-- `maxInactiveTime` - Max time to wait tasks to work on (in ms), after this period the new worker threads will die.
-The last active time of your worker unit will be updated when a task is submitted to a worker or when a worker terminate a task.
-If `killBehavior` is set to `KillBehaviors.HARD` this value represents also the timeout for the tasks that you submit to the pool, when this timeout expires your tasks is interrupted and the worker is killed if is not part of the minimum size of the pool.
-If `killBehavior` is set to `KillBehaviors.SOFT` your tasks have no timeout and your workers will not be terminated until your task is completed.
-Default: 60.000 ms
-
-- `async` - true/false, true if your function contains async pieces else false
-- `killBehavior` - Dictates if your async unit (worker/process) will be deleted in case that a task is active on it.
-**SOFT**: If `currentTime - lastActiveTime` is greater than `maxInactiveTime` but a task is still running, then the worker **wont** be deleted.
-**HARD**: If `lastActiveTime` is greater than `maxInactiveTime` but a task is still running, then the worker will be deleted.
-This option only apply to the newly created workers.
-Default: `SOFT`
-
-## Choose your pool
-
-Performance is one of the main target of these thread pool implementations, we want to have a strong focus on this.
-We already have a bench folder where you can find some comparisons.
-To choose your pool consider that with a FixedThreadPool or a DynamicThreadPool (in this case is important the min parameter passed to the constructor) your application memory footprint will increase.
-Increasing the memory footprint, your application will be ready to accept more CPU bound tasks, but during idle time your application will consume more memory.
-One good choose from my point of view is to profile your application using Fixed/Dynamic thread pool, and to see your application metrics when you increase/decrease the num of threads.
-For example you could keep the memory footprint low choosing a DynamicThreadPool with 5 threads, and allow to create new threads until 50/100 when needed, this is the advantage to use the DynamicThreadPool.
-But in general, **always profile your application**
+- `maxInactiveTime` (optional) - Maximum waiting time in milliseconds for tasks on newly created workers. After this time newly created workers will die.
+ The last active time of your worker will be updated when it terminates a task.
+ If `killBehavior` is set to `KillBehaviors.HARD` this value represents also the timeout for the tasks that you submit to the pool, when this timeout expires your tasks is interrupted before completion and removed. The worker is killed if is not part of the minimum size of the pool.
+ If `killBehavior` is set to `KillBehaviors.SOFT` your tasks have no timeout and your workers will not be terminated until your task is completed.
+ Default: `60000`
+
+- `killBehavior` (optional) - Dictates if your worker will be deleted in case a task is active on it.
+ **KillBehaviors.SOFT**: If `currentTime - lastActiveTime` is greater than `maxInactiveTime` but a task is still executing or queued, then the worker **won't** be deleted.
+ **KillBehaviors.HARD**: If `currentTime - lastActiveTime` is greater than `maxInactiveTime` but a task is still executing or queued, then the worker will be deleted.
+ This option only apply to the newly created workers.
+ Default: `KillBehaviors.SOFT`
+
+#### `YourWorker.hasTaskFunction(name)`
+
+`name` (mandatory) The task function name
+
+This method is available on both worker implementations and returns a boolean.
+
+#### `YourWorker.addTaskFunction(name, fn)`
+
+`name` (mandatory) The task function name
+`fn` (mandatory) The task function
+
+This method is available on both worker implementations and returns a boolean.
+
+#### `YourWorker.removeTaskFunction(name)`
+
+`name` (mandatory) The task function name
+
+This method is available on both worker implementations and returns a boolean.
+
+#### `YourWorker.listTaskFunctions()`
+
+This method is available on both worker implementations and returns an array of the task function names.
+
+#### `YourWorker.setDefaultTaskFunction(name)`
+
+`name` (mandatory) The task function name
+
+This method is available on both worker implementations and returns a boolean.
+
+## General guidance
+
+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.
+
+### Internal Node.js thread pool
+
+Before to jump into each poolifier pool type, let highlight that **Node.js comes with a thread pool already**, the libuv thread pool where some particular tasks already run by default.
+Please take a look at [which tasks run on the libuv thread pool](https://nodejs.org/en/docs/guides/dont-block-the-event-loop/#what-code-runs-on-the-worker-pool).
+
+**If your task runs on libuv thread pool**, you can try to:
+
+- Tune the libuv thread pool size setting the [UV_THREADPOOL_SIZE](https://nodejs.org/api/cli.html#cli_uv_threadpool_size_size).
+
+and/or
+
+- Use poolifier cluster pools that are spawning child processes, they will also increase the number of libuv threads since that any new child process comes with a separated libuv thread pool. **More threads does not mean more fast, so please tune your application**.
+
+### Cluster vs Threads worker pools
+
+**If your task does not run into libuv thread pool** and is CPU intensive then poolifier **thread pools** (_FixedThreadPool_ and _DynamicThreadPool_) are suggested to run CPU intensive tasks, you can still run I/O intensive tasks into thread pools, but performance enhancement is expected to be minimal.
+Thread pools are built on top of Node.js [worker_threads](https://nodejs.org/api/worker_threads.html) module.
+
+**If your task does not run into libuv thread pool** and is I/O intensive then poolifier **cluster pools** (_FixedClusterPool_ and _DynamicClusterPool_) are suggested to run I/O intensive tasks, again you can still run CPU intensive tasks into cluster pools, but performance enhancement is expected to be minimal.
+Consider that by default Node.js already has great performance for I/O tasks (asynchronous I/O).
+Cluster pools are built on top of Node.js [cluster](https://nodejs.org/api/cluster.html) module.
+
+If your task contains code that runs on libuv plus code that is CPU intensive or I/O intensive you either split it either combine more strategies (i.e. tune the number of libuv threads and use cluster/thread pools).
+But in general, **always profile your application**.
+
+### Fixed vs Dynamic pools
+
+To choose your pool consider first that with a _FixedThreadPool_/_FixedClusterPool_ or a _DynamicThreadPool_/_DynamicClusterPool_ your application memory footprint will increase.
+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 static 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**.