diff --git a/content/applications/general/developer_mode.rst b/content/applications/general/developer_mode.rst
index 47176f8ce..0a01bbefe 100644
--- a/content/applications/general/developer_mode.rst
+++ b/content/applications/general/developer_mode.rst
@@ -59,6 +59,8 @@ debug mode, add `?debug=0` instead.
    :ref:`assets mode <frontend/framework/assets_debug_mode>`, and `?debug=tests` enables
    the :ref:`tests mode <frontend/framework/tests_debug_mode>`.
 
+.. _developer-mode/mode-tools:
+
 Locate the mode tools
 =====================
 
diff --git a/content/contributing/development/coding_guidelines.rst b/content/contributing/development/coding_guidelines.rst
index 802d3b776..9463be5d0 100644
--- a/content/contributing/development/coding_guidelines.rst
+++ b/content/contributing/development/coding_guidelines.rst
@@ -589,32 +589,6 @@ Programming in Odoo
 - As in python, use ``filtered``, ``mapped``, ``sorted``, ... methods to
   ease code reading and performance.
 
-
-Make your method work in batch
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-When adding a function, make sure it can process multiple records by iterating
-on self to treat each record.
-
-.. code-block:: python
-
-    def my_method(self)
-        for record in self:
-            record.do_cool_stuff()
-
-For performance issue, when developing a 'stat button' (for instance), do not
-perform a ``search`` or a ``search_count`` in a loop. It
-is recommended to use ``read_group`` method, to compute all value in only one request.
-
-.. code-block:: python
-
-    def _compute_equipment_count(self):
-    """ Count the number of equipment per category """
-        equipment_data = self.env['hr.equipment'].read_group([('category_id', 'in', self.ids)], ['category_id'], ['category_id'])
-        mapped_data = dict([(m['category_id'][0], m['category_id_count']) for m in equipment_data])
-        for category in self:
-            category.equipment_count = mapped_data.get(category.id, 0)
-
-
 Propagate the context
 ~~~~~~~~~~~~~~~~~~~~~
 The context is a ``frozendict`` that cannot be modified. To call a method with
diff --git a/content/developer/cli.rst b/content/developer/cli.rst
index 9250935bd..e55858cb4 100644
--- a/content/developer/cli.rst
+++ b/content/developer/cli.rst
@@ -702,8 +702,9 @@ Database Population
 .. program:: odoo-bin populate
 
 Odoo CLI supports database population features. If the feature is
-:ref:`implemented on a given model <reference/testing/populate/methods>`, it allows automatic data
-generation of the model's records to test your modules in databases containing non-trivial amounts of records.
+:ref:`implemented on a given model <reference/performance/populate/methods>`, it allows automatic
+data generation of the model's records to test your modules in databases containing non-trivial
+amounts of records.
 
 .. code-block:: console
 
@@ -720,8 +721,7 @@ generation of the model's records to test your modules in databases containing n
     of a given model (cf. the :file:`populate` folder of modules for further details).
 
 .. seealso::
-
-    :ref:`reference/testing/populate`
+   :ref:`reference/performance/populate`
 
 .. _reference/cmdline/cloc:
 
diff --git a/content/developer/howtos.rst b/content/developer/howtos.rst
index 431b7b532..c7d96af7a 100644
--- a/content/developer/howtos.rst
+++ b/content/developer/howtos.rst
@@ -12,7 +12,6 @@ Tutorials
     howtos/website
     howtos/backend
     howtos/web_services
-    howtos/profilecode
     howtos/company
     howtos/accounting_localization
     howtos/translations
diff --git a/content/developer/howtos/profilecode.rst b/content/developer/howtos/profilecode.rst
deleted file mode 100644
index aa1c7a6c4..000000000
--- a/content/developer/howtos/profilecode.rst
+++ /dev/null
@@ -1,131 +0,0 @@
-===================
-Profiling Odoo code
-===================
-
-.. warning::
-
-    This tutorial requires :ref:`having installed Odoo <setup/install>`
-    and :doc:`writing Odoo code <backend>`
-
-Graph a method
-==============
-
-Odoo embeds a profiler of code. This embedded profiler output can be used to
-generate a graph of calls triggered by the method, number of queries, percentage
-of time taken in the method itself as well as the time that the method took and
-its sub-called methods.
-
-.. code:: python
-
-    from odoo.tools.misc import profile
-    [...]
-    @profile('/temp/prof.profile')
-    def mymethod(...)
-
-This produces a file called /temp/prof.profile
-
-A tool called *gprof2dot* will produce a graph with this result:
-
-.. code:: bash
-
-    gprof2dot -f pstats -o /temp/prof.xdot /temp/prof.profile
-
-A tool called *xdot* will display the resulting graph:
-
-.. code:: bash
-    
-    xdot /temp/prof.xdot
-    
-Log a method
-============
-
-Another profiler can be used to log statistics on a method:
-
-.. code:: python
-
-    from odoo.tools.profiler import profile
-    [...]
-    @profile
-    @api.model
-    def mymethod(...):
-
-The statistics will be displayed into the logs once the method to be analysed is
-completely reviewed.
-
-.. code:: bash
-
-    2018-03-28 06:18:23,196 22878 INFO openerp odoo.tools.profiler:
-    calls     queries   ms
-    project.task ------------------------ /home/odoo/src/odoo/addons/project/models/project.py, 638
-
-    1         0         0.02          @profile
-                                      @api.model
-                                      def create(self, vals):
-                                          # context: no_log, because subtype already handle this
-    1         0         0.01              context = dict(self.env.context, mail_create_nolog=True)
-
-                                          # for default stage
-    1         0         0.01              if vals.get('project_id') and not context.get('default_project_id'):
-                                              context['default_project_id'] = vals.get('project_id')
-                                          # user_id change: update date_assign
-    1         0         0.01              if vals.get('user_id'):
-                                              vals['date_assign'] = fields.Datetime.now()
-                                          # Stage change: Update date_end if folded stage
-    1         0         0.0               if vals.get('stage_id'):
-                                              vals.update(self.update_date_end(vals['stage_id']))
-    1         108       631.8             task = super(Task, self.with_context(context)).create(vals)
-    1         0         0.01              return task
-
-    Total:
-    1         108       631.85
-
-Dump stack
-==========
-
-Sending the SIGQUIT signal to an Odoo process (only available on POSIX) makes
-this process output the current stack trace to log, with info level. When an
-odoo process seems stuck, sending this signal to the process permit to know
-what the process is doing, and letting the process continue his job.
-
-Tracing code execution
-======================
-
-Instead of sending the SIGQUIT signal to an Odoo process often enough, to check
-where the processes are performing worse than expected, we can use the `py-spy`_ tool to
-do it for us.
-
-Install py-spy
---------------
-
-.. code:: bash
-
-    python3 -m pip install py-spy
-
-Record executed code
---------------------
-
-As py-spy is installed, we now record the executed code lines.
-This tool will record, multiple times a second, the stacktrace of the process.
-
-.. code:: bash
-
-    # record to raw file
-    py-spy record -o profile.json -f speedscope --pid <PID>
-
-    # OR record directly to svg
-    py-spy record -o profile.svg --pid <PID>
-
-where <PID> is the process ID of the odoo process you want to graph.
-
-To open profile.json you can use online tool `speedscope.app`_.
-
-To open profile.svg you should use browser, because other viewer may not
-support interactive part.
-
-
-.. image:: profilecode/flamegraph.svg
-
-
-.. _py-spy: https://github.com/benfred/py-spy
-
-.. _speedscope.app: https://www.speedscope.app/
diff --git a/content/developer/howtos/profilecode/flamegraph.svg b/content/developer/howtos/profilecode/flamegraph.svg
deleted file mode 100644
index a20921ad0..000000000
--- a/content/developer/howtos/profilecode/flamegraph.svg
+++ /dev/null
@@ -1,315 +0,0 @@
-<svg width="1200" height="1078" onload="init(evt)" viewBox="0 0 1200 1078" xmlns="http://www.w3.org/2000/svg"><defs><linearGradient id="background" y2="1" x2="0"><stop stop-color="#eee" offset="5%"/><stop stop-color="#eeeeb0" offset="95%"/></linearGradient></defs><style>.func_g:hover{stroke:#000;stroke-width:.5;cursor:pointer}</style><script type="text/ecmascript"><![CDATA[
-	var details, searchbtn, matchedtxt, svg;
-	function init(evt) {
-		details = document.getElementById("details").firstChild;
-		searchbtn = document.getElementById("search");
-		matchedtxt = document.getElementById("matched");
-		svg = document.getElementsByTagName("svg")[0];
-		searching = 0;
-	}
-
-	// mouse-over for info
-	function s(node) {		// show
-		info = g_to_text(node);
-		details.nodeValue = "Function: " + info;
-	}
-	function c() {			// clear
-		details.nodeValue = ' ';
-	}
-
-	// ctrl-F for search
-	window.addEventListener("keydown",function (e) {
-		if (e.keyCode === 114 || (e.ctrlKey && e.keyCode === 70)) {
-			e.preventDefault();
-			search_prompt();
-		}
-	})
-
-	// functions
-	function find_child(parent, name, attr) {
-		var children = parent.childNodes;
-		for (var i=0; i<children.length;i++) {
-			if (children[i].tagName == name)
-				return (attr != undefined) ? children[i].attributes[attr].value : children[i];
-		}
-		return;
-	}
-	function orig_save(e, attr, val) {
-		if (e.attributes["_orig_"+attr] != undefined) return;
-		if (e.attributes[attr] == undefined) return;
-		if (val == undefined) val = e.attributes[attr].value;
-		e.setAttribute("_orig_"+attr, val);
-	}
-	function orig_load(e, attr) {
-		if (e.attributes["_orig_"+attr] == undefined) return;
-		e.attributes[attr].value = e.attributes["_orig_"+attr].value;
-		e.removeAttribute("_orig_"+attr);
-	}
-	function g_to_text(e) {
-		var text = find_child(e, "title").firstChild.nodeValue;
-		return (text)
-	}
-	function g_to_func(e) {
-		var func = g_to_text(e);
-		// if there's any manipulation we want to do to the function
-		// name before it's searched, do it here before returning.
-		return (func);
-	}
-	function update_text(e) {
-		var r = find_child(e, "rect");
-		var t = find_child(e, "text");
-		var w = parseFloat(r.attributes["width"].value) -3;
-		var txt = find_child(e, "title").textContent.replace(/\([^(]*\)$/,"");
-		t.attributes["x"].value = parseFloat(r.attributes["x"].value) +3;
-
-		// Smaller than this size won't fit anything
-		if (w < 2*12*0.59) {
-			t.textContent = "";
-			return;
-		}
-
-		t.textContent = txt;
-		// Fit in full text width
-		if (/^ *$/.test(txt) || t.getSubStringLength(0, txt.length) < w)
-			return;
-
-		for (var x=txt.length-2; x>0; x--) {
-			if (t.getSubStringLength(0, x+2) <= w) {
-				t.textContent = txt.substring(0,x) + "..";
-				return;
-			}
-		}
-		t.textContent = "";
-	}
-
-	// zoom
-	function zoom_reset(e) {
-		if (e.attributes != undefined) {
-			orig_load(e, "x");
-			orig_load(e, "width");
-		}
-		if (e.childNodes == undefined) return;
-		for(var i=0, c=e.childNodes; i<c.length; i++) {
-			zoom_reset(c[i]);
-		}
-	}
-	function zoom_child(e, x, ratio) {
-		if (e.attributes != undefined) {
-			if (e.attributes["x"] != undefined) {
-				orig_save(e, "x");
-				e.attributes["x"].value = (parseFloat(e.attributes["x"].value) - x - 10) * ratio + 10;
-				if(e.tagName == "text") e.attributes["x"].value = find_child(e.parentNode, "rect", "x") + 3;
-			}
-			if (e.attributes["width"] != undefined) {
-				orig_save(e, "width");
-				e.attributes["width"].value = parseFloat(e.attributes["width"].value) * ratio;
-			}
-		}
-
-		if (e.childNodes == undefined) return;
-		for(var i=0, c=e.childNodes; i<c.length; i++) {
-			zoom_child(c[i], x-10, ratio);
-		}
-	}
-	function zoom_parent(e) {
-		if (e.attributes) {
-			if (e.attributes["x"] != undefined) {
-				orig_save(e, "x");
-				e.attributes["x"].value = 10;
-			}
-			if (e.attributes["width"] != undefined) {
-				orig_save(e, "width");
-				e.attributes["width"].value = parseInt(svg.width.baseVal.value) - (10*2);
-			}
-		}
-		if (e.childNodes == undefined) return;
-		for(var i=0, c=e.childNodes; i<c.length; i++) {
-			zoom_parent(c[i]);
-		}
-	}
-	function zoom(node) {
-		var attr = find_child(node, "rect").attributes;
-		var width = parseFloat(attr["width"].value);
-		var xmin = parseFloat(attr["x"].value);
-		var xmax = parseFloat(xmin + width);
-		var ymin = parseFloat(attr["y"].value);
-		var ratio = (svg.width.baseVal.value - 2*10) / width;
-
-		// XXX: Workaround for JavaScript float issues (fix me)
-		var fudge = 0.0001;
-
-		var unzoombtn = document.getElementById("unzoom");
-		unzoombtn.style["opacity"] = "1.0";
-
-		var el = document.getElementsByTagName("g");
-		for(var i=0;i<el.length;i++){
-			var e = el[i];
-			var a = find_child(e, "rect").attributes;
-			var ex = parseFloat(a["x"].value);
-			var ew = parseFloat(a["width"].value);
-			// Is it an ancestor
-			if (0 == 0) {
-				var upstack = parseFloat(a["y"].value) > ymin;
-			} else {
-				var upstack = parseFloat(a["y"].value) < ymin;
-			}
-			if (upstack) {
-				// Direct ancestor
-				if (ex <= xmin && (ex+ew+fudge) >= xmax) {
-					e.style["opacity"] = "0.5";
-					zoom_parent(e);
-					e.onclick = function(e){unzoom(); zoom(this);};
-					update_text(e);
-				}
-				// not in current path
-				else
-					e.style["display"] = "none";
-			}
-			// Children maybe
-			else {
-				// no common path
-				if (ex < xmin || ex + fudge >= xmax) {
-					e.style["display"] = "none";
-				}
-				else {
-					zoom_child(e, xmin, ratio);
-					e.onclick = function(e){zoom(this);};
-					update_text(e);
-				}
-			}
-		}
-	}
-	function unzoom() {
-		var unzoombtn = document.getElementById("unzoom");
-		unzoombtn.style["opacity"] = "0.0";
-
-		var el = document.getElementsByTagName("g");
-		for(i=0;i<el.length;i++) {
-			el[i].style["display"] = "block";
-			el[i].style["opacity"] = "1";
-			zoom_reset(el[i]);
-			update_text(el[i]);
-		}
-	}
-
-	// search
-	function reset_search() {
-		var el = document.getElementsByTagName("rect");
-		for (var i=0; i < el.length; i++) {
-			orig_load(el[i], "fill")
-		}
-	}
-	function search_prompt() {
-		if (!searching) {
-			var term = prompt("Enter a search term (regexp " +
-			    "allowed, eg: ^ext4_)", "");
-			if (term != null) {
-				search(term)
-			}
-		} else {
-			reset_search();
-			searching = 0;
-			searchbtn.style["opacity"] = "0.1";
-			searchbtn.firstChild.nodeValue = "Search"
-			matchedtxt.style["opacity"] = "0.0";
-			matchedtxt.firstChild.nodeValue = ""
-		}
-	}
-	function search(term) {
-		var re = new RegExp(term);
-		var el = document.getElementsByTagName("g");
-		var matches = new Object();
-		var maxwidth = 0;
-		for (var i = 0; i < el.length; i++) {
-			var e = el[i];
-			if (e.attributes["class"].value != "func_g")
-				continue;
-			var func = g_to_func(e);
-			var rect = find_child(e, "rect");
-			if (rect == null) {
-				// the rect might be wrapped in an anchor
-				// if nameattr href is being used
-				if (rect = find_child(e, "a")) {
-				    rect = find_child(r, "rect");
-				}
-			}
-			if (func == null || rect == null)
-				continue;
-
-			// Save max width. Only works as we have a root frame
-			var w = parseFloat(rect.attributes["width"].value);
-			if (w > maxwidth)
-				maxwidth = w;
-
-			if (func.match(re)) {
-				// highlight
-				var x = parseFloat(rect.attributes["x"].value);
-				orig_save(rect, "fill");
-				rect.attributes["fill"].value =
-				    "rgb(230,0,230)";
-
-				// remember matches
-				if (matches[x] == undefined) {
-					matches[x] = w;
-				} else {
-					if (w > matches[x]) {
-						// overwrite with parent
-						matches[x] = w;
-					}
-				}
-				searching = 1;
-			}
-		}
-		if (!searching)
-			return;
-
-		searchbtn.style["opacity"] = "1.0";
-		searchbtn.firstChild.nodeValue = "Reset Search"
-
-		// calculate percent matched, excluding vertical overlap
-		var count = 0;
-		var lastx = -1;
-		var lastw = 0;
-		var keys = Array();
-		for (k in matches) {
-			if (matches.hasOwnProperty(k))
-				keys.push(k);
-		}
-		// sort the matched frames by their x location
-		// ascending, then width descending
-		keys.sort(function(a, b){
-			return a - b;
-		});
-		// Step through frames saving only the biggest bottom-up frames
-		// thanks to the sort order. This relies on the tree property
-		// where children are always smaller than their parents.
-		var fudge = 0.0001;	// JavaScript floating point
-		for (var k in keys) {
-			var x = parseFloat(keys[k]);
-			var w = matches[keys[k]];
-			if (x >= lastx + lastw - fudge) {
-				count += w;
-				lastx = x;
-				lastw = w;
-			}
-		}
-		// display matched percent
-		matchedtxt.style["opacity"] = "1.0";
-		pct = 100 * count / maxwidth;
-		if (pct == 100)
-			pct = "100"
-		else
-			pct = pct.toFixed(1)
-		matchedtxt.firstChild.nodeValue = "Matched: " + pct + "%";
-	}
-	function searchover(e) {
-		searchbtn.style["opacity"] = "1.0";
-	}
-	function searchout(e) {
-		if (searching) {
-			searchbtn.style["opacity"] = "1.0";
-		} else {
-			searchbtn.style["opacity"] = "0.1";
-		}
-	}
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\ No newline at end of file
diff --git a/content/developer/reference/backend.rst b/content/developer/reference/backend.rst
index ead2caa7c..16938a300 100644
--- a/content/developer/reference/backend.rst
+++ b/content/developer/reference/backend.rst
@@ -14,6 +14,7 @@ Python framework
     backend/module
     backend/reports
     backend/security
+    backend/performance
     backend/testing
     backend/http
     backend/mixins
diff --git a/content/developer/reference/backend/performance.rst b/content/developer/reference/backend/performance.rst
new file mode 100644
index 000000000..1167d9e17
--- /dev/null
+++ b/content/developer/reference/backend/performance.rst
@@ -0,0 +1,540 @@
+:custom-css: performance.css
+
+===========
+Performance
+===========
+
+.. _performance/profiling:
+
+Profiling
+=========
+
+.. currentmodule:: odoo.tools.profiler
+
+Profiling is about analysing the execution of a program and measure aggregated data. These data can
+be the elapsed time for each function, the executed SQL queries...
+
+While profiling does not improve the performance of a program by itself, it can prove very helpful
+in finding performance issues and identifying which part of the program is responsible for them.
+
+Odoo provides an integrated profiling tool that allows recording all executed queries and stack
+traces during execution. It can be used to profile either a set of requests of a user session, or a
+specific portion of code. Profiling results can be either inspected with the integrated `speedscope
+<https://github.com/jlfwong/speedscope>`_ :dfn:`open source app allowing to visualize a flamegraph`
+view or analyzed with custom tools by first saving them in a JSON file or in the database.
+
+.. _performance/profiling/enable:
+
+Enable the profiler
+-------------------
+
+The profiler can either be enabled from the user interface, which is the easiest way to do so but
+allows profiling only web requests, or from Python code, which allows profiling any piece of code
+including tests.
+
+.. tabs::
+
+   .. tab:: Enable from the user interface
+
+      #. :ref:`Enable the developer mode <developer-mode>`.
+      #. Before starting a profiling session, the profiler must be enabled globally on the database.
+         This can be done in two ways:
+
+         - Open the :ref:`developer mode tools <developer-mode/mode-tools>`, then toggle the
+           :guilabel:`Enable profiling` button. A wizard suggests a set of expiry times for the
+           profiling. Click on :guilabel:`ENABLE PROFILING` to enable the profiler globally.
+
+           .. image:: performance/enable_profiling_wizard.png
+
+         - Go to :guilabel:`Settings --> General Settings --> Performance` and set the desired time to
+           the field :guilabel:`Enable profiling until`.
+
+      #. After the profiler is enabled on the database, users can enable it on their session. To do
+         so, toggle the :guilabel:`Enable profiling` button in the :ref:`developer mode tools
+         <developer-mode/mode-tools>` again. By default, the recommended options :guilabel:`Record
+         sql` and :guilabel:`Record traces` are enabled. To learn more about the different options,
+         head over to :ref:`performance/profiling/collectors`.
+
+         .. image:: performance/profiling_debug_menu.png
+
+      When the profiler is enabled, all the requests made to the server are profiled and saved into
+      an `ir.profile` record. Such records are grouped into the current profiling session which
+      spans from when the profiler was enabled until it is disabled.
+
+      .. note::
+         Odoo Online (SaaS) databases cannot be profiled.
+
+   .. tab:: Enable from Python code
+
+      Starting the profiler manually can be convenient to profile a specific method or a part of the
+      code. This code can be a test, a compute method, the entire loading, etc.
+
+      To start the profiler from Python code, call it as a context manager. You may specify *what*
+      you want to record through the parameters. A shortcut is available for profiling test classes:
+      :code:`self.profile()`. See :ref:`performance/profiling/collectors` for more information on
+      the `collectors` parameter.
+
+      .. example::
+
+         .. code-block:: python
+
+            with Profiler():
+                do_stuff()
+
+      .. example::
+
+         .. code-block:: python
+
+            with Profiler(collectors=['sql', PeriodicCollector(interval=0.1)]):
+                do_stuff()
+
+      .. example::
+
+         .. code-block:: python
+
+            with self.profile():
+                with self.assertQueryCount(__system__=1211):
+                    do_stuff()
+
+         .. note::
+            The profiler is called outside of the `assertQueryCount` in order to catch queries made
+            when exiting the context manager (e.g., flush).
+
+      .. autoclass:: Profiler()
+         :special-members: __init__
+
+      When the profiler is enabled, all executions of a test method are profiled and saved into an
+      `ir.profile` record. Such records are grouped into a single profiling session. This is
+      especially useful when using the :code:`@warmup` and :code:`@users` decorators.
+
+      .. tip::
+         It can be complicated to analyze profiling results of a method that is called several times
+         because all the calls are grouped together in the stack trace. Add an **execution context**
+         as a context manager to break down the results into multiple frames.
+
+         .. example::
+
+            .. code-block:: python
+
+               for index in range(max_index):
+                   with ExecutionContext(current_index=index):  # Identify each call in speedscope results.
+                       do_stuff()
+
+.. _performance/profiling/analyse:
+
+Analyse the results
+-------------------
+
+To browse the profiling results, make sure that the :ref:`profiler is enabled globally on the
+database <performance/profiling/enable>`, then open the :ref:`developer mode tools
+<developer-mode/mode-tools>` and click on the button in the top-right corner of the profiling
+section. A list view of the `ir.profile` records grouped by profiling session opens.
+
+.. image:: performance/profiling_web.png
+   :align: center
+
+Each record has a clickable link that opens the speedscope results in a new tab.
+
+.. image:: performance/flamegraph_example.png
+   :align: center
+
+Speedscope falls out of the scope of this documentation but there are a lot of tools to try: search,
+highlight of similar frames, zoom on frame, timeline, left heavy, sandwich view...
+
+Depending on the profiling options that were activated, Odoo generates different view modes that you
+can access from the top menu.
+
+.. image:: performance/speedscope_modes.png
+   :align: center
+
+- The :guilabel:`Combined` view shows all the SQL queries and traces merged togethers.
+- The :guilabel:`Combined no context` view shows the same result but ignores the saved execution
+  context <performance/profiling/enable>`.
+- The :guilabel:`sql (no gap)` view shows all the SQL queries as if they were executed one after
+  another, without any Python logic. This is useful for optimizing SQL only.
+- The :guilabel:`sql (density)` view shows only all the SQL queries, leaving gap between them. This
+  can be useful to spot if eiter SQL or Python code is the problem, and to identify zones in where
+  many small queries could be batched.
+- The :guilabel:`frames` view shows the results of only the :ref:`periodic collector
+  <performance/profiling/collectors/periodic>`.
+
+.. important::
+   Even though the profiler has been designed to be as light as possible, it can still impact
+   performance, especially when using the :ref:`Sync collector
+   <performance/profiling/collectors/sync>`. Keep that in mind when analyzing speedscope results.
+
+.. _performance/profiling/collectors:
+
+Collectors
+----------
+
+Whereas the profiler is about the *when* of profiling, the collectors take care of the *what*.
+
+Each collector specializes in collecting profiling data in its own format and manner. They can be
+individually enabled from the user interface through their dedicated toggle button in the
+:ref:`developer mode tools <developer-mode/mode-tools>`, or from Python code through their key or
+class.
+
+There are currently four collectors available in Odoo:
+
+.. list-table::
+   :header-rows: 1
+
+   * - Name
+     - Toggle button
+     - Python key
+     - Python class
+   * - :ref:`SQL collector <performance/profiling/collectors/sql>`
+     - :guilabel:`Record sql`
+     - `sql`
+     - `SqlCollector`
+   * - :ref:`Periodic collector <performance/profiling/collectors/periodic>`
+     - :guilabel:`Record traces`
+     - `traces_async`
+     - `PeriodicCollector`
+   * - :ref:`QWeb collector <performance/profiling/collectors/qweb>`
+     - :guilabel:`Record qweb`
+     - `qweb`
+     - `QwebCollector`
+   * - :ref:`Sync collector <performance/profiling/collectors/sync>`
+     - No
+     - `traces_sync`
+     - `SyncCollector`
+
+By default, the profiler enables the SQL and the Periodic collectors. Both when it is enabled from
+the user interface or Python code.
+
+.. _performance/profiling/collectors/sql:
+
+SQL collector
+~~~~~~~~~~~~~
+
+The SQL collector saves all the SQL queries made to the database in the current thread (for all
+cursors), as well as the stack trace. The overhead of the collector is added to the analysed thread
+for each query, which means that using it on a lot of small queries may impact execution time and
+other profilers.
+
+It is especially useful to debug query counts, or to add information to the :ref:`Periodic collector
+<performance/profiling/collectors/periodic>` in the combined speedscope view.
+
+.. autoclass:: SQLCollector
+
+.. _performance/profiling/collectors/periodic:
+
+Periodic collector
+~~~~~~~~~~~~~~~~~~
+
+This collector runs in a separate thread and saves the stack trace of the analysed thread at every
+interval. The interval (by default 10 ms) can be defined through the :guilabel:`Interval` option in
+the user interface, or the `interval` parameter in Python code.
+
+.. warning::
+   If the interval is set at a very low value, profiling long requests will generate memory issues.
+   If the interval is set at a very high value, information on short function executions will be
+   lost.
+
+It is one of the best way to analyse performance as it should have a very low impact on the
+execution time thanks to its separate thread.
+
+.. autoclass:: PeriodicCollector
+
+.. _performance/profiling/collectors/qweb:
+
+QWeb collector
+~~~~~~~~~~~~~~
+
+This collector saves the Python execution time and queries of all directives. As for the :ref:`SQL
+collector <performance/profiling/collectors/sql>`, the overhead can be important when executing a
+lot of small directives. The results are different from other collectors in terms of collected data,
+and can be analysed from the `ir.profile` form view using a custom widget.
+
+It is mainly useful for optimizing views.
+
+.. autoclass:: QwebCollector
+
+.. _performance/profiling/collectors/sync:
+
+Sync collector
+~~~~~~~~~~~~~~
+
+This collector saves the stack for every function's call and return and runs on the same thread,
+which greatly impacts performance.
+
+It can be useful to debug and understand complex flows, and follow their execution in the code. It
+is however not recommended for performance analysis because the overhead is high.
+
+.. autoclass:: SyncCollector
+
+.. _performance/profiling/pitfalls:
+
+Performance pitfalls
+--------------------
+
+- Be careful with randomness. Multiple executions may lead to different results. E.g., a garbage
+  collector being triggered during execution.
+- Be careful with blocking calls. In some cases, external `c_call` may take some time before
+  releasing the GIL, thus leading to unexpected long frames with the :ref:`Periodic collector
+  <performance/profiling/collectors/periodic>`. This should be detected by the profiler and give a
+  warning. It is possible to trigger the profiler manually before such calls if needed.
+- Pay attention to the cache. Profiling before that the `view`/`assets`/... are in cache can lead to
+  different results.
+- Be aware of the profiler's overhead. The :ref:`SQL collector
+  <performance/profiling/collectors/sql>`'s overhead can be important when a lot of small queries
+  are executed. Profiling is practical to spot a problem but you may want to disable the profiler in
+  order to measure the real impact of a code change.
+- Profiling results can be memory intensive. In some cases (e.g., profiling an install or a long
+  request), it is possible that you reach memory limit, especially when rendering the speedscope
+  results, which can lead to an HTTP 500 error. In this case, you may need to start the server with
+  a higher memory limit: `--limit-memory-hard $((8*1024**3))`.
+
+.. _reference/performance/populate:
+
+Database population
+===================
+
+Odoo CLI offers a :ref:`database population <reference/cmdline/populate>` feature through the CLI
+command :command:`odoo-bin populate`.
+
+Instead of the tedious manual, or programmatic, specification of test data, one can use this feature
+to fill a database on demand with the desired number of test data. This can be used to detect
+diverse bugs or performance issues in tested flows.
+
+.. _reference/performance/populate/methods:
+
+To populate a given model, the following methods and attributes can be defined.
+
+.. currentmodule:: odoo.models
+
+.. autoattribute:: Model._populate_sizes
+.. autoattribute:: Model._populate_dependencies
+.. automethod:: Model._populate
+.. automethod:: Model._populate_factories
+
+.. note::
+   You have to define at least :meth:`~odoo.models.Model._populate` or
+   :meth:`~odoo.models.Model._populate_factories` on the model to enable database population.
+
+.. example::
+   .. code-block:: python
+
+       from odoo.tools import populate
+
+       class CustomModel(models.Model)
+           _inherit = "custom.some_model"
+           _populate_sizes = {"small": 100, "medium": 2000, "large": 10000}
+           _populate_dependencies = ["custom.some_other_model"]
+
+           def _populate_factories(self):
+               # Record ids of previously populated models are accessible in the registry
+               some_other_ids = self.env.registry.populated_models["custom.some_other_model"]
+
+               def get_some_field(values=None, random=None, **kwargs):
+                   """ Choose a value for some_field depending on other fields values.
+
+                   :param dict values:
+                   :param random: seeded :class:`random.Random` object
+                   """
+                   field_1 = values['field_1']
+                   if field_1 in [value2, value3]:
+                       return random.choice(some_field_values)
+                   return False
+
+               return [
+                   ("field_1", populate.randomize([value1, value2, value3])),
+                   ("field_2", populate.randomize([value_a, value_b], [0.5, 0.5])),
+                   ("some_other_id", populate.randomize(some_other_ids)),
+                   ("some_field", populate.compute(get_some_field, seed="some_field")),
+                   ('active', populate.cartesian([True, False])),
+               ]
+
+           def _populate(self, size):
+               records = super()._populate(size)
+
+               # If you want to update the generated records
+               # E.g setting the parent-child relationships
+               records.do_something()
+
+               return records
+
+Population tools
+----------------
+
+Multiple population tools are available to easily create the needed data generators.
+
+.. automodule:: odoo.tools.populate
+   :members: cartesian, compute, constant, iterate, randint, randomize
+
+.. _performance/good_practices:
+
+Good practices
+==============
+
+.. _performance/good_practices/batch:
+
+Batch operations
+----------------
+
+When working with recordsets, it is almost always better to batch operations.
+
+.. example::
+   Don't call a method that runs SQL queries while looping over a recordset because it will do so
+   for each record of the set.
+
+   .. rst-class:: bad-example
+   .. code-block:: python
+
+      def _compute_count(self):
+          for record in self:
+              domain = [('related_id', '=', record.id)]
+              record.count = other_model.search_count(domain)
+
+   Instead, replace the `search_count` with a `read_group` to execute one SQL query for the entire
+   batch of records.
+
+   .. rst-class:: good-example
+   .. code-block:: python
+
+      def _compute_count(self):
+          if self.ids:
+              domain = [('related_id', 'in', self.ids)]
+              counts_data = other_model.read_group(domain, ['related_id'], ['related_id'])
+              mapped_data = {
+                  count['related_id'][0]: count['related_id_count'] for count in counts_data
+              }
+          else:
+              mapped_data = {}
+          for record in self:
+              record.count = mapped_data.get(record.id, 0)
+
+   .. note::
+      This example is not optimal nor correct in all cases. It is only a substitute for a
+      `search_count`. Another solution could be to prefetch and count the inverse `One2many` field.
+
+.. example::
+   Don't create records one after another.
+
+   .. rst-class:: bad-example
+   .. code-block:: python
+
+      for name in ['foo', 'bar']:
+          model.create({'name': name})
+
+   Instead, accumulate the create values and call the `create` method on the batch. Doing so has
+   mostly no impact and helps the framework optimize fields computation.
+
+   .. rst-class:: good-example
+   .. code-block:: python
+
+      create_values = []
+      for name in ['foo', 'bar']:
+          create_values.append({'name': name})
+      records = model.create(create_values)
+
+.. example::
+   Fail to prefetch the fields of a recordset while browsing a single record inside a loop.
+
+   .. rst-class:: bad-example
+   .. code-block:: python
+
+      for record_id in record_ids:
+          model.browse(record_id)
+          record.foo  # One query is executed per record.
+
+   Instead, browse the entire recordset first.
+
+   .. rst-class:: good-example
+   .. code-block:: python
+
+      records = model.browse(record_ids)
+      for record in records:
+          record.foo  # One query is executed for the entire recordset.
+
+   We can verify that the records are prefetched in batch by reading the field `prefetch_ids` which
+   includes each of the record ids.browsing all records together is unpractical,
+
+   If needed, the `with_prefetch` method can be used to disable batch prefetching:
+
+   .. code-block:: python
+
+      for values in values_list:
+          message = self.browse(values['id']).with_prefetch(self.ids)
+
+.. _performance/good_practices/algorithmic_complexity:
+
+Reduce the algorithmic complexity
+---------------------------------
+
+Algorithmic complexity is a measure of how long an algorithm would take to complete in regard to the
+size `n` of the input. When the complexity is high, the execution time can grow quickly as the input
+becomes larger. In some cases, the algorithmic complexity can be reduced by preparing the input's
+data correctly.
+
+.. example::
+   For a given problem, let's consider a naive algorithm crafted with two nested loops for which the
+   complexity in in O(n²).
+
+   .. rst-class:: bad-example
+   .. code-block:: python
+
+      for record in self:
+          for result in results:
+              if results['id'] == record.id:
+                  record.foo = results['foo']
+                  break
+
+   Assuming that all results have a different id, we can prepare the data to reduce the complexity.
+
+   .. rst-class:: good-example
+   .. code-block:: python
+
+      mapped_result = {result['id']: result['foo'] for result in results}
+      for record in self:
+          record.foo = mapped_result.get(record.id)
+
+.. example::
+   Choosing the bad data structure to hold the input can lead to quadratic complexity.
+
+   .. rst-class:: bad-example
+   .. code-block:: python
+
+      invalid_ids = self.search(domain).ids
+      for record in self:
+          if record.id in invalid_ids:
+              ...
+
+   If `invalid_ids` is a list-like data structure, the complexity of the algorithm may be quadratic.
+
+   Instead, prefer using set operations like casting `invalid_ids` to a set.
+
+   .. rst-class:: good-example
+   .. code-block:: python
+
+      invalid_ids = set(invalid_ids)
+      for record in self:
+          if record.id in invalid_ids:
+              ...
+
+   Depending on the input, recordset operations can also be used.
+
+   .. rst-class:: good-example
+   .. code-block:: python
+
+      invalid_ids = self.search(domain)
+      for record in self - invalid_ids:
+          ...
+
+.. _performance/good_practices/index:
+
+Use indexes
+-----------
+
+Database indexes can help fasten search operations, be it from a search in the or through the user
+interface.
+
+.. code-block:: python
+
+   name = fields.Char(string="Name", index=True)
+
+.. warning::
+   Be careful not to index every field as indexes consume space and impact on performance when
+   executing one of `INSERT`, `UPDATE`, and `DELETE`.
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diff --git a/content/developer/reference/backend/testing.rst b/content/developer/reference/backend/testing.rst
index f89425ee9..b10bd8807 100644
--- a/content/developer/reference/backend/testing.rst
+++ b/content/developer/reference/backend/testing.rst
@@ -732,90 +732,6 @@ you can use the :meth:`~odoo.tests.common.BaseCase.assertQueryCount` method, int
     with self.assertQueryCount(11):
         do_something()
 
-.. _reference/testing/populate:
-
-Database population
--------------------
-
-Odoo CLI offers a :ref:`database population<reference/cmdline/populate>` feature.
-
-.. code-block:: console
-
-    odoo-bin populate
-
-Instead of the tedious manual, or programmatic, specification of test data,
-one can use this feature to fill a database on demand with the desired number of test data.
-This can be used to detect diverse bugs or performance issues in tested flows.
-
-.. _reference/testing/populate/methods:
-
-To specify this feature for a given model, the following methods and attributes can be defined.
-
-.. currentmodule:: odoo.models
-
-.. autoattribute:: Model._populate_sizes
-.. autoattribute:: Model._populate_dependencies
-.. automethod:: Model._populate
-.. automethod:: Model._populate_factories
-
-.. note::
-
-    You have to define at least :meth:`~odoo.models.Model._populate` or :meth:`~odoo.models.Model._populate_factories`
-    on the model to enable database population.
-
-Example model
-~~~~~~~~~~~~~
-
-.. code-block:: python
-
-    from odoo.tools import populate
-
-    class CustomModel(models.Model)
-        _inherit = "custom.some_model"
-        _populate_sizes = {"small": 100, "medium": 2000, "large": 10000}
-        _populate_dependencies = ["custom.some_other_model"]
-
-        def _populate_factories(self):
-            # Record ids of previously populated models are accessible in the registry
-            some_other_ids = self.env.registry.populated_models["custom.some_other_model"]
-
-            def get_some_field(values=None, random=None, **kwargs):
-                """ Choose a value for some_field depending on other fields values.
-
-                    :param dict values:
-                    :param random: seeded :class:`random.Random` object
-                """
-                field_1 = values['field_1']
-                if field_1 in [value2, value3]:
-                    return random.choice(some_field_values)
-                return False
-
-            return [
-                ("field_1", populate.randomize([value1, value2, value3])),
-                ("field_2", populate.randomize([value_a, value_b], [0.5, 0.5])),
-                ("some_other_id", populate.randomize(some_other_ids)),
-                ("some_field", populate.compute(get_some_field, seed="some_field")),
-                ('active', populate.cartesian([True, False])),
-            ]
-
-        def _populate(self, size):
-            records = super()._populate(size)
-
-            # If you want to update the generated records
-            # E.g setting the parent-child relationships
-            records.do_something()
-
-            return records
-
-Population tools
-~~~~~~~~~~~~~~~~
-
-Multiple population tools are available to easily create
-the needed data generators.
-
-.. automodule:: odoo.tools.populate
-    :members: cartesian, compute, constant, iterate, randint, randomize
-
 .. _qunit: https://qunitjs.com/
 .. _qunit_config.js: https://github.com/odoo/odoo/blob/51ee0c3cb59810449a60dae0b086b49b1ed6f946/addons/web/static/tests/helpers/qunit_config.js#L49
 .. _web.tests_assets: https://github.com/odoo/odoo/blob/51ee0c3cb59810449a60dae0b086b49b1ed6f946/addons/web/views/webclient_templates.xml#L594
diff --git a/static/css/performance.css b/static/css/performance.css
new file mode 100644
index 000000000..25b6af75d
--- /dev/null
+++ b/static/css/performance.css
@@ -0,0 +1,7 @@
+.bad-example {
+    border-left: 3px solid red;
+}
+
+.good-example {
+    border-left: 3px solid green;
+}