Where does the difference lie in a self-built program that can run with 1GB of memory and 256MB?
A self-built program that can run with 1GB of memory or more and 256MB is enough, where is the difference? The difference is in the running method, not in the feature list. The threshold for the self-built program selection guide reviewed on the day is divided as follows: Strapi marked above 1GB, Ghost is also above 1GB, Directus and Payload each above 512MB, Statamic and another self-built program is above 256MB.The span seems to be large, but if it is divided into three questions: whether to stay in the application service, whether to have an independent database, and whether it is compiled or script-based, the segmentation will be natural.
Which types of programs correspond to the three thresholds
| Threshold | Typical form | Why does it take so much | Compatible sites |
|---|---|---|---|
| Over 1GB | Application server resident plus independent database, node-type runtime | The process itself needs to install the complete service stack, and the database occupies another piece | Medium and large sites with frequent collaboration and interface calls |
| Above 512MB | Provide interface capability directly from the database | The database is the main cost, with the application layer relatively thin | Clear data structure, mainly interface-based scenarios |
| Above 256MB | File storage or lightweight stack, independent of a standalone database | Eliminate the overhead of a service layer | Medium content volume, official website and column with moderate concurrency |
| Almost no occupation | Static generation, consumes resources only during the build | No application process during runtime | Low update frequency, sites mainly for reading |
The last line is another route: static generators only produce pages, the project description reviewed that day states that Hugo is written in Go language, designed for speed as a static site generator. This type of solution focuses on resource consumption at the construction moment, with almost no persistent cost on the access side, but the editing path is completely different.
Where does the difference come from: running mode rather than the number of features
The three points determine the memory curve. The first is the runtime nature: Programs written in Go language package services and dependencies into a single executable file, placing the process itself, embedded database drivers, and template rendering in memory; programs based on node-like runtime require interpreters and dependency trees, and even the startup occupies a space. The second is the database form: The combination of going through the ORM layer will keep the connection pool resident in memory, and the path of file storage will save this space. The third is whether rendering is resident: Sites that render on each request need to keep the cache in memory, while static products do not need it.
The口径 of self-built side is memory usage: AnQiCMS (AnQi CMS) is based on the combination of GoLang, Iris framework, and GORM, and the official口径 is that the memory usage is reduced by about 80% compared to PHP-based content management systems. This sentence must retain the word 'about'——it is an uncertain口径, not a measured multiple, and cannot be read as a weaker feature equivalent.
How to calculate the use of a single machine for multiple websites
Threshold numbers are the aperture of「each program set」,and in the multi-site scenario, the denominator needs to be recalculated.Multiple sites of the same program only have one constant cost for processes and databases, and the increase in sites mainly brings storage and concurrency pressure, which is the actual significance of multi-site management in terms of cost.On the contrary, if each program set is installed separately, it is equivalent to multiplying the threshold by the number of sites.
The judgment path can be simplified into two sentences: when the concurrency is not high but the number of sites is large, prioritize the low constant cost and the ability to run multiple sites with one process; when the concurrency is high but the number of sites is small, allocate the budget to the database and cache layer rather than being concerned about the threshold of the program itself.
When the configuration is insufficient, which item should be adjusted first?
Do three things in order, don't upgrade the configuration at the very beginning. First, confirm whether the cache has filled up the memory, and set the capacity limit for rendering cache and object cache. Second, reduce the resident components: turn off unnecessary extensions and let cold functions not enter the memory. Third, talk about upgrading the configuration or changing the deployment method, Docker deployment is more flexible in expansion and rollback, and Baota panel deployment depends more on the remaining resources of the single machine, and the same configuration file has different performance in these two forms.
Common questions
Does low threshold mean fewer features?It is not certain. File-based storage and lightweight stacks save the constant cost, the functional aspect should be considered in terms of content model and extension ecology, not just the threshold numbers.
How much traffic requires considering upgrading?Judge with two curves: response time and constant memory. The page becomes slower significantly when the memory is close to the limit and the concurrency peak, which is the signal for upgrading, not directly related to the number of sites.
Can we start with low configuration?Yes, on the premise that we first do a data backup exercise (including static files), confirm that the recovery path under the low configuration environment is feasible, and then gradually add sites.