The stated requirements are a floor, not a target
Adobe publishes system requirements for Magento 2.4.x, and stores often treat them as the specification to build to. They are a minimum to run, not a target to be happy with.
A store built exactly to the stated minimums will technically work and will struggle under real traffic. The gap between "runs" and "runs well" is where a lot of performance complaints actually live.
This article compares the stated requirements with what a real production store needs, so you can size infrastructure to reality rather than to the documentation floor.
What the requirements actually specify
The published requirements cover the supported versions and rough minimums: a supported PHP version, a supported database, a search engine, and baseline memory. They define compatibility, not comfort.
Meeting them means Magento will install and operate. It does not mean the store will be fast, handle concurrency, or have headroom for growth, because minimums are set for the smallest viable case.
This is normal for software requirements. The vendor states what is needed to run; sizing for your actual workload is the operator's job.
Memory: the biggest gap
Memory is where the stated minimum diverges most from reality. Magento is memory-hungry across PHP workers, the database buffer pool, Redis, and the search engine, and they all draw from the same server unless separated.
A store sized to the minimum memory spends its time swapping, evicting cache, and reading from disk. The single most common under-provisioning we see is memory set to what the requirements allow rather than what the workload needs.
CPU and concurrency
The requirements say little about handling concurrent traffic, which is the whole point of a production store. CPU cores determine how many requests can be processed at once, alongside the PHP-FPM worker count.
A store with too few cores serializes work that should run in parallel, and it feels slow under exactly the load that matters, a traffic spike. The minimum is fine for one user testing and inadequate for a busy afternoon.
Sizing CPU to peak concurrency, not average, is what keeps the store responsive when it counts. The requirements do not address peak because they address minimum viability.
Storage: type as well as size
The requirements mention disk space but not disk speed, and speed matters enormously for a database. Fast SSD or NVMe storage changes database performance dramatically compared to slower disks.
A store on slow storage pays a penalty on every database read that misses the buffer pool, and on every write. The stated space requirement can be met on slow storage that then bottlenecks the whole store.
Sizing storage means choosing the type, not just the capacity. The fast storage that a real database needs is not implied by a space minimum.
Separating the services
The biggest reality gap is architectural. The requirements can be read as a single server, and a real store of size separates the database, cache, and search onto their own resources.
On one server, the database, PHP, Redis, and search compete for memory and CPU, and the database buffer pool loses that competition. Separating them lets each be sized and tuned for its role.
This is the difference between a store that meets the requirements and one built to run well. Separation is how a growing store gives each service the resources the shared minimum could never provide.
The search engine's real needs
OpenSearch or Elasticsearch has its own memory and disk appetite that the top-line requirements understate. The search cluster needs memory to hold its indexes and disk headroom to avoid its watermarks.
A search cluster starved of memory is slow, and one starved of disk goes read-only and breaks reindexing. Sizing search to the minimum is how catalog search becomes an intermittent problem under growth.
Search deserves its own resource planning, not a share of the leftover. It is a full service with real requirements beyond the compatibility note.
Cloud sizing and autoscaling
Cloud environments change the sizing conversation but not the underlying reality. The minimums still keep the store running, and real performance still requires provisioning for the actual workload.
Autoscaling helps with the web tier, adding PHP-FPM capacity under load, but it does not solve an undersized database or search cluster. Those are usually fixed-size services that have to be provisioned for peak, not scaled reactively.
The lesson carries over: size the database, cache, and search for the real workload, and let autoscaling handle the elastic web tier. Treating the minimums as sufficient fails the same way in the cloud as on bare metal.
Build to the workload, not the floor
The stated requirements answer "will it run," and the useful question is "will it run well for my store." Those are different, and the gap between them is where under-provisioned stores struggle.
Knowing that your infrastructure is sized to your real workload, with memory for the buffer pool, cores for concurrency, fast storage, and separated services, is what turns a compliant store into a fast one. Checking sizing against reality rather than the minimum is a core part of an infrastructure review.