From P4 Beginner to P7 Expert: Logging Skills Make All the Difference
# **Mastering the Art of Logging: From Rookie Mistakes to Expert Practices**
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## **Prologue — The Alert That Sparked a Realization**
One National Day holiday, I was lazily sprawled on a beach chair, beer in hand, soaking in the sea breeze — absolute bliss.
Suddenly, my phone erupted with alerts:
**"Disk space insufficient"**.
It wasn’t even my project, but curiosity made me poke around. The culprit? Logs. Gigantic, unchecked logs that had completely filled the disk. The colleague responsible sheepishly admitted: *"Forgot to hook up the automatic log cleanup script."* One manual cleanup later, the disk was happy again.
This reminded me that **logging feels trivial until it becomes critical** — either by flooding your system or leaving you stranded without vital information during incidents. Even experienced teams can neglect it due to cognitive bias: “small things” are ignored until they become **big problems**.
So today, let’s explore something all developers do daily, but **most don’t do right**: **writing logs**. Here’s my hard-earned guide to avoiding the pitfalls.
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## **Act One: Common Pitfalls in Newbie Logging**
Over the years, I’ve seen — and made — every logging mistake possible. Our first classic trap: **useless logs**.
### **Case Study: Xiao Zhang’s Log Disaster**
A junior dev, Xiao Zhang, faced an online bug — intermittent failures in order processing. His logs always said:
> “Order process error!”
No trace of *which* user, *which* order, or *why*. Here’s a simplified version of the code:
@Service
public class OrderService {
public void processOrder(OrderDTO order) {
try {
// ...business logic...
String customerName = order.getCustomer().getName(); // May cause NPE
log.info("OrderService start process order...");
} catch (Exception e) {
log.error("OrderService #order process error！");
}
}
}
This snippet contains **three rookie mistakes**:
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### **Mistake #1: Exceptions Swallowed Silently**
No stack trace printed, no rethrow — critical evidence gone. Debugging becomes guesswork.
### **Mistake #2: Missing Key Context**
“Order process error” is meaningless without IDs or parameters. In systems handling massive concurrent requests, this is a **needle in a haystack** problem.
### **Mistake #3: No Exception Details**
Without specifying the error type (NPE, DB timeout, RPC failure), you can’t locate the root cause quickly.
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**Lesson:**
Even if reproduction is possible, **bad logs mean no clues** — effectively logging for nothing.
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## **Act Two: The “Three Realms” of Logging Mastery**
Through years in tech, I’ve mapped dev logging maturity into three realms.
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### **Realm 1: P4 Newbie — “I Was Here” Logging**
#### **Traits**
- Random `System.out.println()` or `e.printStackTrace()`.
- Log statements like `log.info("111")`.
- Heavy use of string concatenation (`"value=" + var`).
#### **Dark Side**
- **Performance killer:** String concatenation runs even when log level is off.
- **Information loss:** Only `e.getMessage()` logged — no full trace.
- **Low value:** No levels or formatting, making centralized log analysis impossible.
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### **Realm 2: P5 Intermediate — “Business Ledger” Logging**
#### **Traits**
- Uses SLF4J/Logback, distinguishes INFO/WARN/ERROR.
- Logs business events (`log.info("Order placed, orderId={}")`).
#### **Pitfalls**
- **Information Islands:** Logs don’t tie together into a complete trace.
- **Missing Correlation:** No `trace_id` or key IDs for linking distributed requests.
**Example Problem Snippet:**
@Service
public class OrderService {
public void createOrder(OrderDTO order) {
try {
String userName = null;
userName.toLowerCase(); // NPE
} catch (Exception e) {
throw new BizException("Order creation failed"); // Error passed upward without detail
}
}
}
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### **Realm 3: P6/P7 Expert — Logging for Observability**
#### **Traits**
Logs as **diagnostic instruments**, not mere records.
#### **Key Principles**
1. **Structure Everything**: Use JSON logs for machine + human parsing.
2. **Context is King**: Attach `trace_id` with MDC for end-to-end tracing.
3. **Prevent Log Bombs**: Avoid large object dumps; implement sampling for high-frequency logs.
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**Example — Structured Error Logging:**log.error(
"{"event":"order_creation_failed", "order_id":"{}", "user_id":"{}", "error":"{}"}",
orderId, userId, e.getMessage()
);
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## **Act Three: The Mature Logging System**
A world-class logging system has **three capabilities**:
1. **Global Traceability** — Link all microservice calls via `trace_id`.
2. **Real-time Alerts** — Integrate logs tightly with alert mechanisms.
3. **Structured Indexing** — Ensure every log is machine-searchable.
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### **Capability One: Cross-System “God’s-Eye View”**
Unify logs across services into a visualizable trace chain — like Alibaba’s EagleEye.
### **Capability Two: “Just Right” Data**
Structured JSON with clear fields, plus rotation + expiration to prevent disk issues.
### **Capability Three: Automated Response**
Trigger alerts or scripts when error rates spike in a trace chain.
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## **Final Reflection**
Master logging is about evolving from **recording**, to **explaining**, to **mapping the entire system**.
Your logging reflects **your control over complexity**.
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> **Note:** Platforms like [AiToEarn](https://aitoearn.ai/) — though focused on cross-platform AI-generated content — share a similar principle: unify output, structure it, and make it actionable. AiToEarn’s integration of generation, publishing, analytics, and [model ranking](https://rank.aitoearn.ai) mirrors how robust logging connects, structures, and monetizes valuable system data.
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