Cobalt Iron Receives European Patent

Cobalt Iron has received a European patent on its technology for dynamic data monitoring fidelity.

European patent no. 3684027, granted on Aug.16, describes new capabilities for the Cobalt Iron Compass® enterprise SaaS backup platform that will automatically and dynamically adjust data collection granularity and frequency in response to a detected event or condition. As a result, Compass will be better able to detect, debug, and remediate transient failures, inefficiencies, and security exposures in complex, distributed IT environments.

Comprehensive data collection and effective monitoring are woefully lacking in the enterprise IT world. For example, enterprise backup has many moving parts, including backup servers, backup server operating systems, a backup catalog or database, backup software, backup agents, storage devices, networking, and maybe cloud resources. Each of these components should be monitored continuously for health, capacity, performance, and ransomware issues, but that monitoring rarely happens.

Furthermore, under certain conditions or events, it is often desirable to perform higher fidelity (i.e., more detailed) and more frequent data collection and monitoring to help identify, analyse, remediate, and track any issues. Yet adequate data collection of these various metrics and conditions is rare. Even when some data collection occurs, it is almost always static in nature, meaning that systems do the same level of data collection at the same frequency no matter the situation or operational status.

Enterprises need more dynamic means of collecting data about IT infrastructure and operations. In particular, when certain conditions or events occur, IT administrators and other IT professionals must be able to collect more information from certain components or operations in order to properly analyse, prepare for, and respond to those conditions or events.

In just one of many examples, failing hardware devices might issue warnings, I/O errors, or transient errors, or they could demonstrate other symptoms. In these scenarios, it is often valuable to have more detailed and more frequent metrics for specific hardware devices or specific components of hardware devices in order to determine the nature and extent of the failures, particularly when it comes to transient errors.

This technology qualified for a patent because, unlike various other IT data collection, monitoring, and reporting tools that are almost all static, Cobalt Iron's technology introduces novel and automated approaches to adjusting the data collection fidelity and frequency levels of IT resources. Fidelity refers to the level of details collected. In essence, this patent discloses techniques to automatically turn the detail level and frequency of data collection up or down.

The techniques introduced in this patent will automatically initiate deeper and more frequent levels of data collection for all infrastructure components and operations that may be associated with a particular condition or event. This will enable administrators and other IT professionals to quickly gain deeper insights into issues in response to device warnings, failures, or other conditions. As a result, Compass will give more precise analysis of the environment and events, minimise risks to IT infrastructure and operations, facilitate problem resolution, and might even capture critical information about an event that would otherwise likely be lost.

Specifically, the newly patented techniques mean Compass will be able to:
• Identify hardware components and operations that might be associated with a certain condition or event, such as failing disk drives, transient hardware problems, network utilisation issues, ransomware attacks, or particular security conditions.
• Continually monitor for and analyse metrics, events, and conditions associated with hardware resources.
• Dynamically adjust data collection fidelity (i.e., adjust detail levels of its metrics, data, and operational data collection) and frequency for those components and operations based on conditions or events in the environment.
• Dynamically resume normal data collection when the condition or event has ceased.

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