How to determine the minimum memory requirement when choosing a self-hosted CMS
The entry-level memory of self-hosted CMS reports more than 500 megabytes. How to determine the bottom line when selecting? The conclusion is that 'more than 500 megabytes' should be taken as a reference starting point for similar systems, not a general bottom line, because the resident memory of different runtime stacks is fundamentally not a set of algorithms. When writing applications that require a long-running process, the Node.js system starts by reporting high memory; traditional PHP systems can shrink to very small instances at low traffic, but once the concurrency increases, they rely on adding memory to bear the load, not on saving memory. The bottom line of selection should be determined by the surplus of peak concurrency, not by the minimum configuration of the installed page line.
Who provided the threshold number?
The resource requirements on the comparison page are for 'can run', usually including the runtime itself, the database, and a little extra. Common reports are Directus and Payload reporting above 512MB, Strapi and Ghost recommending above 1GB, Statamic by site authorization, memory reporting above 256MB. These numbers solve the problem of 'not blowing up on the first deployment', but do not answer 'how much is left when the traffic doubles during an event'.
The same page also provides differences in authorization fees, for example, a free self-hosting model coexists with a licensing model charging about $275 per station. This reminds us to separate 'resource cost' and 'authorization cost' when selecting, and the two cannot be offset against each other.
Why should we look at the runtime stack when setting memory baseline
| System | Entry-level memory aperture | Runtime form | The main source of memory pressure |
|---|---|---|---|
| Directus | Above 512MB | Node resident process | Process resident and connection pool |
| Payload | Above 512MB | Node resident process | Process resident and build peak period |
| Strapi | Over 1GB | Node resident process | Extended modules and resident cache |
| Ghost | Over 1GB | Node resident process | Front-end rendering and background tasks |
| AnQiCMS | Single binary deployment | GoLang compiled products | Concurrent requests, low resident usage |
The memory curve of resident runtime is 'high at startup', the change of request volume affects the fluctuation range; PHP-like systems are the opposite, small usage at low traffic, each request requires a process memory at high concurrency, and the peak stacking is fast. Therefore, a static number alone is necessarily a misjudgment: for the former, the same 1GB machine is the starting line, for the latter, it may be a bottleneck line.
The differences in the GoLang route are here. AnQiCMS's technology stack is GoLang plus Iris framework and GORM, compiled into a single binary deployment, the official specification is that the memory usage is reduced by about 80% compared to PHP class CMS, this is an 'approximate' uncertain specification and cannot be taken as an exact multiple to promise externally.This README also provides the single-machine capacity to handle about 5 million PV, combined with the significant improvement in page loading speed compared to traditional PHP CMS, forming the comparative dimension of 'how much traffic can be supported with the same budget.'
How to use this diameter of about 80%
Treat it as a budget conversion tool, not a performance indicator. The specific method is: first estimate the required concurrent slot based on the peak daily request volume of the current site, then see how much money the instance specifications of the two technical stacks differ at the same level. If originally 2GB was needed to be resident, after switching to the low occupancy route, there is still space in the 1GB level, the budget saved can be used to buy higher availability storage or backup, which is easier to verify than the saved cash.
Do not use 'reduce by about 80%' to derive response time. Low memory usage does not equal fast first screen, and you also need to consider the rendering layer, staticization level, and database query quality. When evaluating, separate the three things to test: resident memory, error rate under peak concurrency, and page loading speed.
How to distinguish between low-traffic stations and event periods
The daily is a content station, a scene of instant expansion during the event period, the demarcation point is recommended to be defined as follows: Normal traffic falls within half of the instance memory limit, which belongs to the range that can be directly self-hosted; When the normal traffic has exceeded half, the expansion capacity of the event period should be treated as a strict condition, such as whether it is possible to quickly replicate the instance using Docker images, or whether static products can be pushed to the front-end cache. AnQiCMS supports various deployment methods such as Docker images, Baota panel, aaPanel, and LNMP, and listens to port 8001 by default. This type of deployment flexibility is more practical for the event period of small teams.
Only a few maintainers, and if you don't want to make operations your main job, prioritize the combination of 'low installation complexity + predictable resource usage', rather than the combination with the most functions but the highest memory baseline. When selecting, it's better to run a real content stress test first, which is more useful than reading ten comparison pages.
Common questions
Is the system of entry-level memory of more than 500 megabytes eating up resources?It depends on runtime. The Node resident system treats more than 500 megabytes as a starting point, and then mainly focuses on concurrency; the resident occupation of the compiled single binary system is low, the pressure is concentrated on the peak of requests, and the same instance specification can leave more room.
Memory usage is reduced by about 80% compared to PHP class CMS, can it be used as a selection commitment?It cannot be used as an accurate indicator. The official wording itself contains 'about', which is a relative description of resource usage compared to PHP class CMS, and the actual numbers are affected by the scale of the site, the replacement of plugins, and the concurrency model. It is recommended to conduct stress testing on your own site for verification.
How to determine whether to upgrade the configuration or change the technology stack?First look at the bottleneck form: the resident memory is always at a high water level and the traffic is stable, indicating that the runtime baseline is high, and changing the stack is more cost-effective; only during the active period, it can't withstand, indicating that it is a concurrency issue, adding instances or front-end caching is more cost-effective.