Amazon S3: Cloud Storage Bucket File Transfer
The Amazon S3 Cloud Storage Bucket File Transfer integration allows you to securely automate file transfers from, to, and between Amazon S3 cloud storage buckets and third-party application folders.Storing data in the cloud becomes an integral part of most modern IT landscapes. With Universal Automation Center (UAC), you can securely automate your AWS tasks and integrate them into existing scheduling workflows. Key Features: Automate file transfers in real-time. Drag-and-drop as a task into any existing scheduling workflow within the UAC. File Transfers can be triggered by a third-party application using the UAC RESTfull web service API: REST API. The following file transfer commands are supported: Upload file(s) to an S3 bucket. Download file(s) from an S3 bucket. Transfer files between S3 buckets. List objects in an S3 bucket. Delete object(s) in an S3 bucket. List S3 bucket names. Create an S3 bucket. Additional Info: Security is ensured by using the HTTPS protocol with support for an optional proxy server. Supports AWS IAM Role-Based Access (RBCA). No Universal Agent needs to be installed on the AWS Cloud – the communication goes via HTTPS.AWS canned ACLs are supported, e.g., to grant full access to the bucket owner.
Amazon SQS: Create, Monitor, and Send Messages
The Amazon SQS integration allows you to create, send, and monitor Amazon SQS messages and automatically trigger a task or workflow in Universal Controller each time a message has been received.Amazon Simple Queue Service (SQS) is a fully managed message queuing service that enables you to decouple and scale microservices, distributed systems, and serverless applications. Using SQS, enterprises can send, store, and receive messages between software components. Key Features: Allows you to monitor for, create, and send Amazon SQS messages. Trigger a task in Universal Controller upon the arrival of a new SQS message. Amazon SQS tasks can be integrated into any existing or new automation workflow. Create and send a SQS message out of any modern third-party application by calling the Universal Controller remote web service API. Set different log-levels for the Amazon SQS task to provide additional information when root-causing potential issues. Additional Information: This integration uses the Python Boto3 module. This enables new Amazon AWS services and the ability to update the current SQS task when new requirements occur. Credentials for Amazon S3 are stored in an encrypted format in the database. IAM Role-Based Access Control (RBAC) is supported. Communication to Amazon AWS is done via the HTTPS protocol. A proxy server connection to Amazon AWS with basic authentication is supported. Amazon AWS with basic authentication is supported.
Amazon SQS: Message
Amazon Simple Queue Service (SQS) is a fully managed message queuing service that enables you to decouple and scale microservices, distributed systems, and serverless applications. This Integration provides the capability to send an AWS SQS message towards an existing queue. Key Features: This Universal Extension provides the following main features: Send a message towards a standard or a FIFO queue. Capability to control the transport of the messages by configuring the message Delay Seconds (for standard queues) and the message group ID and message deduplication ID (for FIFO queues).Capability to fetch dynamically Queue Names list from SQS for selection during task creation.Capability to be authorized via IAM Role-Based Access Control (RBAC) strategy.Capability for Proxy communication via HTTP/HTTPS protocol. What's New in v1.1.0This new release gives the capability to users to rely on AWS credentials set-up on the environment where the extension is running and therefore it is not mandatory to be passed on the task definition as input field. The same applies to AWS Region.
Amazon SQS: Monitor
Amazon Simple Queue Service (SQS) is a fully managed message queuing service that enables you to decouple and scale microservices, distributed systems, and serverless applications. This Universal Extension provides the capability to monitor AWS SQS messages from an existing queue and run Universal Task and/or workflows accordingly.Key FeaturesThis Universal Extension provides the following main features:ActionMonitor AWS SQS messages from a standard or a FIFO queue.Launch a task in Universal Controller with variables holding the id, body, attributes, message attributes and receipt handle for each fetched message.AuthenticationAWS Credentials.IAM Role-Based Access Control (RBAC) strategy.OtherCommunication through Proxy with use of HTTP or HTTPS.What's New V1.1.0 This new release gives the capability to users to rely on AWS credentials set-up on the environment where the extension is running and therefore it is not mandatory to be passed on the task definition as input field. The same applies to AWS Region.
Apache Airflow is an open-source platform created to programmatically author, schedule, and monitor workflows. This integration provides the capability to integrate with Apache Airflow and use it as part of your end-to-end Universal Controller workflow, allowing high-level visibility and orchestration of data-oriented jobs or pipelines. Key Features: This Universal Extension provides the following main features: Triggering a new DAG run. Information retrieval of a specific DAG run. Information retrieval for a task that is part of a specific DAG run. Basic authentication (username/password) and SSL protocol. Using a proxy between Universal Controller and Apache Airflow server. What's new v 1.1.0The action "Trigger DAG Run" has been enhanced. The latest release provides the ability to configure the task to wait for the execution of the DAG Run until it reaches the state of "success" or "failed". Depending on the final DAG Run state, the task finishes with a corresponding status ("success" or "failed").
Apache Kafka: Event Monitor
Apache Kafka is an open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications. A Kafka Event Monitor is a Universal Extension responsible for monitoring events (messages) from topics in Kafka. Key Features: This Universal Extension provides the following main features: Support to consume messages by consumer group subscription, from a specific topic, until a specific condition is met. Filtering is based on the value of the message. When a matching Kafka message is detected, the universal task is finished by publishing information related to the matched message on extension output. Number, String and JSON filter patterns are supported. Support for authenticating to Kafka through PLAINTEXT or SASL_SSL SCRAM security protocol. Typically this extension can be used to monitor events from Kafka and upon successful execution to trigger workflows or other tasks, or just to pass information related to the Kafka event within UAC.
Apache Kafka: Publish Event
Apache Kafka is an open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications. This Integration is responsible for publishing events (messages) to topics in Kafka. Key Features: This Universal Extension supports the following main features: Perform authentication towards Kafka, using PLAINTEXT or SASL_SSL security protocol Send a message to Kafka with the capability to select, the topic, the partition, the message key, the message value and message metadata Capability to control the transport of the messages by configuring the message acknowledgment strategy and the request timeout Capability to fetch dynamically topics and partitions from kafka for selection during task creation Capability to automatically select the serialization method depending on the key/value message data types
AWS Batch is a set of batch management capabilities that enables developers, scientists, and engineers to quickly and efficiently run hundreds of thousands of batch computing jobs on AWS. AWS Batch integration provides the ability to submit new AWS Batch Jobs and read the status for an existing AWS Batch Job. Key Features:This Universal Extension provides the following key features:Support to submit a new Batch Job, with the option to Terminate Job after a timeout period. Support to read Batch Job status for an existing Job ID. Support for authorization via IAM Role-Based Access Control (RBAC) strategy. Support for Proxy communication via HTTP/HTTPS protocol.What's New in v 1.2.0 This new release gives the capability to users to Submit AWS Jobs and wait until the Jobs reach "Success" or "Failure". Key parameters such as job status, id, name and ARN are updated live during execution.
AWS Glue is a serverless data-preparation service for extract, transform, and load (ETL) operations. It makes it easy for data engineers, data analysts, data scientists, and ETL developers to extract, clean, enrich, normalize, and load data. This integration provides the capability to submit a new AWS Glue Job. Key Features:This Universal Extension provides the following key features:Start a Glue job. Support authorization via IAM Role-Based Access Control (RBAC) strategy. Support Proxy communication via HTTP/HTTPS protocol.What's New in v1.1.0This new release gives the capability to users to rely on AWS credentials set-up on the environment where the extension is running and therefore it is not mandatory to be passed on the task definition as input field. The same applies to AWS Region.
AWS Lambda is a serverless compute service that runs your code in response to events and automatically manages the underlying compute resources. You can use AWS Lambda to extend other AWS services with custom logic or create your own back-end services that operate at AWS scale, performance, and security. AWS Lambda can automatically run code in response to multiple events, such as HTTP requests via Amazon API Gateway, modifications to objects in Amazon S3 buckets, table updates in Amazon DynamoDB, and state transitions in AWS Step Functions. Key Features:This Universal Extension provides the following key features:Trigger Lambda function Synchronously or Asynchronously. Support authorization via IAM Role-Based Access Control (RBAC) strategy. Support default or on demand AWS Region. Support Proxy communication via HTTP/HTTPS protocol.What's New v1.1.0This new release gives the capability to users to rely on AWS credentials set-up on the environment where the extension is running and therefore it is not mandatory to be passed on the task definition as input fields. The same applies to AWS Region.
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.
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.
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.
Google BigQuery: Schedule, Trigger, Monitor, and Orchestrate Operations
This integration allows users to schedule, trigger, monitor, and orchestrate the Google BigQuery process directly from the Universal Controller. Key Features: Users can perform the below Google BigQuery operations: BigQuery SQL. List dataset. List tables in a dataset. View job information. Create a dataset. Load local file to a table. Load cloud storage data to a table. Export table data. Additional Info: This task uses Python google-cloud-bigquery and google-auth modules to make REST API calls to Google BigQuery. This task will use the GCP project ID, BigQuery SQL or schema, dataset ID, job ID, location, table ID, cloud storage URI, source file format as parameters of BigQuery function and GCP KeyFile (API KEY) of service account for authenticating the REST API calls to Google BigQuery.
Hitachi Vantara: Pentaho Data Integration
Pentaho Data Integration provides powerful ETL (Extract, Transform, and Load) capabilities and Universal Controller using its universal extension capabilities. Key Features: Run a Pentaho Job from its Carte configured repository Run a Pentaho Job from its Repository Run a Pentaho Job from a remote job definition file Define & Run a Pentaho Job from Universal Controller Script Library Execute a Pentaho Transformation from a Repository Execute a Pentaho Transformation from a remote transformation definition file(XML)Define & Run a Pentaho Transformation from Universal Controller Script Library
Informatica Cloud: Schedule, Control, and Manage
This integration allows users to schedule any data integration task, linear taskflow, or taskflow in the Informatica Cloud. Key Features: Schedule data integration tasks, including linear taskflow, in the Informatica Cloud.All communication is web-service based, using the latest Informatica REST API (version 2 and 3) with support for folders.Log-files including activity-, session-, and error-log are available from the Universal Controller web UI in the same way as the Informatica monitoring console.
Informatica PowerCenter: Schedule, Control, and Manage
This integration allows users to schedule Informatica PowerCenter workflows and tasks, including retrieving the workflow and session log. It's also possible to start a workflow from a certain task onwards. Key Features: Schedules Informatica PowerCenter via its web services hub; therefore, no installation on any Informatica system is required. Based on the standard PowerCenter web services hub using the SOAP protocol. The PowerCenter web services hub interface is called by a Universal Agent running on a Linux server or Windows server. The following actions are supported: Start a task in an Informatica PowerCenter workflow. Start an Informatica PowerCenter workflow. Start an Informatica PowerCenter workflow from a given task onwards.
Inter-Cloud Data Transfer
Stream data from one object store to another without intermediate storage. The Inter-Cloud Data Transfer integration allows users to transfer data to, from, and between major private and public cloud providers like AWS, Google Cloud, and Microsoft Azure. It also supports the transfer of data to and from a Hadoop Distributed File System (HDFS) and to major cloud applications like OneDrive and SharePoint. Integrations within this solution package include: AWS S3 Google Cloud SharePoint Dropbox OneDrive Hadoop HDFS Key Features: Transfer data to, from, and between any cloud provider Transfer between any major storage applications like SharePoint, Dropbox, and others Transfer data to and from a Hadoop File System (HDFS) Download a URL's content and copy it to the destination without saving it in temporary storage Data is streamed from one object store to another (no intermediate storage) Very fast, if the object stores are in the same region Preserves always timestamps and verifies checksums Supports encryption, caching, compression, chunking Perform dry-runs Dynamic token updates for SharePoint connections Regular expression-based include/exclude filter rules Supported actions are: List objects, list directory Copy/move Remove object/object-store Perform dry-runs Monitor object Copy URL What's New in v1.2.0 New choice field for write options Do not overwrite existing objects Replace existing objects Create a new timestamp if it exists Use custom parameters New text field to set the recursion depth The default value is “1” — no recursion allowed New checkbox “Error on no transfer” The task will fail if no transfer has been performed File Monitor incl. Trigger functionality (similar as the agent file monitor in the Universal Controller) Skip if Active Trigger on Exists Use server modtime — time when the file was uploaded to the object store (S3 bucket, Azure Container, etc. ) Task(s) to launch (CSV-List). You can launch one or multiple tasks, if the monitor goes to success. New Remote: SFTP client Support for SFTP streaming Task acts as SFTP client Windows agent support Task can execute rclone installed on Windows Note: * SharePoint Online will only work with the latest Universal Agent 7.2
Microsoft Power BI: Refresh Business Intelligence
This integration allows users to refresh datasets and dataflows in the Microsoft Power BI business analytics service. Key Features: Refresh a dataset in a group-workspace or in my workspace. Refresh a dataflow in a group-workspace. Lookup datasets in a selected group. Lookup dataflows in a selected group. Connection to the Power BI REST API is done via the Python MSAL library. Supports Windows and Linux Universal Agents in order to connect to the Power BI REST API.
Microsoft SQL: Schedule SSRS
This integration can complete various administrative tasks, including publishing reports and moving reports from one server to another server. It's based on the SQL Server Reporting Services 'rs.exe' command-line utility, which can perform many scripted operations related to SQL Server Reporting Services (SSRS). The rs.exe utility requires an input file to tell rs.exe what to do.The list of actual tasks that can be performed includes among others: Deploying / Publishing reports Moving reports Exporting reports to a file Adjust security Cancel a running job Configure SSRS system properties
Microsoft SQL: SSIS Package Execution
SQL Server Integration Services is a platform for building data integrations and data transformation solutions. This integration interactively allows users to list and select the SSIS Folder, Project, Environment Reference, and SSIS Package while creating the job. Further, it can trigger the SSIS package execution in the Microsoft SQL server and monitor the SSIS Package execution, and fetch SSIS logs to the universal controller once the SSIS package execution is completed.
SAP: Batch Input Map
This integration for SAP batch input allows users to schedule and execute batch input sessions in SAP. Batch input sessions enter data non-interactively into an SAP system. It's typically used to transfer data from non-SAP systems to SAP systems or to transfer data between SAP systems. Key Features: Runs a batch input session. You only need to provide the batch input session name in the task variable. It's possible to use wildcards (*) to run multiple batch input sessions. There's no need to create a variant manually for the batch input session in SAP. The SAP task uses the feature inline variants of USAP to create a temporary variant for the ABAP RSBDCSUB with the batch input session name. We are an SAP silver partner. Our product has certified integration with SAP S/4HANA.
SAP: BusinessObjects Report Schedule
This integration schedules any SAP BusinessObjects schedulable resource, including Crystal or Web Intelligence reports, from the Stonebranch Universal Automation Center.Using analytics tools to collect massive amounts of big data from your organization is one thing. Extracting meaning from that data and using it to drive real growth is another. BusinessObjects analytics from SAP can help you unleash the power of collective insight by delivering enterprise business intelligence, agile visualizations, and advanced predictive analytics to all users. We are an SAP silver partner. Our product has certified integration with SAP S/4HANA.
SAP: BusinessObjects Scheduling Web Intelligence Documents and Crystal Reports
SAP: BusinessObjects Scheduling Web Intelligence Documents and Crystal Reports is a centralized suite for data reporting, visualization, and sharing. The integration for SAP BusinessObjects allows scheduling Crystal Reports and Web Intelligence documents. It supports multiple prompts and different output formats like PDF, EXCEL, and Webi. Key Features Schedule SAP Webi reports Schedule Crystal Reports Support multiple prompts as input parameter Support different output formats like MS EXCEL, PDF, Webi Based on the latest RESTful web service SDK - no Agent needs to be installed on the SAP BO Server Exit code processing and error handling In case a report fails (for example, if you provide a wrong BusinessObjects ID, it will fail), and you can re-start the job with the correct ID. In case of a connection error, the task will fail (for example, wrong IP address or Port of the SAP BO HOST). In case a wrong password has been entered, the instance will fail. We are an SAP silver partner. Our product has certified integration with SAP S/4HANA.