Online gaming brings location-independent access to games previously only available in casinos. However, the real-time and high-stakes nature of these games calls for a cloud infrastructure that delivers a smooth experience regardless of how many players are active at any given time.
For DevOps engineers in gaming companies, massive fluctuations in usage are the norm. Cloud-based gaming applications often experience spikes in demand due to tournaments or other events. To deal with these scaling challenges, many teams decided in favor of cloud native and Kubernetes.
Unfortunately, while Kubernetes handles scaling well, it still poses cost issues. So how can gaming companies keep cloud costs at bay without sacrificing performance?
Handling demand spikes in online gaming applications
Scaling cloud resources is a complex task that calls for continuous planning and maintenance to deliver good application performance without overspending. In the gaming industry, where availability has a direct reputational and revenue impact, businesses are forced to optimize for performance, not cost.
To ensure that, engineers often end up assigning too many cloud resources to these apps. Overprovisioning is the reason why 37% of compute resources for cloud native applications are never used on average. Engineers just want to sleep well at night knowing that the application performs up to user expectations.
The native Kubernetes Cluster Autoscaler comes with significant limitations and often fails to scale down capacity to help companies save costs. This is where advanced automation platforms like CAST AI come into play. By scaling cloud resources up and down in response to real-time demand, they ensure the required performance and uptime at all times at the lowest possible cost.
Benefits of cloud infrastructure automation
Dramatic cost reduction
By implementing automation, teams benefit from a dramatically simplified process for controlling their cloud costs and resources.
“I don’t have to think about what kind of cost optimization I need to do, what kind of security best practices or other controls we need to have in place, and things like that. CAST AI is super easy and helpful that way,” said Sanjay Kumar Singh, Head of DevSecOps at Games24x7, which saves around 35% on the cloud per year after integrating CAST AI.
Simplified cloud operations
Cloud gaming already offers a simpler developer experience because teams no longer have to worry as much about optimizing games for numerous hardware platforms. They can create a single piece of software that is delivered to multiple devices seamlessly.
By introducing automation to every aspect of their experience – from DevOps processes to cloud cost optimization – companies improve the productivity and well-being of their entire engineering organization. “We started seeing benefits in cost reduction and ease of operations right after integrating CAST AI into our FinOps stack,” said Sanjay Kumar Singh, Head of DevSecOps at Games24x7.
Automation features that contribute to these benefits
- Automated instance selection and rightsizing – an automation platform selects, provisions, and decommissions instances according to dynamically changing workload demands.
- Autoscaling cloud resources up and down – A specific autoscaling mechanism scales cloud capacity up and down to match real-time demand changes without causing downtime. In an ideal scenario, it’s simple to set up and runs automatically in line with the policies you set for it.
- Automated removal of unused cloud resources – When applied to Kubernetes, an automated solution continuously compacts applications into fewer resources, creating empty instances that are removed without causing any downtime.
- Instantly moving workloads to optimal compute instances – Automation tools don’t only show which instances offer the best price-performance ratio but also allow users to instantly replace some (or all) of the non-optimized resources with the most cost-efficient ones instantly.
- Spot instance automation – The best platforms automate the entire spot instance lifecycle to help teams take advantage of these cost-efficient resources. They determine the best match for a particular workload, provision the instance, and, if an interruption occurs, relocate workloads to a fresh spot instance – or a regular on-demand instance if no spot resources are available.
Begin your automation journey now
We built CAST AI to help Kubernetes teams run their clusters without having to worry about the most time-consuming parts of managing the underlying infrastructure and save a significant amount of money in the process. Our customers typically save over 60%, check out their stories.
You might be thinking that signing up for CAST AI is a commitment. But it’s far from that, as there are no upfront payments. You just implement it, see the benefits, and then pay some percentage out of that.Sanjay Kumar Singh, Head of DevSecOps at Games24x7
CAST AI offers a comprehensive set of automation features, all of which operate together to deliver tangible business results.
In contrast to the open-source options available for some of the automation areas outlined above, implementing the platform is a quick process with mere weeks to reach ROI. Also, CAST AI requires virtually zero supervision when in operation, allowing engineers to focus on solving business-critical challenges rather than infrastructure.
Schedule a demo to get a personalized tour of our platform and learn more about its automation features.