Which machine learning technique can be used for predictive log analysis

I have log data with 100k records. And

These parameters.

It looks like this. message types can be helpful for anomaly type detection. Out of total 15 message 5 message considered as anomaly.

e.g. invalid user, connection closed by invalid user.

Option 1 - Text classification model

Create a classification model using text message, where it classifies the record based on message text.

But I want to to use predictive analytics using date/time parameters so that it can help for future anomaly prediction. For example every week a particular anomaly occurs at particular points of time, the model should be able to predict upcoming anomaly events.

But I am not sure which algorithm can be helpful for this kind of analysis. Any recommendation?

I see anomaly messages are occurring with high frequency so predictive analytics should be possible.