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Google BigQuery

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Nobl9's integration with Google BigQuery enables SLO measurement using data stored in BigQuery tables. This integration allows organizations to define service level objectives based on metrics queried directly from BigQuery datasets and get valuable business insights.

Google BigQuery parameters and supported features in Nobl9
General support:
Release channel: Stable, Beta
Connection method: Agent, Direct
Replay and SLI Analyzer: Not supported
Event logs: Supported
Query checker: Not supported
Query parameters retrieval: Supported
Timestamp cache persistence: Supported
Query parameters:
Query interval: 1 min
Query delay: 0 sec
Jitter: 15 sec
Timeout: 30 sec
Agent details and minimum required versions for supported features:
Plugin name: n9bigquery
Query delay environment variable: BIGQUERY_QUERY_DELAY
Query parameters retrieval: 0.73.2
Timestamp cache persistence: 0.65.0

Creating SLOs with Google BigQuery​

Nobl9 Web​

Follow the instructions below to create your SLOs with Google BigQuery in the Nobl9 web application:

  1. Navigate to Service Level Objectives.

  2. Click .

  3. Select a Service.
    It will be the location for your SLO in Nobl9.

  4. Select your Google BigQuery data source.

  5. Enter Project ID: a unique identifier of your required Google Cloud project.

    • Can contain 6-30 lowercase letters, digits, or hyphens.
      For example, bigquery://project

  6. Select a Location of the BigQuery dataset that contains the data you need to read.

  7. Metric refers to the way of calculating and interpreting calculate and interpret data from your data source.
    • Threshold metric is defined by a single numerical value (the threshold) that separates satisfactory performance from unsatisfactory performance. It's represented by a single time series evaluated against the threshold.
    • Ratio metric expresses the performance as a fraction or proportion, typically by dividing the number of successful events by the total number of potential events (successes + failures). It's represented by two-time series for comparison for good events and total events.
      For ratio metrics, select the Data count method.

      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.

  8. Enter your SQL query.

    Click to open query samples
    Threshold metric
    SELECT response_time AS n9value, created AS n9date FROM `my-project-id` WHERE created BETWEEN DATETIME(@n9date_from) AND DATETIME(@n9date_to)`ORDER BY n9date
    Ratio metric, numerator
    SELECT http_code AS n9value, created AS n9date FROM `my-project-id` WHERE http_code = 200 AND created BETWEEN DATETIME(@n9date_from)  AND DATETIME(@n9date_to) ORDER BY n9date
    Ratio metric, denominator
    SELECT http_code AS n9value, created AS n9date FROM `my-project-id` WHERE created BETWEEN DATETIME(@n9date_from) AND DATETIME(@n9date_to) ORDER BY n9date
  1. Define the Time window for your SLO:
  2. Configure the Error budget calculation method and Objectives:
    • Occurrences method counts good attempts against the count of total attempts.
    • Time Slices method measures how many good minutes were achieved (when a system operates within defined boundaries) during a time window.
    • You can define up to 12 objectives for an SLO.

      • Similar threshold values for objectives
      To use similar threshold values for different objectives in your SLO, we recommend differentiating them by setting varying decimal points for each objective.
      For example, if you want to use threshold value 1 for two objectives, set it to 1.0000001 for the first objective and to 1.0000002 for the second one.
  3. Add the Display name, Name, and other settings for your SLO:
    • Name identifies your SLO in Nobl9. After you save the SLO, its name becomes read-only.
      Use only lowercase letters, numbers, and dashes.
    • Select No data anomaly alert to receive notifications when your SLO stops reporting data for a specified period:
      • Choose up to five supported Alert methods.
      • Specify the delay period before Nobl9 sends an alert about the missing data.
        From 5 minutes to 31 days. Default: 15 minutes
    • Add alert policies, labels, and links, if required.
      Limits per SLO: 20 alert policies or links, 30 labels.
  4. Click CREATE SLO.

    5. SLO configuration use case
    Check the SLO configuration use case for a real-life SLO example.

YAML​

Sample Google BigQuery threshold SLO
apiVersion: n9/v1alpha
kind: SLO
metadata:
  name: api-server-slo
  displayName: API Server SLO
  project: default
  labels:
    area:
      - latency
      - slow-check
    env:
      - prod
      - dev
    region:
      - us
      - eu
    team:
      - green
      - sales
  annotations:
    area: latency
    env: prod
    region: us
    team: sales
spec:
  description: Example BigQuery SLO
  indicator:
    metricSource:
      name: big-query
      project: default
      kind: Agent
  budgetingMethod: Occurrences
  objectives:
    - displayName: Good response (200)
      value: 200
      name: ok
      target: 0.95
      rawMetric:
        query:
          bigQuery:
            query: >-
              SELECT response_time AS n9value, created AS n9date FROM
              `api-server-256112.metrics.http_response` WHERE created BETWEEN
              DATETIME(@n9date_from) AND DATETIME(@n9date_to)`
            projectId: api-server-256112
            location: US
      op: lte
      primary: true
  service: api-server
  timeWindows:
    - unit: Month
      count: 1
      isRolling: false
      calendar:
        startTime: '2022-12-01 00:00:00'
        timeZone: UTC
  alertPolicies:
    - fast-burn-5x-for-last-10m
  attachments:
    - url: https://docs.nobl9.com
      displayName: Nobl9 Documentation
  anomalyConfig:
    noData:
      alertMethods:
        - name: slack-notification
          project: default
      alertAfter: 1h
Click to open field reference
FieldTypeDescription
apiVersion
mandatory
stringAPI version. Use n9/v1alpha
kind
mandatory
stringThe resource type. Use SLO
Metadata
metadata.name
mandatory
stringName identifier for the SLO. Use only lowercase alphanumeric characters
metadata.displayNamestringUser-friendly SLO name
metadata.project
mandatory
stringThe name identifier of the project where you need to host your SLO
metadata.labelsobject (map: string[])Grouping labels for filtering or viewing
metadata.annotationsobject (map: string)Flat string annotations
Spec
spec.descriptionstringSLO description
spec.indicator.metricSource.name
mandatory
stringData source name
spec.indicator.metricSource.project
mandatory
stringProject containing the data source
spec.indicator.metricSource.kind
mandatory
stringData source connection method. Can be Agent or Direct
spec.budgetingMethod
mandatory
enumError budget calculation method. Can be Occurrences or Time slices
spec.objectives
mandatory
arrayYour SLO objective definition, up to 12 objectives per SLO.
spec.objectives[].displayNamestringUser-friendly objective name
spec.objectives[].value
mandatory
numberData point values that is considered "good" (e.g., 200.0).
In SLOs with two or more objectives, keep each objective's value unique.
In ratio (count) metrics, value is retained for legacy purposes.
spec.objectives[].name
mandatory
stringName identifier for this objective
spec.objectives[].op
mandatory
string (enum)Operator for objective. One of:
lte (less than or equal to)
lt (less than)
gte (greater than or equal to)
gt (greater than)
spec.objectives[].target
mandatory
floatThe percentage of the good minutes or occurrences that must meet the desired performance (e.g., is the target is 0.95, the good performance is expected to be observed in at least 95% of the time window)
spec.objectives[].rawMetric/.countMetric
mandatory
objectThe metric type indicator. Set:
rawMetric for a threshold metric
countMetric for a ratio metric.
A ratio metric requires the additional fields:
countMetric.incremental (boolean) the data count method
countMetric.good/.bad and countMetric.total a numerator and denominator queries
spec.objectives[].countMetric.incremental
mandatory
booleanThe data count method for a ratio (countMetric) metric type
spec.objectives[].primarybooleanThe indicator of a primary SLO objective
spec.service
mandatory
stringThe name identifier of a service to host this SLO. The service must exist in the project specified in metadata.project
spec.timeWindows
mandatory
arrayDefines SLO time window for error budget calculation. Set:
isRolling: true for the rolling time window type
isRolling: false for the calendar-aligned type
spec.timeWindows.unit
mandatory
integerThe time window units. One of:
Day | Hour | Minute for the rolling time window
Year | Quarter | Month | Week | Day for the calendar-aligned time window
spec.timeWindows.count
mandatory
integerThe number of units in a time window
spec.timeWindows.startTimestringMandatory for calendar-aligned time windows. Date and time in the format YYYY-MM-DDTHH:mm:ss
spec.timeWindows.timeZonestringMandatory for calendar-aligned time-windows. A valid IANA Time Zone Database name
spec.timeWindows.isRolling
mandatory
boolean
true for the rolling time window type
false for the calendar-aligned type
spec.alertPoliciesarrayThe name identifiers of alert policies to be linked to this SLO (must be from the same project as the SLO). Up to 20 alert policies per SLO.
spec.attachmentsarrayLinks to any additional attributes of this SLO
spec.anomalyConfigobjectSettings for a manual no data anomaly detection rule
spec.noData.alertMethodsarrayList of alert methods for no-data anomaly. Up to five alert methods per SLO. Every alert method must have the name and project fields
spec.noData.alertAfterstringWaiting time before sending a no-data notification. Must be 5m to 31d.
Default: 15m
Source-specific fields
bigquery.query
mandatory
stringYour SQL query. For plugin performance optimization, include 'ORDER by n9date' in your query to define the sorting order. With it, the plugin can retrieve and process data in batches, reducing overall query execution time
bigquery.projectId
mandatory
stringA unique identifier of your required Google Cloud project. Must be a unique string of 6-30 lowercase alphanumeric characters, including hyphens (-)
bigquery.location
mandatory
stringA Google BigQuery dataset to query against

Query samples​

Threshold metric sample:

SELECT
response_time AS n9value,
created AS n9date
FROM `my-google-cloud-project`
WHERE created
BETWEEN DATETIME(@n9date_from)
AND DATETIME(@n9date_to)
ORDER BY n9date

The n9value must be an alias for a numeric field. It's the DATETIME format representation of a date. Conditions are required.

For example, a WHERE or HAVING clause narrows the query to a DATETIME(@n9date_from) and DATETIME(@n9date_to) timeframe.

The queries are validated against columns or aliases.

Data type consistency

When narrowing the query to the interval by the DATETIME(@n9date_from) and DATETIME(@n9date_to) parameters, the data type of the value you're comparing must be the same. For example,

WHERE created
BETWEEN DATETIME(@n9date_from)
AND DATETIME(@n9date_to)

Since the parameters are DATETIME, the created value must also be DATETIME.

Sample query results:

n9value | n9date
256     | 2021-06-15T01:00:47.754070
259     | 2021-06-14T16:35:36.754070
250     | 2021-06-14T17:27:15.754070

Google BigQuery API rate limits​

The following rate limits apply to the BigQuery API:

  • Query jobs. See Quotas and Limits reference.

  • Point density. Point density greater than 1000 data points per minute leads to errors. To address this, add point aggregation to your query.

Google BigQuery cost optimization

BigQuery pricing is based on bytes read by the query.

Since BigQuery queries must contain the where clause with date between filter, as required by the Nobl9 agent, your can use partitioning on the date_col column to reduce the number of bytes read. For example,

WHERE
{date_col} BETWEEN
DATETIME(@n9date_from)
AND DATETIME(@n9date_to)

Learn more about storage and query costs estimation and partitioned tables.

Check out these related guides and references:
Adding Google BigQuery as a data sourceAdding data sourcesGetting StartedBigQuery docsQueriesBigQuery docsQuotas and LimitsBigQuery docsCreating SLOs via TerraformTerraform
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