Every day, we developers are hustling to keep up with the ever-evolving complexities of cloud infrastructure – and one of the biggest disruptions is the introduction of AI into cloud infrastructure. AWS, for example, has rolled out a wide range of fully managed machine learning services, which may soon help developers optimize their infrastructure more intelligently than ever before.
If your organization is still dealing with the provisioning headaches of traditional VM architecture, it’s probably time to make the switch to containers.
Containers are just a different way to run applications — but in the end, they need to serve your business’s goals.
On the first day at my previous job, my manager asked whether we were getting a good return on investment (ROI) from our cloud infrastructure. After just two days on the job, I could clearly see that we weren’t. Our VM’s CPUs were running at five percent on average, and memory was running below 40 percent.
Does the following conversation sound familiar?
CEO: Our AWS bill has gone to the roof. Why?
VP of engineering: We’re adding new customers! We need enough capacity to keep up with the demand.
CTO: But our average CPU and memory utilization are quite low. Why do we need more capacity if we’re not using all the infrastructure we already have?
VP of engineering: We get traffic spikes throughout the day. We need to be ready for them.