setting-up-synthetic-monitoring
关于
This skill automates synthetic monitoring setup for applications, enabling proactive tracking of performance and availability. It configures uptime, transaction, and API monitoring by identifying critical endpoints and designing monitoring scenarios. Use it when you need to set up performance tracking, configure alerts, or establish dashboards for key user journeys.
快速安装
Claude Code
推荐/plugin add https://github.com/jeremylongshore/claude-code-plugins-plusgit clone https://github.com/jeremylongshore/claude-code-plugins-plus.git ~/.claude/skills/setting-up-synthetic-monitoring在 Claude Code 中复制并粘贴此命令以安装该技能
技能文档
Overview
This skill streamlines the process of setting up synthetic monitoring, enabling proactive performance tracking for applications. It guides the user through defining key monitoring scenarios and configuring alerts to ensure optimal application performance and availability.
How It Works
- Identify Monitoring Needs: Determine the critical endpoints, user journeys, and APIs to monitor based on the user's application requirements.
- Design Monitoring Scenarios: Create specific monitoring scenarios for uptime, transactions, and API performance, including frequency and location.
- Configure Monitoring: Set up the synthetic monitoring tool with the designed scenarios, including alerts and dashboards for performance visualization.
When to Use This Skill
This skill activates when you need to:
- Implement uptime monitoring for a web application.
- Track the performance of critical user journeys through transaction monitoring.
- Monitor the response time and availability of API endpoints.
Examples
Example 1: Setting up Uptime Monitoring
User request: "Set up uptime monitoring for my website example.com."
The skill will:
- Identify example.com as the target endpoint.
- Configure uptime monitoring to check the availability of example.com every 5 minutes from multiple locations.
Example 2: Monitoring API Performance
User request: "Configure API monitoring for the /users endpoint of my application."
The skill will:
- Identify the /users endpoint as the target for API monitoring.
- Set up monitoring to track the response time and status code of the /users endpoint every minute.
Best Practices
- Prioritize Critical Endpoints: Focus on monitoring the most critical endpoints and user journeys that directly impact user experience.
- Set Realistic Thresholds: Configure alerts with realistic thresholds to avoid false positives and ensure timely notifications.
- Regularly Review and Adjust: Periodically review the monitoring configuration and adjust scenarios and thresholds based on application changes and performance trends.
Integration
This skill can be integrated with other plugins for incident management and alerting, such as those that handle notifications via Slack or PagerDuty, allowing for automated incident response workflows based on synthetic monitoring results.
GitHub 仓库
相关推荐技能
content-collections
元Content Collections 是一个 TypeScript 优先的构建工具,可将本地 Markdown/MDX 文件转换为类型安全的数据集合。它专为构建博客、文档站和内容密集型 Vite+React 应用而设计,提供基于 Zod 的自动模式验证。该工具涵盖从 Vite 插件配置、MDX 编译到生产环境部署的完整工作流。
creating-opencode-plugins
元该Skill为开发者创建OpenCode插件提供指导,涵盖命令、文件、LSP等25+种事件类型。它详细说明了插件结构、事件API规范及JavaScript/TypeScript实现模式,帮助开发者构建事件驱动的模块。适用于需要拦截操作、扩展功能或自定义AI助手行为的插件开发场景。
sglang
元SGLang是一个专为LLM设计的高性能推理框架,特别适用于需要结构化输出的场景。它通过RadixAttention前缀缓存技术,在处理JSON、正则表达式、工具调用等具有重复前缀的复杂工作流时,能实现极速生成。如果你正在构建智能体或多轮对话系统,并追求远超vLLM的推理性能,SGLang是理想选择。
evaluating-llms-harness
测试该Skill通过60+个学术基准测试(如MMLU、GSM8K等)评估大语言模型质量,适用于模型对比、学术研究及训练进度追踪。它支持HuggingFace、vLLM和API接口,被EleutherAI等行业领先机构广泛采用。开发者可通过简单命令行快速对模型进行多任务批量评估。
