Settings for common alerting policies

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To create an alerting policy, you must describe what is to be monitored, when the alerting policy is triggered, and how you want to be notified. This page contains settings that you can use to create alerting policies. Most sections in this page have the following elements:

  • Title: Lists the relevant product name and a brief description of the alerting policy.
  • Summary: A brief description of the alerting policy. For full information, see the product documentation.
  • Steps to create an alerting policy: Outline of the steps required to create an alerting policy. For detailed information on these steps, see Creating an alerting policy.
  • New condition: These fields specify what is being monitored and how the data is aggregated.

  • Condition alert trigger: These fields specify when the alerting policy triggers. By changing the duration window, you can reduce how often a policy triggers.
When you only want to configure a chart that displays quota data, you can use the settings in the New condition table. Alerting conditions, Metrics Explorer, and the Dashboard editor use slightly different notation:
New condition dialog
field name
Dashboard editor
(Advanced tab)
Metrics Explorer
Rolling window function Alignment function Advanced options
Aligner
Rolling window Alignment period Minimum alignment period
Across time series
Time series group by
Group By Group By
Across time series
Time series aggregation
Group by function Aggregator

Billing

To be notified if your billable or forecasted charges exceed a budget, create an alert by using the Budgets and alerts page of the Google Cloud console:

  1. Sign in to the Google Cloud console:
    Sign in to Google Cloud console
  2. Open the console Navigation menu , and then select Billing. If you have more than one Cloud Billing account, then do one of the following:
    • To manage Cloud Billing for the current project, select Go to linked billing account.
    • To locate a different Cloud Billing account, select Manage billing accounts and choose the account for which you'd like to set a budget.
  3. In the Billing navigation menu, select Budgets & alerts.
  4. Click Create budget.
  5. Complete the budget dialog. In this dialog, you select Google Cloud projects and products, and then you create a budget for that combination. By default, you are notified when you reach 50%, 90%, and 100% of the budget. For complete documentation, see Set budgets and budget alerts.

BigQuery execution time

To create an alerting policy that triggers when the 99th percentile of the execution time of a BigQuery query exceeds a user-defined limit, use the following settings.

New condition
Field

Value
Resource and Metric In the Resources menu, select BigQuery Project.
In the Metric categories menu, select Query.
In the Metrics menu, select Query execution times.
Filter
Across time series
Time series group by
priority
Across time series
Time series aggregation
99th percentile
Rolling window 5 m
Rolling window function sum
Configure alert trigger
Field

Value
Condition type Threshold
Alert trigger Any time series violates
Threshold position Above threshold
Threshold value You determine this value; however, a threshold of 60 seconds is recommended.
Retest window most recent value

BigQuery usage

To create an alerting policy that triggers when the ingested BigQuery metrics exceed a user-defined level, use the following settings.

New condition
Field

Value
Resource and Metric In the Resources menu, select BigQuery Dataset.
In the Metric categories menu, select Storage.
Select a metric from the Metrics menu. Metrics specific to usage include Stored bytes, Uploaded bytes, and Uploaded bytes billed. For a full list of available metrics, see BigQuery metrics.
Filter project_id: Your Google Cloud project ID.
dataset_id: Your dataset ID.
Across time series
Time series group by
dataset_id: Your dataset ID.
Across time series
Time series aggregation
sum
Rolling window 1 m
Rolling window function mean
Configure alert trigger
Field

Value
Condition type Threshold
Alert trigger Any time series violates
Threshold position Above threshold
Threshold value You determine the acceptable value.
Retest window 1 minute

Compute Engine early boot validation

Early Boot Validation shows the pass/fail status of the early boot portion of the last boot sequence. Early boot is the boot sequence from the start of the UEFI firmware until it passes control to the bootloader.

To create an alerting policy that triggers when the early boot sequence fails for any of your Compute Engine VM instances, use the following settings.

New condition
Field

Value
Resource and Metric In the Resources menu, select VM Instance.
In the Metric categories menu, select Instance.
In the Metrics menu, select Early boot validation.
Filter status = failed
Across time series
Time series group by
status
Across time series
Time series aggregation
sum
Rolling window Use default.
Rolling window function Use default
Configure alert trigger
Field

Value
Condition type Threshold
Alert trigger Any time series violates
Threshold position Above threshold
Threshold value 0
Retest window 1 minute

Compute Engine late boot validation

Late Boot Validation shows the pass/fail status of the late boot portion of the last boot sequence. Late boot is the boot sequence from the bootloader until completion. This includes the loading of the operating system kernel.

To create an alerting policy that triggers when the late boot sequence fails for any of your Compute Engine VM instances, use the following settings.

New condition
Field

Value
Resource and Metric In the Resources menu, select VM Instance.
In the Metric categories menu, select Instance.
In the Metrics menu, select Late boot validation.
Filter status = failed
Across time series
Time series group by
status
Across time series
Time series aggregation
sum
Rolling window Use default.
Rolling window function Use default
Configure alert trigger
Field

Value
Condition type Threshold
Alert trigger Any time series violates
Threshold position Above threshold
Threshold value 0
Retest window 1 minute

Logging monthly log bytes ingested

To create an alerting policy that triggers when your monthly log bytes ingested exceeds your user-defined limit for Cloud Logging, use the following settings.

New condition
Field

Value
Resource and Metric In the Resources menu, select Global.
In the Metric categories menu, select Logs-based metric.
In the Metrics menu, select Monthly log bytes ingested.
Filter None.
Across time series
Time series aggregation
sum
Rolling window 60 m
Rolling window function max
Configure alert trigger
Field

Value
Condition type Threshold
Alert trigger Any time series violates
Threshold position Above threshold
Threshold value You determine the acceptable value.
Retest window Minimum acceptable value is 30 minutes.

Recommendations AI prediction

To set up a Recommendations AI prediction alert, use the following settings in the alerting policy.

New condition
Field

Value
Resource and Metric In the Resources menu, select Consumed API.
In the Metric categories menu, select Api.
In the Metrics menu, select Request count.
Filter service = recommendationengine.googleapis.com
method = google.cloud.recommendationengine.v1beta1.PredictionService.Predict
response_code != 200
Across time series
Time series aggregation
sum
Rolling window 1 m
Rolling window function sum
Configure alert trigger
Field

Value
Condition type Threshold
Alert trigger Any time series violates
Threshold position Above threshold
Threshold value 0
Retest window 5 minutes

Recommendations AI user event recording reduction

To set up a Recommendations AI event recording reduction alert, use the following settings in the alerting policy.

New condition
Field

Value
Resource and Metric In the Resources menu, select Consumed API.
In the Metric categories menu, select Api.
In the Metrics menu, select Request count.
Filter service = recommendationengine.googleapis.com
method = google.cloud.recommendationengine.v1beta1.PredictionService.CollectUserEvent
response_code != 200
Across time series
Time series aggregation
sum
Rolling window 1 m
Rolling window function sum
Configure alert trigger
Field

Value
Condition type Metric absence
Alert trigger Any time series violates
Trigger absence time 10 minutes

Spanner high priority CPU usage

To create an alerting policy that triggers when your high priority cpu utilization for Cloud Spanner is above a recommended threshold, use the following settings.

New condition
Field

Value
Resource and Metric In the Resources menu, select Cloud Spanner Instance.
In the Metric categories menu, select Instance.
In the Metrics menu, select CPU Utilization by priority.

(The metric.type is spanner.googleapis.com/instance/cpu/utilization_by_priority).
Filter instance_id = YOUR_INSTANCE_ID
priority = high
Across time series
Time series group by
location for multi-region instances;
leave it blank for regional instances.
Across time series
Time series aggregation
sum
Rolling window 10 m
Rolling window function mean
Configure alert trigger
Field

Value
Condition type Threshold
Alert trigger Any time series violates
Threshold position Above threshold
Threshold value 45% for multi-region instances;
65% for regional instances.
Retest window 10 minutes

Spanner 24 hour rolling usage

To create an alerting policy that triggers when the 24 hour rolling average of your cpu utilization for Cloud Spanner is above a recommended threshold, use the following settings.

New condition
Field

Value
Resource and Metric In the Resources menu, select Cloud Spanner Instance.
In the Metric categories menu, select Instance.
In the Metrics menu, select Smoothed CPU utilization.

(The metric.type is spanner.googleapis.com/instance/cpu/smoothed_utilization).
Filter instance_id = YOUR_INSTANCE_ID
Across time series
Time series aggregation
sum
Rolling window 10 m
Rolling window function mean
Configure alert trigger
Field

Value
Condition type Threshold
Alert trigger Any time series violates
Threshold position Above threshold
Threshold 90%
Retest window 10 minutes

Spanner storage

To create an alerting policy that triggers when your storage for your Cloud Spanner instance is above a recommended threshold, use the following settings.

New condition
Field

Value
Resource and Metric In the Resources menu, select Cloud Spanner Instance.
In the Metric categories menu, select Instance.
In the Metrics menu, select Storage used.

(The metric.type is spanner.googleapis.com/instance/storage/used_bytes).
Filter instance_id = YOUR_INSTANCE_ID
Across time series
Time series aggregation
sum
Rolling window 10 m
Rolling window function max
Configure alert trigger
Field

Value
Condition type Threshold
Condition triggers if Any time series violates
Threshold position Above threshold
Threshold value Set the threshold to 75% of the maximum storage per node, multiplied by the number of nodes. For the current node limits, see Cloud Spanner Quotas & limits.
Retest window 10 minutes

Trace over quota on API usage

To create an alerting policy that triggers when your monthly Cloud Trace spans ingested exceeds your quota, use the following settings.

New condition
Field

Value
Resource and Metric In the Resources menu, select Consumed API.
In the Metric categories menu, select Api.
In the Metrics menu, select Request count.

(The metric.type is serviceruntime.googleapis.com/api/request_count).
Filter service = cloudtrace.googleapis.com
response_code = 429
Across time series
Time series aggregation
sum
Rolling window 1 m
Rolling window function sum
Configure alert trigger
Field

Value
Condition type Threshold
Alert trigger Any time series violates
Threshold position Above threshold
Threshold value 0
Retest window 1 minute

Trace monitor monthly span-usage

To create an alerting policy that triggers when your monthly Cloud Trace spans ingested exceeds a user-defined limit, use the following settings.

New condition
Field

Value
Resource and Metric In the Resources menu, select Global.
In the Metric categories menu, select Billing.
In the Metrics menu, select Monthly trace spans ingested.
Filter
Across time series
Time series aggregation
sum
Rolling window 60 m
Rolling window function max
Configure alert trigger
Field

Value
Condition type Threshold
Alert trigger Any time series violates
Threshold position Above threshold
Threshold value You determine the acceptable value.
Retest window Minimum acceptable value is 30 minutes.

Trace export errors

To create an alerting policy that triggers if there are errors exporting Cloud Trace data to BigQuery, use the following settings.

New condition
Field

Value
Resource and Metric In the Resources menu, select Cloud Trace.
In the Metric categories menu, select Bigquery_export.
In the Metrics menu, select Spans Exported to BigQuert.
Filter status != ok
Across time series
Time series group by
status
Across time series
Time series aggregation
sum
Rolling window 1 m
Rolling window function rate
Configure alert trigger
Field

Value
Condition type Threshold
Alert trigger Any time series violates
Threshold position Above threshold
Threshold value 0
Retest window 1 minute

Uptime check monitoring

To create an alerting policy for an uptime check, or to create a chart that displays the success or latency status of an uptime check, see Alerting on uptime checks.