After a fresh install of Ubuntu server 20.04 on a Raspberry Pi (3b+ in this case) you may find that the default login (user: “ubuntu” password: “ubuntu”) won’t get you logged in.
After waiting for a few minutes while googling this the Rpi output some cloud-init and SSH-key messages. When trying again the default ubuntu/ubuntu login worked just fine.
So, it turns out that even though the login screen is shown and it looks like the OS has fully booted, it won’t be possible to log in until the cloud-init etc. have finished (which may take 5min or so)!
After having received several inquiries from people about how to get started with EdgeX Foundry I’ve decided to write a hands-on tutorial. Hopefully this will make it easier for newcomers to setup a system, configure data ingestion, data export & many other things.
Incidentally, getting started with EdgeX Foundry is also an excellent way to learn how to practically leverage new concepts and technologies in IT. In addition to learning about open source IoT solutions, the guide also covers topics like:
Docker
Building, running and monitoring containers
Grouping containers with docker-compose
Microservices
REST APIs
MQTT
Python scripting
Tools like Postman, cURL, etc.
The guide started as a blog post but ended up being way too long. Now it’s in PDF format and clocks in at 48 pages. Hopefully not too long for those looking to get started 🙂
In early 2020 a new feature was added to the PowerEdge 14G servers called “Telemetry Streaming’. This feature makes it possible to send a continuous stream of telemetry containing in-depth information about the state of the server and its various components including, but not limited to, the following:
CPU, Memory and Fans
FPGA and GPU
PCIe slots
Airflow inside server
Power usage information
Since the level and depth of information collected with this method FAR exceeds what has been previously possible using IPMI or other tools, this feature can help in several areas. For example:
Power ML algorithms for Anomaly Detection
Provide detailed inventory, usage and status information
This post aim to describe three methods with which to enable the Telemetry Streaming feature in the iDRAC9 on Dell EMC 14G PowerEdge servers:
Enable using RACADM / SSH
Enable using provided GitHub scripts
Enable using Redfish and Postman
Enabling using RACADM and Redfish are selective methods while using the GitHub script enables ALL reports in one go. Personally I’d recommend being selective to start with until it is clear what data is required / desired.
Note that enabling everything will result in just shy of 3M data points / 24h / server
This article contains the practical steps to set up and configure Telemetry Streaming. It assumes it has already been enabled using one of the methods described in the previous article here. In this blog post we use the following:
Update and install:
sudo apt update
sudo apt upgrade -y
sudo apt install python3-venv python3-pip jq -y
Create a virtual environment:
python3 -m venv NAME-OF-ENV
source ./NAME-OF-ENV/bin/activate
Download the repositories from GitHub:
git clone https://github.com/jonas-werner/idrac9-telemetry-streaming.git
git clone https://github.com/dell/iDRAC-Telemetry-Scripting.git
Install the Python modules:
cd idrac9-telemetry-streaming
pip3 install -r requirements.txt
Command for viewing the JSON data:
cat aaa | sed 's/\x27/"/g' | jq
Installing Docker
Installing prerequisite packages:
sudo apt install apt-transport-https ca-certificates curl software-properties-common -y
Adding the key for Docker-CE:
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
Adding the repository for Docker-CE
sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu eoan stable"
Installing Docker-CE
sudo apt update
sudo apt install docker-ce -y
Adding user to docker group:
sudo usermod -aG docker ${USER}
Installation and commands for InfluxDB
Download the container image:
docker pull influxdb
Run the image, create DB and add credentials:
docker run \
-d \
--name influxdb \
-p 8086:8086 \
-e INFLUXDB_DB=telemetry \
-e INFLUXDB_ADMIN_USER=root \
-e INFLUXDB_ADMIN_PASSWORD=pass \
-e INFLUXDB_HTTP_AUTH_ENABLED=true \
influxdb
View data in the container using the "influx" client:
docker exec -it influxdb influx -username root -password pass
Commands for the "influx" client:
show databases
use DB_NAME
show measurements
select * from MEASUREMENT
show field keys from MEASUREMENT
drop measurement MEASUREMENT **DELETES THE DATA**
Downloading and running Grafana
Download the container image:
docker pull grafana/grafana
Run the Grafana instance:
docker run -d --name=grafana -p 3000:3000 grafana/grafana
