Megmonit agent is purpose-built for containers and supports Docker containers natively. In Kubernetes Megaamonit integrates into the Kubelet binary to-discover all containers in the machine and collects CPU, memory, filesystem, and network usage statistics , also provides the overall machine usage by analyzing the ‘root’ container on the machine.

Megamonit with help of opentracing libraries like (Jaeger,Zipkin) will enable you to observe every request at scale. In real-time. Across web, mobile, microservices, and monoliths. Use distributed traces to understand performance problems and identify the teams that can fix them.

MegaMonit monitors the inputs and the outputs across operational systems, this enhances its capabilities of determining thresholds and consequentially setting them at a certain level that will eventually impact the customers if not taken care of.

MegaMonit monitors the inputs and the outputs across operational systems, this enhances its capabilities of determining thresholds and consequentially setting them at a certain level that will eventually impact the customers if not taken care of.

Artificial intelligence has extensively fortified its stance as the best option to avail to identify patterns while scanning and absorbing terabytes of data, that have proved to be cumbersome for humans. We at MEGAMONIT integrate AI as an extension of the abilities of the human skill set but not as a mere substitution.

MEGAMONIT helps you to identify and prioritize the actual problems that would be overbearing on your customers in times to come, rather than producing a plethora of unnecessary metrics and overwhelm the process of anomaly detection for the users.

MEGAMONIT is integrated with various plugins to process human language better and make the content better. It identifies the various groups of information people are looking for, analyzes the content, strives to understand the context behind it and provides a nearly accurate kind of information catering to the customer needs.