In December, when reports emerged of a new flu strain ravaging Wuhan, most of us assumed the problem would fade away. It is only three months later and we are dealing with a global pandemic. Citizens have been ordered to stay indoors as healthcare systems attempt to “flatten the curve.” These changes have been unpredictable. With all of this change, the question most relevant to the world is: How adaptable are you?

The economic ramifications of this pandemic will be extreme. They are already extreme. Businesses in the travel and tourism sectors have been crippled. Airlines have collapsed. Any industry involved in non-essential products is facing a huge downswing. 

Conversely, there have been significant upswings as well. Internet usage from homes has increased as office-based employees have moved into the digital workspace. Office applications have seen usage and users surge. Away from work, streaming services providers have recorded significant first-time install booms in Spain and Italy, two of the hardest-hit countries. Live-streaming viewership of other channels have ballooned by over 66%. 

Upswings, downswings. The lesson of COVID-19 is this: Life is unpredictable. You never know when the next news report is going to evolve into the worst pandemic in a century. Similarly, in business, you never know when circumstances are going to radically change, for better or for worse. The commercial landscape is full of events that are low probability, but not zero probability.

The Impact of COVID-19 on Cloud Businesses

This unpredictability is especially true for companies that conduct their business in the cloud. Rapidly changing demands in infrastructure are a natural hazard of the territory. COVID-19 seems like a total curveball. But it has merely intensified pressures that were always there. 

Stewart Butterfield, the Slack CEO, is confident that their infrastructure can handle the influx of users and the spike in usage. His confidence is admirable. However, without the right tools, dealing with swings and spikes in cloud usage is difficult. Now more than ever, IT and DevOps teams need to find ways to make their cloud bills as lean as possible. 

When we built Opsani, we weren’t predicting a major global pandemic. But the technology of Continuous Cloud Optimization is built precisely to confer businesses with an invaluable attribute: adaptability to unpredictability

The Opsani engine gives Cloud Ops teams a way to keep costs as low as possible while perpetually fine-tuning their application performance. In most development scenarios, performance tuning only occurs when applications are already struggling, or in response to a downtime event, or when the application fails to meet SLA requirements. 

This is a poor approach to application optimization. Why? Because it leaves you unable to adapt to the unpredictable. In the cloud as in life, if all you can do is react once things have gone wrong, you will probably be overwhelmed. 

But when cloud operators can be agile, they can support their companies during unexpected circumstances. Instead of blindly trying millions of resource and parameter combinations, the Opsani AI engine efficiently determines the most cost-effective settings. This means the infrastructure is always nimble and ready to respond. In situations like COVID-19, whatever the shift in cloud burden for businesses, the infrastructure is ready. 

This adaptability is baked into the core of the Opsani tech. In a continuous cycle of predicting, measuring, and adjusting, our tool constantly seeks ways to optimize resource allocation, as new challenges and requirements arise. 

The COVID-19 outbreak is a tragedy. Everyone at Opsani hopes that our fellow citizens around the world can pull through it safely and with their health intact. But on the other side, we should remember this lesson: So-called “black swan events” can always occur. History is full of them. Ahead of COVID-19, I think there was an unspoken agreement that something like this couldn’t happen; not in 2020, not in our world. 

We all need to think a little more like AI engines, and approach data without any preconceived notions or biases. New and unlikely scenarios are always possible.