This is a collection of NGSI-v2 tutorials for the FIWARE system. Each tutorial consists of a series of exercises to demonstrate the correct use of individual FIWARE components and shows the flow of context data within a simple Smart Solution either by connecting to a series of dummy IoT devices or manipulating the context directly or programmatically.
How to Use
Each tutorial is a self contained learning exercise designed to teach the developer about a single aspect of FIWARE. A summary of the goal of the tutorial can be found in the description at the head of each page. Every tutorial is associated with a GitHub repository holding the configuration files needed to run the examples. Most of the tutorials build upon concepts or enablers described in previous exercises the to create a complex smart solution which is "powered by FIWARE".
The tutorials are split according to the chapters defined within the FIWARE catalog and are numbered in order of difficulty within each chapter hence the an introduction to a given enabler will occur before the full capabilities of that element are explored in more depth.
It is recommended to start with reading the full Core Context Management: The NGSI-v2 Interface Chapter before moving on to other subjects, as this will give you an fuller understanding of the role of context data in general. However it is not necessary to follow all the subsequent tutorials sequentially - as FIWARE is a modular system, you can choose which enablers are of interest to you.
Docker and Docker Compose
To keep things simple all components will be run using Docker. Docker is a container technology which allows to different components isolated into their respective environments.
- To install Docker on Windows follow the instructions here
- To install Docker on Mac follow the instructions here
- To install Docker on Linux follow the instructions here
Docker Compose is a tool for defining and running multi-container Docker applications. A series of
are used configure the required services for the application. This means all container services can be brought up in a
single command. Docker Compose is installed by default as part of Docker for Windows and Docker for Mac, however Linux
users will need to follow the instructions found here
You can check your current Docker and Docker Compose versions using the following commands:
docker-compose -v docker version
Important In recent versions,
docker-composeis already included as part of of the main
dockerclient, Please ensure that you are using Docker version 20.10 or higher and Docker Compose 1.29 or higher and upgrade if necessary. If you are unable to upgrade and stuck using an older version you can still run the tutorials by adding a
legacyparameter at the end the
./servicesscript commands e.g.
services start legacy
If using a linux distro with an outdated docker-compose, the files can be installed directly as shown:
sudo curl -L "https://github.com/docker/compose/releases/download/1.24.0/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose sudo chmod +x /usr/local/bin/docker-compose
If you are using docker-compose in Ubuntu with VMware and faced the following error: ERROR: Couldn't connect to Docker daemon at http+docker://localunixsocket - is it running?
It can be solved by owning the
/var/run/docker.sock Unix socket as shown:
sudo chown $USER /var/run/docker.sock
The tutorials which use HTTP requests supply a collection for use with the Postman utility. Postman is a testing framework for REST APIs. The tool can be downloaded from www.getpostman.com. All the FIWARE Postman collections can downloaded directly from the Postman API network
Cygwin for Windows
We will start up our services using a simple Bash script. Windows users should download cygwin to provide a command-line functionality similar to a Linux distribution on Windows.
Apache Maven is a software project management and comprehension tool. Based on the concept of a project object model (POM), Maven can manage a project's build, reporting and documentation from a central piece of information. Maven can be used to define and download our dependencies and to build and package Java or Scala code into a JAR file.
The following NGSI-v2 and NGSI-LD Data models are used within the tutorials:
List of Tutorials
Core Context Managment: The NGSI-v2 Interface
These first tutorials are an introduction to the FIWARE Context Broker, and are an essential first step when learning to use FIWARE
Internet of Things, Robots and third-party systems
In order to make a context-based system aware of the state of the real world, it will need to access information from Robots, IoT Sensors or other suppliers of context data such as social media. It is also possible to generate commands from the context broker to alter the state of real-world objects themselves.
201. Introduction to IoT Sensors
202. Provisioning an IoT Agent
203. IoT over MQTT
204. Using an alternative IoT Agent
205. Creating a Custom IoT Agent
206. IoT over IOTA Tangle
250. Introduction to Fast-RTPS and Micro-RTPS
Core Context Management: History Management
These tutorials show how to manipulate and store context data so it can be used for further processesing
301. Persisting Context Data using Apache Flume (MongoDB, MySQL, PostgreSQL)
302. Persisting Context Data using Apache NIFI (MongoDB, MySQL, PostgreSQL)
303. Querying Time Series Data (MongoDB)
304. Querying Time Series Data (Crate-DB)
305. Big Data Analysis (Flink)
Security: Identity Management
These tutorials show how to create and administer users within an application, and how to restrict access to assets, by assigning roles and permissions.
401. Administrating Users and Organizations
402. Managing Roles and Permissions
403. Securing Application Access
404. Securing Microservices with a PEP Proxy
405. XACML Rules-based Permissions
406. Administrating XACML via a PAP
Processing, Analysis and Visualization
These tutorials show how to create, process, analyze or visualize context information
NGSI-LD for NGSI-v2 Developers
These tutorials show how to use NGSI-LD which combines context data management with linked data concepts.