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Log4J
Logging is the process of recording events that happen inside your application while it runs.
Instead of printing random println! statements, logging gives you:
structured output control over verbosity ability to route logs to files, systems, or dashboards
In production systems, logs are not optional. They are your only visibility into system behavior.
In real systems:
- pipelines fail at 2 AM
- APIs timeout
- data gets corrupted silently
Without logs, you’re gone.
Logging helps you:
- trace failures
- debug issues
- audit data movement
- monitor system health
Example:
ETL job fails -> logs show which partition failed Streaming job lags -> logs show processing delay API ingestion fails -> logs show error response
log4rs is inspired by Java framework log4j. Same idea in a different ecosystem.
Tools
https://github.com/sevdokimov/log-viewer
https://github.com/Better-Player/log4j-rs
LogViewPlus https://www.logviewplus.com/log-viewer.html
Another one https://www.xplg.com/log4j-viewer-analyzer/
Apart from this, there are a lot of Big Data Real-time log viewers, such as
- Splunk
- Logstash
Log Levels
| Level | Purpose |
|---|---|
| ERROR | Something failed |
| WARN | Something unexpected |
| INFO | General events |
| DEBUG | Debugging info |
| TRACE | Very detailed debugging |
supported by the macros
info! warn! error! debug! trace!
log4rs implementation
| Concept | Meaning |
|---|---|
| Appender | Where logs go (console, file) |
| Encoder | Format of logs (text, JSON) |
| Logger | Rules for filtering logs |
| Root | Default logging behavior |
git clone https://github.com/gchandra10/rust_log4rs_demo