A major North American oil and gas company faced significant challenges with their cloud-based drilling software platform. The testing process was entirely manual, involving over a thousand test cases, leading to lengthy test cycles and inefficiencies. Additionally, there was no performance testing in place, and the documentation for business scenarios and use cases was inadequate. These issues were causing delays and increasing operational costs, making it difficult for the company to maintain its competitive edge in the industry.

• Lengthy Test Cycles: The manual testing process, which involved a large number of test cases, resulted in long test cycles. This extended timeline hindered the company’s ability to quickly release updates and improvements.
• Lack of Performance Testing: There was no mechanism to measure and track the performance of the server, API, and application. Without performance testing, identifying and addressing bottlenecks was challenging.
• Insufficient Documentation: Business scenario coverage and use case documentation were missing. This lack of documentation made issue resolution more difficult and time-consuming, as there were no clear guidelines to follow.

Airo stepped in with a comprehensive AI Data Engineering solution designed to tackle these challenges head-on. Our approach included:

• Performance Testing with JMeter: We implemented performance testing using JMeter to evaluate server, API, and application performance. This allowed the company to track performance parameters in real-time and take corrective measures proactively.
• Test Automation: Airo conducted a thorough automation assessment and developed Python scripts to automate the testing process. This automation covered all environments, including Development (DEV), Quality Assurance (QA), User Acceptance Testing (UAT), and Production (PROD). By automating these processes, we significantly reduced the manual effort required.
• Comprehensive Documentation: We created detailed documentation for business scenarios and use cases. This documentation provided clear guidance for the testing process and facilitated easier issue resolution, ensuring that all stakeholders had access to the necessary information.

The implementation of Airo’s AI Data Engineering solutions led to significant improvements and benefits for the oil and gas company’s manufacturing operations:

• 50% Improvement in Test Cycles: Automation reduced the test cycle time by 50%. This drastic reduction allowed the company to expedite release cycles, bringing new features and improvements to market much faster.
• Enhanced Performance Tracking: With the implementation of JMeter for performance testing, the company could now effectively track performance parameters. This capability enabled them to identify performance issues early and take proactive measures to improve system performance.
• Improved Documentation: The comprehensive documentation we provided ensured that all business scenarios and use cases were well-documented. This documentation made it easier to resolve issues quickly and maintain consistency across all testing processes.

Partnering with Airo proved to be transformative for the company’s approach to testing their cloud-based drilling software platform. The integration of AI Data Engineering solutions, including test automation and performance testing, streamlined operations, reduced manual effort, and enhanced overall efficiency.

By collaborating with Airo, the oil and gas company was able to optimize their testing processes, improve system performance, and ensure sustainable growth. Our solutions allowed them to focus on their core business activities while we handled the complexities of test automation and performance tracking.