support, and its scalability. PeerSpot users take note of the advantages of these features in their reviews:
Patrik B., Technical Lead at a tech services company, writes, “The licensing cost is very less for NeoLoad. It is user-friendly and easy to understand because they have created so many useful functionalities. When I started working with this tool, we just had to do the initial assessment about whether this tool will be able to support our daily work or not. I could easily understand it.”
A Global Delivery Head at a consultancy firm notes, “The API support is much better with this solution, compared with the competition. Pricing for it is also more affordable than its competitor. We have used Tricentis NeoLoad and we find it scalable.”
