How-to guides for Jitterbit Studio

How-to guides cover common, practical tasks in Studio with complete, working examples. While the User Interface and Design reference documentation explains what each setting, function, and connector does, these guides show how to build complete, working implementations directly in your own project.

Where to start

If you are new to Studio or looking for the most broadly applicable patterns, these guides cover the foundations:

• Call a REST API using the HTTP v2 connector: The general-purpose pattern for outbound REST calls when no dedicated connector exists for your endpoint. If an application connector is available for your system, use that first.
• Chain and control operations: How to link operations using the Invoke Operation tool or RunOperation scripts, with conditional logic and error handling.
• Configure error handling in operations: How to set success and failure actions, capture errors, and build resilient operation chains.
• Manage endpoint credentials: Best practices for storing and referencing API keys and credentials securely using project variables.

Studio how-to guides

API and connectivity

• Authenticate API endpoints using JWT
• Build dynamic query strings for REST API calls
• Call a REST API using the HTTP v2 connector
• Expose a Studio operation as a REST API
• Filter database query results using API request parameters
• Handle pagination when reading from an API
• Implement an OAuth 2.0 authorization code flow with token storage
• Manage endpoint credentials
• Receive Slack events in a Studio operation
• Reuse endpoints and scripts
• Support SOAP MTOM/XOP messages
• Trigger a Studio operation from a webhook

Data handling

• Detect and deduplicate records using hash functions
• Filter records using conditions
• Handle arrays using Get and Set
• Handle timezones in datetime operations
• Perform a bulk upsert to a database
• Populate and use a dictionary
• Process incremental records using a high-watermark
• Read a zipped Base64-encoded file
• Set up bidirectional sync between two systems
• Split a file into individual records using SCOPE_CHUNK
• Validate and enrich records before a CRM upsert
• Split a file into individual records using SourceInstanceCount

Operations and scheduling

• Configure error handling in operations
• Configure operation chunking for large datasets
• Manage asynchronous operations
• Manage workflows using controller scripts
• Retry a failed operation
• Schedule an operation to run automatically
• Use a naming convention for variables
• Chain and control operations

Notifications

• Generate a summary log after processing records
• Send an email notification from a Studio operation
• Send a Microsoft Teams notification from a Studio operation
• Send a Slack notification from a Studio operation

AI patterns

• Analyze files using OpenAI file inputs
• Build a multi-turn LLM chat with conversation history
• Connect to an MCP server using the MCP Client connector
• Implement an LLM tool-calling loop
• Process documents with AI
• Route LLM responses to Studio operations using function calling
• Use Azure OpenAI in a Studio operation
• Use OpenAI to process data in a Studio operation

Connector patterns

• Enrich contact data using ZoomInfo
• Handle failed messages using a Dead Letter Queue
• Publish and receive Google Pub/Sub messages
• Read and parse Google Docs content
• Read and write files in Box
• Send and receive Azure Service Bus messages
• Store and retrieve session state using Cloud Datastore
• Write data to a Google Sheets spreadsheet
• Map source dates to Salesforce Date fields and log response errors
• Query Salesforce records using SOQL
• Sync HubSpot form submissions to Salesforce
• Send changed Salesforce object records to a database via Salesforce workflow rule and API Manager
• Send changed Salesforce object records to a database via Salesforce flow and API Manager

AI agent how-to guides

These guides cover building complete AI agents on the Jitterbit Harmony platform using Studio, API Manager, and App Builder together. They are located within the AI agents documentation.

• How to build a reactive AI agent: Build a basic agent that responds to user queries without memory or tools, providing the foundation for all agent patterns.
• How to build a contextual AI agent: Add conversation memory to a reactive agent using Cloud Datastore to store and retrieve history across turns.
• How to build an AI agent with RAG tools: Extend a contextual agent with Retrieval-Augmented Generation to query data sources and improve response accuracy.
• How to build an AI agent with MCP: Build an agent using the MCP Client connector to consume tools from a Model Context Protocol server.
• How to build a composite agent: Route user queries to multiple specialized agents based on content analysis.
• How to build an AI agent with LLM fine-tuning: Train an OpenAI model on your organization's data and use the fine-tuned model in an agent.
• How to build an intelligent application: Embed an AI agent exposed as a REST API into an App Builder application.

Agent how-to guides

These guides cover installation, configuration, and maintenance tasks for private agents. They are located within the Agents documentation.

• Migrate agents
• Custom PostgreSQL install on Windows
• Reset the PostgreSQL admin user password
• Change PostgreSQL password encryption method from MD5 to SCRAM
• Add the latest Salesforce DigiCert global certificate to the trust store
• Rolling upgrades

Connector setup guides

Connector setup guides cover how to configure the external system so that Jitterbit can connect to it, such as setting up authentication, creating required fields, or enabling specific features in the third-party application. They are different from the Studio how-to guides above, which describe how to build and structure integrations in Studio (including the Connector patterns that use a specific connector).

These guides are located within each connector's documentation.