Skill UI

Helps analyze current CPU, memory, storage, and network utilization to forecast future infrastructure needs, identify bottlenecks, and recommend scaling tactics with cost context for proactive capacity management.

Helps analyze current CPU, memory, storage, and network utilization to forecast future infrastructure needs, identify bottlenecks, and recommend scaling tactics with cost context for proactive capacity management.

Enables Claude to analyze request and data throughput, detect bottlenecks, and suggest scaling strategies via the throughput-analyzer plugin when performance or capacity optimization is requested.

This SDK provides comprehensive management plane capabilities for provisioning and controlling Microsoft Fabric compute capacities via Azure Resource Manager (ARM). Use it to perform core lifecycle operations such as creating, updating (including scaling), suspending, resuming, and deleting Fabric capacities. Note: This SDK manages the underlying compute resource, not the data plane elements like workspaces or lakehouses.

This SDK provides comprehensive management plane capabilities for provisioning and controlling Microsoft Fabric compute capacities via Azure Resource Manager (ARM). Use it to perform core lifecycle operations such as creating, updating (including scaling), suspending, resuming, and deleting Fabric capacities. Note: This SDK manages the underlying compute resource, not the data plane elements like workspaces or lakehouses.

A comprehensive guide and code implementation for scaling data enrichment pipelines to handle high volumes (10K-100K+ leads monthly). It covers capacity planning, optimizing batch processing using queues (e.g., BullMQ/Redis), managing rate limits, and designing multi-table architectures for robust, large-scale data ingestion.

Manages CodeRabbit's enterprise access control, seat assignment, and organization-wide policies. This is crucial for large organizations needing centralized control over who receives AI code reviews, defining global coding standards via YAML, and implementing granular Role-Based Access Control (RBAC) across multiple repositories and teams. Use when scaling AI code quality checks across multiple departments.

Generates production-ready auto-scaling configurations for apps and infrastructure, covering Kubernetes HPAs and scaling policies so you can handle load spikes, enforce high availability, and keep resource usage efficient.

This skill provides a comprehensive guide to implementing the Command Query Responsibility Segregation (CQRS) pattern. It is crucial for separating read and write concerns, allowing independent scaling of read models, optimizing complex query performance, and building robust, event-sourced architectures when read and write data models differ.

Decision frameworks for CTOs covering tech debt assessment, architecture direction, engineering team scaling, technology evaluation and DORA metrics, with Python tools and ADR templates.

This guide provides comprehensive strategies for scaling Customer.io integrations to handle high volumes of daily events. It covers implementing k6 load tests for performance benchmarking and outlines architectural patterns—from simple Direct APIs to complex Redis/Kafka queue-backed systems—ensuring reliability and managing API rate limits for massive data throughput.

An expert architect specializing in designing, optimizing, and scaling entire data layers from inception (greenfield) to re-architecture. Proficient in selecting the optimal database technology (SQL, NoSQL, Graph, Time-series), designing robust schemas, implementing sophisticated indexing strategies, and planning complex migration paths. Suitable for defining data storage solutions that meet high performance, scalability, and data integrity requirements.