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Datadog | The Monitor blog

Introducing our open source AI-native SAST Instrument and monitor Boomi integration flows with OpenTelemetry and Datadog Not all index scans are equal: How we cut query latency by over 99% Platform engineering metrics: What to measure and what to ignore Integrate Recorded Future threat intelligence with Datadog Cloud SIEM CI/CD security: threat modeling using a MITRE-style threat matrix CI/CD security: How to secure your GitHub ecosystem Ingress NGINX is EOL: A practical guide for migrating to Kubernetes Gateway API Operating agentic AI with Amazon Bedrock AgentCore and Datadog LLM Observability: Lessons from NTT DATA Introducing the Datadog Code Security MCP Capture and analyze custom heatmaps in Session Replay Understand session replays faster with AI summaries and smart chapters Monitor ClickHouse query performance with Datadog Database Monitoring How we designed empathetic alert sounds for on-call engineers Search and act across Datadog to resolve issues faster with Bits Assistant Measure the business impact of every product change with Datadog Experiments Analyzing round trip query latency Configuring JavaScript caches for better performance Introducing Bits AI Dev Agent for Code Security Datadog achieves ISO 42001 certification for responsible AI Monitor Nutanix clusters, hosts, and VMs with Datadog Monitor Juniper Mist in Datadog A new Host Map for modern infrastructure Annotate traces to improve LLM quality with Datadog LLM Observability What’s new in Cloud SIEM: AI-powered investigations, enhanced threat intelligence, and scalable security operations Explore Kubernetes with native OpenTelemetry data Monitor Oracle Fusion Cloud Applications with Datadog Announcing the Datadog Terraform provider v4.0.0 Scaling Kubernetes workloads on custom metrics How to design cloud environments for AI-powered threat analysis Monitor Aruba Central in Datadog How we centralize and remediate risks with Datadog Case Management Accelerate incident response with Datadog and ServiceNow Monitor your application and network load balancer logs Understanding Karpenter architecture for Kubernetes autoscaling Tools for collecting metrics and logs from Karpenter Monitor Karpenter with Datadog What your product data is actually saying Key metrics for monitoring Karpenter Securing Datadog’s platform in the AI age: The role of observability data Four ways engineering teams use the Datadog MCP Server to power AI agents Approaching your observability migration with the right mindset Meet the new Bits AI SRE: Deeper reasoning, twice as fast Key learnings from the 2026 State of DevSecOps study Use plain English to query your multi-cloud infrastructure in Resource Catalog Simplifying troubleshooting across the user journey with Datadog Synthetic Monitoring Protect your OCI resources with Datadog Cloud Security This Month in Datadog - 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Getting optimal performance with AWS EBS Provisioned IOPS
2013-07-24 · via Datadog | The Monitor blog

Amazon Web Services (AWS) offers two flavors of networked block storage as a service with Elastic Block Storage (EBS): Standard and Provisioned IOPS. The two offerings differ primarily by performance, meaning that the speed of an application hosted on AWS using EBS for storage will be impacted by this choice. Although EBS Provisioned IOPS is the higher performance option, you get the best performance if and only if certain conditions (which are described below) are met.

What AWS EBS Standard and Provisioned IOPS provide

To optimize your EBS volumes for Provisioned IOPS, it is important to understand how it differs from Standard. Performance for EBS is primarily measured in input/output operations per second (IOPS).

In the EBS case, IOPS refer to operations on blocks that are up to 16 KB in size.1 Standard volumes deliver 100 IOPS on average. This is roughly to number of IOPS that a single desktop-class 7200 rpm SATA hard drive can deliver. In comparison, a similar desktop-class SSD drive can deliver anywhere between 5,000 and 100,000 IOPS. Server-class SSD drives can go much higher.

EBS Provisioned IOPS can deliver a maximum of 4,000 IOPS, if and only if the conditions described below are met.

Required conditions for EBS Provisioned IOPS optimal performance

Meeting these conditions should lead to disk volumes using Provisioned IOPS that deliver between 90% and 100% of their expected performance 99.9% of the time in a given year:

  1. Your application sends enough requests to the volume as measured by the average queue length (i.e. the number of pending operations) of that volume.
  2. The read and write operations apply to blocks of 256 KB or less. For example if your block size is 1024 KB, you should expect only 1/4 of the provisioned IOPS you purchased.
  3. The blocks on the volume have been read at least once. The first time a block is accessed, there is a 50 percent reduction in IOPS. Performance is restored after first access.
  4. No EBS snapshot is pending.
  5. Total read/write operations do not exceed 128MB/s per EBS volume.

While these extensive conditions are normal for a networked storage service, they’re easy to overlook if you’re not aware that they’re necessary to optimize performance.

The one-metric test for optimal EBS Provisioned IOPS performance

The one metric that matters is VolumeQueueLength from AWS CloudWatch. Let’s see what happens when an application is pushing too many IOPS to an EBS volume. The graph below shows an EBS volume that has maxed out. For a Provisioned IOPS volume, the rule of thumb is to keep the VolumeQueueLength at 1 per 100 IOPS.

The graph below shows an example of the VolumeQueueLength over 24 hours for an EBS volume.

aws ebs performance

When the volume is maxed out I/O operations queue up and cause a delay that is directly visible by the operating system via various I/O related metrics (e.g. % of CPU spent in “I/O wait”). At that point your application is likely to go only as fast as that EBS volume goes.

Below is an example of the CPU IOWait metric for the server in the same timeframe. Notice that as much as 27% of the CPU cycles are diverted away from the application as the instance is waiting for the EBS volume to process all the I/O requests.

aws ebs performance

Maintaining the conditions mentioned above to achieve optimal performance for Provisioned IOPS in EBS can be accomplished through careful monitoring. To ensure that our EBS volumes at Datadog are constantly running at optimal performance, we have set up a dashboard that constantly tracks VolumeQueueLength and other key EBS performance metrics.

For more on how to avoid these and other EBS performance issues, check out our free eBook The Top 5 Ways to Improve Your AWS EC2 Performance.