Merging upstream version 1.29.0.

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

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diff --git a/docs/tutorials/longer-metrics-storage.md b/docs/tutorials/longer-metrics-storage.md
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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 default [database
-engine](#using-the-database-engine)**, but you can stick with or switch to the 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 is currently the default method of storing metrics, but if you're not sure which database you're
-using, check out your `netdata.conf` file and look for the `memory mode` setting:
-
-```conf
-[global]
-    memory mode = dbengine
-```
-
-If `memory mode` is set to anything but `dbengine`, change it and restart Netdata using the standard command for
-restarting services on your system. 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 a day's worth of metrics when Netdata collects roughly
-4,000 metrics every second. If you increase either `page cache size` or `dbengine disk space`, Netdata will retain even
-more historical metrics.
-
-But before you change these options too dramatically, read up on 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
-
-In previous versions, Netdata used a round-robin database to store 1 hour of per-second metrics. 
-
-To see if you're still using this database, or if you would like to switch to it, open your `netdata.conf` file and see
-if `memory mode` option is set to `save`.
-
-```conf
-[global]
-    memory mode = save
-```
-
-If `memory mode` is set to `save`, then you're using the round-robin database. If so, the `history` option is set to
-`3600`, which is the equivalent to 3,600 seconds, or one hour. 
-
-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.
-
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