In a typical multi-instance datasource the LogicMonitor data ingest process is such that we periodically run Active Discovery to discover objects we can instrument, and then at the specified polling interval execute the data collection task for each instance object, one after the other.

While this approach is reasonable for collection types such as SNMP and WMI, it is sometimes less practical for devices that expose data for all instances in a single query.

For example, on a device that speaks SNMP we can query it for instances via an snmp “walk” and then do an successive snmp “get” against each of the instances. But for many devices that expose metrics via an API or CLI, there’s no ability to get data for only single instance one at a time. Meaning: each time we query the device we get data across all of its instances. Because of the atomicity in our data collection mechanism, our standard model dictates that we’d have do this exact same query over and over  once per instance  but then throw out the data for everything except the instance on which this collection task is based.

The BATCHSCRIPT collection mechanism solves this problem by allowing for the collection of all datasource instances within a single data collection task. Because data collection is much more efficient, this approach decreases the load both on the Collector and the target device  especially for devices with many instances.


Using BATCHSCRIPT vs. SCRIPT Collection

In our standard Script Data Collection mechanism, data values are typically output from the script as key/value pairs along the lines of:

key1: value1
key2: value2
key3: value3

In SCRIPT mode, the same script runs once per instance and uses the provided instance id (wildvalue) as the “foreign key” to identify the instance associated with a particular data collection task. We then create datapoints with key/value post-processor using “key1”, “key2”, “key3” as the keys.

In BatchScript mode the key/value pairs need to be output as:

instance1.key1: value1
instance1.key2: value2
instance1.key3: value3
instance2.key1: value1
instance2.key2: value2
instance2.key3: value3

where the instance ids specified as the prefix correspond to the instance ids provided in Active Discovery. Again you’d create three datapoints  each using the key/value post-processor but with keys specified as ##WILDVALUE##.key1, ##WILDVALUE##.key2, ##WILDVALUE##.key3, and so on.

Note that the key names, both in script output and in the datapoint definitions, must start with ##WILDVALUE##. Keys of the format key1.##WILDVALUE## are not supported.



Example – Using Groovy BatchScript for Datasource Data Collection

Consider the SCRIPT datasource presented in Groovy Data Collection Example, in which we query an HTTP API to instrument the power supplies in a Palo Alto firewall. If we were to rewrite that script to do BATCHSCRIPT collection, it would look like this:



// import the logicmonitor http helper class
import com.santaba.agent.groovyapi.http.*;
// get the hostname, paloalto api key, and instance information from the device property & instance property tables
hostname = hostProps.get("system.hostname");
api_key = hostProps.get("paloalto.apikey.pass");
instance = instanceProps.get("wildvalue");
// because we named our instances "slot_name/entry_description" we need to split those apart for later use
(instance_slot, instance_entry) = instance.split('/');
// specify the api command to get the power supplies
api_command = "";
// encode the special characters in the api command so we can send them in an http request
encoded_command =;
// setup the url to run this command
url = "https://" + hostname + "/api/?type=op&key=" + api_key + "&cmd=" + encoded_command;
// do an http get on the url, and retrieve the body of the http response (as opposed to the headers)
response_text = HTTP.body(url);
// because the paloalto returns a response in xml format, we need to parse the xml into an groovy object
response = new XmlSlurper().parseText(response_text);
// iterate over the response object to get the power supply "slots"
{ slot ->
    // get the slot name using from the "name" node on the "slot" object
    slot_name =;
    // iterate through each of the "entries" in this slot
    { entry ->
        // get the description field
        entry_desc = entry.description.text();
        // assemble an instance id to match what we did in active discovery
        instance_id = slot_name + "/" + entry_desc;
        // print the power supply detail as key-value pairs, including the instance_id
        println instance_id + ".max_voltage:" + entry.max.text();
        println instance_id + ".min_voltage:" + entry.min.text();
        println instance_id + ".cur_voltage:" + entry.Volts.text();
// return with a response code that indicates we ran successfully
return (0);

From here we create three datapoints: one for max_voltage, min_voltage, and cur_voltage. We’ll use the key-value post-processor to extract the values using keys ##WILDVALUE##.max_voltage, ##WILDVALUE##.min_voltage, and ##WILDVALUE##.cur_voltage.



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