Do Cloud-Native Architectures Make Apps More Reliable?

Why are we moving our applications to cloud-native architectures? Companies are undergoing massive migration transformations to move monolithic, on-premises applications to cloud-native architectures. Why are they doing this? What benefits are they hoping to get from using a cloud-native architecture?

While there are many advantages, one of the significant customer-facing advantages is improved availability and reliability. In short, cloud-native architectures are supposed to keep applications operating more effectively.

But do cloud-native architectures really make applications more reliable?

Reliability Vs. Availability

Before we answer that question, let’s talk about the difference between reliability and availability. Reliability and availability are two distinct but related concepts. According to Architecting for Scale, reliability is:

“[T]he ability of a system to perform the operations it is intended to perform without making a mistake. Availability, on the other hand, is the ability of a system to be operational when needed to perform those operations.”

Simply put, a system that adds 2 + 3 and returns 6 has poor reliability. A system that is asked to add 2 + 3 and doesn’t return a result has poor availability.

In general, reliability problems are easier to solve than availability problems. Simple test suites can often catch reliability problems. Availability problems often can’t be caught without operating production systems at scale. However, cloud-native architectures can help improve both an application’s reliability and availability.

How Cloud-Native Improves Reliability

Cloud-native architectures help improve an application’s reliability in many ways.

A cloud-native application is composed of microservices. Each service is a self-contained, API-based mini-application. Since each service is self-contained and necessarily simpler than the whole application, the complexity of each service is reduced. Reduced complexity means fewer bugs and higher reliability.

Each service is also easier for a single developer to wrap their mind around, rather than needing to think as deeply about the interactions within a giant monolith. This means it’s easier for developers to focus, which means better, more innovative and higher-quality changes. These changes are less likely to negatively impact the system’s overall reliability.

How Cloud-Native Improves Availability

Deployments in a cloud-native application are automated and go out much more frequently than in a traditional monolithic deployment process. While a monolith may be deployed once a week or once or twice a month, a typical microservice may be deployed daily or multiple times daily.

This means fewer changes per deployment, which means higher overall availability. Additionally, since the changes are smaller, rollbacks are easier to implement when there is a problem. Finally, this means shorter downtime during deployment-related outages.

Improving an application’s availability usually involves improving two key operational metrics: MTTD and MTTR.

MTTD, or mean time to detection, is how long it takes from when a problem first occurs until it has been first noticed. Observability systems, logging and monitoring often focus on improving this metric. Systems monitor specific metrics and notify when the metric strays from a normal range. Modern observability systems use AI tools to detect abnormal patterns and issues.

Observability systems can monitor complex monolithic applications, yet they can miss important indicators in large complex systems. In a simpler, microservices-based system, problem indicators are more visible and faster to detect, improving MTTD.

MTTR, or mean time to repair, is how long it takes after a problem has been first noticed until it is resolved and no longer an issue. This is mainly driven by an engineer trying to identify the root cause of a problem, fix the problem and then deploy the fix.

Often, observability systems can pinpoint which service is causing a particular problem with reasonable accuracy. This means that only a single service or two needs to be analyzed to fix an issue. In addition, given that individual services are much simpler than a monolithic application, it’s easy and faster to identify a problem in a service. Then, as discussed previously, the more straightforward change can be deployed quicker with less likelihood of negatively impacting the rest of the application, improving MTTR.

All of this improves an application’s availability.

Keeping Applications Operating

Keeping their critical applications operating is essential for most modern companies and leveraging tools and processes to improve availability and reliability is crucial for nearly all applications.

Cloud-native application architectures help maintain an application’s operability more easily and with less complexity than a traditional monolithic application.

Lee Atchison

Lee Atchison is an author and recognized thought leader in cloud computing and application modernization with more than three decades of experience, working at modern application organizations such as Amazon, AWS, and New Relic. Lee is widely quoted in many publications and has been a featured speaker across the globe. Lee’s most recent book is Architecting for Scale (O’Reilly Media). https://leeatchison.com

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