Snowflake - API Based

Overview

The API-based Snowflake integration replaces the Datadog Agent-based Snowflake integration, and offers additional functionality. After setting up the API-based Snowflake integration, it is recommended to uninstall the Agent-based Snowflake integration to reduce API call volume to Snowflake.

It can be difficult to effectively monitor and optimize Snowflake infrastructure and data retrieval. Issues arise which may lead to inefficient resource utilization, higher costs, and a degraded customer experience.

With Datadog’s Snowflake integration, you can uncover long-running queries to improve performance and reduce costs, identify real time security threats, and monitor your Snowpark workloads.

After parsing your Snowflake data, Datadog populates the out-of-the-box overview dashboard with insights across all your collected resources. It also offers recommended monitors to help you get started on alerting on failed Snowpark executions or an abnormal amount of login attempts.

Note: Metrics are collected with queries to Snowflake. Queries made by the Datadog integration are billable by Snowflake.

Setup

Installation

No installation steps are required.

Configuration

Connect your Snowflake account

  1. Find your Snowflake account URL.
The account menu with the copy account URL option selected in the Snowflake UI
  1. Enable the resources you are interested in collecting:
Account and Organization usage metrics

The table below describes the types of metrics collected and their associated metric prefixes.

TypeDescriptionMetric prefixes collected
Account usageStorage usage, credit consumption, and query metrics at an account level.
Collected hourly.
snowflake.auto_recluster
snowflake.billing
snowflake.data_transfer
snowflake.logins
snowflake.pipe
snowflake.query
snowflake.replication
snowflake.storage
snowflake.storage.database
snowflake.storage.table
Organization usageCredit consumption, data transfer history, and budget metrics at an organization level.
Collected daily.
snowflake.organization
Logs

The table below describes the types of logs collected and which Snowflake tables are included.

TypeDescriptionSnowflake tables included
Query historyHistory of query executions.
Query history logs can be enriched with access history logs to provide more insight into how data is used through queries and its lineage.
SNOWFLAKE.ACCOUNT_USAGE.QUERY_HISTORY
Login historyHistory of Snowflake logins.
Utilize these logs with Cloud SIEM to better detect and respond to security threats in your environment.
SNOWFLAKE.ACCOUNT_USAGE.LOGIN_HISTORY
Event tableMessage and event data generated by your functions and procedures.
Requires additional GRANT privileges.
Your custom event table
Cloud Cost Management

Enable Cloud Cost Management to receive Snowflake cost metrics aggregated from the SNOWFLAKE.ORGANIZATION_USAGE.USAGE_IN_CURRENCY_DAILY table. You can use these metrics with Cloud Cost Management to gain additional insight into your cost and usage.

  1. Create a Datadog-specific role and user to monitor Snowflake. Execute the series of commands below in your Snowflake environment to create a user accessible for Datadog.
-- Create a new role intended to monitor Snowflake usage. The name of the role is customizable.
create role DATADOG;

-- Grant privileges on the SNOWFLAKE database to the new role.
grant imported privileges on database SNOWFLAKE to role DATADOG;
                
-- Grant usage to your default warehouse to the role DATADOG.
grant usage on warehouse <WAREHOUSE> to role DATADOG;

-- Grant ORGANIZATION_BILLING_VIEWER to the new role. Do this if you wish to collect Snowflake cost data.
grant database role SNOWFLAKE.ORGANIZATION_BILLING_VIEWER to role DATADOG;

-- Grant usage on the database, schema, and table of the event table.
grant usage on database <EVENT_TABLE_DATABASE> to role DATADOG:
grant usage on schema <EVENT_TABLE_DATABASE>.<EVENT_TABLE_SCHEMA> to role DATADOG;
grant select on table <EVENT_TABLE_DATABASE>.<EVENT_TABLE_SCHEMA>.<EVENT_TABLE_NAME> to role DATADOG:
                        
-- Create a user.
create user <USERNAME>
LOGIN_NAME = <USERNAME>
password = <PASSWORD>
default_warehouse =<WAREHOUSE>
default_role = DATADOG

-- Grant the monitor role to the user.
grant role DATADOG to user <USERNAME>
Notes:
  • By default, this integration monitors the SNOWFLAKE database and ACCOUNT_USAGE schema. This database is available by default and only viewable by users in the ACCOUNTADMIN role or any role granted by the ACCOUNTADMIN.
  • To collect organization metrics, the user must have the ORGADMIN role.
  1. Configure key-pair authentication. The public key is assigned to the user created earlier, and the private key is uploaded to Datadog, allowing Datadog to connect to your Snowflake account.
    a. Create and upload a private key following the Snowflake instructions.
    b. Create a public key following the Snowflake instructions.
    c. Assign the public key to the user created earlier following the Snowflake instructions.
Certain IP address prefixes must be allow-listed for Datadog to collect data from your Snowflake account. The list of IP prefixes belonging to Datadog can be found in the IP Ranges page, and the range to allow can be found under webhooks.

Custom metrics

The Snowflake integration supports custom queries to collect custom metrics. Users can write custom SQL queries to extract specific data and view it as metrics and metric tags in Datadog.

By default, the integration connects to the shared SNOWFLAKE database and ACCOUNT_USAGE schema. If you are querying a table outside the ACCOUNT_USAGE schema, ensure your configured role has the appropriate permissions to access the table.

The table below describes the fields used to define custom metrics.

FieldDescriptionRequired
Custom Metric IdentifierThis is an identifier for the custom metric, used to distinguish separate custom metrics in each account.Yes
QueryThis is the SQL to execute. It can be a simple statement or a multiline script. All of the rows of the results are evaluated. Use the pipe if you require a multiline script.Yes
Metadata ColumnsThis is a list representing each column ordered sequentially from left to right. There are two required fields for each column:
- Custom Column Name:
This is the suffix to append to the metric_prefix to form the full metric name. If the type is specified as Tag Key, the column is instead applied as a tag to every metric collected by this query.
- Metadata Type:
This is the submission method (for example, gauge, count, or rate). This can also be set to tag each metric in the row with the name and value (<name>:<row_value>) of the item in this column.
Yes

Notes:

  • At least one item in the defined columns should be a metric type (gauge, count, rate, distribution).
  • The number of items in columns must equal the number of columns returned in the query.
  • The order in which the items in columns are defined must be in the same order returned in the query.

Example:

Custom metrics tab in the Snowflake integration tile

Validation

To verify the result, search for the metrics using Metrics Summary:

Snowflake metrics in the Metric Summary page

Data Collected

Metrics

snowflake.storage.storage_bytes.total
(gauge)
The average number of bytes of table storage used including bytes for data currently in Time Travel.
Shown as byte
snowflake.storage.stage_bytes.total
(gauge)
The average number of bytes of stage storage used by files in all internal stages.
Shown as byte
snowflake.storage.failsafe_bytes.total
(gauge)
The average number of bytes of data in Fail-safe.
Shown as byte
snowflake.storage.database.storage_bytes
(gauge)
The average number of bytes of database storage used.
Shown as byte
snowflake.storage.database.failsafe_bytes
(gauge)
The average number of bytes of Fail-safe storage used.
Shown as byte
snowflake.billing.virtual_warehouse.avg
(gauge)
The average overall credits billed per hour for virtual warehouses.
Shown as unit
snowflake.billing.virtual_warehouse.sum
(gauge)
The sum of overall credits billed for virtual warehouses.
Shown as unit
snowflake.billing.cloud_service.avg
(gauge)
The average overall credits billed per hour for cloud services.
Shown as unit
snowflake.billing.cloud_service.sum
(gauge)
The total overall credits billed for cloud services.
Shown as unit
snowflake.billing.total_credit.avg
(gauge)
The average overall of credits used per hour for the account. This is the sum of snowflake.billing.cloudservice and snowflake.billing.virtualwarehouses.
Shown as unit
snowflake.billing.total_credit.sum
(gauge)
The total overall of credits used for the account. This is the sum of snowflake.billing.cloudservice and snowflake.billing.virtualwarehouses.
Shown as unit
snowflake.billing.warehouse.cloud_service.avg
(gauge)
The average credits used per hour for cloud services by warehouse.
Shown as unit
snowflake.billing.warehouse.cloud_service.sum
(gauge)
The total credits used for cloud services by warehouse.
Shown as unit
snowflake.billing.warehouse.virtual_warehouse.avg
(gauge)
The average credits used per hour by warehouse.
Shown as unit
snowflake.billing.warehouse.virtual_warehouse.sum
(gauge)
The total credits used by warehouse.
Shown as unit
snowflake.billing.warehouse.total_credit.avg
(gauge)
The average total number of credits used per hour for the warehouse. NOTE: This value does not take into account adjustments which may be higher than your actual credit consumption.
Shown as unit
snowflake.billing.warehouse.total_credit.sum
(gauge)
The total number of credits used for the warehouse. NOTE: This value does not take into account adjustments which may be higher than your actual credit consumption.
Shown as unit
snowflake.logins.fail.count
(count)
Total failed login attempts.
Shown as error
snowflake.logins.success.count
(count)
Total successful login attempts.
Shown as success
snowflake.logins.total
(count)
Total number of login attempts.
Shown as attempt
snowflake.query.executed
(gauge)
The average number of queries executed.
Shown as query
snowflake.query.queued_overload
(gauge)
Average number of queries queued because the warehouse was overloaded.
Shown as query
snowflake.query.queued_provision
(gauge)
Average number of queries queued because the warehouse was being provisioned.
Shown as query
snowflake.query.blocked
(gauge)
Average number of queries blocked by a transaction lock.
Shown as query
snowflake.query.execution_time
(gauge)
Average query execution time.
Shown as millisecond
snowflake.query.compilation_time
(gauge)
Average query compilation time.
Shown as millisecond
snowflake.query.bytes_scanned
(gauge)
Average query bytes scanned.
Shown as byte
snowflake.query.bytes_written
(gauge)
Average query bytes written.
Shown as byte
snowflake.query.bytes_deleted
(gauge)
Average query bytes deleted.
Shown as byte
snowflake.data_transfer.bytes.avg
(gauge)
Average bytes transferred.
Shown as byte
snowflake.data_transfer.bytes.sum
(gauge)
Total bytes transferred.
Shown as byte
snowflake.auto_recluster.credits_used.avg
(gauge)
Average credits billed for automatic reclustering.
Shown as unit
snowflake.auto_recluster.credits_used.sum
(gauge)
Total credits billed for automatic reclustering.
Shown as unit
snowflake.auto_recluster.bytes_reclustered.avg
(gauge)
Average bytes reclustered.
Shown as byte
snowflake.auto_recluster.bytes_reclustered.sum
(gauge)
Total bytes reclustered.
Shown as byte
snowflake.auto_recluster.rows_reclustered.avg
(gauge)
Average rows reclustered.
Shown as row
snowflake.auto_recluster.rows_reclustered.sum
(gauge)
Total rows reclustered.
Shown as row
snowflake.storage.table.active_bytes.avg
(gauge)
Average bytes owned by (and billed to) this table that are in the active state.
Shown as byte
snowflake.storage.table.time_travel_bytes.avg
(gauge)
Average bytes owned by (and billed to) this table that are in the Time Travel state.
Shown as byte
snowflake.storage.table.failsafe_bytes.avg
(gauge)
Average bytes owned by (and billed to) this table that are in the Fail-safe state.
Shown as byte
snowflake.storage.table.retained_bytes.avg
(gauge)
Average bytes owned by (and billed to) this table that are retained after deletion because they are referenced by one or more clones of this table.
Shown as byte
snowflake.pipe.credits_used.avg
(gauge)
Average number of credits billed for Snowpipe data loads.
Shown as unit
snowflake.pipe.credits_used.sum
(gauge)
Total number of credits billed for Snowpipe data loads.
Shown as unit
snowflake.pipe.bytes_inserted.avg
(gauge)
Average number of bytes loaded from Snowpipe.
Shown as byte
snowflake.pipe.bytes_inserted.sum
(gauge)
Total number of bytes loaded from Snowpipe.
Shown as byte
snowflake.pipe.files_inserted.avg
(gauge)
Average number of files loaded from Snowpipe.
Shown as file
snowflake.pipe.files_inserted.sum
(gauge)
Total number of files loaded from Snowpipe.
Shown as file
snowflake.replication.credits_used.avg
(gauge)
Average number of credits used for database replication.
Shown as unit
snowflake.replication.credits_used.sum
(gauge)
Total number of credits used for database replication.
Shown as unit
snowflake.replication.bytes_transferred.avg
(gauge)
Average number of bytes transferred for database replication.
Shown as byte
snowflake.replication.bytes_transferred.sum
(gauge)
Total number of bytes transferred for database replication.
Shown as byte
snowflake.query.bytes_spilled.local
(gauge)
Avg volume of data spilled to local disk.
Shown as byte
snowflake.query.bytes_spilled.remote
(gauge)
Avg volume of data spilled to remote disk.
Shown as byte
snowflake.organization.contract.amount
(gauge)
The average amount for the given contract
snowflake.organization.credit.virtual_warehouse.sum
(gauge)
The sum of credits used by warehouse.
snowflake.organization.credit.virtual_warehouse.avg
(gauge)
The average credits used per day by warehouse.
snowflake.organization.credit.cloud_service.sum
(gauge)
The sum of credits billed for cloud services
snowflake.organization.credit.cloud_service.avg
(gauge)
The average overall credits billed for cloud services
snowflake.organization.credit.cloud_service_adjustment.sum
(gauge)
Sum of credits adjusted for included cloud services.
snowflake.organization.credit.cloud_service_adjustment.avg
(gauge)
Average of credits adjusted for included cloud services.
snowflake.organization.credit.total_credit.sum
(gauge)
The sum of overall of credits used for the organization. This is the sum of snowflake.organization.credit.cloudservice.sum and snowflake.organization.credit.virtualwarehouse.sum.
snowflake.organization.credit.total_credit.avg
(gauge)
The average number of overall of credits used for the organization. This is the sum of snowflake.organization.credit.cloudservice.avg and snowflake.organization.credit.virtualwarehouse.avg.
snowflake.organization.credit.total_credits_billed.sum
(gauge)
The total number of credits billed for the account in the day. It is the sum of snowflake.organization.credit.cloudservice.sum, snowflake.organization.credit.virtualwarehouse.sum, and snowflakeweb.organization.credit.cloudservice_adjustment.sum.
snowflake.organization.credit.total_credits_billed.avg
(gauge)
The average number of credits billed for the account in the day. It is the sum of snowflake.organization.credit.cloudservice.avg, snowflake.organization.credit.virtualwarehouse.avg, and snowflakeweb.organization.credit.cloudservice_adjustment.avg.
snowflake.organization.currency.usage
(gauge)
Sum of the total number of credits charged per day.
snowflake.organization.currency.usage_in_currency
(gauge)
Sum of the total amount charged for the day.
snowflake.organization.warehouse.virtual_warehouse.sum
(gauge)
Sum of number of credits used for the warehouse.
snowflake.organization.warehouse.virtual_warehouse.avg
(gauge)
Average number of credits used for the warehouse.
snowflake.organization.warehouse.cloud_service.avg
(gauge)
Average number of credits used for cloud services.
snowflake.organization.warehouse.cloud_service.sum
(gauge)
Sum of credits used for cloud services.
snowflake.organization.warehouse.total_credit.sum
(gauge)
The total number of credits used by the warehouse. Sum of snowflake.organization.warehouse.cloudservice.sum and snowflake.organization.warehouse.totalcredit.sum.
snowflake.organization.warehouse.total_credit.avg
(gauge)
The average total number of credits used by the warehouse. Sum of snowflake.organization.warehouse.cloudservice.avg and snowflake.organization.warehouse.totalcredit.avg
snowflake.organization.storage.average_bytes
(gauge)
Number of bytes of database storage used, including data in Time Travel and Fail-safe.
Shown as byte
snowflake.organization.storage.credits
(gauge)
Sum of total number of credits used for all accounts in the organization. Sum of credits used for database storage and stages.
snowflake.organization.rate.effective_rate
(gauge)
The rate after applying any applicable discounts per the contract for the organization.
snowflake.organization.data_transfer.bytes_transferred
(gauge)
Number of bytes transferred during the usage date.
Shown as byte
snowflake.organization.balance.capacity
(gauge)
The amount of capacity in currency that is available for use. This is the end of day balance.
snowflake.organization.balance.on_demand_consumption
(gauge)
The amount of consumption at on demand prices that will be invoiced given that all the free usage and capacity balances have been exhausted. This is a negative value (e.g. -250) until the invoice is paid. This is the end of day balance.
snowflake.organization.balance.rollover
(gauge)
The amount of rollover balance in currency that is available for use. At the end of a contract term
snowflake.organization.balance.free_usage
(gauge)
The amount of free usage in currency that is available for use. This is the end of day balance

Events

The Snowflake Web integration does not include any events.

Service Checks

The Snowflake Web integration does not include any service checks.

Troubleshooting

Need help? Contact Datadog support.

Agent check: Snowflake

The Snowflake Agent check is no longer supported, it is recommended to switch to the API-based integration for additional functionality and reduced API call volume to Snowflake.

Agent: Overview

This check monitors Snowflake through the Datadog Agent. Snowflake is a SaaS-analytic data warehouse and runs completely on cloud infrastructure. This integration monitors credit usage, billing, storage, query metrics, and more.

Note: Metrics are collected with queries to Snowflake. Queries made by the Datadog integration are billable by Snowflake.

Agent: Setup

Follow the instructions below to install and configure this check for an Agent running on a host.

Agent: Installation

The Snowflake check is included in the Datadog Agent package.

Note: The Snowflake check is not available in Datadog Agent v6 using Python 2. To use Snowflake on Agent v6 see Use Python 3 with Datadog Agent v6 or upgrade to Agent v7.

Agent: Configuration

Snowflake recommends granting permissions to an alternate role like `SYSADMIN`. Read more about controlling ACCOUNTADMIN role for more information.
  1. Create a Datadog specific role and user to monitor Snowflake. In Snowflake, run the following to create a custom role with access to the ACCOUNT_USAGE schema.

    Note: By default, this integration monitors the SNOWFLAKE database and ACCOUNT_USAGE schema. See “Collecting Organization Data” for information on how to monitor the ORGANIZATION_USAGE schema. This database is available by default and only viewable by users in the ACCOUNTADMIN role or any role granted by the ACCOUNTADMIN.

    use role ACCOUNTADMIN;
    grant imported privileges on database snowflake to role SYSADMIN;
    
    use role SYSADMIN;
    

    Alternatively, you can create a DATADOG custom role with access to ACCOUNT_USAGE.

    -- Create a new role intended to monitor Snowflake usage.
    create role DATADOG;
    
    -- Grant privileges on the SNOWFLAKE database to the new role.
    grant imported privileges on database SNOWFLAKE to role DATADOG;
    
    -- Grant usage to your default warehouse to the role DATADOG.
    grant usage on warehouse <WAREHOUSE> to role DATADOG;
    
    -- Create a user, skip this step if you are using an existing user.
    create user DATADOG_USER
    LOGIN_NAME = DATADOG_USER
    password = '<PASSWORD>'
    default_warehouse = <WAREHOUSE>
    default_role = DATADOG
    default_namespace = SNOWFLAKE.ACCOUNT_USAGE;
    
    -- Grant the monitor role to the user.
    grant role DATADOG to user <USER>;
    
  2. Edit the snowflake.d/conf.yaml file, in the conf.d/ folder at the root of your Agent’s configuration directory to start collecting your Snowflake performance data. See the sample snowflake.d/conf.yaml for all available configuration options.

        ## @param account - string - required
        ## Name of your account (provided by Snowflake), including the platform and region if applicable.
        ## For more information on Snowflake account names,
        ## see https://docs.snowflake.com/en/user-guide/connecting.html#your-snowflake-account-name
        #
      - account: <ORG_NAME>-<ACCOUNT_NAME>
    
        ## @param username - string - required
        ## Login name for the user.
        #
        username: <USER>
    
        ## @param password - string - required
        ## Password for the user
        #
        password: <PASSWORD>
    
        ## @param role - string - required
        ## Name of the role to use.
        ##
        ## By default, the SNOWFLAKE database is only accessible by the ACCOUNTADMIN role. Snowflake recommends
        ## configuring a role specific for monitoring:
        ## https://docs.snowflake.com/en/sql-reference/account-usage.html#enabling-account-usage-for-other-roles
        #
        role: <ROLE>
    
        ## @param min_collection_interval - number - optional - default: 15
        ## This changes the collection interval of the check. For more information, see:
        ## https://docs.datadoghq.com/developers/write_agent_check/#collection-interval
        ##
        ## NOTE: Most Snowflake ACCOUNT_USAGE views are populated on an hourly basis,
        ## so to minimize unnecessary queries, set the `min_collection_interval` to 1 hour.
        #
        min_collection_interval: 3600
    
        # @param disable_generic_tags - boolean - optional - default: false
        # Generic tags such as `cluster` will be replaced by <integration_name>_cluster to avoid
        # getting mixed with other integration tags.
        # disable_generic_tags: true
    
    In the default `conf.yaml`, the min_collection_interval is 1 hour. Snowflake metrics are aggregated by day, you can increase the interval to reduce the number of queries.
    Note: Snowflake ACCOUNT_USAGE views have a known latency of 45 minutes to 3 hours.
  3. Restart the Agent.

Collecting Organization Data

By default, this integration monitors the ACCOUNT_USAGE schema, but it can be set to monitor organization-level metrics instead.

To collect organization metrics, change the schema field to ORGANIZATION_USAGE and increase the min_collection_interval to 43200 in the integration’s configuration. This reduces the number of queries to Snowflake, as most organization queries have a latency of up to 24 hours.

Note: To monitor organization metrics, your user must have the ORGADMIN role.

    - schema: ORGANIZATION_USAGE
      min_collection_interval: 43200

Only some organization metrics are enabled by default. To collect all available organization metrics, utilize the metric_groups configuration option:

    metric_groups:
      - snowflake.organization.warehouse
      - snowflake.organization.currency
      - snowflake.organization.credit
      - snowflake.organization.storage
      - snowflake.organization.contracts
      - snowflake.organization.balance
      - snowflake.organization.rate
      - snowflake.organization.data_transfer

Additionally, you can monitor both account and organization metrics at the same time:

    instances:
    - account: example-inc
      username: DATADOG_ORG_ADMIN
      password: '<PASSWORD>'
      role: SYSADMIN
      schema: ORGANIZATION_USAGE
      database: SNOWFLAKE
      min_collection_interval: 43200

    - account: example-inc
      username: DATADOG_ACCOUNT_ADMIN
      password: '<PASSWORD>'
      role: DATADOG_ADMIN
      schema: ACCOUNT_USAGE
      database: SNOWFLAKE
      min_collection_interval: 3600

Collecting data for multiple environments

If you want to collect data for multiple Snowflake environments, add each environment as an instance in your snowflake.d/conf.yaml file. For example, if you needed to collect data for two users named DATADOG_SYSADMIN and DATADOG_USER:

instances:
  - account: example-inc
    username: DATADOG_SYSADMIN
    password: '<PASSWORD>'
    role: SYSADMIN
    database: EXAMPLE-INC

  - account: example-inc
    username: DATADOG_USER
    password: '<PASSWORD>'
    role: DATADOG_USER
    database: EXAMPLE-INC

Proxy configuration

Snowflake recommends setting environment variables for proxy configuration.

You can also set the proxy_host, proxy_port, proxy_user, and proxy_password under init_config in the snowflake.d/conf.yaml.

Note: Snowflake automatically formats the proxy configurations and sets standard proxy environment variables. These variables also impact every requests from integrations, including orchestrators like Docker, ECS, and Kubernetes.

Private connectivity to Snowflake configuration

If private connectivity (such as AWS PrivateLink) is enabled in Snowflake, you can configure the Snowflake integration by updating the account configuration option to the following format:

      - account: <ACCOUNT>.<REGION_ID>.privatelink

Snowflake custom queries

The Snowflake integration supports custom queries. By default, the integration connects to the shared SNOWFLAKE database and ACCOUNT_USAGE schema.

To run custom queries in a different schema or database, add another instance to the sample snowflake.d/conf.yaml and specify the database and schema options. Ensure the user and role have access to the specified database or schema.

Configuration options

The custom_queries option has the following options:

OptionRequiredDescription
queryYesThis is the SQL to execute. It can be a simple statement or a multiline script. All of the rows of the results are evaluated. Use the pipe if you require a multiline script.
columnsYesThis is a list representing each column ordered sequentially from left to right.

There are 2 required pieces of data:
- name: This is the suffix to append to the metric_prefix to form the full metric name. If the type is specified as tag, the column is instead applied as a tag to every metric collected by this query.
- type: This is the submission method (gauge, count, rate, etc.). This can also be set to tag to tag each metric in the row with the name and value (<name>:<row_value>) of the item in this column.
tagsNoA list of static tags to apply to each metric.
Notes:
  • At least one item in the defined columns should be a metric type (for example, gauge, count, rate).

  • The number of items in the columns must equal the number of columns returned in the query.

  • The order in which the items in columns are defined must be in the same order returned in the query.

custom_queries:
  - query: select F3, F2, F1 from Table;
    columns:
      - name: f3_metric_alias
        type: gauge
      - name: f2_tagkey
        type: tag
      - name: f1_metric_alias
        type: count
    tags:
      - test:snowflake

Example

The following example is a query that counts all queries in the QUERY_HISTORY view tagged by database, schema, and warehouse names.

select count(*), DATABASE_NAME, SCHEMA_NAME, WAREHOUSE_NAME from QUERY_HISTORY group by 2, 3, 4;
Custom query configuration

The custom query configuration in instances looks like the following:

custom_queries:
  - query: select count(*), DATABASE_NAME, SCHEMA_NAME, WAREHOUSE_NAME from QUERY_HISTORY group by 2, 3, 4;
    columns:
      - name: query.total
        type: gauge
      - name: database_name
        type: tag
      - name: schema_name
        type: tag
      - name: warehouse_name
        type: tag
    tags:
      - test:snowflake

Agent: Validation

Run the Agent’s status subcommand and look for snowflake under the Checks section.

Agent: Data Collected

Note: Only metrics from the following metric groups are enabled by default: snowflake.query.*, snowflake.billing.*, snowflake.storage.*, and snowflake.logins.*.

If you would like to collect metrics from other metric groups, please refer to the example config file for this integration.

Agent: Metrics

See Metrics for a list of metrics provided by this check.

Agent: Events

Snowflake does not include any events.

Agent: Service Checks

snowflake.can_connect
Returns CRITICAL if the check cannot authenticate Snowflake credentials. Returns OK otherwise.
Statuses: ok, critical

Agent: Troubleshooting

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Further Reading

Additional helpful documentation, links, and articles: