Application development is evolving at a rapid pace to keep up with the demands of today’s digital world. Applications are now expected to not only perform complex tasks, but also deliver results faster and with higher accuracy. The challenge of delivering an enhanced user experience, even as the application development complexity increases, has led to higher expectations from not only developers, but also from performance engineers.
The increasing complexity of and dependencies in applications has made performance engineering a critical part of application development. As the velocity of product delivery is increasing with growing competition, it has become imperative for enterprises to maintain a high level of performance and mitigate risks from application downtime, outages, and performance issues.
Enterprises spend over US$5 billion in performance testing. This spend can be significantly reduced by leveraging AI systems. This research focused on how AI systems can assist designers, architects, developers, testers, and the operations teams to significantly enhance application performance.
Application performance engineering across the SDLC
Key factors that make performance engineering indispensable
AI adoption in performance engineering
Adoption maturity of AI systems for performance engineering
