Skill UI

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.

This skill guides users on building robust, event-driven pipelines within Oracle Cloud Infrastructure (OCI). It covers setting up OCI Events rules to monitor resource state changes (Compute, Object Storage, Identity). Events can then be routed to Oracle Notification Service (ONS) topics for real-time alerting or directly to OCI Functions (serverless processing) for complex, automated actions.

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 guide provides comprehensive solutions for common API errors encountered when integrating with Persona for identity verification (KYC). It covers critical issues including 401 unauthorized keys, 422 invalid templates, webhook signature mismatches, rate limit handling (429), and state management conflicts. Use this resource when debugging or optimizing automated identity validation workflows.

A comprehensive guide for diagnosing and reducing high memory consumption in Qdrant. This resource is crucial when dealing with reports of 'memory leak', 'out of memory', or excessive RAM growth. It details how Qdrant manages resident memory and OS page cache, and provides advanced techniques such as quantization, using float16/int8 data types, and strategically storing components on disk (like HNSW indexes or sparse vectors) to minimize the memory footprint and ensure stable, scalable operation.

This guide provides best practices for scaling multi-tenant deployments in Qdrant. It advises against the inefficient 'one collection per tenant' approach. Solutions include using shared collections with payload filtering, implementing custom sharding for large-scale tenants (100k+), and employing tiered multitenancy for unevenly sized workloads, ensuring optimal resource utilization and performance.

This guide provides comprehensive guidelines for performing vertical scaling on Qdrant instances. Vertical scaling involves upgrading the computational resources (CPU, RAM, or disk) of existing nodes rather than adding new nodes. It is the recommended first step when single nodes experience resource exhaustion (e.g., RAM usage > 80%, CPU saturation). The guide covers sizing guidelines, best practices for cloud deployment, and clearly defines the thresholds when horizontal scaling becomes necessary.

This guide provides implementation patterns for optimizing costs and tuning performance when integrating with QuickNode's blockchain RPC endpoints. It covers best practices using the QuickNode SDK and standard Web3 libraries, offering solutions for stable connectivity, error handling, and resource management in advanced blockchain development workflows.

qzcli is a powerful command-line interface (CLI) tool designed for managing complex GPU compute jobs on the Qizhi platform. Modeled after industry standards like kubectl, it allows users to log in, discover available resources (nodes, workspaces), submit interactive or highly complex batch jobs (including matrix sweeps), and monitor job status efficiently. It is essential for handling high-performance computing (HPC) and distributed machine learning training workflows.

A comprehensive guide for diagnosing and resolving common Salesforce API, SOQL, and integration errors. This resource details specific error codes, analyzes root causes (e.g., insufficient permissions, malformed queries, API limits), and provides actionable solutions and best practices for developers and administrators.