Skill UI

Comprehensive guide for setting up Continuous Integration/Continuous Deployment (CI/CD) pipelines for Palantir Foundry integrations using GitHub Actions. This workflow covers running PySpark unit tests, performing SDK integration tests with mocked APIs, and implementing custom linting rules to enforce Foundry-specific best practices. Use this when ensuring code quality and validating complex business logic changes in an automated build process.

This comprehensive guide provides quick, actionable solutions for the top common Palantir Foundry API and data transformation errors. It covers critical issues such as 401 Unauthorized, 403 Forbidden, ObjectTypeNotFound, and OutOfMemoryError. By offering specific code examples and best practices, this resource helps users efficiently debug and resolve complex issues in their Foundry pipelines.

This guide provides a comprehensive workflow for building robust ETL data pipelines within Palantir Foundry. It teaches how to utilize Python transforms, including the @transform_df decorator, for dataset-to-dataset processing. Key topics covered include multi-input joins, implementing incremental updates for efficiency, low-level file I/O, and configuring Spark resources for heavy computations. Essential for data engineers working with complex data modeling in Foundry.

This workflow provides comprehensive SDK access to the Palantir Foundry Ontology. It enables users to query, filter, link, and mutate Ontology objects, and execute defined business actions. Use this skill for building sophisticated, data-driven applications that require deep interaction with structured enterprise data, including cross-object navigation and advanced server-side aggregation.

This comprehensive bundle collects all necessary diagnostic artifacts for troubleshooting Palantir Foundry issues. It gathers SDK versions, environment variables (with secrets automatically redacted), API connectivity status, and recent application error logs. This structured output is essential for creating detailed, actionable support tickets when reporting persistent platform malfunctions.

This skill provides a comprehensive guide for deploying Palantir Foundry integrated applications to major cloud platforms, such as GCP Cloud Run, AWS Lambda, and Docker. It covers best practices including containerization using Docker, implementing robust secrets management via cloud secret managers, establishing health check endpoints, and configuring environment-specific scopes. This process ensures applications are production-ready, secure, and highly available.

This guide teaches best practices for configuring robust, enterprise-grade Role-Based Access Control (RBAC) within Palantir Foundry. Learn how to define project roles (Viewer, Editor, Owner), manage organization-level groups to enforce least privilege, establish secure service user accounts for external integrations, and utilize marking-based data classification to ensure data governance and security across large datasets.

A comprehensive, step-by-step guide demonstrating how to interact with Palantir Foundry using the official Python SDK. This example covers listing ontologies, querying object types, retrieving single records by primary key, reading datasets, and applying business actions, making it ideal for developers starting a new Foundry integration or learning core API patterns.

This comprehensive guide provides step-by-step instructions for installing and configuring the Palantir Foundry SDK. It covers both the Platform SDK for direct REST API data access and the OSDK for Ontology-based workflows. Users will learn how to set up authentication using OAuth2 client credentials or Bearer tokens, ensuring secure and seamless integration into their development environment for both production and development use cases.

A comprehensive guide for executing major Palantir Foundry migrations. It covers data migration (bulk and incremental sync), API version upgrades, and re-platforming using advanced patterns like the Strangler Fig pattern. Use this when transitioning data from legacy systems into Foundry or upgrading existing platform integrations.

This skill guides the setup of comprehensive observability for Palantir Foundry integrations. It covers structured logging, Prometheus metrics (latency, errors), health checks, and Prometheus alert rules, enabling robust monitoring of API integration health, performance, and reliability. Use this when implementing production-grade monitoring for Foundry APIs.

This guide provides advanced techniques for optimizing performance within Palantir Foundry. It covers efficient pagination, implementing client-side caching, using batch object retrieval (solving the N+1 problem), and tuning Spark transforms with memory configuration and incremental updates. Use this when experiencing slow API responses or inefficient data pipeline builds in Foundry.