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What is Launchable?
Having a team of highly skilled developers is not sufficient if the testing methodologies are obstructing their workflow; in fact, around 80% of software tests may prove to be ineffective. The real challenge is determining which 80% of those tests can be deemed unnecessary. By leveraging your data, we can identify the crucial 20%, thereby speeding up your release cycles. Our predictive test selection tool is influenced by machine learning strategies used by industry leaders such as Facebook, making it accessible for organizations of all sizes. We support a wide array of programming languages, testing frameworks, and continuous integration systems—simply integrate Git into your existing workflow. Launchable harnesses machine learning to analyze your test failures in conjunction with your source code, avoiding the pitfalls of conventional code syntax evaluation. This adaptability allows Launchable to seamlessly extend its compatibility to almost any file-based programming language, catering to diverse teams and projects that utilize various languages and tools. At present, we offer immediate support for languages such as Python, Ruby, Java, JavaScript, Go, C, and C++, while also pledging to continually broaden our language support as new ones emerge. By streamlining the testing process, we empower organizations to significantly boost their overall efficiency and focus on what truly matters—their core development goals. Ultimately, our approach not only optimizes testing but also enhances the productivity of development teams.
What is BlazeMeter?
BlazeMeter provides a robust, open-source solution designed for enterprises that integrates all critical features for effective left and right shift testing. The platform's intuitive interface allows users to easily create new tests or leverage existing scripts, running them at scale within a continuous testing framework. Furthermore, users can perform tests, produce detailed reports, and analyze historical data trends, enabling a greater focus on innovation rather than tool management. Continuous testing plays a crucial role in ensuring quality, volume, and speed in product delivery; however, managing multiple tools can consume valuable time and resources. BlazeMeter streamlines this complexity through a highly user-friendly platform that includes all necessary functionalities. It enables comprehensive shift-left testing, equipping users to captivate the market with innovative breakthroughs. Additionally, BlazeMeter supports interaction with CLIs, APIs, UIs, and a variety of open-source tools, facilitating a seamless workflow. By significantly reducing the time spent on setup, maintenance, and daily operations, users can experience enhanced efficiency. Ultimately, BlazeMeter not only boosts productivity but also elevates your testing strategy to unprecedented levels, positioning you for future success.
Integrations Supported
Android
Apptim
Bitbucket
Curiosity Modeller
Cypress
Fleece AI
GenRocket
GitHub
GitLab
Google Chrome
Integrations Supported
Android
Apptim
Bitbucket
Curiosity Modeller
Cypress
Fleece AI
GenRocket
GitHub
GitLab
Google Chrome
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
$149 per month
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Launchable
Company Location
United States
Company Website
www.launchableinc.com
Company Facts
Organization Name
BlazeMeter
Date Founded
2011
Company Location
United States
Company Website
www.blazemeter.com
Categories and Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Software Testing
Automated Testing
Black-Box Testing
Dynamic Testing
Issue Tracking
Manual Testing
Quality Assurance Planning
Reporting / Analytics
Static Testing
Test Case Management
Variable Testing Methods
White-Box Testing
Categories and Features
API Testing
Functional Testing
Fuzz Testing
Load Testing
Penetration Testing
Runtime and Error Detection
Security Testing
UI Testing
Validation Testing
Automated Testing
Hierarchical View
Move & Copy
Parameterized Testing
Requirements-Based Testing
Security Testing
Supports Parallel Execution
Test Script Reviews
Unicode Compliance
Load Testing
API Load Testing
Database Load Testing
Load Test Performance Reporting
Mail Load Testing
Multilocation Load Testing
Multiple Protocol Support
Test Script Customization
Web Application Testing
Software Testing
Automated Testing
Black-Box Testing
Dynamic Testing
Issue Tracking
Manual Testing
Quality Assurance Planning
Reporting / Analytics
Static Testing
Test Case Management
Variable Testing Methods
White-Box Testing