I would like a direction for a ML technique to predict when an anomaly will occur in a system, like when the CPU use differs from a normal state.
My data consists of system metrics collected from AWS EC2 instances such as CPU Utilization, Disk operations, Memory Use etc. Each row of the data consists of a timestamp and values for the metrics.
My idea was to perhaps build a LSTM Recurrent Neural Network since I´m working with time series. Do you think this would be a good approach for this problem?