14 AWS EBS Optimization Strategies to Increase Performance

Optimizing AWS EBS costs requires a deep understanding of storage volume types, throughput, and IOPS configurations. Over-provisioning or choosing the wrong volume type can lead to unnecessary costs, especially when hidden expenses like snapshot storage and data transfer add up. By right-sizing volumes, selecting the optimal volume type, and automating snapshot management, you can significantly cut costs without sacrificing performance. 

Optimizing AWS EBS performance is essential for maintaining fast, reliable storage that scales with your workload’s demands. Many teams face performance bottlenecks because of incorrect volume types, over-provisioned IOPS, or inefficient snapshot management, which leads to slower response times and increased costs.

This challenge is common: without ongoing monitoring and fine-tuning, EBS volumes can quickly fall out of alignment with workload requirements, causing unnecessary delays and wasted resources.

Studies show that modern EBS volumes like gp3 can deliver up to 3,000 baseline IOPS and reach throughput levels of 1,000 MiB/s, but many workloads never utilize this potential due to poor configuration or oversizing.

That’s where optimization strategies make a difference. By right-sizing volumes, choosing the most suitable volume types, and automating snapshot management, you can significantly enhance performance while keeping costs under control. 

In this blog, you’ll explore key AWS EBS optimization strategies that ensure your storage remains high-performing and cost-efficient, no matter how demanding your workloads become.

What is Amazon EBS & Why Does It Matter?

Amazon Elastic Block Store (EBS) is a scalable, high-performance block-level storage service built to work directly with Amazon EC2 instances.

It provides persistent storage, ensuring your data remains safe and available even if the EC2 instance is stopped or terminated. This reliability makes EBS a key choice for applications that need durable, low-latency, and dependable storage.

EBS volumes attach to EC2 instances and support a wide range of workloads, such as database storage, file systems, and even boot volumes. Because EBS is tightly integrated with EC2, your storage moves in sync with your compute resources.

This makes it easy to scale both compute and storage together, ensuring your applications run smoothly as demand grows.

Here’s why Amazon EBS matters:

1.Data Durability

Amazon EBS keeps your data safe and persistent, even if an EC2 instance is stopped or terminated. This reliability is especially important if you're running critical applications such as databases, because the data remains intact regardless of the instance’s lifecycle.

2.Performance Consistency

EBS lets you choose from a range of volume types to match different workload requirements. For example, Provisioned IOPS SSD (io2) delivers predictable, low-latency performance for database workloads, while Throughput Optimized HDD (st1) is well-suited for large-scale data processing that requires high throughput.

3.Scalability

With EBS, storage can be scaled up or down on demand without any service disruption. This flexibility is valuable for applications with growing or fluctuating storage needs, allowing you to adjust capacity as needed without downtime.

4.Integration with EC2

Since EBS integrates tightly with EC2, engineers can easily attach, detach, or resize volumes. This smooth connection makes storage management simple and ensures that compute and storage can scale together based on performance and capacity requirements.

5.Cost Optimization

EBS also supports cost control by offering different volume types and performance options. You can choose the most suitable configuration for each workload and avoid over-provisioning. This ensures you pay only for the storage and performance you actually need.

Once you understand why Amazon EBS matters, it becomes easier to see how its key features support reliable and scalable storage.

Key Features You Should Know About Amazon EBS

Amazon EBS offers scalable, high-performance storage for EC2 instances and includes features that make managing, backing up, and optimizing data much easier.

Understanding these key capabilities helps you make the most of EBS, ensuring your applications get the right balance of performance, reliability, and cost efficiency.

1.Volume Types

Amazon EBS provides multiple volume types to support a wide range of workload requirements. You can choose:

• gp3 (General Purpose SSD): Best when engineers need a good balance of cost and performance.
• io2 (Provisioned IOPS SSD): Ideal for high-performance, I/O-intensive workloads such as databases.
• st1 / sc1 (Throughput Optimized & Cold HDD): Suitable for large-scale, sequential data processing that requires high throughput.

2.Snapshots

EBS snapshots make it easy to create incremental backups by storing only the changes since the previous snapshot. This approach keeps backups efficient, cost-effective, and quick to restore.

You can also automate snapshot scheduling and manage retention policies to avoid unnecessary storage costs while maintaining reliable recovery points.

3.Encryption

EBS supports seamless encryption for data at rest, in transit, and during snapshot operations. You can rely on AWS Key Management Service (KMS) to manage keys, ensuring sensitive data remains protected and compliant with security standards without adding operational complexity.

4.Dynamic Resizing

EBS volumes can be scaled up dynamically without any downtime. You can increase volume size, IOPS, or throughput on the fly, allowing applications to grow or boost performance as needed, without service interruptions or instance restarts.

5.Multi-Attach

Selected EBS volume types, such as io2, offer Multi-Attach support, allowing a single volume to connect to multiple EC2 instances simultaneously.

This feature benefits high-availability architectures that rely on shared storage across instances to maintain redundancy and support failover.

6.Performance Metrics

EBS integrates directly with Amazon CloudWatch, giving engineers access to essential performance metrics like IOPS, throughput, and latency.

Tracking these metrics helps ensure volumes consistently meet application performance expectations and allows teams to troubleshoot performance bottlenecks proactively.

7.Data Lifecycle Management

EBS also includes tools to automate long-term storage management, such as deleting outdated snapshots or transitioning data between storage classes.

You can configure Data Lifecycle Manager (DLM) policies to streamline snapshot management, improve operational efficiency, and eliminate unnecessary storage costs.

Knowing the features also helps make sense of how AWS EBS pricing works.

Suggested Read: AWS EBS Basics 2026: Block Storage Guide

How are AWS EBS Costs Calculated?

AWS EBS costs depend on several factors, such as volume size, provisioned IOPS, snapshot storage, and data transfer. Understanding how each component affects pricing helps you optimize storage costs while still meeting the performance requirements of your workloads.

Once you understand how EBS costs are calculated, it becomes easier to identify the strategies that can help you optimize them effectively.

14 AWS EBS Optimization Strategies You Can Use

Optimizing EBS volumes is crucial for maintaining consistent performance while keeping storage costs under control. By applying these techniques, you can improve storage efficiency, eliminate unnecessary resource usage, and ensure your AWS environment runs at peak performance without overspending.

1.Right-Size Your EBS Volumes

Over-provisioning EBS volumes often leads to unnecessary spending, so it’s important to ensure your volumes match your application’s actual storage requirements and adjust them based on real usage patterns.

How to Implement:

• Monitor Usage: Use AWS CloudWatch to track key metrics like IOPS, throughput, and latency over time. For example, if you’re using a Provisioned IOPS (io2) volume but only consuming a small portion of the allocated IOPS, consider resizing to a more cost-effective option such as gp3.
  Tip: For predictable workloads, analyze burst credit consumption. If a gp2/gp3 volume frequently exhausts burst credits, the workload likely needs higher baseline IOPS rather than short-term surges.
• Adjust Volume Size: Resize EBS volumes based on actual data usage. You can modify the volume size through the AWS CLI or the AWS Management Console without downtime for most volume types.
• Utiiize Trusted Advisor: Use AWS Trusted Advisor to receive recommendations for underutilized resources and right-size EBS volumes based on current workload patterns.

2.Select the Optimal EBS Volume Type

Choosing an EBS volume type that doesn’t align with your workload can lead to performance bottlenecks and higher costs, so selecting the right one is essential.

How to Implement:

• Match Workload to Volume Type: For general-purpose workloads, gp3 is usually the most cost-efficient option. If you’re running high-throughput or database workloads, io2 may be a better fit.
• Benchmark for Optimal Performance: Use AWS EC2 Performance Insights to identify which volume type best aligns with your workload’s performance and latency requirements.

3.Automate Snapshot Management

Since EBS snapshots are incremental, managing retention effectively helps you reduce long-term storage costs while maintaining reliable backups.

How to Implement:

• Set Snapshot Policies: Use AWS Data Lifecycle Manager (DLM) to automate snapshot creation and deletion. Configure policies to automatically delete snapshots older than a specific timeframe or beyond a defined count.
• Limit Snapshot Frequency: For non-critical data, schedule snapshots less frequently (such as weekly instead of daily) to reduce storage overhead.
• Snapshot Encryption: Enable encryption for new snapshots to maintain compliance and ensure data security without adding operational complexity.
  Tip: Maintain a consistent snapshot tagging strategy that includes application name, environment, and retention policy. This makes cost attribution far clearer during monthly audits.

4.Use EBS-Optimized Instances for High-Performance Needs

EBS-Optimized instances provide dedicated bandwidth between EC2 and EBS, resulting in improved I/O performance and lower network contention for storage-heavy workloads.

How to Implement:

• Select EBS-Optimized Instances: For high-throughput workloads such as databases or big data pipelines, use EBS-Optimized instances like C5, M5, or R5 for consistent, dedicated throughput.
• Check Network Compatibility: Ensure the selected instance type supports the required throughput levels. Instances with higher network bandwidth (such as M5n or C5n) can better sustain increased EBS performance.
• Monitor I/O Performance: Track throughput and EC2 network performance using CloudWatch to detect throttling. Adjust the instance type or EBS volume type when needed.

5.Use CloudWatch Alarms for EBS Performance

Setting up proactive monitoring helps identify performance issues early and ensures optimal volume performance.

How to Implement:

• Create Alarms: Set up CloudWatch Alarms for metrics such as IOPS and volume latency. For example, configure an alarm to notify you when volume IOPS exceed optimal thresholds, indicating a potential need for a different volume type.

6.Use RAID for Performance and Redundancy

RAID configurations enhance performance and provide redundancy for mission-critical workloads that require high availability.

How to Implement:

• RAID 0 for Performance: Use RAID 0 for workloads that require maximum throughput, such as analytics or large-scale data processing. It stripes data across multiple volumes for improved performance.
• RAID 1 for Redundancy: Use RAID 1 to mirror volumes and improve redundancy for critical applications, ensuring workload continuity in case of a failure.
• RAID 10 for Combined Benefits: Use RAID 10 to combine the performance of RAID 0 with the redundancy of RAID 1, delivering both high throughput and fault tolerance.
  Tip: Always benchmark RAID performance on your specific instance family. Some burstable instance types throttle disk bandwidth earlier than expected, which can mask the true benefit of RAID.

7.Avoid Unused Volumes

Unused EBS volumes contribute to unnecessary costs and should be regularly removed to maintain a clean, cost-optimized environment.

How to Implement:

• Audit Volumes: Use AWS CLI or AWS Config to routinely identify unused volumes and determine whether they’re still needed.
• Automate Cleanup: Create automated workflows using AWS Lambda and CloudWatch to remove idle volumes after a defined period.
• Monitor Usage: Perform periodic audits to ensure that only actively used volumes are retained.

8.Implement EBS Multi-Attach for High-Availability Workloads

EBS Multi-Attach enables a single EBS volume to be attached to multiple EC2 instances, supporting shared storage for highly available applications.

How to Implement:

• Attach io2 Volumes: Attach io2 volumes to multiple EC2 instances to support shared block-level storage.
• Use for Clustering: Ideal for clustered databases or shared storage architectures where multiple instances need simultaneous access.
  Tip: When using Multi-Attach, ensure the application layer handles write ordering and locking correctly. EBS does not manage concurrency control across instances.
• Configure EC2 Instances: Ensure all EC2 instances are within the same Availability Zone and support Multi-Attach to avoid configuration issues.

9.Use EBS I/O Metrics for Tuning

Real-time monitoring of I/O metrics helps engineers identify bottlenecks and optimize performance at the right time.

How to Implement:

• Optimize Based on Data: If QueueLength increases, consider increasing provisioned IOPS or switching to a higher-performance volume to avoid throttling.
• Set Up CloudWatch Alarms: Configure alarms for threshold breaches and trigger proactive tuning actions.

10.Use EBS with EC2 Auto Scaling

Integrating EBS with EC2 Auto Scaling ensures storage and compute resources scale proportionally with workload demand.

How to Implement:

• Scale EC2 and Volumes Together: Use AWS Auto Scaling to adjust EC2 instances and EBS volumes as CPU, memory, or I/O demands rise.
• Automate Resizing: Automatically resize both EC2 instances and EBS volumes to adapt to workload changes.
• Ensure Auto Scaling Policies Align: Configure policies that synchronize EC2 instance scaling with volume size adjustments for consistency.

11.Implement Data Tiering for Cost-Effective Storage

Data tiering helps you optimize storage by keeping frequently accessed data on high-performance volumes while shifting cold data to lower-cost options.

How to Implement:

• Move Data Based on Usage: Shift infrequently accessed data from gp3 to st1 or sc1 volumes to reduce storage costs.
• Automate Transitions: Use AWS Data Lifecycle Manager to automate transitions based on data access patterns.
  Tip: Before shifting cold data to st1 or sc1, validate whether the workload performs small random reads. HDD-backed volumes handle sequential workloads well but perform poorly with random access patterns.
• Monitor Data Access: Track how frequently data is accessed and modify tiering policies as needed.

12.Split Large Volumes into Smaller Volumes for Better Management

Breaking large datasets into smaller volumes can improve performance, simplify management, and prevent I/O bottlenecks.

How to Implement:

• Distribute Data Across Volumes: Split large datasets across multiple smaller volumes based on usage patterns.
• Prevent Bottlenecks: Spread I/O across multiple volumes to avoid single-volume performance limitations in high-traffic applications.
• Reassess Volume Size Periodically: Review volume sizing regularly and adjust based on data growth.

13.Automate EBS Volume Encryption for Compliance

Automatically applying encryption ensures data security and compliance without requiring manual configuration.

How to Implement:

• Enable Encryption by Default: Use AWS KMS to automatically encrypt all new volumes and snapshots.
• Maintain Consistency: Ensure every volume and snapshot across your environment is encrypted.
• Automate Key Management: Implement KMS key rotation policies to maintain compliance.

14.Use Amazon EFS Instead of EBS for Shared Data

For workloads needing shared access across multiple instances, Amazon EFS provides a scalable and fully managed alternative.

How to Implement:

• Migrate to Amazon EFS: Move workloads like web servers or media processing pipelines to EFS for shared file-level access.
• Optimize EFS for Performance: Configure EFS performance modes such as General Purpose or Max I/O based on application needs.

After covering the key optimization strategies, it’s also helpful to see how EBS-optimized instances can further improve your AWS performance.

How to Improve AWS Performance Using EBS-Optimized Instances?

EBS-Optimized instances offer dedicated, high-throughput connections between EC2 instances and EBS volumes, helping reduce latency and maintain consistent I/O performance.

To maximize performance with EBS-Optimized instances, you should apply the following strategies:

1.Choose the Right Instance Type

Pick EC2 instances that match your workload’s I/O needs. For storage-heavy or I/O-intensive applications, instances such as M5, C5, or R5 provide higher EBS-Optimized throughput, helping you handle demanding workloads more efficiently.

2.Pair with High-Performance EBS Volumes

Combine EBS-Optimized instances with Provisioned IOPS (io2) or gp3 volumes to achieve high throughput and low latency. This alignment ensures your storage layer can keep up with the instance’s capabilities, preventing unnecessary I/O slowdowns.

3.Optimize EBS Throughput

Tune the throughput and IOPS of both your EC2 instance and attached EBS volumes to balance cost and performance. Use gp3 volumes for applications that need high throughput, and io2 volumes for applications that need consistent, low-latency, high I/O performance.

4.Use CloudWatch for Monitoring

Use Amazon CloudWatch to continuously monitor key metrics, including EBS throughput, latency, and burst credits. Reviewing this data helps you refine your instance type or adjust volume settings to reliably meet performance goals.

5.Optimize Data Placement

Spread data across multiple EBS volumes to improve overall I/O performance. For high-traffic or mission-critical applications, consider RAID configurations to boost throughput and provide additional redundancy.

6.Ensure Network and Instance Compatibility

Make sure your EBS-Optimized instance is paired with the right network bandwidth tier. Instances with stronger network performance can fully leverage EBS throughput, helping maintain smooth and consistent performance under heavy load.

Also Read: AWS Well-Architected Framework: Insights from AWS Lambda Product Lead

How Sedai Improves AWS EBS Optimization for Performance and Cost?

Many tools claim to optimize AWS EBS, but most rely on static configurations and manual adjustments that fail to adapt to dynamic workload changes. These conventional methods can lead to over-provisioned volumes, unnecessary costs, and underutilized resources, ultimately affecting both performance and efficiency.

Sedai sets itself apart by delivering autonomous optimization for AWS EBS. Using its intelligent reinforcement learning framework, Sedai continuously learns from real-time workload behavior and adjusts EBS resources based on actual demand. This proactive approach helps maintain optimal performance while keeping unnecessary costs under control.

By automating EBS management, Sedai ensures resources are scaled efficiently, prevents over-provisioning and underutilization, and maintains a cost-effective, high-performing storage environment.

Here’s what Sedai offers:

• Dynamic EBS volume rightsizing (Storage & IOPS): Sedai monitors real workload usage and adjusts EBS volume sizes and IOPS configurations in real time, preventing both over-provisioning and under-provisioning. This dynamic rightsizing helps ensure optimal performance while reducing costs by up to 40%.
• Optimal volume type selection: Sedai reviews usage patterns to recommend the most suitable EBS volume types, whether gp3, io2, st1, or others. By aligning the volume type with the workload’s specific requirements, Sedai minimizes idle resources and ensures that volumes remain cost-efficient without compromising performance.
• Autonomous scaling decisions: Powered by machine learning, Sedai automatically adjusts EBS volumes and the compute resources associated with them according to real-time workload behavior. This reduces resource bottlenecks and delivers more consistent performance, since allocations are based on live usage patterns.
• Automatic performance remediation: Sedai identifies performance degradation, resource pressure, or inefficiencies such as throttling and resolves them before they impact workloads. It reduces the need for manual intervention and improves engineering productivity by up to 6x.
• Full-stack cost and performance optimization: In addition to EBS improvements, Sedai optimizes the complete cloud stack, including compute, storage, networking, and cloud commitments. This broader optimization achieves up to 50% savings in cloud costs while improving overall performance across AWS environments.
• Multi-cloud and hybrid-cloud support: Sedai provides consistent optimization across AWS, Azure, GCP, and on-prem Kubernetes clusters. Its unified optimization engine supports smooth resource management even in complex, hybrid, or multi-cloud architectures.
• SLO-driven scaling for EBS: Sedai aligns scaling decisions with Service Level Objectives (SLOs) and Service Level Indicators (SLIs), ensuring steady performance during traffic spikes or workload fluctuations. This maintains reliability and ensures that storage resources remain aligned with application requirements at all times.

With Sedai, AWS EBS resources are optimized dynamically, allowing your environment to scale efficiently while maintaining performance and reducing costs.

Sedai automates the entire adjustment and optimization process, eliminating the complexity of manual tuning and ensuring your storage infrastructure consistently operates at peak efficiency.

If you’re ready to optimize your AWS EBS usage with Sedai, use our ROI calculator to see how much you can save by improving performance and automating resource adjustments.

Must Read: AWS Fargate: Features, Pricing & Cost Optimization

Final Thoughts

Optimizing AWS EBS is essential for maintaining high performance and controlling costs across your cloud infrastructure. By coupling EBS with Amazon S3 for infrequent data access or using AWS Glacier for long-term archiving, you can further reduce costs without compromising performance.

This is where Sedai takes it a step further. By analyzing usage patterns and automating the integration of EBS with other AWS storage services, Sedai optimizes your cloud environment to ensure each resource is used efficiently, delivering savings without impacting system reliability.

Through continuous monitoring and intelligent adjustments, Sedai helps you maintain the ideal balance of performance, cost, and scalability across your AWS storage.

Achieve comprehensive visibility into your AWS EBS resources and cut unnecessary costs right away.

FAQs

Q1. How can I manage EBS costs effectively in a multi-region setup?

A1. In a multi-region setup, you can manage EBS costs more efficiently by using cross-region snapshot sharing to avoid unnecessary redundancy. Automating data transfer and archiving with Amazon Data Lifecycle Manager helps keep storage use under control and reduces costs across regions.

Q2. How do I optimize EBS for burstable workloads?

A2. For burstable workloads, choose gp3 volumes and rely on Burst Balance metrics to scale resources cost-effectively. Monitoring CloudWatch metrics allows you to adjust IOPS and throughput based on real-time demand so you can avoid over-provisioning.

Q3. What strategies can I use to optimize EBS for high-availability applications?

A3. To support high-availability applications, use EBS Multi-Attach to share volumes across multiple EC2 instances. Pairing this with RAID 1 or RAID 10 configurations adds redundancy and fault tolerance, helping maintain uptime even if an instance fails.

Q4. How can I optimize EBS snapshot management for cost control?

A4. To keep snapshot costs optimized, set up automated snapshot policies through AWS Data Lifecycle Manager. Rely on incremental snapshots to reduce storage needs and use retention policies to automatically delete older snapshots that are no longer required.

Q5. What impact does using EBS-optimized instances have on my overall AWS cost optimization?

A5. EBS-optimized instances help minimize latency and throughput bottlenecks by reserving dedicated bandwidth for EBS volumes. Although they come with additional costs, the improved performance supports I/O-intensive workloads more efficiently, preventing performance-related issues that can otherwise increase operational expenses.