How to create clusters based on sentence similarity?
For this problem, I would start with a simple bag of words model and use that as a baseline. 

This is an example : https://medium.com/@MSalnikov/text-clustering-with-k-means-and-tf-idf-f099bcf95183 , http://brandonrose.org/clustering

For logs, this might be sufficient since it will easily filter out common words like date etc. 

If this does not work well for a given usecase, next step is to try Doc2Vec and similar methods that project sentences to a vector space.