Scalable Timeseries with infinimesh and/or Timeseries Plugin

Our infinimesh® platform is built to make data privacy and data ownership possible, without any doubt. To achieve this, we have built our platform in a cloud-native way and entirely API driven. It allows our customers to integrate our cloud into their systems without compromising IT Security or even move to a public cloud provider. We understand ourselves as a stretched workbench for any IoT related ideas our customers might have.

This blog post shows how easily infinimesh extends to an ultra-scalable time series, designed for high throughput and rapid prototyping, using the time series plugin from our GitHub space. Note that we use here Redis in the standalone mode. We urgently advise you to set up a Redis cluster if you want to run the plugin in production!

The plugin comes as a ready-to-ship docker container, including Redislab TimeSeries and Grafana to enable easy PoC and Hackathons.

To get it running, you need to have either a working docker environment or Kubernetes (likemicrok8s) installed. Of course, any cloud provider works, too. That is the beauty of cloud-native development.

Let’s get started:
1. Check out the plugin repository:

a. git clone https://github.com/InfiniteDevices/plugins.git

2. edit the docker-compose.yaml in timeseries:

USERNAME = YOUR INFINIMESH User
PASSWORD = YOUR INFINIMESH Password
API_URL = FQDN-API-Endpoint (ex: https://api.infinimesh.cloud)

3. Then run everything via:

docker-compose -f timeseries/docker-compose.yml --project-directory . up --build

After a few seconds, the connector and the time series backend are available, and infinimesh pushes data into:

4. After some time, Grafana will be ready. Connect your browser tohttp://localhost:3000and follow the instructions to change the default admin credentials (admin/admin). Please note that the setup disappears when the docker container gets deleted.

The memory and CPU footprint shows that the plugin, which we used for this blog post, does not consume too many resources:

Dashboard

We have built a sample dashboard that can be easily imported. The sample dashboard shows all captured data in one graph. Feel free to use this as a starting point to create your powerful dashboards.

Add the Redis data source

Note: We provision in the newest container (build 77c68e4) redis as default data source – this step is not necessary anymore. 

When you login into Grafana the first time using an image prior to build 77c68e4, you have to add the data source by clicking:

Type “redis” into the search field:

and select this data source by clicking into it. The following shows the setup, just put redis://redis:6379 into the address field and click “save and test“:

Now Grafana can talk to the Redis time-series backend. You can now import the dashboard by Create -> Import -> Upload JSON File and select sample-dashboard.json from the directory in which you have synced the repository. You should now see the Dashboard:

All data we captured from the very beginning are displayed there. You can now start to explore Grafana and build awesome dashboards. With this approach, we also enable our customers to excel in rapid prototyping using infinimesh technology.

For example, here we selected some data points (pressing Ctrl + select the data point) to get fast insight into the data (this is the SMA solar plant):

Links:
Grafana: https://grafana.com/
Redislabs: https://oss.redislabs.com/redistimeseries/
Docker Desktop: https://www.docker.com/products/docker-desktop