Some S3 lifecycle policies are configured to transition objects from Standard storage to Intelligent-Tiering after a fixed number of days (e.g., 30 days). This creates a delay where objects reside in S3 Standard, incurring higher storage costs without benefit. Since Intelligent-Tiering does not require prior access history and can be used immediately, it is often more efficient to place objects directly into Intelligent-Tiering at the time of upload. Lifecycle transitions introduce unnecessary intermediate costs that can be avoided entirely through configuration changes.
VPC Interface Endpoints are commonly deployed to meet network security or compliance requirements by enabling private access to AWS services. However, these endpoints often remain provisioned even after the original use case is deprecated. In some cases, the applications have been decommissioned; in others, traffic routing has changed and the endpoint is no longer used. Since interface endpoints generate hourly charges whether or not they are used, identifying and removing inactive ones can eliminate unnecessary costs.
Manual snapshots are often created for operational tasks like upgrades, migrations, or point-in-time backups. Unlike automated backups, which are automatically deleted after a set retention period, manual snapshots remain in place until explicitly deleted. Over time, this can lead to an accumulation of snapshots that are no longer needed but still incur monthly storage charges. This is particularly common in environments where snapshots are taken frequently but not consistently reviewed. If left unmanaged, manual snapshots can become a source of ongoing cost, especially for large databases or when snapshots are copied across regions.
GCP VM instances are often provisioned with more CPU or memory than needed, especially when using custom machine types or legacy templates. If an instance consistently consumes only a small portion of its allocated resources, it likely represents an opportunity to reduce costs through rightsizing. Without proactive reviews, these oversized instances can remain unnoticed and continue to incur unnecessary charges.
NAT Gateways are convenient for enabling outbound access from private subnets, but in data-intensive environments, they can quietly become a major cost driver. When large volumes of traffic flow through the gateway—particularly during batch processing, frequent software updates, or hybrid cloud integrations—the per-GB charges accumulate rapidly. In some cases, replacing a managed NAT Gateway with a self-managed NAT instance can substantially reduce costs, provided that the organization is prepared to operate and maintain the alternative solution.
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.
