Redis:
Utilized as an in-memory data structure store for caching purposes.
This structure ensures that data from the Unified Namespace is systematically
stored, processed, and made visually accessible, providing OT professionals with
real-time insights and analytics on shop floor operations.
graph LR
2["`fa:fa-user **OT Professional / Shopfloor**
Monitors and manages the shopfloor, including safety, automation and maintenance`"]
style 2 fill:#dddddd,stroke:#9a9a9a,color:#000000
51["`**Unified Namespace**
The central source of truth for all events and messages on the shop floor.`"]
style 51 fill:#aaaaaa,stroke:#47a0b5,color:#000000
subgraph 64 [Historian]
style 64 fill:#ffffff,stroke:#47a0b5,color:#47a0b5
65["`**kafka-to-postgresql-v2**
Stores in the database the Kafka messages that follow the Data Model V2 schema`"]
style 65 fill:#aaaaaa,stroke:#47a0b5,color:#000000
66["`**TimescaleDB**
An open-source time-series SQL database`"]
style 66 fill:#aaaaaa,stroke:#47a0b5,color:#000000
67["`**Grafana**
Visualization and analytics software`"]
style 67 fill:#aaaaaa,stroke:#47a0b5,color:#000000
68["`**factoryinsight**
Analytics software that allows data analysis, like OEE`"]
style 68 fill:#aaaaaa,stroke:#47a0b5,color:#000000
69["`**grafana-datasource-v2**
Grafana plugin to easily connect to factoryinsight`"]
style 69 fill:#aaaaaa,stroke:#47a0b5,color:#000000
70["`**Redis**
In-memory data structure store used for caching`"]
style 70 fill:#aaaaaa,stroke:#47a0b5,color:#000000
end
65-. Stores data .->66
51-. Stores data in a
predefined schema via .->65
67-. Performs SQL queries .->66
67-. Includes .->69
69-. Extracts KPIs and other
high-level metrics .->68
68-. Queries data .->66
68<-.->70
65<-.->70
2-. Visualize real-time
dashboards .->67
The cache in the United Manufacturing Hub is Redis, a
key-value store that is used as a cache for the other microservices.
How it works
Recently used data is stored in the cache to reduce the load on the database.
All the microservices that need to access the database will first check if the
data is available in the cache. If it is, it will be used, otherwise the
microservice will query the database and store the result in the cache.
By default, Redis is configured to run in standalone mode, which means that it
will only have one master node.
What’s next
Read the Cache reference documentation
to learn more about the technical details of the cache microservice.
2 - Database
The database microservice is the central component of the United Manufacturing
Hub and is based on TimescaleDB, an open-source relational database built for
handling time-series data. TimescaleDB is designed to provide scalable and
efficient storage, processing, and analysis of time-series data.
You can find more information on the datamodel of the database in the
Data Model section, and read
about the choice to use TimescaleDB in the
blog article.
How it works
When deployed, the database microservice will create two databases, with the
related usernames and passwords:
grafana: This database is used by Grafana to store the dashboards and
other data.
factoryinsight: This database is the main database of the United Manufacturing
Hub. It contains all the data that is collected by the microservices.
Read the Database reference documentation
to learn more about the technical details of the database microservice.
3 - Factoryinsight
Factoryinsight is a microservice that provides a set of REST APIs to access the
data from the database. It is particularly useful to calculate the Key
Performance Indicators (KPIs) of the factories.
How it works
Factoryinsight exposes REST APIs to access the data from the database or calculate
the KPIs. By default, it’s only accessible from the internal network of the
cluster, but it can be configured to be
accessible from the external network.
The APIs require authentication, that can be either a Basic Auth or a Bearer
token. Both of these can be found in the Secret factoryinsight-secret.
What’s next
Read the Factoryinsight reference documentation
to learn more about the technical details of the Factoryinsight microservice.
4 - Grafana
The grafana microservice is a web application that provides visualization and
analytics capabilities. Grafana allows you to query, visualize, alert on and
understand your metrics no matter where they are stored.
It has a rich ecosystem of plugins that allow you to extend its functionality
beyond the core features.
How it works
Grafana is a web application that can be accessed through a web browser. It
let’s you create dashboards that can be used to visualize data from the database.
Thanks to some custom datasource plugins,
Grafana can use the various APIs of the United Manufacturing Hub to query the
database and display useful information.
What’s next
Read the Grafana reference documentation
to learn more about the technical details of the grafana microservice.
5 - Kafka to Postgresql V2
The Kafka to PostgreSQL v2 microservice plays a crucial role in consuming and
translating Kafka messages for storage in a PostgreSQL database. It aligns with
the specifications outlined in the Data Model v2.
How it works
Utilizing Data Model v2, Kafka to PostgreSQL v2 is specifically configured to
process messages from topics beginning with umh.v1.. Each new topic undergoes
validation against Data Model v2 before message consumption begins. This ensures
adherence to the defined data structure and standards.
Message payloads are scrutinized for structural validity prior to database insertion.
Messages with invalid payloads are systematically rejected to maintain data integrity.
The microservice then evaluates the payload to determine the appropriate table
for insertion within the PostgreSQL database. The decision is based on the data
type of the payload field, adhering to the following rules:
Numeric data types are directed to the tag table.
String data types are directed to the tag_string table.
What’s next
Read the Kafka to Postgresql v2
reference documentation to learn more about the technical details of the
Kafka to Postgresql v2 microservice.
6 - Umh Datasource V2
The plugin, umh-datasource-v2, is a Grafana data source plugin that allows you to fetch
resources from a database and build queries for your dashboard.
How it works
When creating a new panel, select umh-datasource-v2 from the Data source drop-down menu. It will then fetch the resources
from the database. The loading time may depend on your internet speed.
Select the resources in the cascade menu to build your query. DefaultArea and DefaultProductionLine are placeholders
for the future implementation of the new data model.
Only the available values for the specified work cell will be fetched from the database. You can then select which data value you want to query.
Next you can specify how to transform the data, depending on what value you selected.
For example, all the custom tags will have the aggregation options available. For example if you query a processValue:
Time bucket: lets you group data in a time bucket
Aggregates: common statistical aggregations (maximum, minimum, sum or count)
Handling missing values: lets you choose how missing data should be handled
Configuration
In Grafana, navigate to the Data sources configuration panel.
Select umh-v2-datasource to configure it.
Configurations:
Base URL: the URL for the factoryinsight backend. Defaults to http://united-manufacturing-hub-factoryinsight-service/.
Enterprise name: previously customerID for the old datasource plugin. Defaults to factoryinsight.
API Key: authenticates the API calls to factoryinsight.
Can be found with UMHLens by going to Secrets → factoryinsight-secret → apiKey. It should follow the format Basic xxxxxxxx.
