8 products found for "Azure"
Snowflake: Schedule, Trigger, Monitor, and Orchestrate Operations
This integration allows Stonebranch users to orchestrate, schedule, trigger, and monitor the Snowflake load and unload processes from different data sources (including cloud storage or local virtual machines), directly from the Stonebranch Universal Automation Center. Key Features: Users can orchestrate the following Snowflake functionalities: Snowflake loading processes: Load data from AWS S3 to Snowflake. Load data from Azure storage to Snowflake. Load data from Google storage to Snowflake. Load internal stage file to Snowflake table. Copy from local server to internal staging. Snowflake unloading processes: Unload Snowflake data to AWS S3. Unload Snowflake data to Azure storage. Unload Snowflake data to Google storage. Unload Snowflake data to internal staging. Unload from internal stage to local server. Snowflake execute commands: Execute a Snowflake command.
RClone: Cloud File Transfer
This Universal Extension provides the capability to perform fast and secure data transfers between cloud-based storage services as well as local or distributed file systems. It acts as an interface to RClone, an open source command line program that manages data transfers and supports a vast number of Cloud Providers, including AWS, Google Cloud, and Microsoft Azure. A complete list of Rclone supported Cloud Storage Providers is available on the Rclone official site. Key Features This Universal Extension is an interface for Rclone and as an interface it supports the following key features: ActionsCopy objects between two storages, including copying and renaming the destination objects, as well as copying data from a URL.Move objects between two storages, including moving and renaming the destination objects.Synchronize two storages.List objects on a storage, including listing with details or in JSON format for machine parsing.Create objects on a storage.Delete objects from a storage.OptionsSupport for dry runs. Allows users to execute a Universal Task without making any permanent changes on the target storage.Advanced filtering capability for files or objects to be listed or transferred.Capability not to overwrite files or objects during data transfersSupport for providing additional Rclone options according to the user needs.OutputProgress of the selected Action is visible, during Universal Task Instance execution.
Databricks: Automate Jobs and Clusters
This integration allows users to perform end-to-end orchestration and automation of jobs and clusters in Databricks environment either in AWS or Azure. Key Features: Uses Python module requests to make REST API calls to the Databricks environment. Uses the Databricks URL and the user bearer token to connect with the Databricks environment. With respect to Databricks jobs, this integration can perform the below operations: Create and list jobs. Get job details. Run new jobs. Run submit jobs. Cancel run jobs. With respect to the Databricks cluster, this integration can perform the below operations: Create, start, and restart a cluster. Terminate a cluster. Get a cluster-info. List clusters. With respect to Databricks DBFS, this integration also provides a feature to upload files larger files.
Microsoft Teams: Send and Receive Notifications
This integration enables users to receive task-related notifications and send task-related approvals through a Teams channel. It uses incoming webhooks to integrate Microsoft Teams with the Stonebranch Universal Automation Center (UAC). Key Features: Using this task, UAC task-related information can be sent directly to an operational Teams channel. Send interactive messages to a Teams channel to trigger an approval process for manual tasks whenever user intervention is needed. End-users can request notifications within Teams alerting them about UAC task results. Task results can include items like completed workflows and task failures. Additional Info: Requires serverless infrastructure (e.g., AWS Lambda, Microsoft Azure Functions, or Google Cloud Functions).
Azure Logic Apps: Schedule, Trigger, and Monitor Workflows
This integration can trigger and monitor the execution of Azure Logic workflows and retrieve Azure Logic workflow output execution. The Stonebranch Universal Controller (UC) integrates with Logic apps through REST APIs securely through the Azure Oauth 2.0 authentication mechanism. Key Features: Passes dynamic input parameters (JSON format) to each Azure Logic app workflow. Triggers a workflow, monitors it until the process is completed, and then delivers the results to UC. Customers can manage and control Logic app workflow execution from UC, with the capability to employ other dependencies like time triggers or event-based jobs/workflows. This task offers ITSM integration capability, enabling the auto-creation of incidents in Logic apps workflow execution failure.
Azure Virtual Machines: Start, Stop, and Terminate Instances
This integration allows users to utilize Azure Virtual Machine (VM) name, resource group, subscription ID, and access token as inputs to a start, stop, terminate, list, and check the status of Azure VMs. Key Features: Uses a Python request module to interact with the Azure cloud platform. Expands user ability to start/stop/terminate/check/list Azure VMs that belong to a subscription and resource group. In the Stonebranch Universal Controller (UC), this task reaches and stays in the success state until the Azure instance is completely started, stopped, or terminated. Scheduling this task in UC with the right dependencies set up would start and stop EC2 instances based on business needs using a UC workflow. This task helps to dynamically manage VM operations. It could potentially reduce the Azure VM running cost in the cloud. Important: This integration uses Azure Oauth 2.0 access token for Azure API authentication. Users may need to use the UC web services task to refresh the access token periodically.
Azure Data Factory: Schedule, Trigger, and Monitor
This integration allows users to schedule, trigger, and monitor the Azure Data Factory pipeline process directly from the Universal Controller. Key Features: Uses Python modules azure-mgmt-resource and azure-mgmt-datafactory to make REST API calls to Azure Data Factory. Use the Azure tenant ID, subscription ID, client ID, client secret, resource group, and location for authenticating the REST API calls to Azure Data Factory. Perform the following Azure Data Factory operations: Run a pipeline. Get a pipeline info. List all pipelines. Cancel pipeline run. List factory by resource group. Azure Data Factory triggers user can perform the following operations from UAC: Start trigger. Stop trigger. List trigger by factory. UAC also can restart a failed pipeline either from the failed step or from any activity name in the failed pipeline.
Azure Blob: Manage File Transfers
The integration for Azure Blob Storage allows secure transfer of files from Azure Blob Storage containers and folders.Storing data in the cloud becomes an integral part of most modern IT landscapes. With the Stonebranch Universal Automation Center, you can securely automate your AWS, Azure, Google, and MinIO file transfers and integrate them into your existing scheduling flows. Key Features: The following file transfer commands are supported: Upload file(s) to an Azure Blob Storage container. Download file(s) from an Azure Blob Storage container. Transfer files between Azure Blob Storage containers. List objects in an Azure Blob Storage container. Delete object(s) in an Azure Blob Storage container. List Azure Blob Storage container names. Create an Azure Blob Storage container. File transfer can be triggered by a third-party application using the Universal Automation Center RESTfull web service API: REST API. The integration for Azure Blob Storage can be integrated into any existing scheduling workflow in the same way as any standard Linux or Windows task type. Security is ensured by using the HTTPS protocol with support for an optional proxy server. Supports Azure token-based Shared Access Signature (SAS). No Universal Agent needs to be installed on the Azure cloud – the communication goes via HTTPS.