The COVID pandemic forced many education programs to rely upon online learning as their primary means of education for the academic year. Tools that had been used to supplement a classroom-first industry were now the main portal for students and educators. This meant more students and teachers coming onto the platform, and almost all users relying on the system to learn, educate, and communicate.

One startup, Apprendis, became the main platform of learning for science related subjects for thousands of students and teachers. With a small team of three, they needed to quickly scale while meeting the new needs of all users.


The startup used Cloudwatch, but did not have a dedicated IT team to manually configure all the alerts and review all alerts that Cloudwatch sent their way. Moreover, it was difficult to determine which ones were true problems and which ones were noise. Specifically, at a startup, how can one or two people keep up with all the alerts from Cloudwatch to prevent the system from going down? Once an alert was investigated and found to be a concern, how quickly could changes be made before the system goes down?


The startup implemented InsightFinder to automatically alert the team with the issues  that mattered, help them quickly find the root cause, and resolve the issues before their customers feel any glitches. As a result, this AWS cloudwatch customer maintained 100% uptime with proactive incident prevention during their over 800% pandemic growth.

Because InsightFinder caught 100% of their software bugs and security breaches, it allows the team to scale their system and ship new features without hiring an army of DevOps engineers. Because of InsightFinder’s real time alerting capability, it is feasible for a small technical team to keep up with important alerts and find the root cause right within the InsightFinder using CloudWatch data only.

What’s next?

As this platform continues to scale in both size and breadth of offerings,  it uses InsightFinder to monitor its system and identify any potential issues before their customers get impacted. Most recently, this Cloudwatch customer changed its underlying infrastructure to further scale how many users we can handle simultaneously. InsightFinder helped Apprendis monitor performance and make sure the changes made had no errors, and a positive impact. InsightFinder allows companies of all sizes to innovate more quickly with their existing Cloudwatch data and have confidence that InsightFinder will help them scale.

Other Resources

A major credit card company’s mobile payment service experienced severe performance degradation on a Friday afternoon.
InsightFinder utilizes the industry’s best unsupervised multivariate machine learning algorithms to analyze a large amount of production system data.