logback
Logback - flexible and powerful logging framework for Java and Spring Boot applications. Successor to Log4j with native SLF4J support, async logging, and automatic file rotation. USE WHEN: user mentions "logback", "spring boot logging", "java logging configuration", asks about "logback-spring.xml", "rolling file appender", "async logging in java" DO NOT USE FOR: SLF4J API usage - use `slf4j` instead, Log4j2 - use separate Log4j2 skill, Node.js logging - use `winston` or `pino` instead, Python logging - use `python-logging` instead
What this skill does
# Logback - Quick Reference
## When to Use This Skill
- Configure logging in Spring Boot/Java applications
- File appender with rotation
- High-performance async logging
> **Deep Knowledge**: Use `mcp__documentation__fetch_docs` with technology: `logback` for comprehensive documentation.
## Configuration
### logback-spring.xml (Spring Boot)
```xml
<?xml version="1.0" encoding="UTF-8"?>
<configuration>
<include resource="org/springframework/boot/logging/logback/defaults.xml"/>
<property name="LOG_PATH" value="${LOG_PATH:-logs}"/>
<property name="LOG_FILE" value="${LOG_FILE:-app}"/>
<!-- Console Appender -->
<appender name="CONSOLE" class="ch.qos.logback.core.ConsoleAppender">
<encoder>
<pattern>%clr(%d{yyyy-MM-dd HH:mm:ss.SSS}){faint} %clr(${LOG_LEVEL_PATTERN:-%5p}) %clr(${PID:- }){magenta} %clr(---){faint} %clr([%15.15t]){faint} %clr(%-40.40logger{39}){cyan} %clr(:){faint} %m%n${LOG_EXCEPTION_CONVERSION_WORD:-%wEx}</pattern>
</encoder>
</appender>
<!-- Rolling File Appender -->
<appender name="FILE" class="ch.qos.logback.core.rolling.RollingFileAppender">
<file>${LOG_PATH}/${LOG_FILE}.log</file>
<rollingPolicy class="ch.qos.logback.core.rolling.SizeAndTimeBasedRollingPolicy">
<fileNamePattern>${LOG_PATH}/${LOG_FILE}.%d{yyyy-MM-dd}.%i.log.gz</fileNamePattern>
<maxFileSize>100MB</maxFileSize>
<maxHistory>30</maxHistory>
<totalSizeCap>3GB</totalSizeCap>
</rollingPolicy>
<encoder>
<pattern>%d{yyyy-MM-dd HH:mm:ss.SSS} [%thread] %-5level %logger{36} - %msg%n</pattern>
</encoder>
</appender>
<!-- Async Appender -->
<appender name="ASYNC" class="ch.qos.logback.classic.AsyncAppender">
<appender-ref ref="FILE"/>
<queueSize>512</queueSize>
<discardingThreshold>0</discardingThreshold>
</appender>
<!-- Logger Configuration -->
<logger name="com.myapp" level="DEBUG"/>
<logger name="org.springframework" level="INFO"/>
<logger name="org.hibernate.SQL" level="DEBUG"/>
<root level="INFO">
<appender-ref ref="CONSOLE"/>
<appender-ref ref="ASYNC"/>
</root>
<!-- Profile-specific -->
<springProfile name="prod">
<root level="WARN">
<appender-ref ref="ASYNC"/>
</root>
</springProfile>
</configuration>
```
### JSON Format (ELK Stack)
```xml
<appender name="JSON" class="ch.qos.logback.core.ConsoleAppender">
<encoder class="net.logstash.logback.encoder.LogstashEncoder">
<includeMdcKeyName>requestId</includeMdcKeyName>
<includeMdcKeyName>userId</includeMdcKeyName>
</encoder>
</appender>
```
## MDC Usage
```java
import org.slf4j.MDC;
MDC.put("requestId", UUID.randomUUID().toString());
MDC.put("userId", user.getId());
try {
// Business logic
} finally {
MDC.clear();
}
```
## When NOT to Use This Skill
- **SLF4J API questions**: Focus on API usage, not Logback implementation details
- **Log4j2 configuration**: Different XML structure and features
- **Application code logging**: Use SLF4J API, Logback is just the implementation
- **Non-Java projects**: Use language-appropriate logging frameworks
- **Simple console output**: System.out may be sufficient for basic scripts
## Anti-Patterns
| Anti-Pattern | Why It's Bad | Solution |
|--------------|--------------|----------|
| Synchronous file appender in high-traffic | Blocks application threads | Use `AsyncAppender` wrapper |
| No rolling policy | Logs fill disk space | Use `RollingFileAppender` with size/time policies |
| Logging to console in production | Performance overhead, lost logs | Use file appenders, ship to centralized logging |
| DEBUG level in production | Performance impact, disk usage | Use INFO or WARN in production profiles |
| Not clearing MDC | Memory leaks, wrong context in threads | Always clear MDC in finally block |
| Hardcoded log paths | Breaks across environments | Use properties: `${LOG_PATH}` |
## Quick Troubleshooting
| Issue | Cause | Solution |
|-------|-------|----------|
| Configuration not loaded | Wrong file name/location | Use `logback-spring.xml` in src/main/resources |
| Logs not rotating | Missing rolling policy | Add `SizeAndTimeBasedRollingPolicy` |
| Performance degradation | Synchronous appenders | Wrap with `AsyncAppender` |
| MDC values not appearing | Pattern missing MDC placeholders | Add `%X{key}` to pattern |
| Duplicate log entries | Logger additivity enabled | Set `additivity="false"` on logger |
| Profile-specific config ignored | Using logback.xml instead | Rename to `logback-spring.xml` for Spring profiles |
Related in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.