QA Programmer Performance Testing & Engineering teams have extensive experience in providing cutting-edge services to global clients. Our Performance Testing and Load Testing expertise spans a wide range of applications including client-server, web, distributed, mobile, cloud databases, high-volume transaction systems, and highly complex applications. QA Programmer Performance Center of Excellence (PCoE) provides end-to-end performance testing solutions to help our clients launch future-proof applications with high responsiveness, availability, and scalability.
QA Programmer website performance testing covers performance engineering, including capacity planning, baseline test, load, stress, endurance, and benchmarking against competitors, production monitoring, and consulting. Our key website performance testing differentiators include:
Load and performance testing is designed to simulate real-life load on any website or application. A comprehensive range of services makes our performance testing portfolio effective and the product/solution, efficient.
QA Programmer follows a process-oriented approach for the successful deployment of performance testing: In the assessment stage, the first step is getting the client’s sign-off on deliverables and involves:
QA Programmer’s’ business-efficient performance engineering framework‘ plays a key role in performing end-to-end testing & engineering, while our ’analytics-driven workload modeller ‘ helps avoid all workload modeling hassles. We maintain a dedicated pool of resources with expertise on a wide range of tools, technology stacks, and processes.
• Access to QA Programmer Testing as a Service (TaaS) and cloud-enabled performance test lab on a pay-as-you-go model that reduces overall costs.
• On-demand performance testing, load testing, & engineering services with access to performance analysts and architects.
• Proprietary IP-led processes and techniques to jumpstart performance engagements.
• Strategic alliances and partnerships with leading tool vendors
• Statistical analysis with actionable inferences and recommendations aligned with performance objectives