r/MachineLearning - [Discussion] Multivariate multi step time series forecasting with LSTM

I'm new to RNNs and LSTM and would like some direction with a problem I have. I have a data set containing system metrics (like CPU utilization, disk operations, memory use) of an AWS EC2 instance with a total of 7 columns and around 8000 rows. Each row represent 5 minutes of system performance. I want to build a LSTM model to forecast the features for let's say the next half hour based on previous time steps. What would be the best approach for solving a problem like this?