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ThousandEyes

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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 the following metrics:

  • 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.

  • HTTP Server Availability - is the availability for a given agent. For HTTP Server Availability, Nobl9 receives status codes of an http response, for example, 200, 201, 400, or 501.

    warning

    When there are multiple ThousandEyes agents, Nobl9 can receive multiple HTTP response status codes in a single request. In this situation, Nobl9 ingests only the highest status code.

  • HTTP Server Throughput - is the Wire Size divided by the Receive Time (in bits per second). For more information, refer to the ThousandEyes documentation.

  • HTTP Server Total Time - time (in milliseconds) of ThousandEyes agent receiving the last byte of your server's response.

  • DNS Server Resolution Time - time (in milliseconds) of ThousandEyes agent receiving the response from the DNS server about your domain.

  • DNS DNSSEC Valid - 1 if keychain for a domain record is valid, 0 otherwise.

Each measurement is obtained per ThousandEyes test interval.

note

For details about all ThousandEyes metric types, check ThousandEyes Knowledge Base | ThousandEyes documentation and ThousandEyes Test Data | ThousandEyes documentation.

The following table is an overview of the supported ThousandEyes tests and corresponding Nobl9 names:

NameResponse
property read		Nobl9 YAML nameAggregation*Minimum agent (supported channel)
Network >
End-to-End metrics		avgLatencynet-latencymean0.33.0 (stable, beta)
Network >
End-to-End metrics		Lossnet-lossmean0.33.0 (stable, beta)
Web >
Page load		pageLoadTimeweb-page-loadmean0.33.0 (stable, beta)
Web >
Page load		domLoadTimeweb-dom-loadmean0.33.0 (stable, beta)
Web >
HTTP server		responseTimehttp-response-timemean0.33.0 (stable, beta)
Web >
HTTP server		responseCodehttp-server-availabilitymax0.52.0 (stable, beta)
Web >
HTTP server		throughputhttp-server-throughputmean0.52.0 (stable, beta)
Web >
HTTP server		totalTimehttp-server-total-timemean0.68.0-beta01 (beta) 0.67.2 (stable)
DNS >
Server metric		resolutionTimedns-server-resolution-timemean0.68.0-beta01 (beta) 0.67.2 (stable)
DNS >
DNSSEC		validdns-dnssec-validlogical conjunction0.68.0-beta01 (beta) 0.67.2 (stable)

*) If your test returns more than one result per round.

warning

Whenever your ThousandEyes SLO has incompatible data source version/channel, the SLO config won't be served to your data source.

Authentication​

Nobl9 requires OAUTH_BEARER_TOKEN to communicate with ThousandEyes.

To get the OAUTH_BEARER_TOKEN:

  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​

To ensure data transmission between Nobl9 and your data source, it may be necessary to list Nobl9 IP addresses as trusted.

IP addresses to add to your allowlist:
  • 18.159.114.21
  • 18.158.132.186
  • 3.64.154.26
⚠ Applies to app.nobl9.com only. In all other cases, contact Nobl9 support.

You can add the Thousandeyes data source using the direct or agent connection methods. For both methods, start with these steps:

  1. Navigate to Integrations > Sources.
  2. Click .
  3. Click the relevant Source icon.
  4. Choose a relevant connection method (Agent or Direct), 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. Select one of the following Release Channels:
    • The stable channel is fully tested by the Nobl9 team. It represents the final product; however, this channel does not contain all the new features of a beta release. Use it to avoid crashes and other limitations.
    • The beta channel is under active development. Here, you can check out new features and improvements without the risk of affecting any viable SLOs. Remember that features in this channel may be subject to change.

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

  1. Select a Project.
    Specifying a project is helpful when multiple users are spread across multiple teams or projects. When the Project field is left blank, Nobl9 uses the default project.
  2. Enter a Display Name.
    You can enter a user-friendly name with spaces in this field.
  3. Enter a Name.
    The name is mandatory and can only contain lowercase, alphanumeric characters, and dashes (for example, my-project-1). Nobl9 duplicates the display name here, transforming it into the supported format, but you can edit the result.
  4. Enter a Description.
    Here you can add details such as who is responsible for the integration (team/owner) and the purpose of creating it.
  5. Specify the Query delay to set a customized delay for queries when pulling the data from the data source.
    • The default value in ThousandEyes integration for Query delay is 1 minute.
    info
    Changing the Query delay may affect your SLI data. For more details, check the Query delay documentation.
  6. Click Add Data Source.

Direct using CLI - YAML​

The YAML for setting up a direct connection to ThousandEyes looks like this:

apiVersion: n9/v1alpha
kind: Direct
metadata:
  name: thousandeyes-direct
  displayName: Thousandeyes direct
  project: thousandeyes-direct
spec:
  description: Direct integration with 1000 eyes
  sourceOf:
    - Metrics
    - Services
  releaseChannel: beta # string, one of: beta || stable
  queryDelay:
      unit: Minute # string, one of: Second || Minute
      value: 720 # numeric, must be a number less than 1440 minutes (24 hours)
  logCollectionEnabled: false # boolean, defaults to 'false'. Set to true if you'd like your source to collect logs. It's a beta functionality available only through direct release channel. Reach out to support@nobl9.com to activate it.
  thousandEyes:
    oauthBearerToken: "" #secret
FieldTypeDescription
queryDelay.unit
mandatory
enumSpecifies the unit for the query delay. Possible values: Second | Minute.
• Check query delay documentation for default unit of query delay for each source.
queryDelay.value
mandatory
numericSpecifies the value for the query delay.
• Must be a number less than 1440 minutes (24 hours).
• Check query delay documentation for default unit of query delay for each source.
logCollectionEnabled
optional
booleanOptional. Defaults to false. Set to true if you'd like your direct to collect event logs. Beta functionality available only through direct release channel. Reach out to support@nobl9.com to activate it.
releaseChannel
mandatory
enumSpecifies the release channel. Accepted values: beta | stable.
Source-specific fields
thousandEyes.oauthBearerToken
mandatory
string, secretRequired to communicate with ThousandEyes. See authentication section above for more details.

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 one of the following Release Channels:
    • The stable channel is fully tested by the Nobl9 team. It represents the final product; however, this channel does not contain all the new features of a beta release. Use it to avoid crashes and other limitations.
    • The beta channel is under active development. Here, you can check out new features and improvements without the risk of affecting any viable SLOs. Remember that features in this channel may be subject to change.
  1. Enter a Project.
  2. Enter a Display Name.
  3. Enter a Name.
  4. Create a Description.
  5. Customize the Query Delay.
  6. Click Add Data Source.

Agent using CLI - YAML​

The YAML for setting up an agent connection to ThousandEyes looks like this:

apiVersion: n9/v1alpha
kind: Agent
metadata:
  name: thousandeyes
  displayName: ThousandEyes
  project: thousandeyes
spec:
  sourceOf:
    - Metrics
    - Services
  releaseChannel: beta
  queryDelay:
      unit: Minute
      value: 720
  thousandEyes: {}

FieldTypeDescription
queryDelay.unit
mandatory
enumSpecifies the unit for the query delay. Possible values: Second | Minute.
• Check query delay documentation for default unit of query delay for each source.
queryDelay.value
mandatory
numericSpecifies the value for the query delay.
• Must be a number less than 1440 minutes (24 hours).
• Check query delay documentation for default unit of query delay for each source.
releaseChannel
mandatory
enumSpecifies the release channel. Accepted values: beta | stable.
Source-specific fields
warning

You can deploy only one agent in one YAML file by using the sloctl apply command.

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
metadata:
  name: nobl9-agent-nobl9-dev-thousandeyes-secret
  namespace: default
type: Opaque
stringData:
  thousandeyes_oauth_bearer_token: "<THOUSANDEYES_OAUTH_BEARER_TOKEN>"
  client_id: "unique_client_id"
  client_secret: "unique_client_secret"
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: nobl9-agent-nobl9-dev-thousandeyes-agent-deployment
  namespace: default
spec:
  replicas: 1
  selector:
    matchLabels:
      nobl9-agent-name: "my-unique-agent-name"
      nobl9-agent-project: "thousandeyes"
      nobl9-agent-organization: "nobl9-dev"
  template:
    metadata:
      labels:
        nobl9-agent-name: "my-unique-agent-name"
        nobl9-agent-project: "thousandeyes"
        nobl9-agent-organization: "nobl9-dev"
    spec:
      containers:
        - name: agent-container
          image: nobl9/agent:0.73.2
          resources:
            requests:
              memory: "350Mi"
              cpu: "0.1"
          env:
            - name: N9_CLIENT_ID
              valueFrom:
                secretKeyRef:
                  key: client_id
                  name: nobl9-agent-nobl9-dev-thousandeyes-secret
            - name: N9_CLIENT_SECRET
              valueFrom:
                secretKeyRef:
                  key: client_secret
                  name: nobl9-agent-nobl9-dev-thousandeyes-secret
            - name: THOUSANDEYES_OAUTH_BEARER_TOKEN
              valueFrom:
                secretKeyRef:
                  key: thousandeyes_oauth_bearer_token
                  name: nobl9-agent-nobl9-dev-thousandeyes-secret
            # The N9_METRICS_PORT is a variable specifying the port to which the /metrics and /health endpoints are exposed.
            # The 9090 is the default value and can be changed.
            # If you don’t want the metrics to be exposed, comment out or delete the N9_METRICS_PORT variable.
            - name: N9_METRICS_PORT
              value: "9090"

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 .

  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 a ThousandEyes metric. You can choose between the following ThousandEyes 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

      • HTTP Server Availability

      • HTTP Server Throughput

  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
  metadata:
    name: my-thousandeyes-web-page-load-time-rolling-occurrences
    project: thousandeyes
  spec:
    service: thousandeyes
    indicator:
      metricSource:
        name: thousandeyes
    timeWindows:
      - unit: Hour
        count: 1
        isRolling: true
    budgetingMethod: Occurrences
    objectives:
      - displayName: Good
        op: lte
        rawMetric:
          query:
            thousandEyes:
              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 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

    • http-server-availability

    • http-server-throughput

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

caution

If you want to apply http-server-availability and http-server-throughput as testType, update your agent to the 0.52.0 version.

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

Agent metrics

Creating SLOs via Terraform

Creating agents via Terraform

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