Merging upstream version 1.18.0.

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>

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+# Change how long Netdata stores metrics
+
+Netdata helps you collect thousands of system and application metrics every second, but what about storing them for the
+long term?
+
+Many people think Netdata can only store about an hour's worth of real-time metrics, but that's just the default
+configuration today. With the right settings, Netdata is quite capable of efficiently storing hours or days worth of
+historical, per-second metrics without having to rely on a [backend](../../backends/).
+
+This tutorial gives two options for configuring Netdata to store more metrics. We recommend the [**database
+engine**](#using-the-database-engine), as it will soon be the default configuration. However, you can stick with the
+current default **round-robin database** if you prefer.
+
+Let's get started.
+
+## Using the database engine
+
+The database engine uses RAM to store recent metrics while also using a "spill to disk" feature that takes advantage of
+available disk space for long-term metrics storage.This feature of the database engine allows you to store a much larger
+dataset than your system's available RAM.
+
+The database engine will eventually become the default method of retaining metrics, but until then, you can switch to
+the database engine by changing a single option.
+
+Edit your `netdata.conf` file and change the `memory mode` setting to `dbengine`:
+
+```conf
+[global]
+    memory mode = dbengine
+```
+
+Next, restart Netdata. On Linux systems, we recommend running `sudo service netdata restart`. You're now using the
+database engine!
+
+> Learn more about how we implemented the database engine, and our vision for its future, on our blog: [_How and why
+> we're bringing long-term storage to Netdata_](https://blog.netdata.cloud/posts/db-engine/).
+
+What makes the database engine efficient? While it's structured like a traditional database, the database engine splits
+data between RAM and disk. The database engine caches and indexes data on RAM to keep memory usage low, and then
+compresses older metrics onto disk for long-term storage.
+
+When the Netdata dashboard queries for historical metrics, the database engine will use its cache, stored in RAM, to
+return relevant metrics for visualization in charts.
+
+Now, given that the database engine uses _both_ RAM and disk, there are two other settings to consider: `page cache
+size` and `dbengine disk space`.
+
+```conf
+[global]
+    page cache size = 32
+    dbengine disk space = 256
+```
+
+`page cache size` sets the maximum amount of RAM (in MiB) the database engine will use for caching and indexing.
+`dbengine disk space` sets the maximum disk space (again, in MiB) the database engine will use for storing compressed
+metrics.
+
+Based on our testing, these default settings will retain about two day's worth of metrics when Netdata collects 2,000
+metrics every second.
+
+If you'd like to change these options, read more about the [database engine's memory
+footprint](../../database/engine/README.md#memory-requirements).
+
+With the database engine active, you can back up your `/var/cache/netdata/dbengine/` folder to another location for
+redundancy.
+
+Now that you know how to switch to the database engine, let's cover the default round-robin database for those who
+aren't ready to make the move.
+
+## Using the round-robin database
+
+By default, Netdata uses a round-robin database to store 1 hour of per-second metrics. Here's the default setting for
+`history` in the `netdata.conf` file that comes pre-installed with Netdata.
+
+```conf
+[global]
+    history = 3600
+```
+
+One hour has 3,600 seconds, hence the `3600` value!
+
+To increase your historical metrics, you can increase `history` to the number of seconds you'd like to store:
+
+```conf
+[global]
+    # 2 hours = 2 * 60 * 60 = 7200 seconds
+    history = 7200
+    # 4 hours = 4 * 60 * 60 = 14440 seconds
+    history = 14440
+    # 24 hours = 24 * 60 * 60 = 86400 seconds
+    history = 86400
+```
+
+And so on.
+
+Next, check to see how many metrics Netdata collects on your system, and how much RAM that uses. Visit the Netdata
+dashboard and look at the bottom-right corner of the interface. You'll find a sentence similar to the following:
+
+> Every second, Netdata collects 1,938 metrics, presents them in 299 charts and monitors them with 81 alarms. Netdata is
+> using 25 MB of memory on **netdata-linux** for 1 hour, 6 minutes and 36 seconds of real-time history.
+
+On this desktop system, using a Ryzen 5 1600 and 16GB of RAM, the round-robin databases uses 25 MB of RAM to store just
+over an hour's worth of data for nearly 2,000 metrics.
+
+To increase the `history` option, you need to edit your `netdata.conf` file and increase the `history` setting. In most
+installations, you'll find it at `/etc/netdata/netdata.conf`, but some operating systems place it at
+`/opt/netdata/etc/netdata/netdata.conf`. 
+
+Use `/etc/netdata/edit-config netdata.conf`, or your favorite text editor, to replace `3600` with the number of seconds
+you'd like to store.
+
+You should base this number on two things: How much history you need for your use case, and how much RAM you're willing
+to dedicate to Netdata.
+
+> Take care when you change the `history` option on production systems. Netdata is configured to stop its process if
+> your system starts running out of RAM, but you can never be too careful. Out of memory situations are very bad.
+
+How much RAM will a longer history use? Let's use a little math.
+
+The round-robin database needs 4 bytes for every value Netdata collects. If Netdata collects metrics every second,
+that's 4 bytes, per second, per metric.
+
+```text
+4 bytes * X seconds * Y metrics = RAM usage in bytes
+```
+
+Let's assume your system collects 1,000 metrics per second.
+
+```text
+4 bytes * 3600 seconds * 1,000 metrics = 14400000 bytes = 14.4 MB RAM
+```
+
+With that formula, you can calculate the RAM usage for much larger history settings.
+
+```conf
+# 2 hours at 1,000 metrics per second
+4 bytes * 7200 seconds * 1,000 metrics = 28800000 bytes = 28.8 MB RAM
+# 2 hours at 2,000 metrics per second
+4 bytes * 7200 seconds * 2,000 metrics = 57600000 bytes = 57.6 MB RAM
+# 4 hours at 2,000 metrics per second
+4 bytes * 14440 seconds * 2,000 metrics = 115520000 bytes = 115.52 MB RAM
+# 24 hours at 1,000 metrics per second
+4 bytes * 86400 seconds * 1,000 metrics = 345600000 bytes = 345.6 MB RAM
+```
+
+## What's next?
+
+Now that you have either configured database engine or round-robin database engine to store more metrics, you'll
+probably want to see it in action!
+
+For more information about how to pan charts to view historical metrics, see our documentation on [using
+charts](../../web/README.md#using-charts).
+
+And if you'd now like to reduce Netdata's resource usage, view our [performance guide](../../docs/Performance.md) for
+our best practices on optimization.