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· 2 min read

The StackQL Sumologic provider is now available in the public StackQL Provider Registry. Docs are available at sumologic provider docs.

StackQL is an intelligent API client which uses SQL as a front-end language. StackQL can be used for querying cloud and SaaS providers, as well as provisioning and lifecycle operations.

The StackQL Sumo provider can query, create, update and delete Sumologic collectors and sources, view and manage ingest budgets, health events, dashboards, user and account access and activity, and more.

Some example queries include:

SELECT id, name FROM sumologic.collectors.collectors WHERE region = 'au';

or using built-in functions to simplify and format query outputs, such as:

SELECT alive, datetime(lastSeenAlive/1000, 'unixepoch') AS lastSeenAliveUtc,
datetime(lastSeenAlive/1000, 'unixepoch', 'localtime') AS lastSeenAliveLocal
FROM sumologic.collectors.collectors
WHERE region = 'au' AND id = 116208196;

another example...

SELECT id, email,
firstName || ' ' || lastName AS fullName,
round(julianday('now') - julianday(lastLoginTimestamp), 0) as daysSinceLastLogin
FROM sumologic.users.users WHERE region = 'au';

An example using StackQL with the Sumologic provider to query users and roles and join the results to get a list of users and their roles:

SELECT as email, AS role
FROM sumologic.users.users u
JOIN sumologic.roles.roles r
ON JSON_EXTRACT(u.roleIds, '$[0]') =
WHERE u.region = 'au' AND r.region = 'au';

An example using StackQL and Jupyter is shown here (see stackql/stackql-jupyter-demo):

Use StackQL and Jupyter to query SumoLogic

StackQL can also be used to provision objects in Sumologic, the following query can be used to create a collector for instance:

INSERT INTO sumologic.collectors.collectors(region, data__collector)
SELECT 'au',
'{ "collectorType":"Hosted", "name":"My Hosted Collector", "description":"An example Hosted Collector", "category":"HTTP Collection" }';

Let us know what you think!

· One min read

StackQL is an intelligent API client which uses SQL as a front-end language with support for multi-cloud and SaaS provider environments, you can find more information at

StackQL can provide valuable insights into your cloud and SaaS estates, whether for security posture management, cross-cloud entitlements reporting, cost optimization, or asset/inventory management.

As an interactive analysis tool, Jupyter notebooks can leverage StackQL to provide sources for cloud and SaaS provider data.

GCP Nodes

We've recently added magic function support for running StackQL queries in Jupyter notebooks, making the integration between StackQL and Jupyter more seamless. StackQL magic and be used on a line in a cell or the entire cell itself, as shown here:

The stackql-jupyter-demo Docker image is available from Docker Hub. You can find instructions to run using the Docker Hub image and instructions to run using docker-compose at

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