Skill UI

This skill provides comprehensive Python patterns for managing Oracle Cloud Infrastructure (OCI) Object Storage. It covers best practices for creating buckets, handling both simple and large multipart uploads, safely generating and revoking Pre-Authenticated Requests (PARs), and configuring lifecycle policies to ensure data integrity and proper object management within OCI.

This skill provides a comprehensive solution for deploying containerized applications to Oracle Cloud Infrastructure (OCI). It supports two primary deployment paths: OKE (Oracle Kubernetes Engine) for full Kubernetes orchestration, and Container Instances for a simpler, serverless alternative. Use this skill for automating the entire lifecycle, including pushing images to OCIR, provisioning OKE clusters via Python SDK, and executing Kubernetes deployments using kubectl.

This skill provides a comprehensive guide and code examples for designing robust and scalable Identity and Access Management (IAM) structures within Oracle Cloud Infrastructure (OCI). It covers establishing secure compartment hierarchies, understanding complex policy inheritance rules, implementing least-privilege access controls, and utilizing dynamic groups for service authentication, ensuring best practices for enterprise cloud governance.

This guide provides comprehensive, step-by-step instructions to install and configure the Oracle Cloud Infrastructure (OCI) SDK and Command Line Interface (CLI). It details the secure process of generating RSA key pairs, setting up the mandatory local configuration file, and verifying API connectivity. Use this when integrating OCI services into applications, setting up new cloud environments, or troubleshooting authentication errors.

This skill allows users to programmatically set up a comprehensive observability stack for Oracle Cloud Infrastructure (OCI) resources. It guides the creation of metric queries, alarm rules, custom metric publishing, and detailed log searches using the Python SDK. By automating monitoring and alerting, users gain full control over their infrastructure visibility, eliminating reliance on the OCI Console UI for critical operational checks.

Programmatically query Oracle Cloud Infrastructure (OCI) metrics using the Monitoring Query Language (MQL) and create monitoring alarms via the Python SDK. This skill bypasses the limitations of the OCI console query builder, allowing reliable retrieval of key infrastructure metrics such as CPU utilization, memory usage, network traffic, and disk I/O. Ideal for building robust dashboards, automating resource monitoring, and setting up complex alerting rules.

Provides a comprehensive, production-ready standard 3-tier reference architecture for Oracle Cloud Infrastructure (OCI). The design covers essential components like VCN, public/private subnets, Internet Gateway, NAT Gateway, Service Gateway, and Autonomous Database. It includes deployment steps using Terraform and OCI SDK Python code, making it ideal for designing new cloud environments or migrating existing patterns from other major cloud providers.

This comprehensive guide details the end-to-end process of migrating data and connecting to Oracle Cloud Infrastructure's Autonomous Database (ADB). It walks through provisioning the ADB using the Python SDK, securely downloading the necessary mTLS wallet, establishing a connection using `python-oracledb`, and executing compatibility-aware data migration via Data Pump.

This guide provides production-grade patterns for using the Oracle Cloud Infrastructure (OCI) Python SDK. It addresses critical issues such as preventing Instance Principal memory leaks by implementing a thread-safe singleton client pattern, configuring explicit connection and read timeouts, and implementing robust exponential backoff retry strategies for transient errors (429, 5xx). Essential for building reliable, long-running OCI services.

This skill provides a comprehensive guide for safely upgrading the Oracle Cloud Infrastructure (OCI) Python SDK and Terraform provider. It addresses known breaking changes, schema modifications, and version incompatibility issues common in OCI tools. By implementing version pinning, pre-upgrade testing, and structured rollback procedures, users can ensure a stable and reliable migration process for both code and infrastructure definitions.

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 checklist and implementation guide for utilizing RunwayML's API for advanced AI video generation and image editing. This skill provides the Python SDK pattern, covering tasks like image-to-video creation, model selection, and waiting for task completion. It also includes critical error handling for common issues (e.g., unauthorized access or insufficient credits), making it essential for developers building production-level creative AI applications.