> For the complete documentation index, see [llms.txt](https://edgex-api-advantech.gitbook.io/edgex-api-doc/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://edgex-api-advantech.gitbook.io/edgex-api-doc/advanteched-services-apis/alarm-service-apis.md).
# Alarm Service APIs
## **Content**
* Introduction
* Alarm Service APIs
## Introduction
Alarm service includes a lightweight rule engine, which provides IoT analytics and streaming capability. The rules are based on Source, SQL and Sink.
It is an edge lightweight IoT data analytics / streaming software implemented by Golang, and it can be run at all kinds of resource constrained edge devices. Kuiper rules are based on Source, SQL and Sink.
* Source: The data source of streaming data, such as data from MQTT broker. In EdgeX scenario, the data source is EdgeX message bus, which could be MQTT broker.
* SQL: SQL is where you specify the business logic of streaming data processing. Kuiper provides SQL-like statements to allow you to extract, filter & transform data.
* Sink: Sink is used for sending analysis result to a specified target. For example, send analysis result to another MQTT broker, or an HTTP rest address.
It provides a set of REST API for streams and rules management in addition to CLI.
By default, the REST API are running in port 9081. You can change the port in /etc/kuiper.yaml for the restPort property. We have used support-rulesengine API version 1.0.0 that running in port 48075.
## Alarm Service APIs
### Rules management
* create a rule
* show rules
* describe a rule
* update a rule
* drop a rule
* start a rule
* stop a rule
* restart a rule
* get the status of a rule
#### create a rule
(1) Example for MQTT output:
User application subscribes the broker and topic, then will get the alarm data with JSON format as below.
| |
| ------------------------------ |
| *\[{"RandomValue\_Int8": -6}]* |
(2) Example for Rest API output:
User application implements the your-restapi-server/api/action method, then the RestAPI server will get the alarm data with JSON format as below.
| |
| -------------------------- |
| *{RandomValue\_Int8: -97}* |
(3) CPU temperature example for MQTT output:
* An example of CPU temperature
* Create a sink that both name and type is EdgeX
* The sink result will be published to the topic result and you can get the data context from the MQTT broker as below: \[{"device":"cpu","temperature":62}]
(4) Battery temperature example for MQTT output:
* An example of battery temperature
* Create a sink that name is demo and type is zmq
* The sink result will be published to the topic result and you can get the data context from the MQTT broker as below: \[{"device":"Battery-POC6-01“, "temperature":31}]
(5) Battery remaining capacity example for MQTT output:
* An example of battery remaining capacity
* Create a sink that name is demo and type is zmq
* The sink result will be published to the topic result and you can get the data context from the MQTT broker as below: \[{"device":"Battery-POC6-01“, “capacity":100}
#### show rules
Example:
#### describe a rule
Example:
#### update a rule
Example:
#### drop a rule
Example:
#### start a rule
Example:
#### stop a rule
Example:
#### restart a rule
Example:
#### get the status of a rule
Example:
**Reference:**
1.\
2.\
3.[https://github.com/lf-edge/ekuiper/blob/master/docs/en\_US/restapi/overview.md]()\
4\. [https://github.com/lf-edge/ekuiper/blob/master/docs/en\_US/sqls/streams.md
]()
