Install grafana on synology

In this post, we will discuss a more robust and scalable way of capturing and persisting data for your Home Assistant installation plus a few other optimizations and tricks. Photo by h heyerlein. In previous episodes, we discussed how to run Home Assistant on Docker and how to set up and integrate a basic Zigbee sensor network.

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In my case, this has allowed me to get up and running with a few useful automations and I ended up ordering a few other sensors for my installation. While waiting for these to be delivered, I have started wondering how to be ready to collect all the wealth of data that these devices will be duly noting into the Home Assistant DB and, more importantly, how to have more flexible tools to slice and dice the pile of raw information that will eventually get collected.

While this is convenient to get up and running quickly, it uses a regular file for storing the data and does not necessarily scale up well as soon as you want to retain data for longer periods.

This can be improved by pointing Home Assistant to use a relational database instead - and I will explain shortly how to achieve this. Having addressed the Home Assistant local DB configuration, we can still go one step further and send the sensor data to an additional data storage InfluxDB that is more suited for collecting the type of records that a sensor network captures over time, and that can be connected to act efficiently as a source for dedicated visualization tools such as Grafana.

As I mentioned above, the SQLite support that comes out of the box with Home Assistant can only go so far concerning enabling a reliable and scalable database infrastructure for the data collected in your home.

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For sure, this works fine when you experiment with a few sensors. However, with more sensors and over time you can capture a pretty large amount of data. You may want to run some analysis or perform some more intelligent operation based on historical analysis of your sensor data.

The first thing to notice are the data retention configurations in Home Assistant. With the above values, we are telling recorder to retain 7 days worth of data and purge it on a daily interval. It is also possible to invoke a service recorder. Finally, you can also disable the purging function, however, this would leave you with an ever-growing data file!

Home Assistant uses SQLAlchemy which is a database abstraction layer capable of supporting multiple options, detailed in the documentation page I linked above. The database can be hosted anywhere, as long as your Home Assistant installation can reach it and as long as you are happy with figuring out the alternative approaches!

Once the database is installed, you will need to modify your configuration. In the example, I am storing the actual connection string in the usual secrets. The below explanation assume that you have already created a database in MariaDB and a user with a password that is authorised to connect to the MariaDB instance from the Home Assistant host, as well as with appropriate read and write rights on the specified database name.

To do that, you will have to connect to the DB instance with your mysql client. Finally, perform the below operations. You can watch the startup log to ensure that there are no errors - typical problems can be failed connections to MariaDB which are frequently due to incorrect networking or wrong privilege set up for the user in the database.

Home Assistant data persistence and visualization with Grafana & InfluxDB

One last consideration: any existing historical data that you had in SQLite wouldn't be migrated automatically in MariaDB. I haven't bothered doing this, as any way with the above configuration I am planning to store only 7 days worth of data in it. The next step is to spin up InfluxDB, which will be the secondary, dedicated time-series storage for the sensor data collected by Home Assistant.If you want to implement a solution like this, the only way is to RTFM.

For instance, one can check at what time during the night some motion sensor detected activity. No offence Fibaro but this can be done better. For temperatures and humidity there are panels that allow display of such values over time.

Again, the GUI configurations options seem quite limited and I also notice that the maximum number of values that can be stored seems to be limited. I was never able to capture temperature events for more than, say, a week or so. Note that the graphs are totally configurable in terms of what is displayed and how.

It is also possible to combine totally different series as show on the third plot: Here, humidity and fan speed are displayed in overlay to show how the humidity drops when ventilation is on.

This flexibility allows to set up meaningful dashboards, ie. Influxdb and Grafana are already available as Docker containers, so the decision was easy to let API script run in a Docker container as well.

install grafana on synology

In this case it is a plain Ubuntu container, but you can run the script more or less on any machine that supports Python or whatever language you prefer for that easy task. Setting up Influxdb and Grafana is straight forward with the information provided on the project pages. This brings me to a limitation of this setup: The Fibaro API does not support any kind of event notification. This would be a very handy feature to trigger the script and update the database whenever some value actually changes.

This may be the case for things like motion sensors etc. So at the moment this setup is more suited for long term capture and analysis of metrics such as temperature. If it has changed, it is written to the database. It should be very simple to extend the script with other objects, arrays etc. This is what the code looks like did I mention it is written in Python?

I chose to let the script run every minute. A simple cron job triggers the execution. In fact cron and the script run in another container. However, rather than run a python script on ubuntu, i wanted to use the event functionality in fibaro to write values to the database.

Liken Liken. Du kommentierst mit Deinem WordPress. Du kommentierst mit Deinem Google-Konto. Du kommentierst mit Deinem Twitter-Konto. Du kommentierst mit Deinem Facebook-Konto. Benachrichtigung bei weiteren Kommentaren per E-Mail senden. A note: The two screenshots are actually a single dashboard. I split them for better visibility. Januar um Antwort. Kommentar verfassen Antwort abbrechen Gib hier deinen Kommentar ein Trage deine Daten unten ein oder klicke ein Icon um dich einzuloggen:.

Name erforderlich. Wenn du die Website weiterhin nutzt, stimmst du der Verwendung von Cookies zu.Docker Compose relies on Docker Engine for any meaningful work, so make sure you have Docker Engine installed either locally or remote, depending on your setup.

On desktop systems like Docker Desktop for Mac and Windows, Docker Compose is included as part of those desktop installs. On Linux systems, first install the Docker Engine for your OS as described on the Get Docker page, then come back here for instructions on installing Compose on Linux systems. To run Compose as a non-root user, see Manage Docker as a non-root user. Follow the instructions below to install Compose on Mac, Windows, Windows Serveror Linux systems, or find out about alternatives like using the pip Python package manager or installing Compose as a container.

The instructions below outline installation of the current stable release v1. To install a different version of Compose, replace the given release number with the one that you want. Compose releases are also listed and available for direct download on the Compose repository release page on GitHub. To install a pre-release of Compose, refer to the install pre-release builds section.

Docker Desktop for Mac and Docker Toolbox already include Compose along with other Docker apps, so Mac users do not need to install Compose separately.

Docker install instructions for these are here:. Docker Desktop for Windows and Docker Toolbox already include Compose along with other Docker apps, so most Windows users do not need to install Compose separately. If you are running the Docker daemon and client directly on Microsoft Windows Server, follow the instructions in the Windows Server tab.

Follow these instructions if you are running the Docker daemon and client directly on Microsoft Windows Server with Docker Engine - Enterpriseand want to install Docker Compose. Search for PowerShell, right-click, and choose Run as administrator.

When asked if you want to allow this app to make changes to your device, click Yes. Because this directory is registered in the system PATHyou can run the docker-compose --version command on the subsequent step with no additional configuration. Follow the instructions from the link, which involve running the curl command in your terminal to download the binaries.

These step-by-step instructions are also included below. For alpinethe following dependency packages are needed: py-pippython-devlibffi-devopenssl-devgcclibc-devand make.

To install a different version of Compose, substitute 1.

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If you have problems installing with curlsee Alternative Install Options tab above. Note : If the command docker-compose fails after installation, check your path. Optionally, install command completion for the bash and zsh shell.

Compose can be installed from pypi using pip. If you install using pipwe recommend that you use a virtualenv because many operating systems have python system packages that conflict with docker-compose dependencies.

See the virtualenv tutorial to get started.As part of my Home Automation series, we configured a Grafana dashboard to display status and statistics about SmartThings devices, the local weather and more. I knew that I wanted to leverage Grafana to display health statistics about the Synology disk temperatures, throughput, disk conditions, etc. In short, SNMP Simple Network Management Protocol is a standardized protocol used for collecting and organizing information about devices on your network.

A MIB is a database that contains the properties available to different types of devices. Enabling SNMP on a device allows that device to publish messages on the network, those messages can then be collected and understood by a collector in our case Telegraf that contains the appropriate MIB to understand the messages. In this example, Telegraf can really be run anywhere on the network. Prior to configuring it as a VM on the Synology itself, I ran it on my Windows 10 desktop machine as an easy way to configure the profiles and debug the configuration.

Since SNMP messages are broadcast on the network, the collector just needs to be on the same network. Finally, configure your telegraf. If everything looks good, reboot the server and check the service status to ensure it automatically started on boot.

Technology Home Automation. Where to Run Telegraf In this example, Telegraf can really be run anywhere on the network.Maintained by : InfluxData. Supported architectures : more info amd64arm32v7arm64v8.

InfluxDB is a time series database built from the ground up to handle high write and query loads. InfluxDB is meant to be used as a backing store for any use case involving large amounts of timestamped data, including DevOps monitoring, application metrics, IoT sensor data, and real-time analytics.

A typical invocation of the container might be:.

Swagger ui docker environment variables

The administrator interface is not automatically exposed when using docker run -P and is disabled by default. The adminstrator interface requires that the web browser have access to InfluxDB on the same port in the container as from the web browser. Since -P exposes the HTTP port to the host on a random port, the administrator interface is not compatible with this setting. InfluxDB can be either configured from a config file or using environment variables. To mount a configuration file and use it with the server, you can use this command:.

Then start the InfluxDB container. If the variable isn't in a section, then omit that part. Find more about configuring InfluxDB here. InfluxDB supports the Graphite line protocol, but the service and ports are not exposed by default. To run InfluxDB with Graphite support enabled, you can either use a configuration file or set the appropriate environment variables. Run InfluxDB with the default Graphite configuration:. In order to take advantage of graphite templates, you should use a configuration file by outputting a default configuration file using the steps above and modifying the [[graphite]] section.

The administrator interface is deprecated as of 1. It is disabled by default.

install grafana on synology

If needed, it can still be enabled by setting an environment variable like below:. Read more about this in the official documentation.Learn about Grafana the monitoring solution for every database. Open Source is at the heart of what we do at Grafana Labs. You can install and run Grafana using the official Docker container. The official Grafana Docker image comes in two variants: Alpine and Ubuntu. This page also contains important information about migrating from earlier Docker container versions.

This is the default image. This image is based on the popular Alpine Linux projectavailable in the alpine official image.

Setting up Prometheus and Grafana for monitoring your servers

Alpine Linux is much smaller than most distribution base images, and thus leads to slimmer and more secure images. This variant is highly recommended when security and final image size being as small as possible is desired. The main caveat to note is that it does use musl libc instead of glibc and friendsso certain software might run into issues depending on the depth of their libc requirements.

This image is based on Ubuntuavailable in the Ubuntu official image. Note: If you are on a Linux system, you might need to add sudo before the command. Use these to get access to the latest master builds of Grafana. This tag guarantees that you use a specific version of Grafana instead of whatever was the most recent commit at the time.

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You can install official and community plugins listed on the Grafana plugins page or from a custom URL. Otherwise, the latest will be assumed. You can build your own customized image that includes plugins. This saves time if you are creating multiple images and you want them all to have the same plugins installed on build. Dockerfilethat can be used to build a custom Grafana image.

Replace Dockerfile in above example with ubuntu. Dockerfile to build a custom Ubuntu based image Grafana v6. The Grafana Image Renderer plugin does not currently work if it is installed in Grafana Docker image.

This installs additional dependencies needed for the Grafana Image Renderer plugin to run. Dockerfile to build a custom Ubuntu-based image Grafana v6.

install grafana on synology

This section contains important information if you want to migrate from previous Grafana container versions to a more current one. Grafana Docker image now comes in two variants, one Alpine based and one Ubuntu based, see Image Variants for details.

Grafana Docker image was changed to be based on Alpine instead of Ubuntu. This led to the creation of three volumes each time a new instance of the Grafana container started, whether you wanted it or not. You should always be careful to define your own named volume for storage, but if you depended on these volumes, then you should be aware that an upgraded container will no longer have them. Warning : When migrating from an earlier version to 5. You will also have to change file ownership or user as documented below.

In Grafana v5. Unfortunately this means that files created prior to v5.

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We made this change so that it would be more likely that the Grafana users ID would be unique to Grafana. For example, on Ubuntu There are two possible solutions to this problem.The best way to install Netdata is with our automatic one-line installation scriptwhich works with all Linux distributions, or our. If you want to install Netdata with Docker, on a Kubernetes cluster, or a different operating system, see Have a different operating system, or want to try another method?

Some third parties, such as the packaging teams at various Linux distributions, distribute old, broken, or altered packages. We recommend you install Netdata using one of the methods listed below to guarantee you get the latest checksum-verified packages. Starting with v1. Read about the information collected, and learn how to-opt, on our anonymous statistics page.

The usage statistics are vital for us, as we use them to discover bugs and prioritize new features. To install Netdata from source and get automatic nightly updatesrun the following as your normal user:. To see more information about this installation script, including how to disable automatic updates, get nightly vs.

Scroll down for details about automatic updates or nightly vs. Netdata works on many different operating systems, each with a few possible installation methods.

Below, you can find a few additional installation methods, followed by separate instructions for a variety of unique operating systems. Install with. Install with a pre-built static binary for bit systems. Install Netdata on Docker. Install Netdata on Kubernetes with a Helm chart.

Install Netdata on macOS. Install manually from source. Installation on PFSense. Install Netdata on Synology. Manual installation on FreeNAS. Manual installation on Alpine.

install grafana on synology

If you would prefer to update your Netdata agent manually, you can disable automatic updates by using the --no-updates option when you install or update Netdata using the automatic one-line installation script.

With automatic updates disabled, you can choose exactly when and how you update Netdata. The Netdata team maintains two releases of the Netdata agent: nightly and stable. Nightly : We create nightly builds every 24 hours.

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