Azure Files Standard tier is cost-effective for low-traffic scenarios but imposes per-operation charges that grow rapidly with frequent access. In contrast, Premium tier provides consistent IOPS and throughput without additional transaction charges. When high-throughput or performance-sensitive workloads (e.g., real-time application data, logs, user file interactions) are placed in the Standard tier, transaction costs can significantly exceed expectations.

This inefficiency occurs when teams prioritize low storage cost without considering IOPS or throughput needs, or when workloads grow more active over time without reevaluation of their storage configuration. Unlike Blob Storage, migrating to Azure Files Premium requires creating a new storage account, making this an often-overlooked optimization.

Azure Blob Storage tiers are designed to optimize cost based on access frequency. However, when frequently accessed data is stored in the Cool or Archive tiers—either due to misconfiguration, default settings, or cost-only optimization—transaction costs can spike. These tiers impose significantly higher charges for read/write operations and metadata access compared to the Hot tier.

This misalignment is common in analytics, backup, and log-processing scenarios where large volumes of object-level operations occur regularly. While the per-GB storage rate is lower, the overall cost becomes higher due to frequent access. This inefficiency is silent but accumulates rapidly in active workloads.

Azure users may enable the SFTP feature on Storage Accounts during migration tests, integration scenarios, or experimentation. However, if left enabled after initial use, the feature continues to generate flat hourly charges — even when no SFTP traffic occurs.

Because this fee is incurred silently and independently of storage usage, it often goes unnoticed in cost reviews. When SFTP is not actively used for data ingestion or export, disabling it can eliminate unnecessary charges without impacting other access methods.

When EC2 instances within a VPC access Amazon S3 in the same region without a Gateway VPC Endpoint, traffic is routed through the public S3 endpoint and incurs standard internet egress charges — even though it remains within the AWS network. This results in unnecessary egress charges, as AWS treats this traffic as data transfer out to the internet, billed under the S3 service.

By contrast, provisioning a Gateway Endpoint for S3 allows traffic between EC2 and S3 to flow over the AWS private backbone at no additional cost. This configuration is especially important for data-intensive applications, such as analytics jobs, backups, or frequent uploads/downloads, where the cumulative data transfer can be substantial.

Because the egress cost is billed under S3, it is often misattributed or overlooked during EC2 or networking reviews, leading to silent overspend.

Retention of stale data occurs when old, no longer needed records are preserved within active Snowflake tables. Without lifecycle policies or regular purging, tables accumulate outdated data.

Because Snowflake’s compute charges are tied to how much data is scanned, retaining large volumes of inactive or irrelevant data can drive up both storage and query execution costs unnecessarily.

Snowflake automatically maintains previous versions of data when tables are modified or deleted. For tables with high churn—meaning frequent INSERT, UPDATE, DELETE, or MERGE operations—this can cause a significant buildup of historical snapshot data, even if the active data size remains small.

This hidden accumulation leads to elevated storage costs, particularly when Time Travel retention periods are long and data change rates are high. Often, teams are unaware of how much snapshot data is being stored behind the scenes.

Snapshots are often created for short-term protection before changes to a VM or disk, but many remain in the environment far beyond their intended lifespan. Over time, this leads to an accumulation of snapshots that are no longer associated with any active resource or retained for operational need.Since Azure does not enforce automatic expiration or lifecycle policies for snapshots, they can persist indefinitely and continue to incur monthly storage charges. This inefficiency is especially common in development environments, migration efforts, or manual backup workflows that lack centralized cleanup.Snapshots older than 30–90 days, especially those not tied to a documented backup strategy or workload, are strong candidates for review and removal.

EFS file systems that are no longer attached to any running services — such as EC2 instances or Lambda functions — continue to incur storage charges. This often occurs after workloads are decommissioned but the file system is left behind. A quick indicator of this state is when the EFS file system has no mount targets configured. Without active usage or connection, these orphaned file systems represent pure cost with no functional value. Unlike block storage, EFS does not require an attached instance to incur billing, making it easy for unused resources to go unnoticed.

For Premium SSD and Standard SSD disks 513 GiB or larger, Azure now offers the option to enable Performance Plus — unlocking higher IOPS and MBps at no extra cost. Many environments that previously required custom performance settings continue to pay for additional throughput unnecessarily. By not enabling Performance Plus on eligible disks, organizations miss a straightforward opportunity to reduce disk spend while maintaining or improving performance. The feature is opt-in and must be explicitly enabled on each qualifying disk.

Each Azure VM size has a defined limit for total disk IOPS and throughput. When high-performance disks (e.g., Premium SSDs with high IOPS capacity) are attached to low-tier VMs, the disk’s performance capabilities may exceed what the VM can consume. This results in paying for performance that the VM cannot access. For example, attaching a large Premium SSD to a B-series VM will not provide the expected performance because the VM cannot deliver that level of throughput. Without aligning disk selection with VM limits, organizations incur unnecessary storage costs with no corresponding performance benefit.