The application program interface (API) space, like many other industries, possesses its own lingo. Moreover, there are a lot of terms that are so commonplace that one would assume that those in the field automatically understand them. That, however, is not entirely the case. In fact, for many newcomers, the often subtle definitions of these terms may not be clear-cut. Nowhere is this more apparent than with the stateless vs stateful discussion.
These are popular words in the API space primarily due to their differences. It is not unusual to find articles that discuss what sets the terms apart from each other. This an extremely useful distinction when it comes to the development of APIs and the services using those systems. Both stateless and stateful protocols are the network protocols specifically for web servers and web browsers. The differences between stateless vs stateful primarily draw their foundation from the server-side to save session information.
Indeed, on the surface, the differences are clear. One indicates a lack of state and the other indicates a surplus of state. But wait, what is ‘state’? For that matter, what exactly do these terms mean?
‘Stateful’ and ‘stateless’ have sort of a mutually dependent relationship when it comes to their definitions. To understand one, you need to understand the other. With that said, when talking about computer systems, a “state” is basically an entity’s condition or quality. At an instant in time, to be exact. To be stateful is to essentially rely on these moments in time. Moreover, to change the output when taking the determined inputs and state into account.
In a stateful protocol, if a client sends a request to the server, it then expects a response of some kind. Should it fail to receive any response, it will then resend the request. FTP (File Transfer Protocol) and Telnet are both examples of a stateful protocol.
Below are some stateful protocol features:
- Stateful protocols frequently provide comparatively better performances to the client. This is possible by way of monitoring the connection information.
- The stateful applications typically require backing storage.
- Stateful requests are heavily dependent on the server-side state.
- TCP sessions will often follow stateful protocol due to both systems maintaining information concerning the session itself throughout its life.
Stateless, as you can imagine, is the polar opposite of stateful. In their case, any given response from the server is completely self-sufficient from a state of any kind.
Stateless protocols are the type of network protocols where clients send requests to the server. The server will then respond back in accordance with the current state. There’s no requirement for the server to preserve session information or status concerning each communicating partner for multiple requests. HTTP (Hypertext Transfer Protocol), UDP (User Datagram Protocol), and DNS (Domain Name System) are all examples of a stateless protocol.
Below are some stateless protocol features:
- Stateless protocols simplify the overall design of the server.
- The stateless protocol requires a lesser amount of resources. This is because the system does not need to monitor the multiple link communications and details of the session.
- In a stateless protocol, each packet of information travels on its own without a reference to any other packet.
- Each communication within a stateless protocol is discrete and has no relation to those that precedes or follows it.
Based on the descriptions of each term, it is clear to see that when considering stateless vs stateful, you find two distinct concepts. Now that we have a basic idea of what each entails, we can start shedding light on the main distinctions.
For stateless protocols, there is no requirement for the server to preserve the server information or session details. Stateful protocols, meanwhile, require servers to save status and session information. When it comes to the dependency between the server and the client, stateless protocols do not have a tight one. In fact, they do not have a dependency at all. The same cannot be said for stateful protocols, in which there actually is a tight reliance.
Stateless protocols often work better during instances of a crash. The reason for this is that there is no state, therefore there is no need for state restoration. When a server fails, they can simply restart following a crash. Stateful protocols, on the other hand, do not work that way. They lack stateless protocols’ ability to work better at the time of a crash. This is because stateful servers have to keep the information on their status. Moreover, they need to keep session details of the internal states.
The design of the stateless protocol effectively simplifies the server design. The stateful protocol’s design makes the design of the server incredibly complex, not to mention heavy. Stateless protocols are able to handle the transaction at an exceptionally fast rate. The pace at which stateful protocols handle the transaction tends to be quite slow. Implementing stateless protocols onto the Internet is a relatively easy thing to do. Stateful protocols, meanwhile, are logically heavy to carry out its implementation onto the Internet.
Notable challenges of being stateful
To repeat an earlier point, there are a variety of texts that focus on the differences between stateful and stateless. Along with this recurring topic is also the mention of the downsides pertaining to stateful applications and protocols. Some of these challenges include the following:
- The isolation of resources. A good portion of the market’s container orchestration solutions typically involves only a best-effort approach to resource allocation. These include such solutions as CPU, memory, and storage. This works well for stateless apps, but in regards to stateful ones, it can be a disastrous approach. This could result in customer transactions or data getting lost courtesy of dubious performances.
- Backing storage requirement. Each stateful data service necessitates or supports a different kind of storage type. Block devices and distributed file systems are two noteworthy examples. Moreover, determining the type of backing storage for a stateful application has a tendency to be quite challenging.
- Continuous operations or management of the service’s full life cycle. The process of running a single instance of a database for testing can be rather straightforward. However, the management of the stateful app’s service’s full life cycle can be extremely challenging. Factors that lead to this complexity include production deployment and operation. Both of these entail highly available procedures in deployment, scaling, and error handling.
The key distinction
The most essential difference that separates stateful from stateless applications, and vice versa, is that stateless applications don’t “store” data. Stateful applications, on the other hand, require backing storage. Stateful applications, such as the Cassandra, MongoDB, and MySQL databases, all require some type of persistent storage. That is to say, storage that will effectively withstand any restarts to the service.
The preservation of the state is crucial in regards to running a stateful application. However, any data that flows by way of a stateless service is usually transitory. What’s more, the storage of the state is only in a separate back-end service like a database. Any storage in association with it is, for the most part, momentary. Should the container restart, anything within the storage is completely gone.
As more organizations continue to adopt containers, they are prone to starting off with stateless containers. This is mostly because they are comparatively easier to adopt this new type of architecture. Furthermore, they are better separated from their monolithic application codebase. Taking all of these factors into consideration, they appear more cooperative to independent scaling.
With that, we will transition to another subject that relates to the difference between stateful and stateless. That being the aforementioned ‘containers.’
The containerization of applications is gradually becoming very popular in recent years. This boost in prominence is thanks largely in part to microservices and cloud computing also exploding in popularity. There are many tech companies that are starting to experiment with containerization, ranging from startups to large enterprises.
Containers (alternatively partitions, virtualization engines, or jails) typically bear the resemblance of standard computers. In other words, the programs that run inside them. However, in comparison to a computer functioning on an ordinary operating system, programs inside a container have a restriction. That being they are only able to see the container’s contents and devices that are appointed specifically to that container.
Features pertaining to resource management will often limit the reach of one container’s activities on other containers. The construction of multiple containers can be on each operating system. Moreover, the allocation of a section of the computer’s resources is typical to each different container. Each container consists of any number of various computer programs. Many of these programs operate either at the same time or separately. They can sometimes even interact with one another.
There are three specific challenges when it comes to the widespread adoption of containers:
- It is rather difficult to conquer relentless application-aware storage.
- Management of the application life cycle needs to be preserved long after the first day of deployment.
- Multi-cloud and hybrid cloud support is a key requirement.
Stateful or stateless containers?
The ideal container tends to appear out of the blue, performs its duties, and then promptly disappears. If it executes any operations involving data coming from or going somewhere else, it is given the data. The one providing this data is typically by another process or service. In turn, the result will be handed off to another process. The question here is where could it store the information about its state?
Initially, containers did not have the ability to save state information. There was no arrangement pertaining to continuous storage. Without it, statefulness was pretty much impossible. Their purpose was to only perform operations that did not require statefulness. This would leave certain things like persistent storage and saved state data to other sections of the system.
Those who support purely stateless containers claim that this is the best and most orderly approach. They are of the belief that attempts to introduce statefulness to container deployment are evidence of an obsolete mindset.
The strongest recurring argument in favor of stateless container deployment is that it is very simple. They essentially pop in and out of existence for a particular task and do their job without leaving a trace. If all containers follow this, then the only persistent state data will be what’s in storage and used by the host operating system. Developers need not worry about where to save container state data. Moreover, they don’t need to stress over how to make containers interact with continuous storage.
Stateless vs stateful – Which is Better?
You may be wondering when you should use stateful containers. For that matter, you may also be wondering when are stateless containers the better option. It is no surprise that the answer to these questions depends primarily on the software type that you are deploying. Moreover, it depends on what it needs to do. Does it need to save information concerning its state? Would it be able to get the same results if it were stateless?
For applications that have a design that’s strictly for containers, you can typically ask this question at the microservice level. Chances are good that it may turn out that only a small portion of containers actually need to store state data. This effectively allows the rest to run statelessly.
Again, the main advantage of statelessness is that it is an easy concept. Statefulness, meanwhile, requires a good amount of overhead. This includes continuous storage and, more likely, an entire team for state management. This basically means there is more software to install, manage, and configure. Not only that but there also needs to be more programming time to connect to it by way of the API.
Let’s assume you find yourself needing to make a choice between this overhead or a series of inept workarounds to remain stateless. In this particular case, you might be better off accepting the overhead and including containers that are stateful.
Hopefully, the distinctions inherent with stateful vs stateless are a lot more clear. Understanding the differences between them is important in regards to API, which in turn takes understanding API a step further.