docs: refine .md files

[poolifier.git] / docs / general-guidelines.md

diff --git a/docs/general-guidelines.md b/docs/general-guidelines.md
index c66bda4f387a9579b8097bc7be347105545f30c3..26bc7eda2d909b0ef40aa34d2494a1f766628c85 100644 (file)
--- a/docs/general-guidelines.md
+++ b/docs/general-guidelines.md
@@ -1,4 +1,5 @@
 ## General Guidelines
+
 Performance is one of the main target of these worker pool implementations, poolifier team wants to have a strong focus on this.  
 Poolifier already has a [benchmarks](./benchmarks/) folder where you can find some comparisons.
 
@@ -33,4 +34,4 @@ To choose your pool consider first that with a _FixedThreadPool_/_FixedClusterPo
 By doing so, your application will be ready to execute in parallel more tasks, but during idle time your application will consume more memory.  
 One good choice from poolifier team point of view is to profile your application using a fixed or dynamic worker pool, and analyze your application metrics when you increase/decrease the number of workers.  
 For example you could keep the memory footprint low by choosing a _DynamicThreadPool_/_DynamicClusterPool_ with a minimum of 5 workers, and allowing it to create new workers until a maximum of 50 workers if needed. This is the advantage of using a _DynamicThreadPool_/_DynamicClusterPool_.  
-But in general, **always profile your application**.
\ No newline at end of file
+But in general, **always profile your application**.