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Google Cloud Monitoring

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Google Cloud Monitoring (GCM) provides visibility into the performance, uptime, and overall health of cloud-powered applications. It collects metrics, events, and metadata from Google Cloud, hosted uptime probes, and application instrumentation.

Authentication​

Google Cloud Monitoring authentication requires the user’s credentials to be entered in Nobl9. Users can retrieve their authentication credentials from the Google Cloud Platform (GCP) in the form of a Service account key file. For details on how to get your Service account key file, refer to the Getting Started with Authentication | Google Cloud documentation.

For the direct connection to GCM, the contents of the downloaded Service account key file must be uploaded into the Nobl9 UI. This ensures direct integration with the GCM APIs to retrieve the data, leveraging the SaaS-to-SaaS infrastructure in Nobl9.

For the agent connection, you need to copy and paste your credentials from your credentials.json file and pass those when invoking the agent. Nobl9 agent can use Workload Identity in GCP (Google Cloud Platform) in GKE (Google Kubernetes Engine). For more information, refer to the Deploying the Google Cloud Monitoring agent section.

note

Your user account must have access to one of the following OAuth scopes:

Adding Google Cloud Monitoring 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 Google Cloud Monitoring 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.

Google Cloud Monitoring direct​

Direct configuration in the UI​

A direct connection to Google Cloud Monitoring requires users to enter their credentials which Nobl9 stores safely. To set up this type of connection:

  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. Upload your Service Account Key File to authenticate with GCP (mandatory).
    Retrieve your authentication credentials from the Google Cloud Platform. The file must be in JSON format. For more information, refer to the Getting Started with Authentication | Google Cloud documentation or the Authentication section above.

  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 Google Cloud Monitoring integration for Query delay is 2 minutes.
    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 Google Cloud Monitoring looks like this:

apiVersion: n9/v1alpha
kind: Direct
metadata:
  name: gcm-direct
  project: default
spec:
  gcm:
    serviceAccountKey: |-
     {
      # secret, copy and paste your credentials from the credentials.json file
     }
  sourceOf:
  - Metrics
  releaseChannel: beta
  queryDelay:
      unit: Minute
      value: 720
  logCollectionEnabled: false
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
gcm.serviceAccountKey
mandatory
stringCopy and paste your credentials from the `credentials.json` file. See authentication for more details.

Google Cloud Monitoring agent​

Agent configuration in the UI​

Follow the instructions below to set up an agent connection. Refer to the previous section for the descriptions 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 Google Cloud Monitoring looks like this:

apiVersion: n9/v1alpha
kind: Agent
metadata:
  name: gcm
  displayName: Google Cloud Monitoring # optional
spec:
  description: GCM agent # optional
  sourceOf:
    - Metrics
  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)
  gcm: {}
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.
warning

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

Deploying the Google Cloud Monitoring 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.

warning

Nobl9 agent can use Workload Identity in GCP (Google Cloud Platform) in GKE (Google Kubernetes Engine). As such, the N9_GCP_CREDENTIALS_PATH environment variable has been changed to GOOGLE_APPLICATION_CREDENTIALS. For more information, refer to the Getting started with authentication | Google Cloud documentation.

If you use Kubernetes, you can apply the supplied YAML config file to a Kubernetes cluster to deploy the agent. Remember to swap in your credentials, for example, copy and paste your credentials from the ServiceAccount Key credentials.json file. 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-gcm-gcm
  namespace: default
type: Opaque
stringData:
  client_id: #client_id
  client_secret: #client_secret
data:
  credentials.json: |-
    `CREDENTIALS`
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: nobl9-agent-nobl9-dogfood-default-gcm-test
  namespace: default
spec:
  replicas: 1
  selector:
    matchLabels:
      nobl9-agent-name: gcm-test
      nobl9-agent-project: default
  template:
    metadata:
      labels:
        nobl9-agent-name: gcm-test
        nobl9-agent-project: default
    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-dogfood-default-gcm-test
            - name: N9_CLIENT_SECRET
              valueFrom:
                secretKeyRef:
                  key: client_secret
                  name: nobl9-agent-nobl9-dogfood-default-gcm-test
            # 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"
            # To use Workload Identity in Kubernetes Cluster in Google Cloud Platform,
            # comment out or delete the GOOGLE_APPLICATION_CREDENTIALS environment variable
            # and follow the instructions described here https://cloud.google.com/kubernetes-engine/docs/how-to/workload-identity

            - name: GOOGLE_APPLICATION_CREDENTIALS
              value: "/var/gcp/credentials.json"

            # N9_ALLOWED_URLS is an optional safety parameter that limits the URLs that an Agent is able to query
            # for metrics. URLs defined in the Nobl9 app are prefix-compared against the N9_ALLOWED_URLS list of
            # comma separated URLs.
            # - name: N9_ALLOWED_URLS
            #   value: "http://172.16.0.2/api/v1/query,http://172.16.0.3"
          volumeMounts:
          - name: gcp-credentials
            mountPath: "/var/gcp"
            readOnly: true
      volumes:
      - name: gcp-credentials
        secret:
          secretName: nobl9-agent-nobl9-dogfood-default-gcm-test

Creating SLOs with Google Cloud Monitoring​

Creating SLO in the UI​

Follow the instructions below to create your SLOs with Google Cloud Monitoring in the Nobl9 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 Google Cloud Monitoring as the data source for your SLO.

  5. Enter a Project ID.

  6. Specify the Metric. You can choose either a Threshold Metric, where a single time series is evaluated against a threshold or a Ratio Metric, which allows you to enter two time series to compare (for example, a count of good requests and total requests).

    1. Choose the Data Count Method for your ratio metric:
    • Non-incremental: counts incoming metric values one-by-one. So the resulting SLO graph is pike-shaped.
    • Incremental: counts the incoming metric values incrementally, adding every next value to previous values. It results in a constantly increasing SLO graph.

  7. Specify Query or a Good Query and Total Query for the metric you selected. Your query must follow the Monitoring Query Language syntax.

    • Each query must return only one metric and one time series.
    • Since Nobl9 asks for data every 1 minute, we recommend setting the period for the align delta function to 1 minute, i.e. align delta(1m).
      As a result, Nobl9 receives the difference in a given minute and records it as an SLI.
    • Nobl9 processes a single dataset at a time and doesn't aggregate GCM metrics.
      Make sure your group_by aggregator points to the single dataset—exactly that one you want to observe.
      You can find the available groups on your Google Cloud Observability Monitoring dashboard > Metrics explorer.
Example query
"fetch consumed_api
| metric 'serviceruntime.googleapis.com/api/request_latencies'
| filter (resource.service == 'monitoring.googleapis.com')
| align delta(1m)
| every 1m
| group_by [resource.service],
[value_request_latencies_mean: mean(value.request_latencies)]"
SLI values for good and total
When choosing the query for the ratio SLI (countMetrics), keep in mind that the values ​​resulting from that query for both good and total:
  • Must be positive.
  • While we recommend using integers, fractions are also acceptable.
    • If using fractions, we recommend them to be larger than 1e-4 = 0.0001.
  • Shouldn't be larger than 1e+20.

  1. In step 3 of the SLO wizard, define a Time Window for the SLO.

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

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

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

SLOs using Google Cloud Monitoring - YAML samples​

Here’s an example of Google Cloud Monitoring using rawMetric (threshold metric):

apiVersion: n9/v1alpha
kind: SLO
metadata:
  name: gcm-latency-mean-threshold
  project: my-project
spec:
  service: my-service
  indicator:
    metricSource:
      name: gcm
      project: my-project
    rawMetric:
      gcm:
        projectId: my-project-id
        query: "fetch consumed_api
                | metric 'serviceruntime.googleapis.com/api/request_latencies'
                | filter (resource.service == 'monitoring.googleapis.com')
                | align delta(1m)
                | every 1m
                | group_by [resource.service],
                    [value_request_latencies_mean: mean(value.request_latencies)]"
  timeWindows:
    - unit: Day
      count: 1
      calendar:
        startTime: 2022-01-21 12:30:00 # date with time in 24h format
        timeZone: America/New_York # name as in IANA Time Zone Database
  budgetingMethod: Occurrences
  objectives:
    - displayName: Healthy
      value: 40
      op: lte
      target: 0.99
    - displayName: Slower
      value: 41
      op: gte
      target: 0.98
    - displayName: Critical
      value: 100
      op: gte
      target: 0.95

Querying the Google Cloud Monitoring server​

Nobl9 queries the Google Cloud Monitoring server using the projects.timeSeries.query API every 60 seconds. The number of data points returned is dependent on the amount of data Google Cloud Monitoring can return.

Google Cloud Monitoring API rate limits​

To verify the limits to API usage, go to the Quotas dashboard in the GCM UI. For an API, click the All Quotas button to see your quota.

Getting Started with Authentication | Google Cloud documentation

Creating and Managing Projects | Google Cloud documentation

Monitoring Query Language reference | Google Cloud documentation

projects.timeSeries.query | Google Cloud documentation

Agent metrics

Creating SLOs via Terraform

Creating agents via Terraform

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