Businesses that depend on cloud services live or die by the stability and availability of those platforms. Reliable cloud services are an essential part of employee workflow and sales cycles for businesses across the globe–and any downtime is a waste of money on both idle workers and missed sales opportunities. A stable cloud service is important for website performance, data storage, data retrieval, and online content creation.
In a best-case scenario of cloud service disruption, workers and customers may be unable to interact with services for a few seconds. Worst-case scenarios can include lost work and long periods of service lockout.
The Uptime Endurance Race
One of the most effective ways to gauge a cloud platform’s reliability is to look at how much time it spends working versus not. This ratio is referred to as uptime versus downtime. In business operations, you want a service that is as close to being online 100% of the time as possible.
Amazon’s S3 cloud service experienced a total of 7 minutes of downtime between October 2014 and September 2015, compared with an impressive 99.99% uptime. That means clients were only blocked from content for a few minutes over an entire year. None of those outages were particularly long, either; the seven minutes were spread over 37 brief outage instances. Akamai’s CDN and DNS cloud services comparatively experienced zero downtime over the same duration. It’s important to note that outages may only affect specific regions, so users in different parts of the country may still have access to services while others do not.
Service hiccup frequency is important because any disruption temporarily knocks down services. Brief disruptions can cause significant problems for cloud service customers, but they are still preferable to long-term outages. It is very important that cloud service providers address outages quickly and have the platform back up and running as soon as possible. It’s typical for cloud services to experience a few hours and handful of instances of service loss over the course of a year, but less is always better. Minor disruptions aren’t disastrous and can be worked around, but major outages (lasting for several hours)–as well as frequent brief outages–can be a substantial productivity killer.
Load Testing for Peak Demand Analysis
Comparing uptime and downtime doesn’t tell the entire story, however. An overloaded cloud platform may stay online but offer extremely slow performance. Individual users may experience cloud service disruptions and errors that don’t affect the platform as a whole, but can impact user experience for a large number of people. Additionally, when a service has too many users pushing a lot of data, the platform can quickly get overloaded and provoke a noticeable dip in performance quality.
The easiest way to avoid performance quality problems is to make sure your cloud services have enough power to handle the workload. This is where load testing services come in handy, as they can examine how many concurrent users your platform is able to support. A business does not want to become a victim of its own success, wherein a high demand for services overwhelms the system.
Typical cloud service disruptions occur at what’s called the request stage. You’ve likely experienced this type of error when you performed a search or clicked a link on a website and experienced a long load time that ended with a blank page. An overloaded platform may take so long to respond to user data requests that the device requesting the information experiences a timeout (and stops waiting). In other cases, a simple task that normally takes a few seconds may take several minutes to complete, aggravating employees and customers alike. Request errors can be caused by inefficient programming as well as insufficient hardware. Problems with timeouts and very long load times are typically exacerbated by overflowing the system with requests. It is possible, but unlikely, that server problems here can take down the platform.
Cloud service disruption errors that occur during the execution stage identify problems with platform performance, data access inefficiencies, and occasionally insufficient performance capabilities. Errors that spring up on the application level need to be addressed by debugging software. Additionally, online applications may experience problems because the software can’t communicate with the database and hangs up. Database issues may be addressed by adding database access capacity or replacing a failing system.
Looking at things like uptime/downtime comparison and load testing service quality paints a detailed picture of how reliable your cloud services operate. Service analysis data can be indispensable for a business in addressing online reliability concerns before they become major problems.