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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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Monitor Amazon S3 Express One Zone with Datadog
Candace Shamieh · 2023-11-29 · via Datadog | The Monitor blog
Candace Shamieh

Candace Shamieh

Technical Writer

Amazon Simple Storage Service (S3) now offers a high-performance storage class, S3 Express One Zone, that delivers consistent single-digit millisecond data access for your most latency-sensitive applications. Designed for your most frequently accessed datasets, S3 Express One Zone replicates and stores your data within a single AWS Availability Zone, scales to process millions of requests per minute, and uses hardware and software optimized for low latency. When compared to Amazon S3 Standard, S3 Express One Zone can improve data access speeds by 10 times and reduce request costs by 50 percent.

Datadog is proud to partner with AWS to support the launch of S3 Express One Zone. With Datadog Application Performance Monitoring (APM), you can monitor the interactions between your applications and S3 Express One Zone. APM will provide detailed insights into file I/O latency and throughput patterns so that you can further optimize your application’s code. With APM, you can improve your application’s performance and work optimally with S3 Express One Zone.

In this post, we’ll discuss how Datadog APM can help you:

  • Track S3 Express One Zone requests and performance metrics to optimize your application

  • Verify that you’re using the right S3 storage class for your use case

Track S3 Express One Zone requests and performance metrics to optimize your application

Once you configure your application to send traces to Datadog, you can track indicator metrics, including availability, response times, error rate, and throughput. You can also set alerts that contain controls tailored to APM. APM enables you to view your application’s queries to S3 Express One Zone so that you can make data-driven decisions.

Viewing S3 Express One Zone traces in Datadog APM

For example, let’s say that APM alerts on failed requests for your big data analytics application. You investigate in the Datadog platform and discover that you’re hitting TPS limits because a single S3 directory bucket is storing and handling all data. You quickly partition the data between multiple S3 directory buckets so that your application can scale to the necessary TPS performance requirements.

Use the right S3 storage class for your use case

In addition to utilizing APM to monitor your application’s interactions with S3 Express One Zone, install our S3 and Amazon S3 Storage Lens integrations to start collecting metrics. Our preconfigured S3 and S3 Storage Lens dashboards will help you monitor your other Amazon S3 storage classes outside of S3 Express One Zone, allowing you to compare and contrast as you decide which S3 storage class is best for your use case. Monitoring S3 holistically with Datadog enables you to gain visibility into S3 usage and activity across your entire organization. This makes it easy to visualize performance and determine whether you should continue to use your current storage classes or if S3 Express One Zone will better suit your application’s needs. Datadog APM, integrations, and dashboards inform you of granular-level details so you can verify whether you’re meeting your application’s latency requirements.

View of Datadog’s preconfigured Amazon S3 Storage Lens dashboard

To illustrate, let’s say you’re a financial institution based in New York that provides a risk modeling platform application for investment portfolios and is currently using S3 Standard to store market data, portfolio data, risk models, financial statements, and more. Your users, primarily in North America, require real-time updates on the market. When alerted by Datadog APM that your average latency is not meeting your application’s requirements, you investigate immediately. You see on Datadog’s S3 Storage Lens dashboard that the AWS Regions with the most storage are in central Canada and northern Virginia, so you can’t get much closer in proximity to your users. You decide to switch your storage class to S3 Express One Zone to obtain consistent single-digit millisecond latency and co-locate your storage and compute resources within a single AWS Availability Zone. This allows your application to meet your users’ need for real-time risk assessments and time-sensitive decision-making.

Get started today

By monitoring your application with Datadog APM and leveraging our existing S3 and S3 Storage Lens integrations, you can optimize your application for S3 Express One Zone and verify that you’re using the right storage class for your application’s needs. Get started by sending APM traces to Datadog, installing S3 and S3 Storage Lens integrations, and reading our documentation. If you’re new to Datadog, sign up for a free 14-day trial.

To learn more about Datadog’s growing product portfolio and the new capabilities that we announced at AWS re:Invent 2023, visit our new releases webpage.