System Performance Audit of an IoT Application
Our team worked quickly, understanding the project well and completing all the work on time and to a high quality.
Our client needed a trusted partner to audit and improve the performance of an IoT system containing all technical information for a large number of vehicles under maintenance.
Our team created a data-generator and tested the application architecture with up to 10 million registered vehicles.
Application performance improvement
Delivered high-scalable architecture
Established new performance KPI
Need a performance audit?
Business challenge story
Our client had developed a car management IoT system on their own. This system contains all technical information for thousands of vehicles under maintenance.
One of the main use cases of this system is its feature which enables the client to filter out all vehicles that match certain criteria. When the number of registered vehicles rose to a 7-digit number, the system started having trouble analyzing them for a short period of time. Executing standard business filters would take for the system up to 30+ hours to return the results.
Sometimes they were unsuccessful which used to cause delays due to repetition of tests. In total, when the client had to find all cars matching a criterion, they needed a few days to get the results. This was not acceptable for their business model. The number of registered vehicles in the system was expected to increase significantly, while the existing system was struggling to serve the business needs of the registered vehicles.
To address the challenge our team came up with improved database and application architecture that had to speed the filter execution. The client approached us in order to make sure the outcome of the new system meet all predefined requirements and standards. Moreover, they were eager to understand the magnitude of progress that has been achieved.
First, our Java team developed a data generator that can fill/append both database architecture with specified amount of data in terms of number of registered vehicles. Further on, we tested both solutions (the old and the new one) in order to find out how much of an improvement the new architecture provides.
Our team tested the new architecture with up to 10 million registered vehicles in order to be certain that all standards and requirements were met with due diligence.
Then, we provided recommended indexes for the database as well as general recommendations on the indexing strategy. Lastly, we issued recommendations on the key performance indicators for that application.
Our client now has received a validated feedback which analyzed their performance. They have the confidence that their new architecture performs good, up to the data volumes required. Furthermore, they have an official prove that their new architecture performs much better compared to the old one.
About the client
Our client develops software management systems and offers application software and system solutions for companies in mobility, energy and building, manufacturing and financial service industries.