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WordPress Server CPU Spikes Again: A Complete Troubleshooting Guide for Nginx 499, PHP-FPM, Redis, and W3TC Cold Cache

Figure 1: Alibaba Cloud ECS CPU usage sustained near 100% from 14:33 to 14:42, while memory usage remained generally stable

作者:

The day before, I had just finished optimizing the CDN cache for WordPress article detail pages, focusing on the issue where URLs with query strings could not effectively reuse the cache.

I originally thought that after handling this type of cache penetration, the server CPU alerts would ease.

But on the afternoon of July 28, 2026, an Alibaba Cloud ECS alert showed the CPU usage approaching 100% again.

This time, instead of continuing to focus on article detail pages and query strings, I started from Alibaba Cloud monitoring and checked all the way through:

  • Nginx Access Log
  • PHP-FPM logs and Slowlog
  • W3 Total Cache Object Cache
  • Redis Slowlog
  • W3TC Disk Enhanced Page Cache
  • Actual response times for Cold Cache and Cache HIT

Ultimately, I found:

This CPU saturation was not a simple continuation of the “detail page + query string” issue from the previous article. The core problem was that the server only had 1 vCPU, and when a large number of different URLs missed the Page Cache, they had to enter WordPress to dynamically generate the page. Just a few simultaneous high-cost Cold MISSes were enough to keep all PHP-FPM workers busy and max out the single CPU core.

One highly representative page was:

Plaintext
/page/9/

On the first Cold MISS, the TTFB reached:

Plaintext
10.602379 seconds

After the W3TC Page Cache was built, the second access only took:

Plaintext
0.016091 seconds

This gap ultimately became the key basis for the optimization direction in this round.


1. Alibaba Cloud CPU Sustained Near 100% Again

This alert occurred on the afternoon of July 28, 2026.

Checking the Alibaba Cloud ECS OS monitoring, I could see the CPU rapidly rising to near 100% starting around 14:33, and maintaining that level until about 14:42, when it suddenly dropped.

At the same time, the overall memory usage remained stable, without experiencing exhaustion in sync with the CPU.

Therefore, the initial conclusion was:

This was not a typical case of insufficient memory, but rather a sustained saturation of CPU compute resources.

Figure 1: Alibaba Cloud ECS CPU usage sustained near 100% from 14:33 to 14:42, while memory usage remained generally stable
Figure 1: Alibaba Cloud ECS CPU usage sustained near 100% from 14:33 to 14:42, while memory usage remained generally stable

After further opening Alibaba Cloud process monitoring, I could see that the high-CPU processes were basically:

Plaintext
php-fpm
php-fpm: pool www

This indicated that the main source of the load this time was not Nginx, but rather WordPress PHP dynamic requests.

Figure 2: Alibaba Cloud process monitoring shows that the top processes during the high CPU period were mainly php-fpm, indicating that the main compute pressure came from WordPress PHP dynamic requests
Figure 2: Alibaba Cloud process monitoring shows that the top processes during the high CPU period were mainly php-fpm, indicating that the main compute pressure came from WordPress PHP dynamic requests

2. Nginx Shows a Large Number of 499s

The Nginx Access Log for the production site is currently located at:

Plaintext
/data/wwwlogs/www.shuijingwanwq.com_nginx.log

After extracting the time window from 14:32 to 14:44, I obtained a total of:

Plaintext
844 requests

The status code distribution was as follows:

Plaintext
499    499
200    153
301    130
404     62

That is to say:

499s accounted for about 59%.

An Nginx 499 means the client actively closed the connection before the server finished responding.

Seeing 499s alone does not prove that PHP-FPM is the root cause.

But after aggregating by minute, the situation became very clear:

Plaintext
14:32  total=53   499=0
14:33  total=73   499=49
14:34  total=153  499=147
14:35  total=38   499=30
14:36  total=46   499=39
14:37  total=59   499=47
14:38  total=61   499=42
14:39  total=56   499=31
14:40  total=78   499=58
14:41  total=89   499=49
14:42  total=65   499=7
14:43  total=42   499=0
14:44  total=31   499=0

This was almost perfectly in sync with the Alibaba Cloud CPU curve:

Plaintext
14:33
CPU near 100%
499s start appearing in large numbers

14:34~14:41
CPU remains high for a long time
Large number of 499s

14:42
Pressure starts dropping rapidly

14:43
499s return to 0

Therefore, these 499s were more likely:

The result of clients, the CDN, or crawlers waiting too long and disconnecting early after PHP-FPM became severely congested.


3. This Was Not Caused by a Single IP or URL

Initially, I suspected that a single page was being hit with a large number of requests.

But after analyzing the URLs, I found the requests were highly dispersed.

The first-level path distribution was roughly as follows:

Plaintext
/tag/         373
/category/    102
/en/           85
/2026/         83
/page/         76
/               25
/wp-json/      24
...

Among them:

Plaintext
/tag/
/category/
/page/

These three types of pages combined accounted for about 65% of the requests in this time window.

The specific URLs were also highly dispersed, for example:

Plaintext
/tag/app/
/tag/mysql-5-7/page/3
/tag/electron/
/page/9
/page/19?query-62-page=61
/page/109?query-62-page=127
/category/.../page/17/?noamp=mobile
...

The source IPs were also quite dispersed, with no single IP accounting for the majority of requests.

The User-Agents included many automated crawlers, such as:

Plaintext
Sogou web spider
bingbot
SemrushBot
Baiduspider
meta-externalagent
ClaudeBot
Googlebot

Therefore, this was more like:

Multiple crawlers or automated programs simultaneously traversing a large number of different URLs for historical articles, tags, categories, and pagination, rather than a simple flood request from one IP to a single address.


4. This Time It Was Not a Query String-Driven Issue

The day before, I had just dealt with the issue where:

Plaintext
Article detail page + Query String

prevented the CDN and W3TC cache from being effectively reused.

So naturally, I initially suspected the same problem had reoccurred.

But after analyzing the 499s this time, I found:

Plaintext
With Query String: 135
Without Query String: 364

That is, approximately:

73% of the 499 requests had no Query String at all.

Therefore, the previous day’s optimization was still meaningful, but it could not solve this CPU alert.

The two types of problems can be distinguished as follows:

The previous article focused on solving:

Plaintext
Same article detail page
+
Different meaningless Query Strings
+
Causing unnecessary cache fragmentation or penetration

What I faced this time was more like:

Plaintext
Large number of different URLs
+
Each experiencing its first Cold Cache
+
Simultaneously entering PHP for dynamic generation

5. All 7 PHP-FPM Workers Were Exhausted

PHP-FPM currently has Slowlog enabled:

Plaintext
request_slowlog_timeout = 3s
slowlog = /usr/local/php/var/log/slow.log
request_terminate_timeout = 600s

This means that if a single PHP request executes for more than 3 seconds, it will be logged in the Slowlog.

After checking the PHP-FPM logs for this incident window, a very critical entry appeared:

Plaintext
[28-Jul-2026 14:32:57]
WARNING: [pool www] server reached max_children setting (7), consider raising it

This meant:

Before the machine’s CPU officially entered a prolonged 100% plateau, all 7 PHP-FPM workers were already busy.

Moreover, starting from 14:32, multiple workers continuously showed:

Plaintext
executing too slow

Throughout the 14:32–14:44 time window, a total of:

Plaintext
287

instances of executing too slow were recorded.

The PHP-FPM log explicitly recorded that max_children=7 was exhausted, and there were already multiple dynamic requests exceeding 3 seconds prior to this.

Taking PID 49712 as an example, Alibaba Cloud process monitoring showed that it maintained a high CPU usage for a long time during the machine-wide CPU alert, and dropped rapidly after about 14:42.

Figure 3: PHP-FPM Worker 49712 sustained high CPU usage during the CPU alert, and dropped along with the overall system load after approximately 14:42
Figure 3: PHP-FPM Worker 49712 sustained high CPU usage during the CPU alert, and dropped along with the overall system load after approximately 14:42

At this point, the operational process of the CPU alert was basically clear:

Plaintext
Dynamic PHP requests slow down

PHP-FPM workers gradually occupied

All 7 workers busy

New requests start waiting

CPU remains near 100% for a long time

Clients wait too long

Nginx shows a large number of 499s

6. Slowlog Initially Pointed Suspicions at Gutenberg, W3TC, and Polylang

Upon further analysis of the PHP-FPM Slowlog, the files with the highest frequency in the complete call stacks included:

Plaintext
1237  wp-includes/class-wp-block.php

760   Gutenberg navigation.php

190   W3TC ObjectCache_WpObjectCache_Regular.php
189   W3TC ObjectCache_WpObjectCache.php
188   W3TC Cache_Redis.php

185   Polylang translatable-object.php

Aggregated by plugin:

Plaintext
1149  gutenberg
706   w3-total-cache
313   polylang
16    tms-extensions-polylang
6     post-views-counter
6     organize-series
...

This initially made it easy to think that:

Plaintext
Gutenberg Navigation

taxonomy / term

Polylang

W3TC Object Cache

Redis

was the main problem.

But the complete call stack only indicates that:

these components participated in the slow requests.

It does not show which step actually consumed the most time.

So I further analyzed:

At the exact moment the PHP request exceeded 3 seconds and a Slowlog snapshot was captured, what function was PHP executing?


7. About 73% of Slowlog Snapshots Stopped at Redis GET/MGET

The results were highly concentrated:

Plaintext
135  get()   W3TC Cache_Redis.php
53   mget()  W3TC Cache_Redis.php

Total:

Plaintext
188 / 257 ≈ 73%

In contrast:

Plaintext
18  Gutenberg Theme JSON sanitize()
7   merge()
3   mysqli_query()
2   Navigation get_inner_blocks()
...

As a result, the investigation focus temporarily shifted to:

W3TC Object Cache → Redis

After checking W3TC’s Cache_Redis.php, I found that the actual read logic contained:

PHP
$v = $accessor->get( $storage_key );

Therefore, the frequent appearance of get() in the Slowlog did indeed correspond to the underlying Redis Object Cache reads.


8. Redis Also Experienced Genuine Slow Requests

Redis’s overall current state did not show any obvious capacity issues.

Memory:

Plaintext
used_memory       517.82 MB
used_memory_peak  556.27 MB
maxmemory           1.00 GB

And:

Plaintext
evicted_keys          0
blocked_clients        0
rejected_connections  0

Object Cache cumulative:

Plaintext
keyspace_hits     149242618
keyspace_misses     1894018

The hit rate was approximately:

98.75%.

Therefore, there were no signs of Redis evicting large amounts of cache due to memory exhaustion.

However, the Redis Slowlog did contain requests taking tens of milliseconds.

For example:

Plaintext
GET optionsalloptions
approx. 87.6 ms

Additionally, there was one entry:

Plaintext
MGET terms...

followed directly by:

Plaintext
... (675 more arguments)

This meant that a single MGET read several hundred Term Cache Keys.

It temporarily seemed that:

Redis was very likely the root cause of the server slowdown.

Until I continued checking the ECS CPU core count.


9. What Truly Changed the Diagnosis: This Server Only Has 1 vCPU

Executing:

Bash
nproc

The result was only:

Plaintext
1

That is:

The entire ECS has only one CPU core.

At the same time, Redis was also running on the local machine:

Plaintext
redis-server 127.0.0.1:6379

This suddenly tied together many of the previously seemingly unrelated issues.

The server was actually forcing:

Plaintext
PHP-FPM Worker × 7
Redis
Nginx
Other system processes

to compete for the single CPU core.

Therefore, when 7 PHP-FPM workers simultaneously executed relatively heavy WordPress dynamic requests, it easily formed a cycle:

Plaintext
Heavy PHP computation

Single CPU core saturates

Redis also needs to compete for CPU

Object Cache GET/MGET latency increases

PHP requests take longer to complete

Workers cannot be released for a longer time

System remains at high CPU

So:

Redis did experience slow requests, but it was likely both a hotspot and a victim slowed down by CPU saturation, rather than the initial point of failure.

This also meant that I could not simply follow the PHP-FPM suggestion to:

Plaintext
consider raising it

and increase:

Plaintext
pm.max_children = 7

to 14 or higher.

A 1 vCPU machine does not gain more compute resources just because the number of PHP workers increases.


10. The Truly Key Question: Is W3TC Page Cache Actually Fast After a HIT?

Since the problem likely stemmed from a large number of requests entering PHP, the next most important thing was to check whether W3 Total Cache Disk Enhanced was actually working.

Current configuration:

Plaintext
Page Cache:Enabled
Engine:Disk Enhanced
Cache Query String:false

I bypassed the CDN and directly tested several types of URLs via the origin server.

Tag Page

Plaintext
/tag/app/

Three TTFBs:

Plaintext
0.023816 seconds
0.087154 seconds
0.016832 seconds

Category Page

Plaintext
/category/program-development/smslib/yuntongxun/

Results:

Plaintext
0.160287 seconds
0.079870 seconds
0.052548 seconds

Article Detail Page

Plaintext
/2026/03/27/9383/

Results:

Plaintext
0.045637 seconds
0.016188 seconds
0.015945 seconds

These data show that:

When W3TC Disk Enhanced already has an available cache, the origin server itself can be very fast.

The truly abnormal one was the following paginated page.


11. A Page Going from 10.6 Seconds to 0.016 Seconds

Testing:

Plaintext
/page/9/

First time:

Plaintext
HTTP=200
TTFB=10.602379s

Second time:

Plaintext
TTFB=0.016091s

Third time:

Plaintext
TTFB=0.031990s

Meanwhile, after the first access, a new file was generated:

Plaintext
wp-content/cache/page_enhanced/www.shuijingwanwq.com/page/9/_index_slash_ssl.html

The timestamp was exactly:

Plaintext
2026-07-28 16:14:01

Therefore, this almost perfectly reproduced:

Plaintext
First time
Page Cache MISS

Enters PHP-FPM

WordPress full dynamic generation

10.6 seconds

Writes to Disk Enhanced

Second time
Directly uses Page Cache

0.016 seconds

So the most important finding of this investigation was not:

W3TC Page Cache is not working.

Quite the opposite:

W3TC is very fast after a HIT, but the cost of a Cold MISS is extremely high.


12. Why Can Just Over a Hundred Requests Per Minute Max Out the Server?

This time, the minute with the most requests at 14:34 only had about:

Plaintext
153 requests

Looking at the number alone, it does not seem particularly high.

But placed in the current environment:

Plaintext
1 vCPU
+
WordPress block theme
+
Many plugins
+
Some Cold MISS pages taking several seconds or even 10 seconds

the nature of the situation completely changed.

If crawlers continuously access:

Plaintext
/tag/A/
/tag/B/
/tag/C/
/category/A/
/category/B/
/page/9/
/page/19/
/page/109/
...

Every URL could be an independent Cold MISS.

Even if every page can be cached after generation:

Plaintext
URL A: First MISS
URL B: First MISS
URL C: First MISS
URL D: First MISS

Just a few simultaneous high-cost dynamic requests are enough to occupy all 7 PHP-FPM workers.


13. W3TC Page Cache Is Already Approaching 1 GB

At that time:

Plaintext
wp-content/cache/page_enhanced

had reached:

Plaintext
918 MB

Total number of files:

Plaintext
7320

Cache file age distribution:

Plaintext
Under 1 hour:     1414
1–2 hours:        1564
2–6 hours:        4342
Over 6 hours:        0

The W3TC configuration at that time was:

Plaintext
Maximum lifetime: 3600 seconds
Garbage Collection Interval: 3600 seconds
Cache Preload: Disabled

Seeing this, I initially suspected:

Does the Page Cache expire every hour and then constantly regenerate?

But actual testing showed that the situation was not that simple.


14. Caches Over 3 Hours Old Can Still Result in a Direct HIT

I found the following in the existing cache:

Plaintext
/2023/11/21/12193/

Cache generation time:

Plaintext
2026-07-28 12:48:52

And the test had reached approximately 16:21.

Requesting it at this point:

Plaintext
TTFB=0.038573s

Before and after the request:

Plaintext
mtime unchanged
size unchanged
inode unchanged

The bottom of the page also explicitly showed:

Plaintext
Served from: www.shuijingwanwq.com @ 2026-07-28 12:48:52 by W3 Total Cache

Therefore, it can be confirmed that:

Caches over 3 hours old on disk can still be returned directly; they are not immediately deleted from disk after 3600 seconds, nor are they necessarily regenerated on every request.

So, I also abandoned the overly simplistic understanding of:

“Everything becomes a Cold MISS again after 3600 seconds.”

This overly simplistic understanding.


15. Cache Preload Is Not Enabled

W3TC currently has:

Plaintext
pgcache.prime.enabled = false

Meaning Page Cache preloading is not enabled.

In theory, Cache Preload can generate pages in advance, thereby reducing the probability of real visitors incurring a Cold MISS.

But this time, I did not enable it for the time being.

The reason is simple:

Plaintext
The server only has 1 vCPU

And I had already actually encountered:

Plaintext
/page/9/
Cold MISS = 10.6 seconds

For a site with a large number of articles, tags, categories, and pagination, actively generating a large batch of page caches could itself create sustained CPU pressure.

So at this stage, I preferred:

To keep the caches that already consumed a lot of CPU to generate for as long as possible, rather than actively initiating a new massive wave of preloading.


16. Ultimately, Only One Parameter Was Changed: 1 Hour → 12 Hours

In the end, I did not modify Redis, did not adjust PHP-FPM max_children, and did not enable Cache Preload.

I only adjusted:

Performance → Page Cache → Advanced → Maximum lifetime of cache objects

Before modification:

Plaintext
3600 seconds

Which is: 1 hour.

Figure 4: Before adjustment, the maximum lifetime of cache objects for W3 Total Cache Page Cache was 3600 seconds, or 1 hour
Figure 4: Before adjustment, the maximum lifetime of cache objects for W3 Total Cache Page Cache was 3600 seconds, or 1 hour

I then changed it to:

Plaintext
43200 seconds

Which is:

12 hours.

Figure 5: Adjusting the maximum lifetime of cache objects for W3 Total Cache Page Cache from 3600 seconds to 43200 seconds, extending it from 1 hour to 12 hours
Figure 5: Adjusting the maximum lifetime of cache objects for W3 Total Cache Page Cache from 3600 seconds to 43200 seconds, extending it from 1 hour to 12 hours

Other configurations remained unchanged:

Plaintext
Maximum lifetime:
43200 seconds

Garbage Collection Interval:
3600 seconds

Cache Preload:
Disabled

Cache Query String:
Disabled

The purpose of doing this was not to claim that “12 hours is definitely the optimal value.”

Rather, it was to make a simple, low-risk, and easily verifiable adjustment first:

Reduce the probability of the same historical page repeatedly entering high-cost dynamic generation.


17. After Saving, I Did Not Click “Empty All Caches”

I consider this step very important.

After modifying the W3TC settings, right next to it in the dashboard was the:

Empty All Caches

button.

But this time, I did not click it.

The reason comes precisely from the biggest finding of this investigation:

Plaintext
Cold MISS: 10.6 seconds
Cache HIT: 0.016 seconds

There are already over 7,000 cache files on disk now.

If I were to actively Purge All just to “start fresh” with the configuration:

Plaintext
Large number of existing warm caches disappear

Crawlers traverse again

Large number of URL Cold MISSes

WordPress dynamic generation

1 vCPU again bears the pressure of cache warming

This is exactly the opposite of the optimization goal for this round.

So after making the modification, I chose to:

Keep the existing cache and let the new lifetime configuration take effect gradually during natural operation.


18. After Saving, a Yoast SEO Extension Prompt Appeared, Which I Also Temporarily Ignored

After saving the settings, a prompt appeared in the W3TC dashboard:

Plaintext
Activating the Yoast SEO extension for W3 Total Cache may be helpful for your site.

I did not enable it at this stage.

The reason was not that I thought there was a problem with this extension, but because I was currently observing:

Plaintext
Maximum lifetime
3600 → 43200

whether this single adjustment was effective.

If I continued to modify:

Plaintext
Yoast SEO Extension
Redis
PHP-FPM
Cache Preload
CDN

at the same time, then if the CPU alert changed the next time, it would be very difficult to determine which factor actually caused it.

So at this stage, I continued to follow:

Change only one variable at a time.


19. This Investigation Changed My Understanding of Several Issues

CPU Saturation Does Not Necessarily Require a Very High Request Volume

If the server only has 1 vCPU, and a single Cold WordPress page takes 10 seconds, then just a few concurrent dynamic requests are already dangerous enough.

Reaching the max_children Limit Does Not Mean It Should Be Raised

This time, PHP-FPM explicitly warned:

Plaintext
server reached max_children setting (7)

But there was only 1 vCPU.

Adding more workers does not magically produce more CPU.

A Slow Redis Slowlog Does Not Mean Redis Is Necessarily the Root Cause

Redis did indeed experience slow commands at the level of:

Plaintext
10ms
20ms
50ms
80ms

But the server only had one CPU core, and PHP-FPM was competing for that core at full capacity.

Redis might have just been slowed down by the overall system’s CPU saturation.

Redis might have just been slowed down by the overall system’s CPU saturation.

What Truly Matters Is Avoiding Entering PHP as Much as Possible

One W3TC HIT:

Plaintext
approx. 0.016 seconds

One Cold MISS:

Plaintext
10.6 seconds

This order-of-magnitude gap is far more important than continuing to tweak a few PHP parameters.


20. The Previous CDN Optimization Was Not Done in Vain

This investigation also gave me a clearer understanding of the previous day’s CDN optimization for detail page query strings.

The previous article solved:

Plaintext
Same article
+
Meaningless parameters
+
Insufficient cache reuse

It could reduce a portion of the requests reaching the origin server.

What was exposed this time, however, was a much broader scope:

Plaintext
/tag/
/category/
/page/
Feed
Search
REST API
Various historical articles
And a large number of different Cold URLs

So:

Detail page CDN optimization is an effective layer, but it alone cannot solve all CPU alerts.

If subsequent observations show a significant reduction in CPU alerts, it will mean that the two layers of CDN and W3TC optimization are starting to have a compounding effect.


21. Current Production Configuration

After this round, I ultimately only changed:

Plaintext
W3 Total Cache
Page Cache
Maximum lifetime

3600 seconds

43200 seconds

Which is:

1 hour → 12 hours.

The following items were temporarily maintained:

Plaintext
Garbage Collection Interval: 3600 seconds

Cache Preload: Disabled

Cache Query String: Disabled

PHP-FPM max_children: 7

Redis Object Cache: Remains enabled

Yoast SEO W3TC Extension: Not enabled for now

At the same time:

Do not manually empty the existing Page Cache.


22. How to Judge if It Is Effective in the Next Stage

This time, I do not plan to continue making immediate modifications.

What is truly meaningful is letting:

Plaintext
43200 seconds

run in production for a while.

Subsequent focus will be on observing:

Whether CPU alerts decrease;

Whether the duration of single instances approaching 100% shortens;

Whether PHP-FPM still frequently:

Plaintext
reached max_children setting (7)

Whether Nginx will again show hundreds of 499s during the next alert period;

And whether the proportion of Cold MISSes gradually decreases as the Page Cache becomes increasingly warm.

If these metrics improve significantly, it means:

Extending the valid lifetime of already generated caches is the right direction.

If there is no significant effect, I will further consider:

Plaintext
CDN cache strategy for Tag / Category / Page
Access control for low-value crawlers
Why Cold pages take 10 seconds to generate
Dynamic generation cost of Gutenberg Navigation / taxonomy

rather than changing everything all at once right now.


Conclusion

This investigation was very interesting.

At first, I thought it was just an incomplete resolution of the query string cache issue from the previous article.

Then I went on to suspect:

Plaintext
Nginx
PHP-FPM
Gutenberg
Polylang
W3 Total Cache
Redis

Among them, Redis Slowlog did show a large number of abnormal latencies, and about 73% of the PHP Slowlog samples fell on W3TC Redis GET/MGET.

But what truly made me rethink the entire problem was:

Plaintext
nproc = 1

Combined with:

Plaintext
/page/9/

Cold MISS:
10.602379 seconds

Cache HIT:
0.016091 seconds

The answer finally became simple.

The truly scarce resource on this WordPress server right now is:

The single CPU core.

Therefore, rather than having more PHP-FPM workers working simultaneously, I prefer:

Requests not entering PHP at all.

The CDN, W3TC Disk Enhanced, and extending the Page Cache lifetime are all essentially doing the same thing:

Returning cached results directly for pages that have already been generated, as much as possible.

This time, I first increased the maximum lifetime of the W3TC Page Cache from:

1 hour

to:

12 hours.

As for whether it can actually reduce CPU alerts, I will leave it to production data to verify.

系列导航

需要长期技术维护或远程问题排查?

我是拥有 15+ 年经验的 PHP / Go 后端工程师,长期关注已有系统维护、Bug 修复、性能优化、服务器排查、WordPress 网站维护和小功能迭代。

如果你的项目遇到以下情况,可以先从一次小问题排查开始合作:

  • ✅ PHP / Laravel / Yii2 老项目无人维护
  • ✅ Go / Gin 后端接口需要排查或优化
  • ✅ WordPress 网站访问慢、报错或插件冲突
  • ✅ Nginx / MySQL / Redis / Linux 服务器异常
  • ✅ CDN / Cloudflare / DNS / HTTPS 配置问题
  • ✅ 需要长期远程技术支持或兼职维护

更多介绍请查看:关于我 & 合作

微信:13980074657
邮箱:shuijingwanwq@gmail.com
Telegram:@shuijingwan
GitHub:https://github.com/shuijingwan

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