“logging”的搜索结果

When setting up telemetry, debugging distributed systems, or standardizing application output.

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Guide for training outputs, metrics logging, logtree reports, tracing/profiling, and debugging training runs. Use when the user asks about training logs, metrics, debugging, tracing, profiling, timing, Gantt charts, or understanding training output files.

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Follow these patterns when implementing activity emission and audit logging in OptAIC. Use for emitting ActivityEnvelopes on mutations (create, update, delete, execute), designing payloads, and ensuring audit compliance.

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Apply HIPAA-compliant security practices for Abridge clinical AI integrations. Use when securing PHI in transit/at rest, configuring access controls, implementing audit logging, or preparing for HIPAA security audits. Trigger: "abridge security", "abridge HIPAA", "abridge PHI protection", "abridge access control", "abridge audit logging".

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Detect PowerShell Empire framework artifacts in Windows event logs by identifying Base64 encoded launcher patterns, default user agents, staging URL structures, stager IOCs, and known Empire module signatures in Script Block Logging events.

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Windows アプリ開発 (WinUI 3 / Windows App SDK) のテスト・性能・アクセシビリティ・スレッド。 MSTest, xUnit, NUnit, WinAppDriver, Appium, Playwright, WebView2 テスト, CI, WACK, MSIX サイドローディング, version adaptive。LoggingChannel / ETW, WPT, WPA, プロファイリング, GC, 起動性能, XAML 最適化, ListView/GridView 仮想化。UI Automation, AutomationProperties, automation peers, キーボード操作性, ハイコントラスト, Narrator。DispatcherQueue, DispatcherQueueTimer, WinRT 非同期パターン, async/await, ConfigureAwait, スレッドプール, STA/MTA, デッドロック回避, バックグラウンドタスク。

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Pino (高速 JSON 構造化ロガー for Node.js、Fastify 標準ロガー) リファレンス。 logger, child logger, log levels (info / warn / error / debug / trace)、transport、 pretty print (pino-pretty)、redaction (機密情報マスキング)、serializers、 async / sync logging、ファイル出力、structured logging。

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Use when adding monitoring, metrics, logging, or tracing to Spring AI or LLM integration code. Covers token tracking, latency measurement, cost estimation, and prompt/response logging. Use when user mentions AI monitoring, token costs, or LLM observability.

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Read and analyze log entries from Cloud Logging using the gcloud CLI.

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Design robust error handling strategies including try-catch blocks, custom error classes, error boundaries, graceful degradation, and comprehensive logging. Use when implementing exception handling, creating custom error types, setting up error boundaries in React, designing error response formats for APIs, implementing retry logic, handling async errors and promise rejections, logging errors for monitoring, creating user-friendly error messages, or building fault-tolerant systems that fail gracefully.

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Implement comprehensive monitoring, logging, metrics, tracing, and alerting for production applications to ensure reliability and quick incident response. Use when setting up application monitoring, implementing structured logging, creating metrics and dashboards, setting up alerts, implementing distributed tracing, monitoring performance, tracking errors, or building observability into applications.

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Design error handling strategies for TypeScript and Python applications — exception hierarchies, Result/Either types, retry patterns, error boundaries, and structured error logging. Use when designing error handling architecture, choosing between exceptions and Result types, implementing retry logic, or building error recovery flows. Activate on "error handling", "exception hierarchy", "Result type", "retry pattern", "circuit breaker", "error boundary", "Pokemon exception". NOT for debugging specific runtime errors, logging infrastructure setup, or monitoring/alerting configuration.

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Parse Windows PowerShell Script Block Logs (Event ID 4104) from EVTX files to detect obfuscated commands, encoded payloads, and living-off-the-land techniques. Uses python-evtx to extract and reconstruct multi-block scripts, applies entropy analysis and pattern matching for Base64-encoded commands, Invoke-Expression abuse, download cradles, and AMSI bypass attempts.

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Detect PowerShell Empire framework artifacts in Windows event logs by identifying Base64 encoded launcher patterns, default user agents, staging URL structures, stager IOCs, and known Empire module signatures in Script Block Logging events.

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Creates consistent error handling with custom error classes, HTTP status mapping, structured logging, safe client messages, and error taxonomy. Use when standardizing "error handling", "logging", "error responses", or "exception management".

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Complete observability & reliability engineering system. Use when designing monitoring, implementing structured logging, setting up distributed tracing, building alerting systems, creating SLO/SLI frameworks, running incident response, conducting post-mortems, or auditing system reliability. Covers all three pillars (logs/metrics/traces), alert design, dashboard architecture, on-call operations, chaos engineering, and cost optimization.

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通过具体实现示例设计或审查Java的Quarkus服务，涵盖REST API分层、Panache数据访问、Camel消息路由、RabbitMQ集成及异步处理。

• 划分REST API的职责
• 集成Camel与RabbitMQ
• 审查Panache数据保存逻辑

为 Quarkus 应用实现并检查身份认证、访问权限和输入验证，同时涵盖机密信息管理、密码哈希、请求限制、审计日志及依赖项已知漏洞检查。

• 为 Quarkus API 添加 JWT 或 OIDC 认证
• 检查角色权限与数据归属验证
• 审查输入验证与数据库查询

检索学术与技术文献，按预设标准筛选并综合比较。记录检索过程和排除理由，梳理研究分歧与未解问题，区分证据置信度并核查引用，形成可追溯的综述。

• 了解研究主题的整体情况
• 撰写记录检索步骤的文献综述
• 整理研究分歧与未解决问题

检查Django应用的登录、权限、输入处理和生产配置，梳理恶意查询、脚本注入及非预期请求的防护，并审查文件上传、API保护、密钥管理和安全日志。

• 审查登录与用户权限
• 上线前检查生产配置
• 审查输入处理与请求防护

将PyTorch训练代码整理为LightningModule和Trainer结构，配置验证、日志记录、模型保存及多GPU分布式训练。

• 迁移现有PyTorch训练代码
• 添加验证指标记录和模型保存
• 配置多GPU训练

为生产功能设计日志、指标、跨服务追踪和告警，记录请求标识与处理起点，并验证实际输出和通知，帮助了解运行状态及故障原因。

• 完善生产功能的监控信息
• 关联不同服务的日志
• 审查告警与响应操作手册

协助使用FastAPI开发Python网页API，整理输入验证、错误处理和异步调用，并通过代码组织与缓存兼顾实现的可读性和响应性能。

• 设计API路由与输入验证
• 检查异步数据库与API调用
• 整理错误处理和日志

设置和检查OmniRoute的API密钥认证及管理界面登录，区分Bearer凭据与会话Cookie，查询认证状态、获取CSRF令牌，并处理外部身份认证登录。

• 设置OmniRoute的API密钥认证
• 登录和退出管理界面
• 查询认证状态与CSRF令牌