Azure Storage cost optimization to achieve maximum cost savings

Azure storage costs can spiral out of control faster than you think. A few oversized VMs here, some forgotten blob storage there, and suddenly you’re facing a bill that’s double what you budgeted.

The good news? With the right Azure storage cost optimization strategy (from choosing appropriate storage tiers to implementing automated lifecycle policies), you can slash those expenses without sacrificing performance.

In this guide, we’ll cover the main storage options in Azure, when to choose each, cost optimization considerations for each storage type, and ways you can quickly reduce your storage costs. Let’s get to it!

What is Azure Storage Cost Optimization?

Azure Storage Cost Optimization is the strategic practice of minimizing storage expenses while maintaining or improving performance, availability, and functionality of your cloud storage infrastructure. It involves making informed decisions about storage types, access patterns, data lifecycle management, and resource utilization to achieve the best possible return on your storage investment.

At its core, Azure Storage Cost Optimization focuses on ensuring you pay only for what you need, when you need it, while maintaining the performance and reliability requirements of your applications and business processes.

The Main Storage Options in Azure

Data can be stored in any of the available storage options below:

1. Blob Storage

Blob Storage is designed for storing vast amounts of unstructured data optimally. Unstructured data doesn’t stick to a particular definition or model, such as binary data, text, JSON, or XML.

Blob Storage is mainly used for the following purposes:

• Storing log files
• Storing data for backup and recovery
• Storing data for analysis and archiving purposes
• Storing data in multiple locations to promote distributed access.
• Accessing images or documents directly from a browser.

Cost Optimization Considerations:

• Access tier optimization – Use Hot tier for frequently accessed data, Cool tier for infrequently accessed data, and Archive tier for long-term retention
• Lifecycle management policies – Implement automated policies to transition blobs between tiers based on age or access patterns
• Reserved capacity – Purchase reserved capacity for predictable storage needs to achieve significant cost savings
• Data compression – Compress data before storing to reduce storage volume and associated costs
• Redundancy level selection – Choose appropriate redundancy (LRS, ZRS, GRS, RA-GRS) based on durability requirements vs cost trade-offs

2. File Storage

Using the industry-standard Server Message Block (SMB), Network File System (NFS), and Azure Files REST APIs, Azure Files provides fully managed file shares in the cloud. Both cloud and on-premises implementations can concurrently mount Azure file shares.

SMB Azure file shares are available from Windows, Linux, and macOS clients. Linux clients can access NFS Azure file sharing. SMB Azure file shares can also be cached on Windows servers with Azure File Sync for quick access close to where the data is utilized.

Cost Optimization Considerations:

• Standard vs Premium tier selection – Choose Standard for cost-effective general-purpose workloads, Premium for high-performance requirements with predictable costs
• Provisioned vs consumed capacity – Standard tier charges for consumed storage, while Premium requires provisioning capacity upfront
• Share sizing optimization – Right-size file shares to avoid over-provisioning in Premium tier or optimize storage usage in Standard tier
• Snapshot lifecycle management – Implement policies to manage file share snapshots and prevent accumulation of unnecessary snapshot costs
• Access tier optimization – Use Hot tier for frequently accessed files and Cool tier for archival scenarios (where available)

3. Disk Storage

Azure Disk Storage provides high-performance, durable block storage for Azure virtual machines. Managed disks are designed to provide enterprise-grade durability and availability, with built-in redundancy and seamless integration with Azure services.

Azure Disk Storage offers several performance tiers to meet different workload requirements and cost considerations:

Common Use Cases for Azure Disk Storage:

• Operating system disks for virtual machines
• Database storage for mission-critical applications
• Data disks for applications requiring persistent storage
• High-performance computing workloads requiring low latency
• Development and testing environments with varying performance needs

Cost Optimization Considerations:

• Entity design optimization – Design entities to minimize storage size and reduce the number of properties to lower costs per transaction
• Partition key strategy – Use effective partition keys to ensure balanced load distribution and optimal query performance
• Query optimization – Structure queries to minimize the number of entities scanned and reduce transaction costs
• Data retention policies – Implement automated cleanup of obsolete entities to avoid accumulating unnecessary storage costs
• Batch operations – Use batch transactions when possible to reduce the number of individual operations and associated costs

5. Queue Storage

A service for storing many messages is called Azure Queue Storage. You can access messages from anywhere worldwide with HTTP or HTTPS authenticated calls. A queue message may have a maximum size of 64 KB. Millions of messages may be in a queue up to the storage account’s maximum capacity. Queues are frequently used to build up a backlog of tasks for asynchronous processing.

Common Use Cases for Azure Queue Storage:

• Asynchronous processing of background tasks and job scheduling
• Decoupling application components to improve scalability and reliability
• Workflow coordination between distributed services and microservices
• Order processing and inventory management systems
• Event-driven architectures and notification systems

Cost Optimization Considerations:

• Message retention policies – Set appropriate message time-to-live (TTL) values to automatically clean up processed messages and avoid storage accumulation
• Batch processing – Process messages in batches to reduce the number of individual operations and minimize transaction costs
• Queue scaling – Monitor queue depth and scale processing capacity to prevent message buildup and associated storage costs
• Message size optimization – Keep messages as small as possible while staying within the 64KB limit to maximize cost efficiency
• Regional placement – Deploy queues in the same region as processing applications to minimize data transfer costs

6. Data Lake Storage

Azure Data Lake Storage Gen2 is a highly scalable and cost-effective data lake solution built on Azure Blob Storage. It combines the scalability and cost benefits of object storage with the performance and analytics capabilities required for big data workloads.

Data Lake Storage Gen2 introduces a hierarchical namespace that enables efficient data organization and management while maintaining compatibility with existing Blob Storage APIs and tools. This unique architecture provides both file system semantics and object storage economics.

Common Use Cases for Azure Data Lake Storage:

• Storing large volumes of structured, semi-structured, and unstructured data for analytics
• Data warehousing and business intelligence solutions
• Machine learning and artificial intelligence workloads
• IoT data ingestion and processing
• Log and telemetry data collection and analysis

Cost Optimization Considerations:

• Access tier optimization – Leverage Hot, Cool, and Archive tiers based on data access patterns and analytics requirements
• Lifecycle management – Implement automated policies to transition data between tiers as it ages or becomes less frequently accessed
• Compression strategies – Apply appropriate data compression techniques to reduce storage volume and associated costs
• Partitioning strategies – Organize data using effective partitioning schemes to minimize data scanning costs in analytics queries
• Reserved capacity – Consider reserved capacity pricing for predictable, long-term storage requirements

When Should You Use Each Storage Type?

Azure Storage Account Pricing Models: How Does Storage Pricing in Azure Work?

Azure storage offers a flexible pricing model to accommodate various usage patterns and business needs.

4 Crucial Factors Affecting Azure Storage Costs

Several factors influence Azure storage costs, and understanding these factors is essential for effectively managing expenses and optimizing your storage usage. Here are crucial factors that impact Azure storage costs:

1. Redundancy Level – Azure provides options for data redundancy to ensure data durability. The choice of redundancy level, such as Locally Redundant Storage (LRS), Zone-Redundant Storage (ZRS), Geo-Redundant Storage (GRS), or Read-Access Geo-Redundant Storage (RA-GRS), directly impacts costs. More redundant options generally come with higher costs.
2. Access Tiers (Blob Storage) – Azure Blob Storage introduces access tiers – Hot, Cool, and Archive. The selected access tier depends on data access frequency. While the Hot access tier incurs higher costs but provides lower latency, the Cool and Archive tiers offer cost savings for less frequently accessed data.



3. Data Transfer Costs – The transfer of data to and from Azure incurs costs, encompassing data movement between Azure regions, transfer to the internet, and transfer between Azure services.
4. Storage Capacity Used – The amount of storage space you consume directly correlates with costs. With data growth, storage expenses increase. Regularly monitoring and optimizing storage capacity are essential for effective cost management.

5 Best Practices for Reducing Azure Storage Costs

We’ll delve into strategies and best practices for reducing Azure storage costs, focusing on key aspects such as analyzing storage usage, implementing data lifecycle management, utilizing storage tiers effectively, leveraging Azure Blob Storage features, and optimizing data transfer and network costs.

1. Analyzing Storage Usage and Identifying Inefficiencies

The first step towards cost reduction is gaining insights into your storage usage patterns. Azure provides robust tools like Azure Monitor and Azure Storage Analytics that offer visibility into your storage metrics. Analyze these metrics to identify inefficiencies, such as underutilized resources or irregular access patterns. By understanding how your storage is utilized, you can make informed decisions to optimize and rightsize your storage infrastructure.

2. Implementing Data Lifecycle Management Policies

Azure Storage Lifecycle Management enables you to define policies that automatically transition data between storage tiers or delete obsolete data based on predefined criteria. By setting up lifecycle policies, you ensure that data is stored in the most cost-effective tier while maintaining accessibility when needed. This not only streamlines operations but also minimizes unnecessary storage costs.

3. Utilizing Storage Tiers Effectively

Azure Blob Storage offers different access tiers – Hot, Cool, and Archive, each catering to varying data access frequencies. Optimize costs by strategically placing data in the most suitable tier. Frequently accessed data may reside in the Hot tier for lower latency, while infrequently accessed data can be moved to the Cool or Archive tier for cost savings.

4. Leveraging Azure Blob Storage Features for Cost Savings

Azure Blob Storage provides features that can significantly impact costs. Utilize data compression and deduplication to reduce storage space requirements. Implementing soft delete can protect against accidental data deletions, avoiding potential data recovery costs. Additionally, take advantage of features like versioning to manage changes to your data efficiently.

5. Optimizing Data Transfer and Network Costs

Data transfer costs can contribute significantly to your overall Azure expenses. Optimize data transfer by strategically selecting Azure regions, leveraging Azure Content Delivery Network (CDN) for caching, and minimizing unnecessary data movement between Azure services. Efficient network usage not only improves performance but also helps control costs associated with data transfer.

Reducing Azure storage costs is essential and it is a holistic endeavor that involves a combination of analytical insights, automation, and strategic decision-making.

Quick Wins for Immediate Azure Storage Cost Savings

This section provides actionable steps you can take today, this week, and over the next 90 days to start reducing your Azure storage costs immediately.

Immediate Actions to Implement Today

1. Identify and Delete Unattached Disks

Navigate to Azure Portal > All Resources > Filter by “Disk” > Look for disks with “Unattached” status. These disks continue billing even when not connected to VMs and often represent 10-20% of wasted storage spend.

2. Review Blob Storage Access Tiers

Go to your storage accounts and check if data in Hot tier hasn’t been accessed in 30+ days. Move infrequently accessed data to Cool tier for immediate 50% savings, or Archive tier for 80% savings.

3. Enable Storage Analytics

Turn on Azure Storage Analytics in your storage accounts to start collecting usage metrics. This data is essential for making informed optimization decisions and costs pennies to enable.

4. Set Up Basic Cost Alerts

Create budget alerts in Azure Cost Management for your storage accounts. Set thresholds at 80% and 100% of your expected monthly storage costs to catch unexpected spikes early.

5. Audit Premium Storage Usage

Review all Premium SSD and Premium Blob storage usage. Identify development, testing, or non-critical workloads that can be moved to Standard tiers for 60-70% cost reduction.

Cost-Saving Actions to Take This Week

6. Implement Basic Lifecycle Policies

Create simple lifecycle management rules to automatically move blobs to Cool tier after 30 days and Archive tier after 90 days. This single action can reduce storage costs by 30-50% for typical workloads.

7. Clean Up Blob Snapshots

Identify old blob snapshots that are no longer needed. Snapshots accumulate costs over time and are often forgotten. Delete snapshots older than your backup retention requirements.

8. Right-Size Managed Disks

Check disk utilization in Azure Monitor. Disks with less than 50% utilization can often be downsized. Even reducing from P30 (1TB) to P20 (512GB) saves $73/month per disk.

9. Enable Soft Delete with Shorter Retention

Configure blob soft delete with a 7-day retention instead of the default 30 days to balance data protection with cost efficiency.

10. Consolidate Small Files

If you have many small files in blob storage, consider consolidating them into larger files or using Azure Data Lake Storage Gen2 for better cost efficiency with hierarchical namespace.

Expected Savings by Action

Monthly Azure Storage Cost Optimization Checklist

Every Month

• Review cost trends and identify unexpected increases
• Audit unattached disks and unused storage accounts
• Check lifecycle policy effectiveness and adjust rules if needed
• Review access tier distribution and optimize based on usage patterns
• Validate snapshot retention policies and clean up old snapshots

Every Quarter

• Analyze reserved capacity opportunities for stable workloads
• Review and optimize data redundancy levels
• Audit premium storage usage and identify downgrade opportunities
• Assess data compression opportunities for large datasets
• Review regional placement strategy for cost and performance optimization

Every Six Months

• Comprehensive storage architecture review
• Benchmark costs against industry standards
• Evaluate new Azure storage features for cost optimization
• Review and update governance policies and cost allocation strategies
• Training update for teams on latest cost optimization practices

How Can Turbo360 Help You Optimizing Your Azure Storage Costs?

This section will explain how Turbo360 will help us optimize your Azure Storage Spent.

Automate Tasks to Change the Access Tier of Blobs

Consider Blob storage, all the data must be kept from the Hot tier, which is costly. Only the frequently accessed or modified data can be stored in the hot tier, and less frequently accessed data can be stored in the cool tier.

The data stored only for backup and recovery purposes can be stored in the archive tier, which costs much less. But manually identifying these resources and moving them to the required tiers is tedious. Turbo360 offers automated tasks to quickly move the least modified blobs to the required tiers.

Automated Tasks to Delete Blobs Based on Created or Modified at

Turbo360’s automated tasks enable you to achieve Azure storage cost optimization by enabling you to automatically delete blobs that were created or modified before a particular date. This helps us eliminate the unnecessary obsolete blobs in a single click.

Cost Analyzer in Turbo360

Turbo360 Cost Analyzer helps us visualize the cost spent across multiple subscriptions in a single place. So we can set up views and monitors to get alerted whenever there is a violation in the configured trend, determining the cost spent on storage resources.

Other Storage Account-Related Features in Turbo360

Turbo360 also allows us to view, resubmit and delete the messages in storage queues. It is also possible to query the entities in a storage table and get alerted whenever there is a violation of the configured rules by setting multi-metric monitoring for Azure Storage Account.

Conclusion

Achieving cost optimization in Azure Storage involves a combination of proactive monitoring, intelligent scaling, automation, and leveraging platform recommendations. By incorporating these best practices into your cloud management strategy, organizations can ensure that their storage resources are both efficient and cost-effective.

Related reading

• Azure Cost Optimization Best Practices
• A Complete guide on Azure Cost Management
• How to optimize Azure Blob Storage cost?