Optimizing AWS EBS with AWS Compute Optimizer and it’s challenges

Amazon Elastic Block Store (Amazon EBS) is a block-level storage service provided by Amazon Web Services (AWS) that is designed to be used with Amazon Elastic Compute Cloud (EC2) instances. EBS is a popular choice for storing block data in the cloud, but it's important to ensure that your EBS volumes are optimized for performance and cost-effectiveness. 

One way to do this is by using AWS Compute Optimizer, a service that uses machine learning algorithms to analyze your resources and provide recommendations for optimization. AWS Compute Optimizer helps customers to reduce costs, improve application performance, and increase resource efficiency by providing recommendations that ensure optimal use of their workloads.

To check if your EBS storage is optimized using AWS Compute Optimizer, follow these steps:

Step 1: Log in to your AWS account and navigate to the Compute Optimizer dashboard.

Step 2: Select the AWS Region where your EBS volumes are located. In Filter, add your region.

Step 3: Check the "Recommendations" tab to view a list of resources that Compute Optimizer has analyzed.

Step 4: Filter the recommendations by selecting "EBS volumes" under the "Recommendations per AWS resource type".

Step 5: Review the recommendations for each EBS volume and take action as necessary.

Advantages of using Compute Optimizer for EBS :

  • Improved cost optimization: The Compute Optimizer helps identify underutilized EBS volumes and suggests resizing them to save on storage costs.
  • Increased efficiency: Optimizing EBS storage ensures that your resources are being used efficiently, which can lead to better performance and faster application response times.
  • Automated analysis: The Compute Optimizer continuously analyzes your EBS volumes and provides recommendations to optimize your storage usage, reducing the need for manual monitoring.
  • Easy to use: The Compute Optimizer is integrated with AWS Management Console, making it easy for users to access and act on optimization recommendations.

This is great, Isn’t it? 

However, despite its benefits, why aren't customers immediately adopting this solution?

Let’s deep dive further to understand the nuances and challenges of this solution.

1. Recommendation only: It's essential to note that while the Compute Optimizer provides valuable recommendations for optimizing EBS volumes, it doesn't carry out these operations. AAWS Compute Optimizer only provides advice and helps users to understand the potential benefits and drawbacks of making these optimizations. It's up to the user to decide whether or not to implement these recommendations based on their specific use case and workload requirements.

2. Disk utilization not monitored: Compute Optimizer provides recommendations of EBS volumes by analyzing metrics such as VolumeReadBytes, VolumeWriteBytes, VolumeReadOps, and VolumeWriteOps. This approach is not sufficient to provide valuable insights into disk utilization.

In fact, without monitoring the disk utilization, it can be challenging to detect patterns and trends in storage usage, which could ultimately result in over-provisioning. This is because if you don't have a clear idea of how much storage you're actually using, you might end up allocating more than you need, which can lead to wastage of resources and increased costs.

3. Manual risk assessment: Furthermore, users must thoroughly understand the Compute Optimizer's recommendations before implementing them to avoid any unintended consequences or performance issues. It's crucial to consider the impact of these changes on the resources. A thorough analysis of the workload and disk utilization is necessary to determine the optimal configuration and settings for EBS volumes. 

Some crucial challenges are - 

  • Downtime: Shrinking EBS volumes will require downtime for your applications or services, which can impact availability and user experience.
  • Performance Impact: Expanding EBS volumes will result in the performance of the applications running on the EC2 instance to be affected, leading to slower response times, increased latency, and lower throughput.
  • Potential inaccuracies: The Compute Optimizer recommendations are based on historical usage data of the past 14 days, which may not accurately reflect current usage patterns or future needs. To opt for a longer duration of historical usage data customers will need to pay additional charges.
  • DevOps effort: Implementing the recommendations provided by Compute Optimizer would require your DevOps team spending hours in planning,executing and monitoring these changes.

Well, that’s too bad.
How do we optimize EBS storage without worrying about these challenges and ensure our applications have optimal performance along with cost savings ?

The answer is - Lucidity Auto-Scaler

Our industry-first Auto-Scaler solution can monitor disk utilization and automatically resize EBS volumes as needed. It can dynamically expand and shrink EBS volumes based on disk utilization, optimizing resource allocation and cost-efficiency in AWS. By doing so, it ensures a healthy disk utilization of 75-80% so that your applications have the necessary resources to function effectively while potentially reducing costs by up to 70%. By focusing on th automated shrinking without a downtime, businesses can save significant costs on storage resources and improve operational efficiency.

Head over to see the magic here.

Need a demo? Just hit Request demo and our team will showcase the solution for you.

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