Adding upstream version 1.18.1.upstream/1.18.1

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

4 files changed, 390 insertions, 24 deletions

diff --git a/docs/getting-started.md b/docs/getting-started.md
index ce3558192..44e257383 100644
--- a/docs/getting-started.md
+++ b/docs/getting-started.md
@@ -159,14 +159,13 @@ Find the `SEND_EMAIL="YES"` line and change it to `SEND_EMAIL="NO"`.
 
 ## Change how long Netdata stores metrics
 
-By default, Netdata stores 1 hour of historical metrics and uses about 25MB of RAM.
+By default, Netdata uses a database engine uses RAM to store recent metrics. For long-term metrics storage, the database
+engine uses a "spill to disk" feature that also takes advantage of available disk space and keeps RAM usage low.
 
-If that's not enough for you, Netdata is quite adaptable to long-term storage of your system's metrics.
+The database engine allows you to store a much larger dataset than your system's available RAM.
 
-There are two quick ways to increase the depth of historical metrics: increase the `history` value for the round-robin
-that's enabled by default, or switch to the database engine.
-
-We have a tutorial that walks you through both options: [**Changing how long Netdata stores
+If you're not sure whether you're using the database engine, or want to tweak the default settings to store even more
+historical metrics, check out our tutorial: [**Changing how long Netdata stores
 metrics**](../docs/tutorials/longer-metrics-storage.md).
 
 **What's next?**:
diff --git a/docs/tutorials/dimension-templates.md b/docs/tutorials/dimension-templates.md
new file mode 100644
index 000000000..67648b9d6
--- /dev/null
+++ b/docs/tutorials/dimension-templates.md
@@ -0,0 +1,169 @@
+# Use dimension templates to create dynamic alarms
+
+Your ability to monitor the health of your systems and applications relies on your ability to create and maintain
+the best set of alarms for your particular needs.
+
+In v1.18 of Netdata, we introduced **dimension templates** for alarms, which simplifies the process of writing [alarm
+entities](../../health/README.md#entities-in-the-health-files) for charts with many dimensions.
+
+Dimension templates can condense many individual entities into one—no more copy-pasting one entity and changing the
+`alarm`/`template` and `lookup` lines for each dimension you'd like to monitor.
+
+They are, however, an advanced health monitoring feature. For more basic instructions on creating your first alarm,
+check out our [health monitoring documentation](../../health/), which also includes
+[examples](../../health/README.md#examples).
+
+## The fundamentals of `foreach`
+
+Our dimension templates update creates a new `foreach` parameter to the existing [`lookup`
+line](../../health/README.md#alarm-line-lookup). This is where the magic happens.
+
+You use the `foreach` parameter to specify which dimensions you want to monitor with this single alarm. You can separate
+them with a comma (`,`) or a pipe (`|`). You can also use a [Netdata simple pattern](../../libnetdata/simple_pattern/README.md)
+to create many alarms with a regex-like syntax.
+
+The `foreach` parameter _has_ to be the last parameter in your `lookup` line, and if you have both `of` and `foreach` in
+the same `lookup` line, Netdata will ignore the `of` parameter and use `foreach` instead.
+
+Let's get into some examples so you can see how the new parameter works.
+
+> ⚠️ The following entities are examples to showcase the functionality and syntax of dimension templates. They are not
+> meant to be run as-is on production systems.
+
+## Condensing entities with `foreach`
+
+Let's say you want to monitor the `system`, `user`, and `nice` dimensions in your system's overall CPU utilization.
+Before dimension templates, you would need the following three entities:
+
+```yaml
+ alarm: cpu_system
+    on: system.cpu
+lookup: average -10m percentage of system
+ every: 1m
+  warn: $this > 50
+  crit: $this > 80
+
+ alarm: cpu_user
+    on: system.cpu
+lookup: average -10m percentage of user
+ every: 1m
+  warn: $this > 50
+  crit: $this > 80
+
+ alarm: cpu_nice
+    on: system.cpu
+lookup: average -10m percentage of nice
+ every: 1m
+  warn: $this > 50
+  crit: $this > 80
+```
+
+With dimension templates, you can condense these into a single alarm. Take note of the `alarm` and `lookup` lines.
+
+```yaml
+ alarm: cpu_template
+    on: system.cpu
+lookup: average -10m percentage foreach system,user,nice
+ every: 1m
+  warn: $this > 50
+  crit: $this > 80
+```
+
+The `alarm` line specifies the naming scheme Netdata will use. You can use whatever naming scheme you'd like, with `.`
+and `_` being the only allowed symbols.
+
+The `lookup` line has changed from `of` to `foreach`, and we're now passing three dimensions.
+
+In this example, Netdata will create three alarms with the names `cpu_template_system`, `cpu_template_user`, and
+`cpu_template_nice`. Every minute, each alarm will use the same database query to calculate the average CPU usage for
+the `system`, `user`, and `nice` dimensions over the last 10 minutes and send out alarms if necessary.
+
+You can find these three alarms active by clicking on the **Alarms** button in the top navigation, and then clicking on
+the **All** tab and scrolling to the **system - cpu** collapsible section.
+
+![Three new alarms created from the dimension template](https://user-images.githubusercontent.com/1153921/66218994-29523800-e67f-11e9-9bcb-9bca23e2c554.png)
+
+Let's look at some other examples of how `foreach` works so you can best apply it in your configurations.
+
+### Using a Netdata simple pattern in `foreach`
+
+In the last example, we used `foreach system,user,nice` to create three distinct alarms using dimension templates. But
+what if you want to quickly create alarms for _all_ the dimensions of a given chart? 
+
+Use a [simple pattern](../../libnetdata/simple_pattern/README.md)! One example of a simple pattern is a single wildcard
+(`*`).
+
+Instead of monitoring system CPU usage, let's monitor per-application CPU usage using the `apps.cpu` chart. Passing a
+wildcard as the simple pattern tells Netdata to create a separate alarm for _every_ process on your system:
+
+```yaml
+ alarm: app_cpu
+    on: apps.cpu
+lookup: average -10m percentage foreach *
+ every: 1m
+  warn: $this > 50
+  crit: $this > 80
+```
+
+This entity will now create alarms for every dimension in the `apps.cpu` chart. Given that most `apps.cpu` charts have
+10 or more dimensions, using the wildcard ensures you catch every CPU-hogging process.
+
+To learn more about how to use simple patterns with dimension templates, see our [simple patterns
+documentation](../../libnetdata/simple_pattern/README.md).
+
+## Using `foreach` with alarm templates
+
+Dimension templates also work with [alarm templates](../../health/README.md#entities-in-the-health-files). Alarm
+templates help you create alarms for all the charts with a given context—for example, all the cores of your system's
+CPU.
+
+By combining the two, you can create dozens of individual alarms with a single template entity. Here's how you would
+create alarms for the `system`, `user`, and `nice` dimensions for every chart in the `cpu.cpu` context—or, in other
+words, every CPU core.
+
+```yaml
+template: cpu_template
+      on: cpu.cpu
+  lookup: average -10m percentage foreach system,user,nice
+   every: 1m
+    warn: $this > 50
+    crit: $this > 80
+```
+
+On a system with a 6-core, 12-thread Ryzen 5 1600 CPU, this one entity creates alarms on the following charts and
+dimensions:
+
+-   `cpu.cpu0`
+    -   `cpu_template_user`
+    -   `cpu_template_system`
+    -   `cpu_template_nice`
+-   `cpu.cpu1`
+    -   `cpu_template_user`
+    -   `cpu_template_system`
+    -   `cpu_template_nice`
+-   `cpu.cpu2`
+    -   `cpu_template_user`
+    -   `cpu_template_system`
+    -   `cpu_template_nice`
+-   ...
+-   `cpu.cpu11`
+    -   `cpu_template_user`
+    -   `cpu_template_system`
+    -   `cpu_template_nice`
+
+And how just a few of those dimension template-generated alarms look like in the Netdata dashboard.
+
+![A few of the created alarms in the Netdata dashboard](https://user-images.githubusercontent.com/1153921/66219669-708cf880-e680-11e9-8b3a-7bfe178fa28b.png)
+
+All in all, this single entity creates 36 individual alarms. Much easier than writing 36 separate entities in your
+health configuration files!
+
+## What's next?
+
+We hope you're excited about the possibilities of using dimension templates! Maybe they'll inspire you to build new
+alarms that will help you better monitor the health of your systems.
+
+Or, at the very least, simplify your configuration files.
+
+For information about other advanced features in Netdata's health monitoring toolkit, check out our [health
+documentation](../../health/). And if you have some cool alarms you built using dimension templates, 
diff --git a/docs/tutorials/longer-metrics-storage.md b/docs/tutorials/longer-metrics-storage.md
index e227f5bda..1ef3f8d8e 100644
--- a/docs/tutorials/longer-metrics-storage.md
+++ b/docs/tutorials/longer-metrics-storage.md
@@ -7,30 +7,27 @@ Many people think Netdata can only store about an hour's worth of real-time metr
 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.
+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.
+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`:
+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
 ```
 
-Next, restart Netdata. On Linux systems, we recommend running `sudo service netdata restart`. You're now using the
-database engine!
+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/).
@@ -55,10 +52,11 @@ size` and `dbengine disk space`.
 `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.
+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.
 
-If you'd like to change these options, read more about the [database engine's memory
+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
@@ -69,15 +67,18 @@ 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.
+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]
-    history = 3600
+    memory mode = save
 ```
 
-One hour has 3,600 seconds, hence the `3600` value!
+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:
 
diff --git a/docs/tutorials/monitor-hadoop-cluster.md b/docs/tutorials/monitor-hadoop-cluster.md
new file mode 100644
index 000000000..6d6e79708
--- /dev/null
+++ b/docs/tutorials/monitor-hadoop-cluster.md
@@ -0,0 +1,197 @@
+# Monitor a Hadoop cluster with Netdata
+
+Hadoop is an [Apache project](https://hadoop.apache.org/) is a framework for processing large sets of data across a
+distributed cluster of systems.
+
+And while Hadoop is designed to be a highly-available and fault-tolerant service, those who operate a Hadoop cluster
+will want to monitor the health and performance of their [Hadoop Distributed File System
+(HDFS)](https://hadoop.apache.org/docs/r1.2.1/hdfs_design.html) and [Zookeeper](https://zookeeper.apache.org/)
+implementations.
+
+Netdata comes with built-in and pre-configured support for monitoring both HDFS and Zookeeper.
+
+This tutorial assumes you have a Hadoop cluster, with HDFS and Zookeeper, running already. If you don't, please follow
+the [official Hadoop
+instructions](http://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-common/SingleCluster.html) or an
+alternative, like the guide available from
+[DigitalOcean](https://www.digitalocean.com/community/tutorials/how-to-install-hadoop-in-stand-alone-mode-on-ubuntu-18-04).
+
+For more specifics on the collection modules used in this tutorial, read the respective pages in our documentation:
+
+-   [HDFS](../../collectors/go.d.plugin/modules/hdfs/README.md)
+-   [Zookeeper](../../collectors/go.d.plugin/modules/zookeeper/README.md)
+
+## Set up your HDFS and Zookeeper installations
+
+As with all data sources, Netdata can auto-detect HDFS and Zookeeper nodes if you installed them using the standard
+installation procedure.
+
+For Netdata to collect HDFS metrics, it needs to be able to access the node's `/jmx` endpoint. You can test whether an
+JMX endpoint is accessible by using `curl HDFS-IP:PORT/jmx`. For a NameNode, you should see output similar to the
+following:
+
+```json
+{
+  "beans" : [ {
+    "name" : "Hadoop:service=NameNode,name=JvmMetrics",
+    "modelerType" : "JvmMetrics",
+    "MemNonHeapUsedM" : 65.67851,
+    "MemNonHeapCommittedM" : 67.3125,
+    "MemNonHeapMaxM" : -1.0,
+    "MemHeapUsedM" : 154.46341,
+    "MemHeapCommittedM" : 215.0,
+    "MemHeapMaxM" : 843.0,
+    "MemMaxM" : 843.0,
+    "GcCount" : 15,
+    "GcTimeMillis" : 305,
+    "GcNumWarnThresholdExceeded" : 0,
+    "GcNumInfoThresholdExceeded" : 0,
+    "GcTotalExtraSleepTime" : 92,
+    "ThreadsNew" : 0,
+    "ThreadsRunnable" : 6,
+    "ThreadsBlocked" : 0,
+    "ThreadsWaiting" : 7,
+    "ThreadsTimedWaiting" : 34,
+    "ThreadsTerminated" : 0,
+    "LogFatal" : 0,
+    "LogError" : 0,
+    "LogWarn" : 2,
+    "LogInfo" : 348
+  }, 
+  { ... }
+  ]
+}
+```
+
+The JSON result for a DataNode's `/jmx` endpoint is slightly different:
+
+```json
+{
+  "beans" : [ {
+    "name" : "Hadoop:service=DataNode,name=DataNodeActivity-dev-slave-01.dev.loc
+al-9866",
+    "modelerType" : "DataNodeActivity-dev-slave-01.dev.local-9866",
+    "tag.SessionId" : null,
+    "tag.Context" : "dfs",
+    "tag.Hostname" : "dev-slave-01.dev.local",
+    "BytesWritten" : 500960407,
+    "TotalWriteTime" : 463,
+    "BytesRead" : 80689178,
+    "TotalReadTime" : 41203,
+    "BlocksWritten" : 16,
+    "BlocksRead" : 16,
+    "BlocksReplicated" : 4,
+    ...
+  },
+  { ... }
+  ]
+}
+```
+
+If Netdata can't access the `/jmx` endpoint for either a NameNode or DataNode, it will not be able to auto-detect and
+collect metrics from your HDFS implementation.
+
+Zookeeper auto-detection relies on an accessible client port and a whitelisted `mntr` command. For more details on
+`mntr`, see Zookeeper's documentation on [cluster
+options](https://zookeeper.apache.org/doc/current/zookeeperAdmin.html#sc_clusterOptions) and [Zookeeper
+commands](https://zookeeper.apache.org/doc/current/zookeeperAdmin.html#sc_zkCommands).
+
+## Configure the HDFS and Zookeeper modules
+
+To configure Netdata's HDFS module, navigate to your Netdata directory (typically at `/etc/netdata/`) and use
+`edit-config` to initialize and edit your HDFS configuration file.
+
+```bash
+cd /etc/netdata/
+sudo ./edit-config go.d/hdfs.conf
+```
+
+At the bottom of the file, you will see two example jobs, both of which are commented out:
+
+```yaml
+# [ JOBS ]
+#jobs:
+#  - name: namenode
+#    url: http://127.0.0.1:9870/jmx
+#
+#  - name: datanode
+#    url: http://127.0.0.1:9864/jmx
+```
+
+Uncomment these lines and edit the `url` value(s) according to your setup. Now's the time to add any other configuration
+details, which you can find inside of the `hdfs.conf` file itself. Most production implementations will require TLS
+certificates.
+
+The result for a simple HDFS setup, running entirely on `localhost` and without certificate authentication, might look
+like this:
+
+```yaml
+# [ JOBS ]
+jobs:
+  - name: namenode
+    url: http://127.0.0.1:9870/jmx
+
+  - name: datanode
+    url: http://127.0.0.1:9864/jmx
+```
+
+At this point, Netdata should be configured to collect metrics from your HDFS servers. Let's move on to Zookeeper.
+
+Next, use `edit-config` again to initialize/edit your `zookeeper.conf` file.
+
+```bash
+cd /etc/netdata/
+sudo ./edit-config go.d/zookeeper.conf
+```
+
+As with the `hdfs.conf` file, head to the bottom, uncomment the example jobs, and tweak the `address` values according
+to your setup. Again, you may need to add additional configuration options, like TLS certificates.
+
+```yaml
+jobs:
+  - name    : local
+    address : 127.0.0.1:2181
+
+  - name    : remote
+    address : 203.0.113.10:2182
+```
+
+Finally, restart Netdata.
+
+```sh
+sudo service restart netdata
+```
+
+Upon restart, Netdata should recognize your HDFS/Zookeeper servers, enable the HDFS and Zookeeper modules, and begin
+showing real-time metrics for both in your Netdata dashboard. 🎉
+
+## Configuring HDFS and Zookeeper alarms
+
+The Netdata community helped us create sane defaults for alarms related to both HDFS and Zookeeper. You may want to
+investigate these to ensure they work well with your Hadoop implementation.
+
+-   [HDFS alarms](https://raw.githubusercontent.com/netdata/netdata/master/health/health.d/hdfs.conf)
+-   [Zookeeper alarms](https://raw.githubusercontent.com/netdata/netdata/master/health/health.d/zookeeper.conf)
+
+You can also access/edit these files directly with `edit-config`:
+
+```bash
+sudo /etc/netdata/edit-config health.d/hdfs.conf
+sudo /etc/netdata/edit-config health.d/zookeeper.conf
+```
+
+For more information about editing the defaults or writing new alarm entities, see our [health monitoring
+documentation](../../health/README.md).
+
+## What's next?
+
+If you're having issues with Netdata auto-detecting your HDFS/Zookeeper servers, or want to help improve how Netdata
+collects or presents metrics from these services, feel free to [file an
+issue](https://github.com/netdata/netdata/issues/new?labels=bug%2C+needs+triage&template=bug_report.md).
+
+-   Read up on the [HDFS configuration
+    file](https://github.com/netdata/go.d.plugin/blob/master/config/go.d/hdfs.conf) to understand how to configure
+    global options or per-job options, such as username/password, TLS certificates, timeouts, and more.
+-   Read up on the [Zookeeper configuration
+    file](https://github.com/netdata/go.d.plugin/blob/master/config/go.d/zookeeper.conf) to understand how to configure
+    global options or per-job options, timeouts, TLS certificates, and more.