Scalability is a topic of constant discussion in the technology sector. An important catchphrase. Every single IT representative ever has said something like, “Our technology is eminently adaptable and capable of adaptive accessibility across many change vectors.” What does it all mean, though, and why is “scalability” such a hot buzzword in IT marketing?
To begin, it’s safe to presume that “scalability” in the context of IT platforms and applications means expanding in size. Although the ‘flexibility-factor’ in cloud computing results from the cloud model’s capacity to permit companies to both raise and lower (downwards) the quantity of technology consumption depending upon cyclically changing needs, normally when we talk scalability, we mean the drive to get bigger.
Developer Operations and Autonomous Cloud Activist at Dynatrace. Grabner argues that modern scalability could be measured by a number of key factors that measure the behavior of a scaling application (or other type of lower-level software service), which helps to justify the need for businesses to consider how their software behaves when the business is driving towards increased scale.
According to Grabner, scalability can be defined as a measure of a program’s ability to adapt to changes in workload behavior, whether those changes are planned (such as increased traffic on Monday morning when all employees log on to their systems) or unplanned (such as when a viral news story drives people to visit a particular website) (measured in page load times and responsiveness).
The Logic of Grocery Store Apps
To simplify the concept of scalability, I often use a grocery store as an illustration. To accommodate growth, a supermarket can either hire more cashiers to work the registers during peak shopping times (such as the evenings and weekends) or build and activate more automated self-service checkouts. The supermarket can essentially modify its operational strategy to accommodate greater throughput from the same core estate of business (presuming it has also provisioned for product stock levels), guaranteeing that customers’ shopping experiences (the time it takes from entering to leaving the shop) remain constant regardless of the store’s volume. “The parallel in software scaling boils down to whether an application or service can handle greater throughput in terms of more users, more computations, and more input/output while maintaining the same performance or end user experience,” explained Grabner of Dynatrace.
Service Level Indicators (SLIs) can be used to measure the progress of an IT scalability project and validated against Service Level Objectives (SLOs) to ensure that the Service Level Agreements (SLAs) set out by the company are satisfied.
Distinguishing scalability definitions
Couchbase is an open source document-oriented database business, and Jeff Morris is the vice president of product and solutions marketing there. Morris argues that the ideal of universal scalability is a “sexy aim” for two reasons, one being that it aligns with the world’s overall goals of greater connectedness and scalability.
“Most of us know that data processing needs will keep rising until every place, thing, action, and app on Earth is profiled, instrumented, analyzed, and automated and transported to the cloud and/or whatever is beyond clouds. “Software engineers are always plotting their next big thing, and they do it with the full anticipation that it will be huge and eventually all-encompassing at tremendous scale,” said Morris.
Morris of Couchbase posits that the expansion of the technology sector is driven, in part, by the cultivation and promotion of a number of crucial ‘change vectors’ that address these hopes (including processing power in the form of CPU speed, cloud, memory, storage, database, user concurrency, programming logic, website uptime, network availability etc.). He argues that these metrics serve as “scalability differentiators” since they can be maintained until the metric in question reaches a physical or mathematical ceiling or becomes more simply “commoditized” across vendors. Morris examines the reasons for our constant pursuit of technological breakthroughs and concludes that the competitor eventually adapts, overcomes obstacles, and develops a new and superior advantage.
Cloudinary’s Chief Technology Officer Tal Lev-Ami has stated that the firm was founded to address a scalability issue in the industry.
You could say that the three of us were consultants helping businesses create web apps. A recurring issue was the lack of a tool to assist developers in the smart management of massive collections of digital photographs. It took a lot of time and effort to manually upload, index, and modify photographs for our clients “at scale.” “Launching an apparently straightforward ‘product sale’ campaign may involve an overlay that advertises that discount on thousands of online product photos, said Lev-Ami, adding that this may be a massive undertaking for developers.
The solution is AI.
As with many other IT firms trying to solve the problem of scaling, Cloudinary employs some kind of AI to aid in its work. When it comes to large-scale digital picture and video management, AI can be used to intelligently reformat videos so that they are suitable for use in a variety of settings by automatically identifying the most significant visual features. Auto-tagging media assets to make them more discoverable and re-usable is just one example of how AI aids creative teams. All of this aids scalability by freeing site developers from boring, repetitive coding tasks.
Keeping the potential for massive upward growth (while still functioning successfully at a lower-scale factor) is often the hallmark of excellence in terms of the underlying architecture upon which any single software platform is designed. “With every software innovation aiming to be the ‘next big thing,'”
In Jason McGee’s line of work, he must be well-versed in all matters pertaining to the scalability of technological systems. McGee, a vice president and chief technology officer for IBM Cloud Platform as well as a fellow at IBM, claims that businesses of all sizes may reap substantial benefits from moving their applications to the cloud.
On the other hand,” McGee offers some words of caution. Whether it’s Black Friday, peak travel season, or a category five hurricane, “the capacity to scale applications and ensure that they are constantly functioning and available to clients [users] is a high responsibility.” Application high availability and continuous operation require the ability to expand to thousands of Kubernetes clusters and the presence of several availability zones in all main geographic locations of the world.
No of the conditions,
McGee cites an example from The Weather Company, which receives around 30,000,000 daily page visits on average (The Weather Company was acquired by IBM in 2016). The weather information on weather.com and wunderground.com is relied upon by millions of users every day, therefore the sites need to be able to quickly and efficiently transfer petabytes of data, especially during extreme weather occurrences.
When severe weather, such as a hurricane, strikes, page views can increase fivefold, reaching 150 million per day. This is in addition to the 25 billion on-demand forecasts and 40 billion API requests that are made each day to connect the forecast to other app services. According to IBM’s McGee, “the difference between life and death can be the availability and reliability of meteorological information in these extreme situations and their capacity to function at a high level during moments of intense demand.”
These days, scalability is a major consideration for cloud-based systems. Due to the competitive nature of the software industry, the best software platforms are those that allow for future development while continuing to function well at smaller scales.
