Revolutionize Application Monitoring with Cavisson’s AI-Powered APM Suite
Simplify complexity, accelerate resolution, and ensure seamless application performance with cutting-edge AI capabilities.
Simplify complexity, accelerate resolution, and ensure seamless application performance with cutting-edge AI capabilities.
AI-Driven Monitoring for Today’s Complex Applications
With the advent of micro-services based architecture, software development and deployment have never been as complex as we witness it today. With distributed computing being another cornerstone, managing critical applications and their numerous components has become a resource intensive activity for teams across the organization.
With automatic root cause analysis, anomaly/outlier detection, metric correlation, and intelligent flow-path analysis, engineers can rely on machine learning to intelligently monitor larger numbers of objects, cut through the noise to provide clear visibility, and enable continual awareness of increasingly complex systems. This document provides an overview of critical AI capabilities implemented across Cavisson’s product suite.
AutoRCA
Cavisson’s monitoring solution comes equipped with a powerful AutoRCA or automatic root cause analysis which identifies the reason behind a generated alert by taking into account all the metrics captured across your entire application stack. Utilizing the Bayesian network algorithm, millions of metrics are analyzed and a causal relationship is established to accurately narrow down the root cause behind critical issues plaguing the application. The AutoRCA feature is integral for organizations monitoring hundreds of services and thousands of hosts and containers as it can take hours of digging to find the root cause. Instead of relying on manual guesswork or a time-consuming, wide-ranging exploration of possible root causes, AutoRCA saves a massive amount of time that further aids organizations on focusing more on delivering than debugging.
Outlier Detection
Monitoring large fleets of servers, containers, IoT devices, or application instances makes it difficult to keep tabs on the health and performance of any individual member of the fleet. Cavisson’s outlier detection algorithms constantly evaluate large fleets or groups to identify if any member of the fleet starts behaving abnormally, as compared to its peers. Using outlier detection, engineers can automatically identify unhealthy application servers, databases, or other systems in need of maintenance, without having to define ahead of time what normal, healthy behavior looks like.
Anomaly Detection
Anomaly detection addresses one of the core challenges in monitoring dynamic, responsive, ever-scaling infrastructure: How to define normal versus abnormal performance. Setting static thresholds often leads to false alarms due to normal variations in key metrics like website traffic and customer checkouts, which tend to rise and fall depending on the time of day, day of the week, or day of the month. Anomaly detection accounts for those expected variations, as well as long-term trends, to intelligently flag behavior that is truly unexpected. Cavisson’s anomaly detection algorithms are rooted in established statistical models, but have been heavily adapted for the domain of high-scale infrastructure and application monitoring.
Flowpath Analyzer
An advanced debugging tool that goes beyond simply tracing the path of a transaction and analyzes the flow of transactions across multiple paths, even those with diverse method combinations, to identify problematic patterns and pinpoint the specific methods causing issues. Anomaly detection accounts for those expected variations, as well as long-term trends, to intelligently flag behavior that is truly unexpected. Cavisson’s anomaly detection algorithms are rooted in established statistical models, but have been heavily adapted for the domain of high-scale infrastructure and application monitoring.
With advanced AI capabilities deployed at multiple points i.e. for analyzing transactions, detecting anomalies/outliers across metrics and automatically detecting the root cause behind critical issues, Cavisson’s monitoring solution provides an enterprise-ready approach towards monitoring today’s complex and distributed applications with the help of proven, production ready AI based analysis to drastically reduce the MTTR.
Organizations utilizing Cavisson’s monitoring suite have witnessed a massive uptick in the productivity across IT operations and development as teams now focus more on creating value adds for end users instead of spending countless hours to identify and fix issues.
Today to harness Cavisson’s cutting edge AI based monitoring capabilities and elevate your end user experience by building resistance to failure.