In the era of cloud computing, the pay-as-you-go model is favored by a large number of small and medium-sized enterprises, developers and temporary project users for its elasticity, flexibility and pay-as-you-go features. However, after using pay-as-you-go cloud servers for a period of time, many users often find that the bill costs have "quietly" increased, far exceeding the original estimate. What exactly causes this situation? The hidden cost factors behind this are often the key to determining whether you can use cloud resources efficiently.
Billing basis: hourly billing ≠ host-only billing
When many users first come into contact with pay-as-you-go cloud servers, they mistakenly believe that the cost only comes from the "number of hours the cloud host is used", such as 0.1 yuan per hour for a 1-core 2G instance. In fact, the billing structure of cloud vendors is far more than just computing resources. Ancillary resources such as storage, network, bandwidth, and security services are also involved in billing, and the proportion is often not low.
Therefore, when you see that the instance itself only costs a few cents per hour, don't take it lightly. The "fatness" of cloud bills usually starts with these "scraps".
Hidden cost 1: public network bandwidth outflow
Public network bandwidth fees are one of the primary factors that lead to a surge in pay-as-you-go cloud server fees. Especially for high-concurrency Web services, video distribution, download distribution, and application scenarios with large API calls, outflow fees are charged by GB, which is much higher than the host rental itself.
Optimization suggestions:
Limit unnecessary public network exports such as FTP and backend open ports; use CDN to accelerate resource delivery and reduce source station outflow; reasonably configure bandwidth limits to prevent malicious calls from exhausting traffic
Hidden cost 2: Long-term mounting of data disks and snapshots
Many users frequently create data disks, system snapshots, and image backups during use, but fail to clean them up in time, resulting in continuous billing of resources that are mounted for a long time and not used.
Optimization suggestions:
Periodically inspect storage resources and release redundant disks and snapshots in time;
Use automatic snapshot policies to set retention periods, such as automatically overwriting old snapshots in 7 days;
Enable archive storage or cold storage for disks of inactive projects to reduce costs;
Hidden cost three: EIP billing logic is complex
EIP is often overlooked in pay-as-you-go billing. It may be billed in multiple dimensions: binding + traffic + occupancy time. If EIP resources are not released, they will continue to be billed even if they are not bound to a host.
Possible cost methods:
Bandwidth billing: monthly pricing based on maximum bandwidth
Traffic billing: actual usage (GB)
Occupancy billing: hourly pricing, even if not used, fees may be incurred
Optimization suggestions:
Release EIP in time after the project is completed, do not just unbind; you can choose annual and monthly bandwidth and limit the maximum rate; it is recommended to use NAT gateway + SNAT combination for low-frequency access services;
Hidden cost 4: automatic activation of monitoring, log, and security services
Some cloud vendors enable cloud monitoring (such as collecting indicators/alarm notifications), log services (continuously writing and storing for 30 days or more), cloud firewall or WAF trial version (automatically converted to billing version after free period) by default. Although the price of each of these "auxiliary services" is not high, the cumulative cost may increase by 50 to 200 yuan/month.
Optimization suggestions:
Go to the resource console and check item by item whether unnecessary services are enabled; turn off the automatic subscription functions, such as log collection and monitoring indicator aggregation; use the free version or community alternative tools;
Hidden cost five: continuous billing caused by unreleased instances
Some users simply stop cloud server instances after short-term testing, rather than "release and delete". In the pay-as-you-go billing model, stopping does not mean terminating billing, and disks and IPs are still in operation.
Optimization suggestions:
Use the console to release the instance and confirm that the resource cleanup is successful; you can set automatic shutdown and automatic release policies (support some platforms); for test hosts, use temporary server pool scheduling;
Hidden cost six: CPU surge in burst performance instances
Some cloud platforms provide "burst performance instances (T series)", which are priced according to the baseline CPU usage. When exceeding the baseline, points will be consumed or enter the additional billing range. Once the system continues to run under high load, it will be forced to switch to a higher level of billing.
Optimization suggestions:
Clearly understand the performance points rules for burst instances; high CPU load businesses are recommended to use standard computing instances; configure automatic monitoring alarms and adjust specifications in a timely manner.
Pay-as-you-go cloud servers do bring great flexibility to elastic computing, but flexibility also means responsibility. Cloud hosts that cost only a few cents per hour may eventually pile up bills that exceed the budget if the relevant resources are used without management. Understanding the billing model, mastering the source of hidden costs, and continuously managing resources are the keys to truly mastering the cost efficiency of cloud computing.
