Skill UI

A comprehensive guide and implementation guide for using the Azure Event Hubs SDK in TypeScript. It demonstrates best practices for high-throughput event streaming, including batch event sending, targeted partitioning, and robust event consumption. Covers advanced features like checkpointing, starting from specific positions, and handling event properties, making it ideal for building scalable, real-time data ingestion pipelines.

A comprehensive guide and implementation guide for using the Azure Event Hubs SDK in TypeScript. It demonstrates best practices for high-throughput event streaming, including batch event sending, targeted partitioning, and robust event consumption. Covers advanced features like checkpointing, starting from specific positions, and handling event properties, making it ideal for building scalable, real-time data ingestion pipelines.

This skill details advanced techniques for enhancing the effective context capacity of LLMs. It outlines four core strategies—Compaction, Observation Masking, KV-Cache Optimization, and Context Partitioning—to prevent context limits from constraining task complexity. By strategically managing token usage, users can reduce operational costs, minimize latency, and implement robust, long-running agent systems for handling large documents or conversations.

Actionable guidance for analyzing plans, indexing, connection pooling, partitioning, and detecting N+1 queries to keep PostgreSQL and MySQL workloads fast and reliable.

Automates designing and implementing table partitioning strategies to keep large databases performant, optimize time-series workloads, and shorten maintenance windows, with guidance on key selection, SQL scripts, and query tuning.

Expert guidance on designing highly scalable, distributed NoSQL databases, specifically covering Apache Cassandra and Amazon DynamoDB. This skill emphasizes the 'Query-First' modeling approach, teaching best practices like partitioning, denormalization, single-table design, and avoiding common anti-patterns (e.g., hot partitions, joins) to ensure optimal read/write performance at massive scale.

Provides PostgreSQL optimization advice covering index design, query plan inspection, partitioning, JSONB tweaks, connection pooling, and tuning checkpoints to stabilize OLTP workloads.

Guides building, tuning, and validating production Apache Spark jobs, covering DataFrame/RDD choices, partitioning, broadcast joins, skew handling, caching, and cluster configuration for big data pipelines.

This guide provides advanced patterns and best practices for optimizing Apache Spark jobs. It covers critical areas like effective partitioning, memory tuning, minimizing data skew, and optimizing different types of joins (broadcast, bucket). Use this when troubleshooting slow, large-scale data processing workflows or needing to scale Spark pipelines efficiently and reliably.

Master advanced techniques for scaling Supabase projects to handle high production load. This skill covers six critical layers: implementing read replicas for analytics, optimizing connectivity using connection pooling (Supavisor), upgrading compute resources, utilizing CDN caching for Storage, deploying Edge Functions regionally, and performing database table partitioning. Ideal for engineers preparing for traffic spikes or optimizing large-scale database architectures.

A comprehensive guide for deploying and optimizing the Windsurf AI IDE across large, complex organizations (50+ developers). Covers critical enterprise topics including monorepo partitioning strategies, managing workspace performance degradation, central configuration distribution, credit budgeting models, and necessary network/IT infrastructure whitelisting for seamless large-scale adoption.

This guide details the design and implementation of security zones and conduits for Industrial Automation and Control Systems (IACS) following the stringent standards of IEC 62443-3-2. It enables risk-based network partitioning, assigning Security Level Targets (SL-T), and enforcing granular conduit controls. Use this when retrofitting flat OT networks or designing greenfield facilities to achieve IEC 62443 compliance, validating boundaries against the Purdue Reference Model.