Many website owners and businesses using Japanese cloud servers find that their servers are consistently under high load, such as a load average that consistently exceeds the number of CPU cores, CPU utilization remaining stable at 80% or even approaching 100%, disk I/O being constantly full, or a significant slowdown in system response. Japanese data centers are often used for cross-border business deployments due to their geographical proximity to East Asia, low network latency, and high-quality international bandwidth. However, if servers are consistently under high load, it not only affects access speed and stability but can also cause serious hardware wear and tear, service anomalies, data loss, and potential security risks. Therefore, to address the issue of persistent high load on Japanese cloud servers, it is essential to identify the risk points at the source and implement systematic optimization based on the business scenario to ensure the server operates continuously in a more stable and secure manner.

　　When a server is under high load, the most direct risk is a decrease in business response speed. When users access websites or APIs, the server CPU cannot process requests in a timely manner, leading to a significant increase in response latency. If a Japanese data center is being used, the user base is typically from mainland China or Southeast Asia, who are inherently more sensitive to network latency. Once the server's processing speed decreases, the overall access experience will deteriorate exponentially. For scenarios with high real-time requirements, such as e-commerce, gaming, and live streaming, high load can lead to request backlog, timeouts, and page loading failures. In severe cases, it can even cause Nginx or PHP-FPM processes to crash, rendering the service completely unavailable.

　　High load can also lead to system resource exhaustion. When CPU usage is consistently close to 100%, the system cannot allocate time slices in a timely manner, resulting in slow system command response, difficulty in SSH login, and challenges for maintenance personnel to handle issues promptly. If memory is consistently insufficient, the system will frequently trigger swap, causing increased disk I/O and triggering a cascading failure effect. If the disk itself is a cloud disk or a SATA disk with weak IOPS capabilities, I/O saturation will occur, making the entire system unresponsive. Especially in the environment where Japanese cloud servers commonly use shared bandwidth and shared I/O, if a server consumes too many resources, it may trigger the service provider's rate-limiting policy, further degrading performance.

　　Besides performance issues, prolonged high load can also affect data security. The risks are most pronounced when databases are running under high pressure. If write operations in MySQL, MariaDB, or PostgreSQL are forced to be delayed or even interrupted under high load, in extreme cases this can lead to table corruption, index anomalies, or even trigger InnoDB crash recovery. This is extremely harmful to business operations, especially cross-regional operations, as data synchronization delays will further exacerbate the chain of failures, thus affecting secondary business systems.

　　High load can also hide security vulnerabilities. Websites deployed in Japanese data centers are often targets for attackers to test, scan, or intrude due to their convenient international access. If scripts or port scanning programs are implanted on the server, they will continuously consume a large amount of CPU or bandwidth, causing the load to rise continuously. Many administrators mistakenly believe it is due to busy business operations, ignoring the presence of malicious processes. If there is a sudden spike in CPU usage, saturated network bandwidth, or a large number of suspicious connections pointing to overseas IPs, be vigilant and promptly investigate abnormal programs.

　　After recognizing the risks of long-term high load, it is necessary to start from actual business needs and combine a series of optimization strategies to reduce the load and ensure that the Japanese cloud server maintains a good operating condition. First, it is necessary to identify the source of the load, which can be done using:

top -o %CPU
htop

　　Identify the primary processes consuming bandwidth. If the issue stems from web services, check the configuration of Nginx, Apache, or Node.js. High database usage indicates slow queries, missing indexes, or excessive connection counts. Web attack traffic necessitates filtering and blocking based on logs. This forms the foundation of all optimization efforts.

　　Application-layer optimization is crucial for reducing high load. For static resource websites, CDNs should be used whenever possible to distribute traffic to edge nodes without consuming resources on the Japanese server itself. This is especially important for users in Southeast Asia and mainland China, where using domestic or global CDNs can significantly alleviate bandwidth pressure. If the business relies on dynamic computing, such as PHP or Python services, adjust the process pool based on user traffic. For example, PHP-FPM can be optimized as follows:

pm = dynamic
pm.max_children = 50
pm.start_servers = 10
pm.max_spare_servers = 20

　　If the server has limited memory, parameters need to be adjusted appropriately to avoid excessive processes causing memory overflow and higher load.

　　Database optimization is equally important. Japanese cloud servers are often used for cross-border business database deployments; if database performance is not optimized, even the best-performing servers will continue to experience high loads after migration. Slow query logs should be checked regularly.

SHOW FULL PROCESSLIST;

　　And confirm whether any necessary indexes are missing. Additionally, configure the InnoDB cache appropriately, for example:

innodb_buffer_pool_size = 1G

　　Typically, 50% to 70% of server memory should be used to improve database query efficiency and reduce disk I/O pressure.

　　Caching strategies are also a significant way to reduce load. Redis or Memcached can reduce database pressure, while static page caching or page caching can reduce repetitive calculations in dynamic languages ​​like PHP. For frameworks like WordPress, Discuz, and Laravel, enabling Redis Object Cache or page caching can significantly reduce CPU usage, suitable for websites with significant traffic spikes. For API services, response caching and rate limiting strategies can also be configured appropriately based on business needs.

　　Network layer optimization is also crucial. During cross-border access, if bandwidth is saturated by attackers or malicious crawlers, the server will also experience high load. Simple rate limiting can be configured using Nginx.

limit_req_zone $binary_remote_addr zone=one:10m rate=5r/s;

　　This is combined with Fail2ban to automatically block abnormal IPs. When the Japanese server experiences a large number of web crawlers, overseas attack sources, or proxy scanning activities, the rate limiting policy can protect the server from overload.

　　Performance can also be improved at the system level through kernel parameter tuning. For example:

net.core.somaxconn = 65535
fs.file-max = 1000000

　　This can improve network connectivity and the number of file descriptors, making the server more stable under high concurrency. For servers with high IO loads, enabling noatime mounting can reduce disk writes and improve response speed.

　　If all optimizations fail to resolve the persistent high load issue, scaling up should be considered. Japanese cloud servers typically offer the ability to upgrade CPU, memory, and bandwidth, and can also split services into multiple nodes. For example, migrating the database to a high-speed SSD node, placing static resources in object storage, and creating a load-balanced cluster for web services can address the load issue at its root, significantly reducing the pressure on the cloud server.