Merging upstream version 1.16.0.

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

4 files changed, 7 insertions, 7 deletions

diff --git a/docs/why-netdata/1s-granularity.md b/docs/why-netdata/1s-granularity.md
index 08985454..0d12a2d4 100644
--- a/docs/why-netdata/1s-granularity.md
+++ b/docs/why-netdata/1s-granularity.md
@@ -34,13 +34,13 @@ So, the monitoring industry fails to massively provide high resolution metrics,
 2. Data collection needs optimization, otherwise it will significantly affect the monitored systems.
 3. Data collection is a lot harder, especially on busy virtual environments.
 
-## What does netdata do differently?
+## What does Netdata do differently?
 
 Netdata decentralizes monitoring completely. Each Netdata node is autonomous. It collects metrics locally, it stores them locally, it runs checks against them to trigger alarms locally, and provides an API for the dashboards to visualize them. This allows Netdata to scale to infinity.
 
 Of course, Netdata can centralize metrics when needed. For example, it is not practical to keep metrics locally on ephemeral nodes. For these cases, Netdata streams the metrics in real-time, from the ephemeral nodes to one or more non-ephemeral nodes nearby. This centralization is again distributed. On a large infrastructure, there may be many centralization points.
 
-To eliminate the error introduced by data collection latencies on busy virtual environments, Netdata interpolates collected metrics. It does this using microsecond timings, per data source, offering measurements with an error rate of 0.0001%. When running [in debug mode, netdata calculates this error rate](https://github.com/netdata/netdata/blob/36199f449852f8077ea915a3a14a33fa2aff6d85/database/rrdset.c#L1070-L1099) for every point collected, ensuring that the database works with acceptable accuracy.
+To eliminate the error introduced by data collection latencies on busy virtual environments, Netdata interpolates collected metrics. It does this using microsecond timings, per data source, offering measurements with an error rate of 0.0001%. When running [in debug mode, Netdata calculates this error rate](https://github.com/netdata/netdata/blob/36199f449852f8077ea915a3a14a33fa2aff6d85/database/rrdset.c#L1070-L1099) for every point collected, ensuring that the database works with acceptable accuracy.
 
 Finally, Netdata is really fast. Optimization is a core product feature. On modern hardware, Netdata can collect metrics with a rate of above 1M metrics per second per core (this includes everything, parsing data sources, interpolating data, storing data in the time series database, etc). So, for a few thousands metrics per second per node, Netdata needs negligible CPU resources (just 1-2% of a single core). 
 
diff --git a/docs/why-netdata/immediate-results.md b/docs/why-netdata/immediate-results.md
index 9afe4afd..12333671 100644
--- a/docs/why-netdata/immediate-results.md
+++ b/docs/why-netdata/immediate-results.md
@@ -20,7 +20,7 @@ Open-source solutions rely almost entirely on configuration. So, you have to go
 
 Monitoring SaaS providers offer a very basic set of pre-configured metrics, dashboards and alarms. They assume that you will configure the rest you may need. So, once more, the result will reflect your skills, your experience, your understanding.
 
-## What does netdata do?
+## What does Netdata do?
 
 1. Metrics are auto-detected, so for 99% of the cases data collection works out of the box.
 2. Metrics are converted to human readable units, right after data collection, before storing them into the database.
diff --git a/docs/why-netdata/meaningful-presentation.md b/docs/why-netdata/meaningful-presentation.md
index 6414d023..f6fd0756 100644
--- a/docs/why-netdata/meaningful-presentation.md
+++ b/docs/why-netdata/meaningful-presentation.md
@@ -42,9 +42,9 @@ Of course, it is just not practical to work that way when the database has 10,00
 
 So, they collect very limited metrics. Basic dashboards can be created with these metrics, but for any issue that needs to be troubleshooted, the monitoring system is just not adequate. It cannot help. So, engineers are using the console to access the rest of the metrics and find the root cause.
 
-## What does netdata do?
+## What does Netdata do?
 
-In netdata, the meaning of metrics is incorporated into the database:
+In Netdata, the meaning of metrics is incorporated into the database:
 
 1. all metrics are converted and stored to human-friendly units. This is a data-collection process, not a visualization process. For example, cpu utilization in Netdata is stored as percentage, not as kernel ticks.
 
diff --git a/docs/why-netdata/unlimited-metrics.md b/docs/why-netdata/unlimited-metrics.md
index e35034a2..a4ecaf3f 100644
--- a/docs/why-netdata/unlimited-metrics.md
+++ b/docs/why-netdata/unlimited-metrics.md
@@ -33,12 +33,12 @@ They can't do otherwise!
 2. It is a lot easier to provide an illusion of monitoring by using a few basic metrics.
 3. Troubleshooting slowdowns is the hardest IT problem to solve, so most solutions just avoid it.
 
-## What does netdata do?
+## What does Netdata do?
 
 Netdata collects, stores and visualizes everything, every single metric exposed by systems and applications.
 
 Due to Netdata's distributed nature, the number of metrics collected does not have any noticeable effect on the performance or the cost of the monitoring infrastructure.
 
-Of course, since netdata is also about [meaningful presentation](meaningful-presentation.md), the number of metrics makes Netdata development slower. We, the Netdata developers, need to have a good understanding of the metrics before adding them into Netdata. We need to organize the metrics, add information related to them, configure alarms for them, so that you, the Netdata users, will have the best out-of-the-box experience and all the information required to kill the console for troubleshooting slowdowns.
+Of course, since Netdata is also about [meaningful presentation](meaningful-presentation.md), the number of metrics makes Netdata development slower. We, the Netdata developers, need to have a good understanding of the metrics before adding them into Netdata. We need to organize the metrics, add information related to them, configure alarms for them, so that you, the Netdata users, will have the best out-of-the-box experience and all the information required to kill the console for troubleshooting slowdowns.
 
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