After deliberation, the GSPANN team devised a detailed plan to reduce costs. Our team introduced automated solutions to manage critical tasks that addressed the issue of high expenditure due to excessive use of resources. This allowed flexibility in adjusting resources during working and non-working hours, which led to significant savings.
Our team created and implemented automated solutions that could adapt according to the workload during the day (18 hours) and night (6 hours). We tested these solutions in a simulated crisis scenario in the East Region of our cloud platforms.
With a strong focus on cost-effectiveness, we made this solution applicable to any project on any cloud platform. Our automated solutions were designed to be easily adapted to other projects or platforms, making the process simpler and more efficient.
By addressing these issues and making the processes more streamlined, the company was able to function more efficiently by freeing engineers’ time to focus on innovative and strategic projects, propelling the business forward. By optimizing company practices and reducing repetitive tasks through automation, we strengthened their technical base, which contributed to long-term success and growth.
Here are some highlights of our solution:
- Solid metrics based on actual data: Our solution was built on reliable metrics derived from real data, such as transactions per second, traffic volume, and CPU and memory usage, enabling accurate data-driven decision-making.
- Dynamic capacity optimization: We introduced automated solutions for critical jobs that enabled capacity adjustments, reducing infrastructure costs.
- Reusable optimization solutions: Our scaling optimization implementation was created to be reusable on both GCP and OpenShift. This feature helped the company save a lot of money in future development costs.