Skill UI

A comprehensive guide to configuring Sentry error tracking and performance monitoring across modern application architectures. Learn how to implement coherent, end-to-end distributed tracing for monoliths, microservices, serverless functions (Lambda/Cloud Functions), event-driven systems, SPAs, and mobile applications, ensuring all application hops are monitored from a single source.

A comprehensive guide and template for deploying applications from idea to production. It covers modern DevOps practices, including containerization with Docker, robust CI/CD workflows using GitHub Actions, and infrastructure management with AWS SAM and Terraform. Includes setup for monitoring, health checks, and scalable cloud deployments.

This guide teaches security teams how to deploy and operationalize Amazon GuardDuty for continuous, comprehensive threat detection across entire AWS accounts and workloads. It covers enabling protection plans for S3, EKS, EC2 runtime monitoring, and Lambda, interpreting various finding severity levels, and building robust, automated incident response playbooks using EventBridge and AWS Lambda for immediate containment actions.

This utility implements comprehensive Cloud Workload Protection (CWPP) by monitoring compute workloads on cloud instances (EC2/GCE). It provides runtime security controls, detecting process anomalies, unauthorized binary execution, cryptomining activity, and suspicious network connections using AWS and Google APIs. Ideal for establishing robust security postures and meeting compliance requirements.

A comprehensive guide and toolkit for optimizing and monitoring consumption-based costs across the Adobe Creative Cloud ecosystem. It provides strategies and code snippets for tracking usage (credits, transactions) for Firefly, PDF Services, Photoshop, and Lightroom APIs. Use this when implementing usage monitoring, managing billing alerts, or reducing operational expenses related to Adobe API calls.

Facilitates the secure deployment of Adobe-powered applications across multiple modern cloud environments, including Vercel (serverless), Google Cloud Run (containers), and Adobe App Builder. This integration manages complex OAuth credential injection and sets up health monitoring endpoints, making it ideal for moving Adobe API integrations into production systems.

This guide provides a comprehensive observability stack for Apple Notes on macOS. Since Notes lacks a built-in metrics API, this solution demonstrates how to monitor key health indicators—such as note/folder counts, system latency, and iCloud sync daemon status—by polling via JXA and Bash scripts. It includes scripts for scheduled health checks, trend visualization, and robust error handling for production monitoring environments.

This skill provides comprehensive deployment scaffolding for Miro REST API v2 integrations. It manages the entire lifecycle, including setting up OAuth 2.0 authentication, handling incoming webhooks, and ensuring continuous health monitoring. It supports deployment across major cloud platforms like Vercel, Fly.io, and Google Cloud Run, simplifying complex multi-environment SaaS application setups.

This skill provides a comprehensive framework for setting up robust observability for Navan API integrations in production environments. It guides users through implementing structured logging, tracking request latency, classifying various errors (auth, rate limit, server), and monitoring the OAuth token refresh lifecycle. Includes practical steps and YAML examples for configuring alerts and building dashboards in platforms like Datadog, CloudWatch, or Prometheus/Grafana.

This skill uses the OCI Usage API and SDK to programmatically track spending across compartments, services, and shapes. It allows users to query granular cost data, set detailed budget alerts (e.g., 80%, 95%, forecast), and identify cost optimization opportunities like utilizing Always Free tiers or preemptible instances, ensuring proactive and precise cloud cost management.

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.