AI Powered Software Downtime Prediction

Predict downtime, software failure rate, availability, site reliability before the code is written

The time to predict software failure rate, software downtime, site reliability is early while there is still time to consider alternatives. Requs AI Predict Software Downtime Prediction makes it possible.

The Problem with Traditional Software Downtime Prediction Methods

Traditionally, software teams wait until the later stages of development to measure key metrics like test hours and downtime incidents. By this point, addressing the root causes of downtime is often too late or too expensive. This reactive approach can lead to costly delays and poor software performance.

The Requs AI Approach

Requs AI offers a proactive solution by leveraging its predictive capabilities early in the project lifecycle. It starts by using its Risk Identification feature to predict the overall risk level of the software. From this, the Defect Prediction capability forecasts the number of defects the project is likely to have. Once a defect profile is established, the Software Downtime Prediction feature then generates the software failure rate prediction, software reliability prediction, and site reliability of the final product.

This approach allows teams to identify and address potential issues with meeting system downtime, availability and site reliability requirements, before they become major problems, saving time, money, and resources.

Predict downtime with confidence

The more questions you answer, the greater the confidence in the software downtime prediction, software reliability prediction, software failure rate prediction and site reliability prediction.
Built from world's largest software defect benchmarking

More than 600 factors measured against actual escaped defects on mission and safety critical systems. Predict defect density with AI from actual historical data from mission and safety critical systems.
Licensing

Dedicated or floating licenses. Yearly subscriptions or perpetual plans. Cloud or Desktop solution.
Tiered editions

Feature tiers allow you to purchase only the Requs AI Predict features you need.
Integrated suite

Requs AI Predict Risk Identification predicts one of seven percentile groups which indicate risk which ultimately affects the downtime prediction. Requs AI Predict Defect Prediction turns that risk into a prediction of defects and technical debt. Requs AI Edge Case Prediction and Requs AI Software FMEA takes the guesswork out of testing by predicting edge cases you might otherwise miss. Want to find out what's really costing you? Our advanced sensitivity analysis identifies the factors wasting your time and money, giving you a powerful tool for ROI analysis.

Software downtime prediction by Requs AI works as follows

Requs AI Predict product suite consisting of Requs AI Predict Risk Identification, Requs AI Predict Defect Prediction and Requs AI Predict Downtime Prediction works in a few simple steps to predict RAM metrics such as availability and site reliability with AI before the code is written:

You provide data: You answer a series of questions about your software’s design, your organization, and your testing practices, as well as any known risks.
The AI analyzes it: The machine learning model takes your answers and matches your specific development factors against a massive database of past projects.
It predicts a defect density in operation: By finding these matches, the model accurately predicts the expected testing and escaped defect density for your software.
It predicts escaped defects and defect discovery rate: It adjusts the defect density prediction by the story points, work effort or predicted size. It then predicts the discovery rate based on your inputs concerning deployment volume.
Site reliability, software availability prediction, software failure rate prediction, software reliability prediction and software downtime prediction are then computed by Requs AI Predict Software Downtime Prediction.
The RAM dashboard forecasts the unreliability, unavailability for the software over several Agile Program Increments. Software is never done. A true forecast considers all future program increments.