My team just got a massive surprise bill because our EKS cluster scaled up during a minor traffic spike and didn't scale back down properly. We’re struggling with "Cloud Waste" from idle resources. What are some automated FinOps guardrails we can put in place to ensure our scaling is cost-effective? I’m looking for specific tools or tagging strategies that help identify orphaned volumes or over-provisioned EC2 instances before they bankrupt us.
3 answers
The first thing you should do is implement "Scale-In" protection only for mission-critical nodes and use "Termination Policies" that target the oldest or most expensive instances first. We saved about 30% monthly by switching to AWS Karpenter instead of the standard Cluster Autoscaler. Karpenter is much smarter at "bin-packing" pods onto the smallest, cheapest instance types available. Also, set up AWS Budgets with an action provider that automatically triggers a Lambda function to throttle non-essential dev environments if the daily spend exceeds a certain threshold.
Have you tried using Spot Instances for your non-critical worker nodes to offset the cost of the traffic spikes?
You should check out the 'AWS Compute Optimizer.' It uses machine learning to suggest the exact instance type you need based on your historical usage.
I second the Compute Optimizer recommendation; it's free and often reveals that you're paying for 4x the RAM you actually use.
We tried Spot Instances, Brian, but our app isn't perfectly stateless yet, so the 2-minute termination notice caused some dropped connections. We’re working on making the microservices more resilient so we can leverage that 70% discount. In the meantime, do you have any tips for better "Right-Sizing" tools that don't require a paid third-party subscription?