StackQL is now available for ARM64-based Linux systems. To download the ARM64 binary, please visit our downloads page, where you can find the appropriate version for your system.
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stackql-deploy is now available in the GitHub Actions Marketplace.
stackql-deploy is a declarative, stateless (and state file-less) infrastructure-as-code and test framework, driven by stackql queries. stackql-deploy is capable of provisioning, updating, de-provisioning and testing cloud and SaaS stacks across all cloud and SaaS providers.
Given this example stackql-deploy stack definition in a GitHub repo, you would simply add the following to your GitHub Actions workflow:
...
jobs:
stackql-actions-test:
name: StackQL Actions Test
runs-on: ubuntu-latest
env:
GOOGLE_CREDENTIALS: ${{ secrets.GOOGLE_CREDENTIALS }}
steps:
- name: Checkout
uses: actions/checkout@v4
- name: Deploy a Stack
uses: stackql/setup-deploy@v1.0.1
with:
command: build
stack-dir: examples/k8s-the-hard-way
stack-env: dev
env-vars: GOOGLE_PROJECT=stackql-k8s-the-hard-way-demo
Example output is shown here:
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Analyzing firewall rules is crucial for maintaining security in your cloud infrastructure. Using StackQL, you can efficiently query and analyze Google Cloud firewall configurations to ensure that your security policies are correctly implemented and that there are no unexpected open ports or protocols that might pose a security risk. Below is a simple query that retrieves important details about the ingress firewall rules for a specific network in a Google Cloud project.
SELECT
name,
source_range,
ip_protocol,
allowed_ports,
direction
FROM (
SELECT
name,
source_ranges.value as source_range,
JSON_EXTRACT(allowed.value, '$.IPProtocol') as ip_protocol,
JSON_EXTRACT(allowed.value, '$.ports') as allowed_ports,
direction
FROM google.compute.firewalls, json_each(sourceRanges) as source_ranges, json_each(allowed) as allowed
WHERE project = 'stackql-k8s-the-hard-way-demo'
AND network = 'https://www.googleapis.com/compute/v1/projects/stackql-k8s-the-hard-way-demo/global/networks/kubernetes-the-hard-way-dev-vpc'
) t
WHERE
source_range = '0.0.0.0/0'
and direction = 'INGRESS';
This query provides a comprehensive list of all ingress firewall rules that apply to any IP address (0.0.0.0/0) within the specified Google Cloud project and network. The results include the firewall rule name, the source IP range, the protocol, the allowed ports, and the direction of the traffic, an example is shown below:
|-----------------------------------------------|--------------|-------------|---------------|-----------|
| name | source_range | ip_protocol | allowed_ports | direction |
|-----------------------------------------------|--------------|-------------|---------------|-----------|
| default-allow-icmp | 0.0.0.0/0 | icmp | null | INGRESS |
|-----------------------------------------------|--------------|-------------|---------------|-----------|
| default-allow-rdp | 0.0.0.0/0 | tcp | ["3389"] | INGRESS |
|-----------------------------------------------|--------------|-------------|---------------|-----------|
| default-allow-ssh | 0.0.0.0/0 | tcp | ["22"] | INGRESS |
|-----------------------------------------------|--------------|-------------|---------------|-----------|
| kubernetes-the-hard-way-dev-allow-external-fw | 0.0.0.0/0 | tcp | ["22"] | INGRESS |
|-----------------------------------------------|--------------|-------------|---------------|-----------|
| kubernetes-the-hard-way-dev-allow-external-fw | 0.0.0.0/0 | tcp | ["6443"] | INGRESS |
|-----------------------------------------------|--------------|-------------|---------------|-----------|
| kubernetes-the-hard-way-dev-allow-external-fw | 0.0.0.0/0 | icmp | null | INGRESS |
|-----------------------------------------------|--------------|-------------|---------------|-----------|
You can use this query to help quickly identify potential security vulnerabilities. Regularly auditing these rules ensures that your cloud environment remains secure and that only the necessary ports and protocols are open to the internet.
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We have released the latest StackQL provider for Google, which includes:
alloydb, apphub, biglake, bigquerydatapolicy, looker and more)More information is available here. Run the following to install or update the Google provider:
-- run from stackql shell
REGSITRY PULL google;
or
# from the command line
stackql registry pull google
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stackql-deploy is a multi-cloud resource provisioning framework using stackql. It is inspired by dbt (data build tool), which manages data transformation workflows in analytics engineering by treating SQL scripts as models that can be built, tested, and materialized incrementally. With StackQL, you can create a similar framework for cloud and SaaS provisioning. The goal is to treat infrastructure-as-code (IaC) queries as models that can be deployed, managed, and interconnected.
This ELT/model-based framework for IaC allows you to provision, test, update, and tear down multi-cloud stacks, similar to how dbt manages data transformation projects, with the benefits of version control, peer review, and automation. This approach enables you to deploy complex, dependent infrastructure components in a reliable and repeatable manner.
StackQL simplifies the interaction with cloud resources by using SQL-like syntax, making it easier to define and execute complex cloud management operations. Resources are provisioned with INSERT statements, and tests are structured around SELECT statements.
Features include:
stackql-deployTo get started with stackql-deploy, run the following:
pip install stackql-deploy
stackql-deploy will automatically download the latest release of stackql using the pystackql Python package. You can then use the info command to get runtime information:
$ stackql-deploy info
stackql-deploy version: 1.1.0
pystackql version : 3.6.1
stackql version : v0.5.612
stackql binary path : /home/javen/.local/stackql
platform : Linux x86_64 (Linux-5.15.133.1-microsoft-standard-WSL2-x86_64-with-glibc2.35), Python 3.10.12
A stackql-deploy project is a directory with declarative SQL definitions to provision, de-provision, or test resources in a stack. The key components and their definitions are listed here:
stackql_manifest.yml : The manifest file for your project, defining resources and properties in your stack.stackql_resources directory : Contains StackQL queries to provision and de-provision resources in your stack.stackql_tests directory : Contains StackQL queries to test the desired state for resources in your stack.Use the init command to create a starter project directory:
stackql-deploy init activity_monitor
You will now have a directory named activity_monitor with stackql_resources and stackql_tests directories and a sample stackql_manifest.yml file, which will help you to get started.
The general syntax for stackql-deploy is described here:
stackql-deploy [OPTIONS] COMMAND [ARGS]...
Commands include:
build: Create or update resources based on the defined stack.teardown: Remove or decommission resources that were previously deployed.test: Execute test queries to verify the current state of resources against the expected state.info: Display the version information of the stackql-deploy tool and current configuration settings.init: Initialize a new project structure for StackQL deployments.Optional global options (for all commands) include:
--custom-registry TEXT: Specify a custom registry URL for StackQL. This URL will be used by all commands for registry interactions.--download-dir TEXT: Define a download directory for StackQL where all files will be stored.--help: Show the help message and exit.Options for build, test, and teardown include:
--on-failure [rollback|ignore|error]: Define the action to be taken if the operation fails. Options include rollback, ignore, or treat as an error.--dry-run: Perform a simulation of the operation without making any actual changes.-e <TEXT TEXT>...: Specify additional environment variables in key-value pairs.--env-file TEXT: Path to a file containing environment variables.--log-level [DEBUG|INFO|WARNING|ERROR|CRITICAL]: Set the logging level to control the verbosity of logs during execution.Using the activity_monitor stack we created previously using the init command, we can start defining a stack and defining the associated queries; here is the manifest file:
version: 1
name: activity_monitor
description: oss activity monitor stack
providers:
- azure
globals:
- name: subscription_id
description: azure subscription id
value: "{{ vars.AZURE_SUBSCRIPTION_ID }}"
- name: location
value: eastus
- name: resource_group_name_base
value: "activity-monitor"
resources:
- name: monitor_resource_group
description: azure resource group for activity monitor
props:
- name: resource_group_name
description: azure resource group name
value: "{{ globals.resource_group_name_base }}-{{ globals.stack_env }}"
# more resources would go here...
globals.stack_envis a variable referencing the user-specified environment label.
Our stackql_resources directory must contain a .iql file (StackQL query file) with the same name as each resource defined in the resources key in the manifest file. Here is an example for stackql_resources/monitor_resource_group.iql:
/*+ createorupdate */
INSERT INTO azure.resources.resource_groups(
resourceGroupName,
subscriptionId,
data__location
)
SELECT
'{{ resource_group_name }}',
'{{ subscription_id }}',
'{{ location }}'
/*+ delete */
DELETE FROM azure.resources.resource_groups
WHERE resourceGroupName = '{{ resource_group_name }}' AND subscriptionId = '{{ subscription_id }}'
Similarly, our stackql_tests directory must contain a .iql file (StackQL query file) with the same name as each resource defined in the stack. Here is an example for stackql_tests/monitor_resource_group.iql:
/*+ preflight */
SELECT COUNT(*) as count FROM azure.resources.resource_groups
WHERE subscriptionId = '{{ subscription_id }}'
AND resourceGroupName = '{{ resource_group_name }}'
/*+ postdeploy, retries=2, retry_delay=2 */
SELECT COUNT(*) as count FROM azure.resources.resource_groups
WHERE subscriptionId = '{{ subscription_id }}'
AND resourceGroupName = '{{ resource_group_name }}'
AND location = '{{ location }}'
AND JSON_EXTRACT(properties, '$.provisioningState') = 'Succeeded'
Now we can build, test, and teardown our example stack using these commands (starting with a dry-run, which will render the target queries without executing them):
# stackql-deploy build|test|teardown {stack_name} {stack_env} [{options}]
stackql-deploy build example_stack prd -e AZURE_SUBSCRIPTION_ID 00000000-0000-0000-0000-000000000000 --dry-run
stackql-deploy build example_stack prd -e AZURE_SUBSCRIPTION_ID 00000000-0000-0000-0000-000000000000
stackql-deploy test example_stack prd -e AZURE_SUBSCRIPTION_ID 00000000-0000-0000-0000-000000000000
stackql-deploy teardown example_stack prd -e AZURE_SUBSCRIPTION_ID 00000000-0000-0000-0000-000000000000
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