Skill UI

A comprehensive workflow bundle covering the entire cloud-native development lifecycle. It guides users through critical phases, including cloud infrastructure setup (AWS, Azure, GCP, Terraform IaC), container orchestration with Kubernetes, robust CI/CD pipeline automation, observability implementation, security hardening, cost optimization, and disaster recovery planning. This ensures best practices across all stages of modern application deployment.

A comprehensive guide detailing systematic strategies and patterns for optimizing cloud spending across major platforms including AWS, Azure, and GCP. It covers best practices for rightsizing resources, leveraging reserved instances, implementing lifecycle policies, and setting up robust cost governance, ensuring cost efficiency without sacrificing performance or reliability.

An expert in designing, implementing, and optimizing scalable, reliable, and cost-effective data pipelines for both batch and streaming data. Covers advanced topics including ETL/ELT patterns, Kappa/Lambda architectures, workflow orchestration (Airflow/Prefect), transformation using dbt/Spark, and managing modern storage formats like Delta Lake and Iceberg. Focuses heavily on data quality, monitoring, and cost optimization strategies.

This guide provides a comprehensive framework for minimizing cloud expenditure on Databricks. It covers identifying cost drivers via system billing tables, implementing cluster policies, utilizing spot instances for batch processing, right-sizing SQL warehouses, and automating the shutdown of idle development clusters. Use it when managing cloud spending or optimizing data platform usage.

This skill provides comprehensive observability tools for Groq API integrations. It instruments the client to track critical performance metrics such as Time to First Token (TTFT), total latency, token throughput, and estimated cost. Furthermore, it sets up Prometheus exporters and alert rules to monitor rate limit status and detect performance degradation in real-time, ensuring robust production monitoring.

An expert architect specializing in designing, implementing, and managing complex hybrid and multi-cloud environments. Expertise spans major public clouds (AWS, Azure, GCP), private clouds (OpenStack, VMware), and container platforms (Kubernetes). Focus areas include cross-cloud networking, Infrastructure as Code (IaC) using Terraform, workload optimization, zero-trust security implementation, and FinOps cost management.

This skill provides a comprehensive framework for monitoring Mistral AI API usage in production. It includes an instrumented client wrapper (TypeScript) to automatically capture critical metrics like latency, token consumption, cost, and error rates. Furthermore, it integrates with Prometheus for metric storage and Grafana for visualization, allowing users to set up sophisticated alerting rules for performance degradation, rate limiting, or cost spikes.

Provides a comprehensive monitoring solution for the Perplexity Sonar API. It tracks critical performance metrics, including latency (p95), cost per query, error rates, and citation quality. This skill is essential for implementing production monitoring dashboards, configuring proactive alerts (e.g., high latency, zero citations), and ensuring the API's stability and high-quality output in real-world applications.

This skill provides comprehensive monitoring capabilities for GPU instances running on Vast.ai. It collects key metrics including GPU utilization, instance uptime, temperature, and accumulated costs. Use this when setting up operational monitoring dashboards, configuring critical alerts (e.g., idle GPUs, high temperature, budget overruns), or automating resource usage tracking in a cloud computing environment.

A comprehensive guide to optimizing cloud expenditure on the Vercel platform. It details how to understand the Fluid Compute pricing model, identify key cost drivers (such as function execution time, bandwidth, and middleware invocations), and implement best practices like edge caching, memory right-sizing, and aggressive asset caching. Use this when analyzing high Vercel billing, implementing cost controls, or managing a SaaS budget.

A powerful tool for architecting production-grade multi-agent workflows. It allows users to define complex, multi-step AI pipelines using structured patterns (sequential, parallel, hierarchical). Key features include defining explicit handoff contracts, implementing robust failure handling, and managing context/cost discipline across long-running processes, ensuring reliable and scalable AI system deployment.

A comprehensive expert system simulating 15+ years of experience in global trade compliance (US, EU, UK, APAC). It specializes in HS/HTS classification, tariff optimization, sanctioned party screening (SDN), and preparing complex customs documentation to ensure legal, cost-effective, and compliant cross-border goods movement.