How I Quickly Added Robust Logging to an Express App with AI‑Powered Trae IDE

Trae: Rescue Tool

After noticing my Express site becoming sluggish with rising server load despite stable UV numbers, I suspected abnormal traffic such as high‑frequency refreshes or crawlers. The project lacked any access logs, making diagnosis impossible, so I turned to the AI‑powered Trae IDE to quickly add logging.

Practical: Stepwise Improve Express Logging

Step One: Quickly Add Basic Logging

I opened

app.js

and asked Trae to add a logging middleware. Within seconds Trae installed

morgan

automatically and inserted the required import and usage code.

Trae prompted me to install

morgan

, clicked "Run", and the package was installed without manual

npm install

.

Behind the scenes Trae used the @Builder mode, which provides a full file system and terminal, allowing direct execution of npm commands.

After installing

morgan

, Trae generated the import and usage code, which I accepted and applied to the file. Running the app now prints request logs to the console.

Console logs are helpful but volatile; they disappear on restart and are hard to analyze.

Step Two: Persist Logs to Files and Enable Rotation

I wanted daily log files to avoid unlimited growth. I instructed Trae, using the

#

command and the "Web" capability, to search for a suitable library. It suggested

rotating-file-stream

, and I accepted the recommendation.

After running the app, an

access.log

file appeared in the

logs

directory, containing detailed entries with timestamps, HTTP methods, URLs, status codes, and response times.

Step Three: Separate Access and Error Logs

To keep logs tidy, I asked Trae to configure

morgan

so that 2xx/3xx responses go to

access.log

and 4xx/5xx responses go to

error.log

, both with daily rotation.

Modify morgan configuration: write successful (2xx/3xx) requests to 'access.log' and error (4xx/5xx) requests to 'error.log', both with daily rotation #Web

Trae produced a comprehensive solution, which I tested by accessing normal pages and non‑existent pages; logs were correctly split.

Step Four: Optimize Write Performance with Buffering

To reduce I/O overhead under heavy traffic, I asked Trae to add a write buffer that flushes every few seconds.

Add write interval to buffer log writes #Web

Trae supplied code that caches log entries in memory and writes them to disk every 5 seconds, improving performance.

Automating Code Commit

Using Trae’s custom agent feature, I created a "Git" agent, linked it to a GitHub MCP server with a personal token, and let the agent handle committing the updated code without manual terminal commands.

Finding the Culprit

Analyzing

access.log

and

error.log

revealed that aggressive foreign spiders ignored

robots.txt

, repeatedly hit the site even after receiving 429 responses, and were blocked by

nginx

. A few fixed IPs also showed crawler‑like patterns.

Further mitigation (rate limiting, IP blacklists) is possible, but the key takeaway is that the logging system pinpointed the source of the problem.

Trae: The Power of a True AI Engineer

The AI‑driven Trae IDE dramatically accelerated the implementation of a full‑featured logging solution for an Express app, from basic middleware to file rotation, error separation, performance buffering, and automated commits. It understands code context, provides accurate suggestions, and reduces the need for manual documentation lookup.

Both occasional backend developers and seasoned engineers can benefit from its ability to research latest library usage, enforce coding rules via custom agents, and streamline repetitive tasks.