udpate managedprocess tutorial with performance notes

Author: Tim Watson

_layouts/managedprocess.html

@@ -27,6 +27,7 @@
               <li><a href="#making_use_of_async"><i class="icon-chevron-right"></i> Making use of Async</a></li>
               <li><a href="#wiring_up_handlers"><i class="icon-chevron-right"></i> Wiring up handlers</a></li>
               <li><a href="#putting_it_all_together"><i class="icon-chevron-right"></i> Putting it all together</a></li>
+              <li><a href="#performance_considerations"><i class="icon-chevron-right"></i> Performance Considerations</a></li>
            </ul>
           </div>
         </div>

tutorials/3.managedprocess.md

@@ -353,3 +353,24 @@ Hopefully this has demonstrated a few benefits of the `ManagedProcess` API, alth
 it's really just scratching the surface. We have focussed on the code that matters -
 state transitions and decision making, without getting bogged down (much) with receiving
 or sending messages, apart from using some simple APIs when we needed to.
+
+### Performance Considerations
+
+We did not take much care over our choice of data structures. Might this have profound
+consequences for clients? The LIFO nature of the pending backlog is surprising, but
+we can change that quite easily by changing data structures.
+
+What's perhaps more of a concern is the cost of using `Async` everywhere - remember
+we used this in the *server* to handle concurrently executing tasks and obtaining
+their results. The `Async` module is also used by `ManagedProcess` to handle the
+`call` mechanism, and there *are* some overheads to using it. An invocation of
+`async` will create two new processes: one to perform the calculation and another
+to monitor the first and handle failure and/or cancellation. Spawning processes is
+cheap, but not free as each process is a haskell thread, plus some additional book
+keeping data.
+
+The cost of spawning two processes for each computation/task might represent just that
+bit too much overhead for some applications. In our next tutorial, we'll look at the
+`Control.Distributed.Process.Platform.Task` API, which looks a lot like `Async` but
+manages exit signals in a single thread and makes configurable task pools and task
+supervision strategy part of its API.