Extract relevant features from time series data
I think the first question you should ask before you start going off on a deep learning model is, can you tell when the failure is going to occur just by looking at a plot of your data? If you can't, then no model will help you deduce when a failure will occur. 

You shouldn't overlook some basic models also such as exponential or poisson distribution models that should model your current problem well.

Lastly, since it's a time series for rare events, some ways to gain more insight might include time between failures, identifying thresholds of the data value triggering a failure, splicing all the data into intervals and the number of failures, etc.. You should also check if the failures follow a pattern.