SaaS Companies Look for Best Performance, Lowest Cost As Cloud Use Spikes
Opsani, the leading provider of AI-driven optimization for cloud applications, released the results of a month-long poll* completed by 1000 C-level executives at SaaS companies, which demonstrates how the spike in cloud services use has affected their organizations’ ability to deliver the best user experience of their products and services, for the lowest costs. Companies surveyed ranged in size from 250 to 5000 employees.
Public cloud use has skyrocketed since the pandemic began. According to analyst firm IDC, cloud revenues have totaled $233.4 billion, a 26 percent year over year increase. Despite this spend increase, 91 percent of respondents in Opsani’s poll were “highly confident” or “confident” that their cloud applications were running efficiently, meaning they felt they were getting the best performance for the lowest cost. That is likely not the case, however, as the survey points to processes and challenges that make the task of cloud optimization near impossible.
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As a result of the surge in cloud usage, modern enterprises are rushing to adopt containers, where they can accelerate the delivery of new features into production daily, rather than quarterly. Opsani’s poll found 95 percent of respondents already deploy mainstream applications via containers, or planned to do so. Unfortunately, optimizing these applications to run effectively without over provisioning on cloud proves difficult in the current landscape.
Avoiding cost creep requires optimizing the application and its environment continuously, but this has become too complex for people to handle. For example, take Google Online Boutique, a 10-tier microservices application and a backend database. It’s a web-based e-commerce app where users can browse items, add them to a cart, and purchase them. To find the optimal performance, there are as many as 75 quintillion configuration permutations that must be adjusted. As a point of reference, there are fewer than 8 quintillion grains of sand on earth. It’s beyond human scale.
Adding to this complexity is the frequency of software updates. Respondents were asked how often their organizations released new code. 14.55 percent said hourly sprints; 43 percent indicated daily updates; and 37 percent released new software weekly. Given the complexity of cloud apps, even those 91 percent who said they were confident of their apps’ performance likely still have significant performance improvements and costs savings to realize if their software is being pushed into production this quickly. When asked how often their organizations optimized their application stack, 82 percent responded “regularly,” and 13 percent said ‘only in emergencies.’
Fortunately, those polled indicated that artificial intelligence and machine learning tools are becoming mainstream, demonstrating awareness that automation can cut costs and boost efficiency. 80.6 percent said their organizations make use of AI tools for faster decision-making purposes; 15 percent said they did not have those tools yet, but were planning to implement them. Where AI used to be a niche technology, Opsani’s poll found widespread acceptance. This indicates a growing use of tools that will take repetitive, mundane tasks out of people’s hands, so they can be redeployed to other, creative value-added jobs.
This was a top concern in the poll, where 54 percent of the respondents indicated that ‘employees wasting time on mundane tasks’ was top of mind when it came to their organizations’ IT and software development talent. 43 percent said their legacy processes were not reflective of today’s technology landscape; 47.6 percent were having difficulty finding the talent needed to complete mission critical tasks; and 35 percent indicated they felt AI would enhance the output of their employee assets.
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When asked about issues that are top of mind when it comes to cloud technology strategy, respondents were fairly evenly split. 65 percent said ‘staying within a certain budget’ was a top priority. 62 percent indicated maximizing resources, such as CPU, bandwidth, etc., was important to them, and ‘making sure cloud apps maintain uptime’ was chosen by another 62 percent.
Uptime was just one of the parameters on executives’ minds; service level objectives were important, too. When asked ‘what are your SLA objective or performance goals for any of your applications or services,’ 63 percent said transactions per second; latency was chosen by 47 percent; dollar per transaction by 43 percent; and IOps and throughput each by 34 percent.
“The poll results were eye-opening in that these leaders realized the importance of optimization, but didn’t realize the complexity required to do it right. This is why we’re seeing more companies rely on AI tools, to place people in positions where they can continue to innovate and add value to the organization,” said Ross Schibler, Co-founder and CEO, Opsani. “AI takes on the difficult and mundane jobs of optimizing the infrastructure, which lets staff work more efficiently to outsmart competitors with ideas, and outlast them with resources.”