By Maxim Melamedov, CEO and Co-Founder of Zesty. Zesty were finalists in the ‘Best Cloud Automation Solution‘ award at The 2024/25 Cloud Awards.

This past November, Netflix live-streamed its first-ever boxing match, with Mike Tyson, the larger-than-life heavyweight legend, facing off against Jake Paul, a feather-ruffling influencer.

It was a highly anticipated event, with Netflix reporting that 108 million global viewers (60 million households) tuned in to watch.

Despite the high turnout, the event wasn’t exactly the smash Netflix was hoping for. Viewers reported glitches, lags, and technical difficulties, quickly taking to social media to voice their frustration.

This is just one example of the considerable consequences of “digital downtime” – connectivity delays across connected networks or platforms. At its worst, downtime can cost millions of dollars per hour, a staggering price tag that is often compounded by disappointed customers, reputational damage, regulatory fines, and lost customer trust and retention.

These streaming stumbles highlight a broader lesson as well: in a world where businesses rely on digital infrastructure for everything from entertainment to critical services, reducing downtime isn’t a luxury, it’s a necessity.  This is far from the first time that huge interest in an event has led to online chaos, with pre-sale ticket launches for high-profile events often causing headaches for millions of fans. While these cases are largely a business problem and can be viewed as such, consider the potential impact of similar downtime in critical sectors like healthcare or public utilities, where outages can cause not just disappointment but real-world harm.

For companies depending on cloud systems, it highlights the importance of cloud optimization, which is key to minimizing the risk of downtime, ensuring seamless user experience, and keeping the consequences at bay.

What causes downtime?

Downtime typically results from failures in digital infrastructure. such as hardware failures, cyberattacks, or network disruptions. However, they can also occur as a result of positive factors, such as peaks in sales or successful digital campaigns which can lead to an overload and a crash.

The cloud can offer straightforward solutions for some of the issues that cause downtime in the first place. However, when mismanaged, it can be a direct contributor to outages.

Organizations today rely on increasingly complex cloud environments, with many adopting a multi-cloud strategy where each platform has unique configurations and is often managed independently. Improper allocation of cloud resources, such as under-provisioning, is another path to outages. Similarly, misconfigurations can lead to bottlenecks, lower performance, or even complete system failure. Additionally, overseeing multiple cloud services without unified management capabilities often causes gaps and vulnerabilities that can lead to downtime.

The rising difficulty of managing and predicting necessary cloud resources can become another source of outages, especially in complex cloud environments. Accurately assessing future needs across thousands or tens of thousands of applications is incredibly challenging. This leads cloud management professionals to opt for costly overprovisioning of resources or to operate reactively, and address problems as they arise rather than prevent them proactively. This results in inefficient cloud resource management and unnecessary costs, which can increase the risk of outages.

The case for cloud infrastructure optimization

Optimized cloud infrastructure is vital to reducing downtime and ensuring system resilience, particularly as businesses attempt to scale and the demands on their systems grow. Automation, machine learning, and predictive analytics allow businesses to maintain cloud resilience even under extreme stress.

One way that cloud optimization provides resilience is through dynamic resource allocation and autoscaling, where compute and storage resources are automatically adjusted based on predictive demand, ensuring that systems aren’t ever overwhelmed.

Consider the surge in viewers during a livestream event (like Netflix’s) or increased web traffic to an e-commerce site on Black Friday — this traffic spike can cause system failures if resources are not dynamically and proportionately allocated. Failure to scale compute resources amidst unpredictable traffic spikes has proven to be a recurring cause of service outages – similar to an incident at Toyota where a critical server ran out of disk space, leading to a major outage that forced the company to halt operations over a dozen manufacturing plants last year.

When resources are properly allocated to handle sudden changes in traffic, it helps ensure continuous uptime and performance optimization.

Automated failover and recovery also help bolster uptime operations by seamlessly switching failing workloads or applications to a backup system before it’s too late. For example, if a localized cloud outage occurs, automated failover could reroute traffic through another region’s infrastructure to ensure uninterrupted service.

Let’s say a natural disaster were to interrupt emergency service calls or disaster management system operations – automatic failover would allow first responders to continue using these critical systems, without relying on infrastructure that was damaged in the incident. Should a similar outage occur at a hospital or throughout a healthcare network, automated failover can be lifesaving – ensuring that cloud-based patient management systems remain accessible.

Even in instances when outages are scheduled – for software updates or other system maintenance – cloud optimization enables automatic rollover so that services can continue as usual without disruption. This capability is imperative for public utility industries, such as wireless networks, water management, or electrical grids, where service interruptions can have billion-dollar consequences and can even prove dangerous to consumers.

These are just a few of the solutions available for mitigating downtime across cloud infrastructures. While each of these tools can be used independently, they are most effective when used in tandem. The result is cloud-based applications that are both scalable and reliable, regardless of traffic conditions. 

Stream on

Netflix’s operational knockout is just one example of the financial and reputational risks of downtime in today’s digital world.

As outside observers, we may never know the core reason behind such issues, yet the incident underscores the critical need for robust, fail-proofed systems that can ensure uptime amid demand spikes, regardless of the underlying infrastructure. To avoid a similar outcome, businesses must adopt proactive cloud optimization strategies that combine tools like autoscaling, failover, and load balancing.

After all, it’s much easier to take a break and relax when you know your systems won’t do the same.