Modern-day global web applications are dynamic and distributed in nature to facilitate horizontal and on-demand scalability. These applications necessitate validation of the quality of user experience and performance. Such aspects make Performance testing fundamentally different from and increasingly complex than regular benchmarking.

Establishing precise, purpose-driven Performance testing to address core principal concerns of the application behavior is critical. We engineer Performance testing solutions based on our meticulous understanding of the various dimensions of applications such as business SLAs, sub-components, platforms, configurations, and the spread of performance tooling.

Cybage understands the unique requirements that arise while testing legacy and newly-formed distributed applications for their performance. Cybage has extensive expertise in providing highly-mature Performance test offerings with rapid proliferation of standards, tools, and matured segment-specific practices.


The Cybage Performance Test Group is well-versed in various open-source, off-the-shelf, and proprietary tools. Following are a few indicative tools:


  • Focused and dedicated Specialized Test Engineering Group
  • Purpose-engineered, comprehensive performance procedures and processes
  • Specialization in emerging Performance testing areas using commercial, open-source and Application Performance Management (APM) tooling
  • Expertise in building on-demand and scalable Performance test labs using cloud services and open-source tools
  • Comprehensive Performance test coverage: user experience, infrastructure consumption, application and code behavior, non-functional SLAs
  • Platform expertise: Windows, LAMP, Java, mobile, cross-platform applications implemented on cloud or on-premise, using virtualization and distributed computing
  • Accelerators: These include a test framework skeleton for open-source tools; system monitoring automated reusable scripts; on-demand scalable clouds lab provisioning automation framework; and identified workload models
  • Maximized ROI and time to market through an effective selection of:
    • Tools
    • Environment
    • Methodology


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