Stateless is a word that gets thrown around in cloud certifications without a lot of explanation. The Associate Cloud Engineer exam treats it as a hint to pick Cloud Run, which is fair, but it helps to understand what stateless actually means and why Cloud Run is built around the assumption.
This article covers the definition of stateless, why Cloud Run requires it, where your application's state should actually live, and how to recognize stateless and stateful scenarios on the ACE exam.
It does not cover container internals, session affinity workarounds, or Cloud Run's second-generation execution environment. The exam is about the concept, not the implementation.
A stateless container does not retain any data or session information between requests. Two requests to the same service can land on completely different instances, and the second request does not depend on anything the first request stored locally.
A stateful container is the opposite. It holds onto data across requests. A user logs in, the container remembers the session. A user adds something to a cart, the container holds that cart in memory. The next request from that user has to come back to the same container or the data is gone.
The Associate Cloud Engineer exam puts it concretely. Stateless does not retain any data or session information. Stateful retains data or session information between requests. That is the line.
Cloud Run scales horizontally. When traffic increases, it adds instances. When traffic drops, it removes them. When traffic goes to zero, it removes all of them. Instances can be created and destroyed at any moment, and a single user's requests can be load-balanced across whichever instances happen to be running.
If your container were stateful, this would break. A user's session would vanish when their instance got terminated. A second request might land on a different instance with no memory of the first one. None of Cloud Run's scaling features would work cleanly.
The Associate Cloud Engineer exam says it directly. Any question that mentions stateless containers, you should strongly consider Cloud Run. The relationship is built in.
Real applications have state. Users do log in. Carts do exist. The pattern with Cloud Run is to keep that state out of the container and put it somewhere designed to hold it.
For relational data, that is Cloud SQL or Spanner. For session data and caching, Memorystore for Redis. For files and blobs, Cloud Storage. For documents, Firestore. The container becomes a stateless layer that talks to these services on every request and reads or writes whatever state is needed.
This is a different mental model than a traditional VM where you might keep an in-memory cache or a local file. With Cloud Run, that is the wrong place for either of those.
If you see the word stateless in a Cloud Run question, that is the hint. The exam guidance is to strongly consider Cloud Run when stateless is mentioned. This is one of the more telegraphed exam patterns, and it works.
If you see a question about migrating a stateful application to Cloud Run, the answer involves moving the state out of the container. Session data goes to Memorystore. Files go to Cloud Storage. The application database goes to Cloud SQL. The container that runs on Cloud Run is then a thin layer that reads and writes from those services.
If you see a question about an application that needs to retain user session data across requests on Cloud Run and the answers all involve in-memory storage or local files, none of those are right. The answer is an external service designed for that data type.
Cloud Run instances do reuse memory across requests within a single instance's lifetime. If an instance handles ten requests in a row, in-memory caches do persist for that instance. That is not the same as the application being stateful. The instance is still ephemeral. Two users hitting the same logical service can hit different instances, so you cannot rely on that memory being there.
This nuance does not show up on the Associate Cloud Engineer exam. The exam treats stateless as a binary signal pointing to Cloud Run. That is the level of abstraction it tests.
Stateless means the container does not retain data between requests. Cloud Run is built around that assumption, which is what makes its scaling model work. State for stateless services lives in Cloud SQL, Memorystore, Cloud Storage, or Firestore depending on what kind of state it is. If you see stateless in an Associate Cloud Engineer exam question, think Cloud Run.
My Associate Cloud Engineer course covers Cloud Run, the stateless requirement, and the comparison with App Engine and GKE that ACE exam questions test.
