Skill UI

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.

A comprehensive guide for rapid incident response for Palantir Foundry systems. This runbook provides structured steps for triage, severity classification (P1-P4), and detailed playbooks for common issues like authentication failures, rate limiting, and build pipeline errors. It guides users through investigation, mitigation, and postmortem documentation to minimize downtime and ensure quick recovery.

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 structured guide for setting up a robust local development environment for Palantir Foundry data pipelines. This workflow enables users to run Python transforms and unit tests using PySpark against sample data, and mock the Foundry API client, ensuring fast, isolated iteration cycles before deploying code to the official Foundry environment. Ideal for data engineers and developers building complex ETL logic.

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 guide provides comprehensive best practices for configuring Palantir Foundry integrations across development, staging, and production environments. It details how to manage environment-specific credentials, hostnames, and scope policies using structured Python code and platform-specific deployment manifests (Docker Compose, Kubernetes, gcloud). Use this skill when implementing resilient, multi-tier SaaS deployments that require strict credential and configuration separation.

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.

A comprehensive checklist for deploying Foundry-integrated applications to a production environment. It guides users through critical go-live procedures, covering pre-deployment credential management, rigorous code quality checks, setting up robust monitoring and alerting systems, and executing safe rollout and rollback strategies. Essential for ensuring system stability during major releases.

This skill provides a robust solution for managing API rate limits, particularly crucial when integrating with enterprise platforms like Palantir Foundry. It implements advanced techniques including exponential backoff, jittered retries for handling 429/5xx errors, and a token bucket rate limiter for controlled batch throughput. Use this to ensure reliable data ingestion and bulk API operations.

This guide provides a comprehensive reference architecture for building production-ready, enterprise-grade applications on Palantir Foundry. It covers the entire data lifecycle, detailing best practices for the standard data pipeline (Raw > Clean > Model), Ontology design, external API integration patterns, and robust multi-layered security models. Use it when designing, planning, or optimizing complex data infrastructure within Foundry.