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IDT Solution
IDT designed and implemented a synthetic monitoring solution using Amazon CloudWatch canaries to simulate frontend user interactions. These canaries continuously tested application availability and functionality, ensuring that any malfunction—down to a single page component—would be detected in real time. The logic and structure of these tests were based on automated runbooks, allowing the monitoring to align closely with product requirements. Alerts generated by the canaries were routed to both the incident management team and the product team through the corporate messaging system, ensuring fast and targeted notification across relevant teams.
SYNTHETIC MONITORING STRATEGY FOR FRONTEND RELIABILITY ON AWS
Executive Summary
SavvyMoney partnered with IDT to develop and implement an automated monitoring solution for its frontend applications using Amazon CloudWatch canaries. The project aimed to proactively identify failures at the component level of the product’s web interface by continuously simulating user interactions. The solution was designed around codified monitoring runbooks provided by the QA team and integrated with a corporate messaging system to ensure timely alerting to both incident response and dedicated operational channels.
SYNTHETIC MONITORING STRATEGY FOR FRONTEND RELIABILITY ON AWS
Executive Summary
SavvyMoney partnered with IDT to develop and implement an automated monitoring solution for its frontend applications using Amazon CloudWatch canaries. The project aimed to proactively identify failures at the component level of the product’s web interface by continuously simulating user interactions. The solution was designed around codified monitoring runbooks provided by the QA team and integrated with a corporate messaging system to ensure timely alerting to both incident response and dedicated operational channels.
SavvyMoney Inc.
Case Study
The Challenge
As part of its operational goals, SavvyMoney required more precise, automated monitoring of its web applications. After an analysis was performed, we identified room for improvement in the existing tools, which could limit the granularity needed to detect failures in specific components of the page, increasing the risk of undetected issues and delayed response. Considering further expansion, a proactive monitoring system was needed, so the user experience could be protected, and engineering teams would be alerted to any problem. A solution was required to simulate user behavior and provide immediate alerts in case of any component-level failure.
The Challenge
As part of its operational goals, SavvyMoney required more precise, automated monitoring of its web applications. After an analysis was performed, we identified room for improvement in the existing tools, which could limit the granularity needed to detect failures in specific components of the page, increasing the risk of undetected issues and delayed response. Considering further expansion, a proactive monitoring system was needed, so the user experience could be protected, and engineering teams would be alerted to any problem. A solution was required to simulate user behavior and provide immediate alerts in case of any component-level failure.
The Challenge
As part of its operational goals, SavvyMoney required more precise, automated monitoring of its web applications. After an analysis was performed, we identified room for improvement in the existing tools, which could limit the granularity needed to detect failures in specific components of the page, increasing the risk of undetected issues and delayed response. Considering further expansion, a proactive monitoring system was needed, so the user experience could be protected, and engineering teams would be alerted to any problem. A solution was required to simulate user behavior and provide immediate alerts in case of any component-level failure.
The Benefits
With this solution, SavvyMoney achieved automated, continuous monitoring of its frontend applications, significantly improving its ability to detect and respond to issues. Failures affecting individual parts of the user interface could now be identified in real time through simulated user actions, reducing detection delays. The integration of QA-defined runbooks ensured that monitoring logic was directly aligned with business needs, while Slack-based alerting enabled immediate awareness among both incident and operational teams. This strengthened SavvyMoney’s reliability posture and supported a smoother, more resilient user experience.
IDT delivered a comprehensive observability solution that gave us full visibility into the performance and reliability of our new analytics platform. Their ability to move quickly without compromising quality was critical to meeting our launch timeline. With real-time diagnostics and streamlined monitoring across our infrastructure, we’re now able to detect and respond to issues before they affect users. We strongly endorse IDT for organizations committed to developing robust, data-driven systems that enhance resilience and efficiency.
Michael York VP, Information Security and DevOps SavvyMoney Inc.
