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ThousandEyes monitors the performance of both local and wide-area networks. ThousandEyes combines Internet and WAN visibility, browser synthetics, end-user monitoring, and Internet Insights to deliver a holistic view of your hybrid digital ecosystem – across cloud, SaaS, and the Internet. It's a SaaS-based tool that helps troubleshoot application delivery and maps Internet performance.

Scope of Support

Currently, Nobl9 integration with ThousandEyes supports 5 different metrics that are focused on latency:

  • Network Latency - is the interval time (in milliseconds) from sending a network packet to when the test-assigned agent receives the response.

  • Network Loss - is the total loss of the network packet (in percents).

  • Page Load - is the interval of time (in milliseconds) from the load event to the point when the website is loaded.

  • DOM Load Time - is the interval of time (in milliseconds) required for the browser to build the website’s Document Object Model (DOM)

  • HTTP Server Response - is the interval between the beginning of the request and the web server successfully sending the first byte of the response to the client.

Each measurement is obtained per ThousandEyes test interval.

The following table is an overview of the ThousandEyes metric and corresponding Nobl9 values:

MetricNobl9 Value
Network Latencynet-latency
Network lossnet-loss
Page loadweb-page-load
DOM load timeweb-dom-load
HTTP Server Responsehttp-response-time


Nobl9 requires OAUTH_BEARER_TOKEN to communicate with ThousandEyes.


  1. Log in to your ThousandEyes account.

  2. Navigate to Account Settings.

  3. Select Users and Roles.

  4. Navigate to the bottom of the page and you will see User API Tokens.

  5. Select OAuth Bearer Token. Currently, Nobl9 only supports OAUTH_BEARER_TOKEN.

Adding ThousandEyes as a Data Source in the UI

To add ThousandEyes as a data source in Nobl9 using the Agent or Direct connection method, follow these steps:

  1. Navigate to Integrations > Sources.

  2. Click the plus button button.

  3. Click the ThousandEyes icon.

  4. Choose Direct or Agent, then configure the source as described below.

ThousandEyes Direct

Direct Configuration in the UI

Direct configuration for ThousandEyes requires users to enter their credentials which Nobl9 stores safely. Follow these steps to set up a direct configuration:

  1. Enter your OAuth Bearer Token.
    Refer to the Authentication section above for more details.

  2. Select a Project (mandatory).
    Specifying a Project is helpful when multiple users are spread across multiple teams or projects. When the Project field is left blank, a default value appears.

  3. Enter a Display name (optional).
    You can enter a friendly name with spaces in this field.

  4. Enter a Name (mandatory).
    The name is mandatory and can only contain lowercase, alphanumeric characters and dashes (for example, my-project-name). This field is populated automatically when you enter a display name, but you can edit the result.

  5. Enter a Description (optional).
    Here you can add details such as who is responsible for the integration (team/owner) and the purpose of creating it.

  6. Click the Add Data Source button.

ThousandEyes Agent

Agent Configuration in the UI

Follow the instructions below to configure your ThousandEyes Agent. Refer to the section above for the description of the fields.

  1. Select a Project (mandatory)

  2. Enter a Display Name.

  3. Enter a Name (mandatory).

  4. Enter a Description (optional).

  5. Click the Add Data Source button.

Deploying ThousandEyes Agent

When you add the data source, Nobl9 automatically generates a Kubernetes configuration and a Docker command line for you to use to deploy the Agent. Both of these are available in the web UI, under the Agent Configuration section. Be sure to swap in your credentials (e.g., replace <OAUTH_BEARER_TOKEN> with your actual token).

If you use Kubernetes, you can apply the supplied YAML config file to a Kubernetes cluster to deploy the Agent. It will look something like this:

# DISCLAIMER: This deployment description contains only the fields necessary for the purpose of this demo.
# It is not a ready-to-apply k8s deployment description, and the client_id and client_secret are only exemplary values.

apiVersion: v1
kind: Secret
name: nobl9-agent-nobl9-dev-thousandeyes-secret
namespace: default
type: Opaque
thousandeyes_oauth_bearer_token: "<THOUSANDEYES_OAUTH_BEARER_TOKEN>"
client_id: "unique_client_id"
client_secret: "unique_client_secret"
apiVersion: apps/v1
kind: Deployment
name: nobl9-agent-nobl9-dev-thousandeyes-agent-deployment
namespace: default
replicas: 1
nobl9-agent-name: "my-unique-agent-name"
nobl9-agent-project: "thousandeyes"
nobl9-agent-organization: "nobl9-dev"
nobl9-agent-name: "my-unique-agent-name"
nobl9-agent-project: "thousandeyes"
nobl9-agent-organization: "nobl9-dev"
- name: agent-container
image: nobl9/agent:0.33.0
memory: "350Mi"
cpu: "0.1"
- name: N9_CLIENT_ID
key: client_id
name: nobl9-agent-nobl9-dev-thousandeyes-secret
key: client_secret
name: nobl9-agent-nobl9-dev-thousandeyes-secret
key: thousandeyes_oauth_bearer_token
name: nobl9-agent-nobl9-dev-thousandeyes-secret

Creating SLOs with ThousandEyes

Creating SLOs in the UI

Follow the instructions below to create your SLOs with ThousandEyes in the UI:

  1. Navigate to Service Level Objectives.

  2. Click the plus button button.

  3. In step 1 of the SLO wizard, select the Service the SLO will be associated with.

  4. In step 2, select ThousandEyes as the Data Source for your SLO, then specify the Metric. For ThousandEyes you can use only a Threshold Metric, where a single time series is evaluated against a threshold, The ThousandEyes metric specification has two fields: testID and testType.

    • Enter a testID. It is an ID of the test configured in ThousandEyes. It is a mandatory field, and it must be a positive number.

    • Choose a testType. It is an end-to-end metric ThousandEyes metric. It is a string field. You can choose between the following ThousandEyes end-to-end metrics supported by Nobl9 (Refer to the Scope of Support section for more details):

      • Network Latency

      • Network Loss

      • Page Load

      • DOM Load Time

      • HTTP Server Response

  5. In step 3, define a Time Window for the SLO.

  6. In step 4, specify the Error Budget Calculation Method and your Objective(s).

  7. In step 5, add a Name, Description, and other details about your SLO. You can also select Alert Policies and Labels on this screen.

  8. When you’re done, click Create SLO.

SLO using ThousandEyes - YAML samples

- apiVersion: n9/v1alpha
kind: SLO
name: my-thousandeyes-web-page-load-time-rolling-occurrences
project: thousandeyes
service: thousandeyes
name: thousandeyes
- unit: Hour
count: 1
isRolling: true
budgetingMethod: Occurrences
- displayName: Good
op: lte
testID: 2280492
testType: web-page-load
value: 75
target: 0.90

Important notes:

The ThousandEyes metric specification expects two fields: testID and testType.

  • testID is an ID of the test configured in ThousandEyes. It is a mandatory field, and it must be a positive number.

  • testType is an end-to-end ThousandEyes metric. It is a string field. Enter one of the below ThousandEyes end-to-end metrics supported by Nobl9 (for more details, refer to the Scope of Support section above).

    • net-latency

    • net-loss

    • web-page-load

    • web-dom-load

    • http-response-time

When the testType field is missing in the ThousandEyes YAML configuration, net-latency value is assumed.


The testType kind is not supported by the Agent version below 0.32.0 (it works as a testID point to the net-latency test type). If you want to apply testType, update the Agent to the version above 0.33.0.

Querying the ThousandEyes Server

Nobl9 queries the ThousandEyes instance once every minute. If the Agent doesn’t collect any data in a given minute, the next query will be extended to the past two minutes.

ThousandEyes API Rate Limits

The ThousandEyes API throttles API requests using a 240 request-per-minute (per organization) limit with each page having max 1000 elements included.

Test Data | ThousandEyes Documentation

ThousandEyes Knowledge Base | ThousandEyes Documentation

ThousandEyes End-to-End Metrics | ThousandEyes Documentation