When an EC2 instance is dedicated primarily to internet-facing traffic, regional differences in data transfer pricing can drive a substantial portion of total costs. Hosting such workloads in a region with higher egress rates leads to elevated expenses without improving performance. Migrating the workload to a lower-cost region can yield significant savings while maintaining equivalent service quality, especially when no strict latency or compliance requirements dictate the original location.
Running non-production clusters solely on On-Demand Instances results in unnecessarily high compute costs. Development, testing, and QA environments typically tolerate interruptions and do not require the continuous availability guaranteed by On-Demand capacity. Introducing Spot-backed node groups in non-production environments can significantly reduce infrastructure expenses without compromising business requirements.
Clusters that no longer run active workloads but remain provisioned continue incurring hourly control plane costs and may also maintain associated infrastructure like node groups or VPC components. Inactive clusters often persist after environment decommissioning, project shutdowns, or migrations. Decommissioning unused clusters eliminates unnecessary operational costs and simplifies infrastructure management.
When Kubernetes workloads request more CPU and memory than they actually consume, nodes must reserve capacity that remains unused. This leads to lower node density, forcing the cluster to maintain more instances than necessary. Aligning resource requests with observed utilization improves cluster efficiency and reduces compute spend without sacrificing application performance.
Workloads with consistently low CPU and memory usage may no longer serve active traffic or scheduled tasks, but continue reserving resources within the cluster. These idle deployments often remain after project migrations, feature deprecations, or experimentation. Removing inactive workloads allows node groups to scale down, reducing infrastructure costs without impacting active services.
Application Load Balancers that no longer serve active workloads may persist after application migrations, architecture changes, or testing activities. When no incoming requests are processed through the ALB, it continues to generate baseline hourly and LCU charges. Identifying and decommissioning unused ALBs helps reduce networking expenses without impacting operational environments.
Classic Load Balancers that no longer serve active workloads will persist if they are not properly decommissioned. This often happens after application migrations, architecture changes, or testing activities. Even if no connections or traffic are passing through the CLB, it continues to incur baseline charges until manually deleted. Identifying and removing unused load balancers helps eliminate waste without impacting operations.
Network Load Balancers that are no longer needed often persist after architecture changes, service decommissioning, or migration projects. When no active TCP connections or traffic flow through the NLB, it still generates hourly operational costs. Identifying and removing these idle resources helps reduce unnecessary networking expenses without affecting service availability.
Gateway Load Balancers that no longer have active traffic flows can continue to exist indefinitely unless proactively decommissioned. This often happens after network topology changes, security architecture updates, or environment deprecations. Without active packet forwarding, the GLB provides no functional benefit but still incurs hourly and data transfer costs.
Oversized instances within Auto Scaling Groups lead to inflated baseline costs, even when scaling adjusts the number of instances dynamically. When workloads consistently use only a fraction of the available CPU, memory, or network capacity, there is an opportunity to downsize to smaller, less expensive instance types without sacrificing performance. Right-sizing helps balance capacity and efficiency, reducing compute spend while preserving workload stability.
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