Why and when do I need to use the global step in tensorflow

I am using tensorflow, but I am not sure why I even need the global_step variable or if it is even necessary for training. I have sth like this:

gradients_and_vars = optimizer.compute_gradients(value) train_op = optimizer.apply_gradients(gradients_and_vars)

and then in my loop inside a session I do this:

_ = sess.run([train_op])

I am using a Queue to feed my data the the graph. Do I even have to instantiate a global_step variable?

My loop looks like this:

while not coord.should_stop():

So this loop stops, when it should stop. So why do I need the global_step at all?