Data center monitoring and management operation including data center analytics failure forecasting operation

A system comprising:

• a processor;
• a data bus coupled to the processor;
• a data center asset client module;
• and, a non-transitory, computer-readable storage medium embodying computer program code, the non-transitory, computer-readable storage medium being coupled to the data bus, the computer program code interacting with a plurality of computer operations and comprising instructions executable by the processor and configured for:
• receiving data center data from a plurality of data center assets within a data center, the data center data comprising data center asset data;
• assigning the data center data to a vectorized input space;
• reducing a dimension of the vectorized input space to a latent space, the latent space providing an operational status analysis (OSA) model dimension;
• decoding the latent space to provide a vectorized decoded output space;
• performing a data center asset operational status forecasting operation using the vectorized decoded output space, the data center asset operational status forecasting operation generating data center asset operational status forecasting data;
• and,
• prioritizing data center asset remediation operations using the data center asset operational status forecasting data;
• and wherein
• the prioritizing uses a reward shaping operation when prioritizing the data center asset remediation operations;
• the reward shaping operation is used to train a policy;
• and,
• the policy is trained using one of semi supervised learning and unsupervised learning.

A non-transitory, computer-readable storage medium embodying computer program code, the computer program code comprising computer executable instructions configured for:

• receiving data center data from a plurality of data center assets within a data center, the data center data comprising data center asset data;
• assigning the data center data to a vectorized input space;
• reducing a dimension of the vectorized input space to a latent space, the latent space providing an operational status analysis (OSA) model dimension;
• decoding the latent space to provide a vectorized decoded output space;
• performing a data center asset operational status forecasting operation using the vectorized decoded output space, the data center asset operational status forecasting operation generating data center asset operational status forecasting data;
• and,
• prioritizing data center asset remediation operations using the data center asset operational status forecasting data;
• and wherein
• the prioritizing uses a reward shaping operation when prioritizing the data center asset remediation operations;
• the reward shaping operation is used to train a policy;
• and,
• the policy is trained using one of semi supervised learning and unsupervised learning.