Why is stateless transactions a problem with web enabled transactions

Kubernetes is a container orchestration tool that performs automatic load balancing and other services to manage a microservices-based architecture. Essentially, it can automatically duplicate containerized microservices, distribute client traffic, balance server resources for optimum performance.

All of this allows you to scale an application to deal with varying levels of client traffic. Kubernetes can spin-up thousands of containerized microservices to manage virtually any number of requests. Key takeaways: When containerized microservice are stateless, they support scalability and high availability because container orchestration and load balancing tools automatically spin up new instances of individual app components as client traffic requires.

This achieves an agile framework that scales up or down to handle any level of traffic. The decision to use stateful versus stateless apps boils down to your scalability requirements and what you need the app to do. If your app needs to store session data to process transactions in-context and if the server can handle the expected processing load, a stateful system is probably best. Therefore, REST API development often goes hand-in-hand with application development — especially when building a scalable, service-oriented application architecture comprised of pluggable, stateless microservices.

DreamFactory itself is a scalable and stateless application that offers cutting-edge tools for building applications and managing API requests and interactions between them.

Want to try DreamFactory for yourself? Sign up for a free hosted trial now! Features Features. Integrations Authentication. File Storage. Much More Resources Customers. Case Studies. Stateless Web App Design. Stateful vs. Never miss out on the latest API tips and news. Join the DreamFactory newsletter list. Product Solutions. Company Blog. About Us. We can very easily extend this fault tolerance mechanism across multiple data centers, so that even the loss of an entire data center will not bring down our service.

Individual processing elements can be quite small in scale: we can keep the architecture of these elements simple by not worrying about trying to make them very powerful, for example, with support for lots of multi-core parallelism.

We can also change the number of processing elements on the fly scaling both out and in in response to changing load — enabling us to make the most efficient use of compute resources at all times. All of this depends, of course, on our ability to build and deploy a highly scalable and very fault-tolerant storage system in which to keep all of our application state.

Because this is an absolutely fundamental requirement of the stateless processing design pattern, there has been a lot of investment in this area, particularly by the main Web-scale players. Many of the solutions that they have built to address this need are available as open source.

For example, one of the leading distributed state stores, Apache Cassandra, was originally developed at Facebook, and is now used by Netflix, Twitter, Instagram and Webex among many others. Test results published by Netflix show Cassandra performance scaling linearly with number of nodes up to , and handling over a million writes per second with 3-way redundancy — more than enough to handle the needs of most telco-style services even with many hundreds of millions of subscribers.

Cassandra includes support for efficient state replication between geographically separate locations, and therefore provides an excellent basis for extremely resilient geo-redundant services. Other design patterns worth mentioning include stream processing based on frameworks such as Heron or Storm and serverless processing, best exemplified by Amazon Lambda.

These have only emerged relatively recently, but they definitely have potential to advance the state of the art in CNF design. For a deeper dive into cloud native architecture, please download the white paper. Skip to Content. In this article, we will cover the fundamental differences between stateful and stateless microservices. Keeping the state is critical for a stateful service. On the other hand, a stateless service can work using only pieces of information available in the request payload, or can acquire the required pieces of information from a dedicated stateful service, like a database.

Here a rapid overview of the main differences between a stateless and stateful service. This may work for stateless microservices, but when it comes to stateful ones, it can be a disastrous approach in which customer transactions or data are lost due to unreliable performance Persistent storage — Each stateful data service may need or support a different kind of storage type for example block devices or distributed filesystems , and determining the type of backing storage for a stateful service can be challenging These challenges are in part because many stateful microservices were built for a legacy environment , and are probably monolithic.

Organizations may begin by attempting to containerize their stateful services, but then they need to develop highly specific tooling to coordinate numerous related instances for high availability or employ other sophisticated strategies to deploy, manage or operate these services.

What about SaaS? Every time it carries each operation from the scratch just like the first time and provides functionality to use print, CDN Content Delivery Network or the Web Servers in order to process every short-term request. For example, someone is searching a question in the search engine and pressed the Enter button. In case if the searching operation gets interrupted or closed due to some reason, you have to start a new one as there is no saved data for your previous request.

A Stateful application remembers specific details of a user like profile, preferences, and user actions. For example, your shopping cart while using any website in Cloud. Each time you select an item and add it in your cart, you add it with the items added previously and eventually, you navigate to the checkout page.