Skill UI

Automate deployment of web, DNS, document, and AWS key Canary Tokens via the Thinkst Canary API to detect breaches through deception, monitor alerts, and report coverage across your environment.

Deploys honeypot shares, canary files, and Thinkst Canary appliances to detect ransomware activity early via deception alerts tied to file access and modification.

Guide to deploying OpenCanary, Cowrie, or T-Pot honeypots to detect unauthorized access, lateral movement, and reconnaissance while forwarding alerts to a SIEM for faster incident response.

Deploys deception technology such as honeypots, honeytokens, Canary devices, and decoy documents across critical segments to alert SOC teams when attackers bypass perimeter defenses and attempt lateral movement, credential abuse, or internal reconnaissance.

This skill monitors for regressions on deployed URLs following deployments, merges, or dependency upgrades. It performs comprehensive checks including HTTP status, console errors, network failures, performance metrics (LCP/CLS/INP), and crucial API endpoint health, ensuring service stability in production or staging environments. Supports quick checks, continuous monitoring, and differential comparison against baselines.

A comprehensive, step-by-step checklist for safely deploying Adobe API integrations (including Firefly, PDF Services, and I/O Events) to a production environment. It covers prerequisite checks, credential security, health monitoring, gradual canary rollouts, error handling, and immediate rollback procedures to ensure maximum system stability and reliability.

A comprehensive checklist for deploying Claude API integrations to a production environment. It covers essential best practices for reliability, observability, and cost control, including authentication procedures, advanced error handling, rate limit management, health check implementation, and infrastructure deployment strategies (e.g., canary releases) to ensure a smooth and stable launch.

This skill provides advanced integration for deploying applications on Fly.io, focusing on edge computing architectures. It covers building production-ready Docker images, configuring `fly.toml` for services and health checks, and executing sophisticated deployment strategies like blue-green and canary releases. It ensures reliable, scalable deployment across multiple regions, including automated rollbacks and micro-VM optimization.