Sold by: Datadog
Deployed on AWS
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Datadog is a SaaS-based unified observability and security platform providing full visibility into the health and performance of each layer of your environment at a glance.
4.4
Overview
Datadog is a SaaS-based unified observability and security platform providing full visibility into the health and performance of each layer of your environment at a glance. Datadog allows you to customize this insight to your stack by collecting and correlating data from more than 600 vendor-backed technologies and APM libraries, all in a single pane of glass. Monitor your underlying infrastructure, supporting services, applications alongside security data in a single observability platform.
Prices are based on committed use per month over total term of the agreement (the Total Expected Use).
Highlights
- Get started in minutes from AWS Marketplace with our enhanced integration for account creation and setup. Turn-key integrations and easy-to-install agent to start monitoring all of your servers and resources in minutes.
- Quickly deploy modern monitoring and security in one powerful observability platform.
- Create actionable context to speed up, reduce costs, mitigate security threats and avoid downtime at any scale.
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Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Quick Launch
Leverage AWS CloudFormation templates to reduce the time and resources required to configure, deploy, and launch your software.
Pricing
Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/month | Overage cost |
|---|---|---|---|
Infra Hosts | 350+ integrations, alerting, custom metrics & unlimited user accounts | $18.00 | |
APM Hosts | Monitor, troubleshoot, and optimize end-to-end application performance | $36.00 | |
App Analytics Add-On | Drill down on performance metrics (Per Analyzed Span) | $2.04 | |
Custom Metrics | Monitor your own custom business metrics (Per 100 custom metrics) | $5.00 | |
Indexed Logs | 15-day retention (Per million log events) | $2.04 | |
Ingested Logs | (Per 1 GB Ingested Logs) | $0.10 | |
Synthetics API Tests | Proactively monitor site availability (Per 10K test runs) | $6.00 | |
Synthetics Browser Tests | Easily monitor critical user journeys (Per 1K test runs) | $15.00 | |
Serverless Functions | Deprecated. Not available for new customers | $6.00 | |
Fargate Tasks | Monitor your Fargate Tasks | $1.20 |
The following dimensions are not included in the contract terms, which will be charged based on your usage.
Dimension | Description | Cost/unit |
|---|---|---|
Custom dimension used for select private offers | Custom dimension used for select private offers | $1.00 |
consumption_unit | Additional Datadog Consumption Units | $0.01 |
Dimensions summary
This contract combines many independent usage dimensions that you mix based on what you monitor. Core dimensions bill per host: Infra Hosts, APM Hosts, Network Hosts, Profiled Hosts, and Fargate Tasks. Others bill by volume: Custom Metrics per 100, Indexed Logs and Ingested Logs per million events or per GB, Synthetics per test-run batch, Real User Monitoring per session block, and Analyzed Logs or Containers per unit. You buy only the dimensions you need and scale each separately. Some dimensions are deprecated for new customers, and custom dimensions support select private offers.
Top-of-mind questions for buyers
A host is any physical or virtual OS instance you monitor, such as a server, VM, or Kubernetes node. For APM Hosts, only hosts actively generating traces count. Uninstrumented hosts like databases or load balancers do not count, even with the agent installed.
Each APM host includes a span ingestion and indexed-span allotment summed across all your hosts. If total use stays under the pooled allotment, you pay nothing extra. Volume above the pooled allotment bills per additional GB ingested or per million indexed spans.
Host dimensions bill per host and include a set container and custom-metric allotment. Containers and Custom Metrics dimensions bill only for volume above those allotments. Custom metrics are counted hourly and averaged monthly across your whole account, not per host. All charges appear on the same invoice.
www.datadoghq.com
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Custom pricing options
Request a private offer to receive a custom quote.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
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Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
Support
Vendor support
Contact our knowledgable Support Engineers via email, live chat, or in-app messages
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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In Log Analysis, Monitoring
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In Monitoring and Observability, Migration
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In Application Performance and UX Monitoring
Sentiment is AI generated from actual customer reviews on AWS and G2
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AI generated from product descriptions
Multi-Vendor Integration
Collects and correlates data from more than 600 vendor-backed technologies and APM libraries in a single platform
Unified Observability Dashboard
Provides full visibility into health and performance across all environment layers in a single pane of glass
Infrastructure and Application Monitoring
Monitors underlying infrastructure, supporting services, applications, and security data simultaneously
Agent-Based Deployment
Includes easy-to-install agent for rapid deployment and monitoring of servers and resources
Security and Performance Analytics
Integrates security data with performance monitoring to enable threat mitigation and downtime prevention
Automated Device Discovery and Configuration
Automatic recognition and configuration of 2,000+ technologies with preconfigured alert thresholds and best practices-based setup without manual intervention
Agentless Monitoring Architecture
Agentless Collector deployment enabling hybrid and multi-cloud visibility with reduced operational overhead and no requirement for continuous agent upgrades
Unified Multi-Environment Visibility
Single-pane-of-glass monitoring across on-premises, hybrid, and multi-cloud infrastructures including AWS services with panoramic performance visibility
Flexible Data Collection Mechanism
Capability to pull metrics from virtually any device or API with support for custom graphs, dashboards, and alerts for application status analysis and trend identification
Performance Forecasting and Customizable Dashboards
Built-in performance forecasting capabilities combined with rich, customizable dashboards and full reporting functionality for actionable infrastructure insights
Data Ingestion and Query Performance
Ingests petabytes of telemetry per day with capability to process hundreds of terabytes and execute tens of millions of queries daily without performance degradation
Knowledge Graph Architecture
Utilizes O11y Knowledge Graph to structure and correlate data across logs, metrics, and traces for fast search and correlation capabilities
Natural Language Processing for Incident Analysis
Implements O11y AI to enable troubleshooting of complex incidents using natural language queries for accelerated root cause analysis
Open Data Lake Foundation
Built on Snowflake data lake architecture providing open data storage without vendor lock-in and enabling cost-efficient telemetry retention
Multi-Signal Correlation
Correlates and contextualizes data across logs, metrics, and traces to provide unified observability across multiple teams and use cases
Standard contract
No
Customer reviews
Willie H.
Powerful Log Insights and Multi-Cloud Visibility, but Costly at Scale
Reviewed on Nov 07, 2026
Review provided by G2
What do you like best about the product?
I like the exceptional level of detail in Datadog’s log traces and how easy it is to search for specific logs using labels and facets.
What do you dislike about the product?
I find Datadog can get expensive at scale, especially when log ingestion volumes and custom metric counts aren’t closely managed.
What problems is the product solving and how is that benefiting you?
Datadog solves our fragmented multi-cloud visibility and slow log diagnostics.
Elba R.
Real-Time Tracing and Integrations, Challenging Setup
Reviewed on Nov 03, 2026
Review provided by G2
What do you like best about the product?
I value Datadog’s real-time tracing engine and its integrations.
What do you dislike about the product?
I find Datadog’s initial installation and configuration quite complex, particularly in a containerized Docker setup.
What problems is the product solving and how is that benefiting you?
I use Datadog for application performance and real-user monitoring. Its real-time tracing and integrations help me connect application errors with user input, and I get real-time latency alerts and error notifications during major performance drops.
Robert H.
Unified Multi-Cloud Visibility, but Agent Setup Takes Effort
Reviewed on Oct 28, 2026
Review provided by G2
What do you like best about the product?
I value Datadog's deep visibility across heterogeneous multi-cloud environments. I appreciate the out-of-the-box AWS and GCP integrations, which let us pull high-resolution metrics from EC2, EKS, and GCP services with consistent, reliable tagging.
What do you dislike about the product?
I found the initial agent setup and configuration complex.
What problems is the product solving and how is that benefiting you?
Datadog solves our multi-cloud visibility fragmentation and the complexity of managing native cloud monitoring tools.
Maribel B.
Powerful Log Insights, but a Cluttered Interface
Reviewed on Oct 26, 2026
Review provided by G2
What do you like best about the product?
I rely on Datadog as our primary centralized hub for monitoring the software development life cycle. I like its granular log filtering and flexible data visualization.
What do you dislike about the product?
I find Datadog’s user interface can feel messy and cluttered for novice users.
What problems is the product solving and how is that benefiting you?
I use Datadog to address application debugging, log fragmentation, and incident management across development environments.
Marlene A.
Fast AWS Setup, Powerful Visibility—But Pricing Adds Up
Reviewed on Oct 25, 2026
Review provided by G2
What do you like best about the product?
I use Datadog as my primary observability platform for real-time visibility across our AWS systems. It helps me avoid switching between separate tools when investigating a backend slowdown.
What do you dislike about the product?
I find Datadog's pricing steep, and its documentation complex.
What problems is the product solving and how is that benefiting you?
I use Datadog to avoid context switching and fragmented observability during production instances.