Storage accounts can accumulate blob data that is no longer actively accessed—such as legacy logs, expired backups, outdated exports, or orphaned files. When these blobs remain in the Hot tier, they continue to incur the highest storage cost, even if they have not been read or modified for an extended period. Without lifecycle management in place, these inactive blobs often go unnoticed and accumulate cost. In many cases, the data could be safely transitioned to a lower-cost tier or deleted altogether, depending on retention needs. Additionally, misconfigured default tier settings at the account or container level can cause even new uploads to be stored in the Hot tier unnecessarily. Azure lifecycle transitions do not incur additional fees, making automation a low-risk optimization method.
NAT Gateways are frequently left running after environments are re-architected, workloads are shut down, or connectivity patterns change. In many cases, they continue to incur hourly charges despite no active traffic flowing through them. Because hourly fees are not tied to whether the gateway is needed—just whether it exists—these resources can quietly drive recurring costs without delivering ongoing value. Identifying and removing unused gateways is a simple way to reduce waste.
Azure VMs are frequently provisioned with more vCPU and memory than needed, often based on template defaults or peak demand assumptions. When a VM operates well below its capacity for an extended period, it presents an opportunity to reduce costs through rightsizing. Without regular usage reviews, these inefficiencies can persist indefinitely.
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.
GCS buckets often persist after applications are retired or data is no longer in active use. Without access activity, these buckets generate storage charges without providing ongoing value. Leaving stale data in Standard storage—designed for frequent access—results in unnecessary cost. If the data must be retained for compliance or future reference, colder tiers offer substantial savings. If it is no longer needed, the data should be deleted.
Managed Disks frequently remain detached after Azure virtual machines are deleted, reimaged, or reconfigured. Some may be intentionally retained for reattachment, backup, or migration purposes, but many persist unintentionally due to the lack of automated cleanup processes. When these detached disks are also inactive—showing no read or write activity—they represent unnecessary ongoing costs. Identifying and removing these orphaned disks can produce meaningful savings without affecting any active workloads.
EBS volumes frequently remain detached after EC2 instances are terminated, replaced, or reconfigured. Some may be intentionally retained for reattachment or backup purposes, but many persist unintentionally due to the lack of automated cleanup. When these detached volumes are also inactive—showing no read or write activity—they represent unnecessary ongoing costs. Identifying and removing these orphaned volumes can produce meaningful savings without affecting running workloads.
Read replicas are intended to improve performance for read-heavy workloads or support cross-region redundancy. However, it's common for replicas to remain in place even after their intended purpose has passed. In some cases, they were provisioned for scaling or analytics workloads that no longer exist; in others, they are tied to live environments but not actively receiving queries. Since each replica incurs full RDS costs, retaining one that is no longer used leads to unnecessary ongoing expenses.
S3 Standard is the default storage class and is often used by default even for data that is rarely accessed. Keeping large volumes of infrequently accessed data in S3 Standard leads to unnecessary costs. Data such as backups, logs, archives, or historical snapshots are often strong candidates for migration to colder tiers like S3 Glacier or Deep Archive. If access patterns are unknown or variable, S3 Intelligent-Tiering can reduce costs without requiring manual transitions.
CloudWatch log groups often persist long after their usefulness has expired. In some cases, they are associated with applications or resources that are no longer active. In other cases, the systems may still be running, but the log data is no longer being reviewed, analyzed, or used by any team. Regardless of the reason, retaining logs that no one is monitoring or using results in unnecessary storage costs. If log data is not needed for operational visibility, debugging, compliance, or auditing purposes, it should either be deleted or managed with a shorter retention policy.
