02 API Queries

API queries for production data, OEE metrics, and data joins in Grafana.

In this tutorial you will learn how to query production data with dynamic time ranges, extract OEE metrics, and join data from multiple queries:

What you will learn

• Use Grafana's time range in API queries

• Query production runs with OEE metrics

• Extract nested JSON values with JSONata

• Combine data from multiple machines

• Join production runs with product data

Prerequisites

• Completed Introduction to the ENLYZE API

• Understanding of GET requests and the root selector $.data

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Dynamic time ranges

In the introduction you queried fixed endpoints. For production data you need a dynamic time range that updates with Grafana's time picker.

Variable	Description
${__from:date:iso}	Start time in ISO format
${__to:date:iso}	End time in ISO format

These variables are automatically replaced with the current time range of the dashboard.

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Querying production runs

The production-runs endpoint returns production runs including OEE metrics.

Configure the query

1. Create a new panel with the Table visualization

2. Select the data source ENLYZE API

3. Configure the query:

Setting	Value
Type	JSON
Parser	Backend
Source	URL
Format	Table
Method	GET
URL	production-runs

1. Expand Headers, Request params and add the following under URL Query Params:

Key	Value
machine	141e0927-62b3-4e76-8398-ad82d20f397f
start	${__from:date:iso}
end	${__to:date:iso}

1. Set the Root selector to $.data

Always configure query parameters through the Grafana interface under Headers, Request params instead of writing them directly into the URL. This is clearer and avoids encoding issues.

The table shows the raw API response. OEE metrics like productivity, availability, and performance are nested objects. In the next step you will extract these values.

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Extracting nested values with JSONata

JSONata lets you extract and restructure nested values directly in the root selector. Replace $.data with:

$.data.{
  "production_order": production_order,
  "start": start,
  "end": end,
  "productivity": productivity.score,
  "availability": availability.score,
  "performance": performance.score,
  "quality": quality.score,
  "yield": quantity_yield.value
}

Each row now contains the extracted OEE scores and the produced quantity (yield).

JSONata basics

Expression	Description
$.data	Access the data array
field.subfield	Nested property
{ "name": value }	Create a new object

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Configuring columns

Instead of JSONata, you can also use the Columns feature of the Infinity query. Expand Parsing options & Result fields and add the following under Columns:

Selector	Title	Type
production_order	Order	String
start	Start	Timestamp
end	End	Timestamp
productivity.score	OEE	Number
availability.score	Availability	Number
performance.score	Performance	Number
quality.score	Quality	Number
quantity_yield.value	Yield	Number

Highlighting OEE values with color

For the OEE columns, colored cells work well. Add a Field override for fields matching the regex /OEE|Availability|Performance|Quality/:

• Unit: Percent (0.0-1.0)

• Min: 0, Max: 1

• Cell type: Color background

• Value mappings: Color gradients from red (< 60%) through orange and yellow to green (> 95%), and null mapped to "NO DATA" in grey

For machines without quality data, the Quality column shows "NO DATA". In this case, the OEE (Productivity) is calculated from Availability and Performance. Learn more in the OEE documentation.

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OEE as a stat panel

You can also display the OEE of the latest production run as a stat panel:

1. Create a new panel with Stat visualization

2. Configure the same production-runs query with the query params as above

3. Set the root selector to $.data[0].productivity.score

4. Set unit to Percent (0.0-1.0), color mode to Background

5. Thresholds: red (base), yellow (0.6), green (0.8)

Following the same pattern, create additional panels for Availability ($.data[0].availability.score), Performance ($.data[0].performance.score), and Quality ($.data[0].quality.score). For Quality, configure a value mapping for null mapped to "NO DATA", since not all machines provide quality data.

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Combining production runs from multiple machines

To display production runs from multiple machines in a single table, configure two queries with a computed column for the machine name in each.

Query A (Kiefel):

Setting	Value
URL	production-runs
Query Params	machine = 141e0927-..., start = ${__from:date:iso}, end = ${__to:date:iso}

Under Computed columns: Selector "Kiefel", Title Machine

Query B (Macchi):

Setting	Value
URL	production-runs
Query Params	machine = cc0d2dcb-..., start = ${__from:date:iso}, end = ${__to:date:iso}

Under Computed columns: Selector "Macchi", Title Machine

Add a Merge transformation to combine both queries into a single table.

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Joining with product data

Production runs only contain a product UUID. To display the product name, join the data with the products endpoint.

Create two queries

Query A (production runs):

Setting	Value
URL	production-runs
Query Params	machine = 141e0927-..., start = ${__from:date:iso}, end = ${__to:date:iso}

Columns: production_order as Order, product as product_uuid, start as Start, productivity.score as OEE

Query B (products):

Setting	Value
URL	products
Root selector	$.data

Columns: uuid as product_uuid, external_id as Product ID, name as Product Name

Important: The join field must have the same column name in both queries (product_uuid).

Join transformation

1. Switch to the Transform tab

2. Add Join by field: Mode INNER, Field product_uuid

3. Optional: add Organize fields to hide product_uuid

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Downtimes

Machine downtimes can be queried via the downtimes endpoint:

Setting	Value
URL	downtimes
Query Params	machine = {uuid}, start = ${__from:date:iso}, end = ${__to:date:iso}
Root selector	$.data

The API returns the start and end time as well as the downtime reason and its category. Use Columns to extract the relevant fields:

Selector	Title	Type
uuid	Downtime ID	String
start	Start	Timestamp
end	End	Timestamp
reason.name	Reason	String
reason.category	Category	String

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Tips

• Always test with a table: Raw data is easier to read in tables. Only switch to other visualizations after the query works.

• Use query params: Configure parameters through the Grafana interface instead of writing them directly into the URL.

• Build the root selector incrementally: Start with $.data, check the data structure, then add JSONata.

• Empty data: Expand the time range or check whether the machine was running during the selected period.

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Next steps

• Working with variables - Create dropdowns for site and machine selection