Table of contents

Overview

With the Analytics API, you can query all check metrics and report on Checkly data in your preferred reporting tool! The Analytics APIs allows queries across different dimensions:

• Aggregated: get the p99, sum, standard deviation or whatever you like from DNS times for API checks, or First Content ful Paint (FCP) score for Browser checks.
• Non-aggregated: Get the raw data points so you can aggregate yourself how you want it.

Use powerful options like quickRange to select time window presets like last30Days or lastMonth, and group results per location or per pageIndex. For aggregated queries you can set the aggregationInterval to get, for instance, data aggregated per week over the last 30 days.

Dive straight into the API reference at developers.checklyhq.com or keep reading for more examples!

There are three main endpoints.

1. /v1/analytics/metrics/: returns all the available metrics for a specific check-type (API or BROWSER)
2. /v1/analytics/browser-checks/{checkId}: returns metrics for Browser checks.
3. /v1/analytics/api-checks/{checkId}: returns metrics for API checks.

The specific endpoints per check type return a JSON response that includes a check’s attributes, period requested, grouped series and a metadata section where you’ll have additional information about the metrics to create rich reports.

The example below is from a Browser check that visits three pages in a typical e-commerce flow

• /login
• /cart
• /cart/add

We can query the for this Browser check using a curl command like:

curl -x GET https://api.checklyhq.com/v1/analytics/browser-checks/79ad4fe0-589a-4924-a027-d18b12eee9cb?metrics=TTFB_avg,TTFB_p99&groupBy=pageIndex&quickRange=last7Days

This command add the following query params:

• metrics=TTFB_avg,TTFB_p99: return average and p99 aggregate of the TTFB (Time to First Byte)
• groupBy=pageIndex: group by page index, i.e. the pages visited int the Browser check.
• quickRange=last7Days: aggregate over the last 7 days.

The response looks as follows 👇

{
    "checkId": "79ad4fe0-589a-4924-a027-d18b12eee9cb",
    "name": "Shopping Cart - Add product",
    "checkType": "BROWSER",
    "activated": true,
    "muted": false,
    "frequency": 5,
    "from": "2023-01-20T12:45:57.494Z",
    "to": "2023-01-27T12:45:57.494Z",
    "tags": [
        "sports"
    ],
    "series": [
        {
            "pageIndex": 0,
            "data": [
                {
                    "pageUrl": "https://mycart.acme.com/login",
                    "pageIndex": 0,
                    "responseTime_avg": 7216.8896,
                    "TTFB_avg": 746.9548609294588,
                    "TTFB_p99": 1059.7
                }
            ]
        },
        {
            "pageIndex": 1,
            "data": [
                {
                    "pageUrl": "https://mycart.acme.com/cart",
                    "pageIndex": 1,
                    "responseTime_avg": 7216.8896,
                    "TTFB_avg": 239.41101193049596,
                    "TTFB_p99": 310.8
                }
            ]
        },
        {
            "pageIndex": 2,
            "data": [
                {
                    "pageUrl": "https://mycart.acme.com/cart/add",
                    "pageIndex": 2,
                    "responseTime_avg": 7216.8896,
                    "TTFB_avg": 1.3732638888888888,
                    "TTFB_p99": 0
                }
            ]
        }
    ],
    "metadata": {
        "responseTime_avg": {
            "unit": "milliseconds",
            "label": "Response time for the full script",
            "aggregation": "avg"
        },
        "TTFB_avg": {
            "unit": "milliseconds",
            "label": "Time To First Byte",
            "aggregation": "avg"
        },
        "TTFB_p99": {
            "unit": "milliseconds",
            "label": "Time To First Byte",
            "aggregation": "p99"
        }
    },
    "pagination": {
        "page": 1,
        "limit": 10
    }
}

Here you will see an example of a request using Postman where the /v1/analytics/browser-check endpoint returns aggregated data (TTFB_p50 and TTFB_p90) for the last 7 days grouping by page.

You must add the X-Checkly-Account and Authorization headers to authenticate.

Following these instructions you’ll learn how to use the Analytics API within a Grafana dashboard:

1. Creating the Data Source

First, you need to create the Data Source with the Analytics API connection. After installing the JSON API plugin you’ll be able to consume any REST API and handle JSON responses.

2. Configuring a component

Next, you can pick a time series component and configure it by selecting the Checkly Analytics API data source and setting the required HTTP header and query parameters to fetch the JSON. You’ll find detailed docs on available parameters in the API docs

In the following image you’ll see all required configuration for a component:

• Fields
• Path
• Query parameters
• Header
• Variables (optional)

1. Designing the dashboard

You can mix multiple components to create a beautiful dashboard. The following screenshot shows a dashboard with three types of results:

• aggregated
• non-aggregated
• and summarized grouped by location.

You can start creating your reports by using our public Google Sheets report example template. The spreadsheet includes the =ChecklyAPI() function to consume the Checkly Public API just entering configuring your credentials.

1. Make a copy of our public Google Sheets template.
2. Add your Account Id and API Key in the Apps Script code (be careful if you’ll share your spreadsheet with your credentials)
3. Navigate the Metrics and Checks pages to confirm Checkly Public API requests are working
4. Go to the Analytics Report page, pick a check, pick a metric and see if the chart shows the correct information

You’ll find dropdown cells to select the check, number of results, quick time range presets, or grouping attribute.

You can even whip up a bash script and use curl and jq to print useful analytics to your terminal. Here is an example script that does the following:

1. It fetches your checks from the /v1/checks endpoint.
2. Loops over your checks and based on the check type, calls the v1/analytics/<checkType> endpoint to gather useful data.

#!
 
ACCOUNT_ID=<your account ID>
TOKEN=<your API token>

rawChecks=$(curl -s --request GET \
  --url 'https://api-test.checklyhq.com/v1/checks?limit=5&page=1' \
  --header "Authorization: Bearer ${TOKEN}" \
  --header "X-Checkly-Account: ${ACCOUNT_ID}") 

checksAndTypes=$(jq -c 'sort_by(.checkType) | [.[] | {id, checkType}]' <<< "${rawChecks}" ) 
printf '\n'
for row in $(echo "${checksAndTypes}" | jq -c '.[]'); do
  checkType=$(jq -r '.checkType' <<< "${row}")
  checkId=$(jq -r '.id' <<< "${row}")

  case $checkType in
    BROWSER)
      rawMetric=$(curl -s --request GET \
        --url "https://api-test.checklyhq.com/v1/analytics/browser-checks/${checkId}?metrics%5B%5D=TTFB_p99&metrics%5B%5D=FCP_p99&metrics%5B%5D=consoleErrors_sum&metrics%5B%5D=availability&quickRange=last30Days" \
        --header "Authorization: Bearer ${TOKEN}" \
        --header "X-Checkly-Account: ${ACCOUNT_ID}")    
      jq -jr '.checkType, " - ", .name' <<< "${rawMetric}"  
      printf '\n'
      jq -r '"availability\tTTFB\tFCP\tErrors", "--------------\t---\t---\t------", (.series[0].data[]| "\(.availability)\t\(.TTFB_p99)\t\(.FCP_p99)\t\(.consoleErrors_sum)")' <<< "${rawMetric}" |  column -t -s $'\t'
      ;;

    API)
      rawMetric=$(curl -s --request GET \
        --url "https://api-test.checklyhq.com/v1/analytics/api-checks/${checkId}?metrics%5B%5D=firstByte_p99&metrics%5B%5D=availability&metrics%5B%5D=dns_p99" \
        --header "Authorization: Bearer ${TOKEN}" \
        --header "X-Checkly-Account: ${ACCOUNT_ID}")
      jq -jr '.checkType, " - ", .name' <<< "${rawMetric}"  
      printf '\n'
      jq -r '"Availability\tTTFB\tDNS", "--------------\t----\t---", (.series[0].data[]| "\(.availability)\t\(.firstByte_p99)\t\(.dns_p99)")' <<< "${rawMetric}" |  column -t -s $'\t'
      ;;

    *)
      echo -n "unknown"
      ;;
  esac
  printf '%.0s\n' {1..2}
done

Save this script in a file called analytics.sh and run it. You will get an output similar to:

Last updated on April 24, 2024. You can contribute to this documentation by editing this page on Github