Machine Learning CAN Help Your NOC Win the Battle

Machine Learning for NOCs and IT Operations Teams

The increasing complexity of IT, customer expectations for application availability and performance, and the importance of supporting new initiatives and digital services together help network operations centers (NOCs) and operations teams. IT like you. Impose unprecedented demands within large and complex organizations.

Machine learning helps noc support and IT operations teams autonomously respond to incidents 24 hours a day, 7 days a week, helping to cost-effectively escalate and meet these demands.

However, before you dive into the world of machine learning and artificial intelligence powered IT Ops tools (sometimes also called AIOps tools), and before you prepare them at the NOC, consider the common issues and how they can be overcome.

Problem 1: Lack of Transparency

In many cases, IT Ops tools with machine learning (ML) technology are opaque. This not only makes it difficult to agree on a result, but can also make it difficult to treat a result. To overcome this problem, companies must choose ML-based IT Ops tools that present their logic in a way that humans can see and understand.

Problem 2: User Has No Control

The second major problem companies face is that many ML-dependent tools cannot edit, preview, and test logic. Therefore, it cannot incorporate tribal / business knowledge. You cannot test logic against past data sets or run a "what if" experiment. To overcome this problem, companies must choose ML-based IT Ops tools with human-friendly dashboards designed to give teams control at all times.

Problem 3: Building Trust Is Not Easy

The last and potentially the most malicious problem is a trustworthy one. After a few months of investing in a new IT operations tool with ML, the organization found that hiring was moderate. Users inside and outside the NOC do not completely trust the new tools, and therefore cannot confidently adopt and use the new tools. In many cases, this is because many ML-dependent IT Ops tools are not deterministic (the same entry provides different results at different times) and are opaque black squares.

Open box machine learning powered IT Ops tools help companies overcome all of these challenges.

These tools are completely transparent, controllable, and reliable, so they can be used by L1, L2, and L3, as well as anyone else outside the NOC, to perform them when performing mission critical activities. You can trust and learn to depend.

BigPanda trains NOC and IT Ops teams within the largest, most complex and dynamic organizations in the world to support digital applications and services in a scalable and cost-effective manner.