Overview
In Information Technology, telemetry data is information that is transmitted from systems and software to be collected and analyzed. Telemetry data contains information from hardware, applications, operating systems, and hypervisors. The results of analysis are used for increasing the resiliency of systems and applications, tuning the infrastructure for optimal operation, and resource planning.
A key outcome from analysis of telemetry data is predictive support for systems, preventing problems in addition to the other noted benefits. Sophistication of the analytics on telemetry data continues to advance, to the point now that the term AIOps is used. AIOps is short for Artificial Intelligence for Operations and denotes the machine learning used on the telemetry data, usually applied to systems.
Systems that usually have telemetry data include servers, networks, and storage. Much of the early focus on analytics has been on storage systems with demonstrable successes from newly introduced products by vendors. Those successes led to a broadening of usage for other vendors and investments to continue to advance the technology – now messaged as AIOps.
Customers gain from the use of telemetry data with analytics. A summary of the gain is a reduction in management needs: fewer situations to deal with and less attentive monitoring required. These gains are the outcome of the analytics. There is also a financial impact; effective analytics and actions frees up staff time, allowing them to focus on other important areas.
The analytics referred to most often is ‘predictive analytics’, learning from data across a large collective of systems to predict failures or impacts and take automated actions. Advanced implementations will make recommendations for changes, initiate service action including dispatching technicians, installing needed updates, and, in some cases, automatically making necessary changes.
Vendors are also benefiting from the improvements with telemetry data and analytics. Managed Services are offered by many vendors, providing expert management of systems or environments for their customers. With the improvements from analytics, the economies of scale are improved when there are many customers for managed services. The viability (and cost) can be greatly improved as a result.
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