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Use when you need to implement or improve Java logging and observability — including selecting SLF4J with Logback/Log4j2, applying proper log levels (ERROR, WARN, INFO, DEBUG, TRACE), parameterized logging, correlation context, secure logging without sensitive data exposure, environment-specific configuration, log aggregation, monitoring, and alerting. This should trigger for requests such as Improve logging; Apply logging; Refactor logging; Add logging support; Review SLF4J structured logging in Java code. Part of Plinth Toolkit

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Configure GKE logging, metrics collection, dashboards, and alerts with Cloud Logging, Cloud Monitoring, and managed Prometheus. Diagnose missing measurements, collection failures, permission errors, and alert rule problems to identify appropriate configuration changes.

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• Setting up GKE logging and metrics collection
• Investigating missing Prometheus metrics
• Planning dashboards and alerts for cluster health

Turn plain-language requests into Cloud Logging queries for Google Cloud. Generate service-specific filters to find errors, investigate issues, or review audit logs using LQL, the language used to search these logs.

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• Finding recent error logs
• Filtering logs for a specific Google Cloud service
• Investigating who changed or accessed a resource

Configure Cloud Logging within one Google Cloud project. Set storage locations, retention periods, routing rules, and viewing permissions; create metrics from logs; and adjust stored volume through exclusions or sampling, which retains only a portion of entries.

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• Set regional log storage and retention periods
• Restrict access to sensitive logs
• Count specific errors with logs-based metrics

Configure Windows security logs for threat detection and incident investigation. Covers detailed audit policies, process command line recording, log storage sizing, and centralized forwarding so monitoring systems receive useful authentication and activity records.

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• Record process launches with their command lines
• Monitor successful and failed sign-ins
• Forward Windows security events to a central monitoring system

Search Windows PowerShell logs for traces of Empire, a framework used after a system is compromised. Identify characteristic launch commands, encoded code, module calls, and communication paths, then report suspicious events with timelines and severity scores.

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• Investigating suspected Empire activity
• Checking encoded commands and communication paths
• Building detection rules from Empire indicators

Investigate slow or failing requests in Google Cloud using Cloud Trace. Filter traces by duration or error status, inspect spans representing individual operations, and retrieve related Cloud Logging entries to investigate bottlenecks and exceptions.

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• Find requests exceeding a latency threshold
• Inspect operation hierarchies within a trace
• Investigate failures using related application logs

Install and configure WizTelemetry Logging in KubeSphere to collect container output and file logs. Use its API to filter logs by workload, time, or keywords, retrieve statistics, and export results.

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• Deploy log collection to selected clusters
• Enable collection of log files inside containers
• Search logs by keyword, workload, and time

Expert logging guidance based on Boris Tane's loggingsucks.com philosophy. Use when implementing logging, adding observability, debugging production issues, or reviewing code that includes log statements. Covers wide events architecture, structured logging, smart sampling, and high-cardinality field design.

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Configures Windows Event Logging with advanced audit policies to generate high-fidelity security events for threat detection and forensic investigation. Use when enabling audit policies for logon events, process creation, privilege use, and object access to feed SIEM detection rules. Activates for requests involving Windows audit policy, event log configuration, security logging, or detection-oriented logging.

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Implement structured logging with JSON formats, log levels (DEBUG, INFO, WARN, ERROR), contextual logging, PII handling, and centralized logging. Use for logging, observability, log levels, structured logs, or debugging.

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Configures Windows Event Logging with advanced audit policies to generate high-fidelity security events for threat detection and forensic investigation. Use when enabling audit policies for logon events, process creation, privilege use, and object access to feed SIEM detection rules. Activates for requests involving Windows audit policy, event log configuration, security logging, or detection-oriented logging.

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Configures Windows Event Logging with advanced audit policies to generate high-fidelity security events for threat detection and forensic investigation. Use when enabling audit policies for logon events, process creation, privilege use, and object access to feed SIEM detection rules. Activates for requests involving Windows audit policy, event log configuration, security logging, or detection-oriented logging.

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Set up monitoring for deployed agents to inspect execution paths, latency, and model interactions. It explains Cloud Trace, prompt and response logging, BigQuery analytics, and external monitoring integrations, with checks for missing data and unwanted content capture.

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• Investigating agent latency and execution errors
• Configuring prompt and response logging
• Analyzing agent events in BigQuery

Generates structured logging infrastructure using os.log/Logger to replace print() statements. Use when user wants to add proper logging, replace print statements, or set up app logging.

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Java logging best practices with SLF4J, structured logging (JSON), and MDC for request tracing. Includes AI-friendly log formats for Claude Code debugging. Use when user asks about logging, debugging application flow, or analyzing logs.

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World-class application logging - structured logs, correlation IDs, log aggregation, and the battle scars from debugging production without proper logsUse when "log, logging, logger, debug, trace, audit, structured log, correlation id, request id, log level, winston, pino, bunyan, log4j, logging, observability, debugging, monitoring, tracing, structured-logs, correlation, aggregation" mentioned.

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Configures structured logging with ILogger<T> and ILoggerFactory following Microsoft best practices. Includes Serilog setup, log enrichment, and logging source generators for high-performance logging.

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Use this skill when the user asks about logging / log hauling operations — short-haul exemption specifics for logging, log truck securement, axle weights, state-by-state logging permits (especially OR, WA, ID, BC), bunk + stake configurations, and how logging fits into FMCSA + state rules. Reference 49 CFR 393 for cargo securement of logs.

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Complete guide for xUnit test output and logging. Use when you need to implement test output, diagnostic logging, or ILogger alternatives in xUnit tests. Covers ITestOutputHelper injection, AbstractLogger pattern, structured output design. Includes XUnitLogger, CompositeLogger, performance test diagnostic tool implementations. Keywords: ITestOutputHelper, ILogger testing, test output xunit, test output, test logging, AbstractLogger, XUnitLogger, CompositeLogger, testOutputHelper.WriteLine, test diagnostics, logger mock, test log, structured output, Received().Log

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Prevents logging sensitive user data with redaction rules, logging policies, and safe log formatting. Use for "PII redaction", "log privacy", "GDPR logging", or "data privacy".

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Build or review Java Spring Boot backends using examples for web APIs, separate application layers, and database access. Covers input validation, error handling, caching, background processing, and logging to guide maintainable implementations.

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• Designing web APIs and separating application layers
• Reviewing database access and transactions
• Adding input validation and centralized error handling

Find console output left in production JavaScript and help remove it, disable it by environment, or replace it with a logging service. Reviews cover source code and browser execution paths, including how to verify the changes.

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• Checking for debug logs before release
• Separating development and production logging
• Configuring builds to remove console output

Plan centralized audit logging for infrastructure and applications. Use configuration examples and checklists to record security events, define retention, assess tamper detection, and connect logs to SIEM platforms, systems that collect and analyze security information.

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• Centralize login and permission-change records
• Add structured audit logs to applications
• Review retention and tamper-detection requirements