When EC2 usage declines, shifts to different instance families, or moves to other services (e.g., containers or serverless), organizations may find that previously purchased Standard Reserved Instances or Savings Plans no longer match current workload patterns.
This misalignment results in underutilized commitments—where costs are still incurred, but no usage is benefiting from the associated discounts. Since these commitments cannot be easily exchanged, refunded, or sold (except for eligible RIs on the RI Marketplace), the only viable path to recoup value is to steer workloads back toward the covered usage profile.
Convertible Reserved Instances provide valuable pricing flexibility — but that flexibility is often underused. When EC2 workloads shift across instance families or OS types, the original RI may no longer apply to active usage. If the RI is not converted, the customer continues paying for unused commitment despite having the ability to adapt it.
Because conversion is a manual process and requires matching or exceeding the original RI’s value, many organizations fail to optimize their coverage. Over time, this leads to growing pools of ineffective RIs that could have been aligned to real workloads.
Many organizations default to Intel-based EC2 instances due to familiarity or assumptions about workload compatibility. However, AWS offers AMD and Graviton-based alternatives that often deliver significantly better price-performance for general-purpose and compute-optimized workloads.
By not testing workloads across available architectures, teams may continue paying a premium for Intel instances even when no specific performance or compatibility benefit exists. Over time, this results in unnecessary compute spend across development, staging, and even production environments.
Non-production EC2 instances are often provisioned for daytime-only usage but remain running 24/7 out of convenience or oversight. This results in unnecessary compute charges, even if the workload is inactive for 16+ hours per day. AWS supports automated schedules to stop and start instances at predefined times, allowing organizations to retain data and instance configuration without paying for unused runtime. Implementing a shutdown schedule for inactive periods (e.g., nights, weekends) can reduce compute costs by up to 60% in typical non-prod environments.
Many EC2 workloads—such as development environments, test jobs, stateless services, and data processing pipelines—can tolerate interruptions and do not require the reliability of On-Demand pricing. Using On-Demand instances in these scenarios drives up cost without adding value. Spot Instances offer significantly lower pricing and are well-suited to workloads that can handle restarts, retries, or fluctuations in capacity. Without evaluating workload tolerance and adjusting pricing models accordingly, organizations risk consistently overpaying for compute.
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.
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.
Detection:
This inefficiency occurs when an EC2 instance remains in a running state but is not actively utilized. These instances may be remnants of past projects, forgotten development environments, or temporarily created for testing and never decommissioned. If an instance shows consistently low or no CPU, network, or disk activity—and no active connections—it likely serves no operational purpose but continues to generate ongoing compute and storage charges.
Workloads are sometimes deployed in specific AWS regions based on legacy decisions, developer convenience, or perceived performance requirements. However, regional EC2 pricing can vary significantly, and placing instances in a suboptimal region can lead to higher compute costs, increased data transfer charges, or both. In particular, workloads that frequently communicate with resources in other regions—or that serve a user base concentrated elsewhere—can incur unnecessary costs. Re-evaluating regional placement can reduce these costs without compromising performance or availability when done strategically.
EC2 instances are often overprovisioned based on rough estimates, legacy patterns, or performance buffer assumptions. If an instance consistently uses only a small fraction of its provisioned CPU or memory, it likely represents an opportunity for rightsizing. These inefficiencies persist unless usage is periodically reviewed and instance types are adjusted to align with actual workload requirements.
