Sold by: Datadog
Deployed on AWS
Quick Launch
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.
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Overview
Free trial: Click "Continue to Subscribe" and create a new Datadog account to receive a 14-day free trial of all Datadog features. At the end of your free trial, your account will automatically convert to a paid Pay-As-You-Go plan detailed in this listing.
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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Buyer guide
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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 actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/unit |
|---|---|---|
Infra Pro Hosts per hour | Infra Pro Hosts per hour | $0.03 |
Additional Containers per hour | Additional Containers per hour | $0.002 |
Additional Custom Metrics per hour (per 100 Metrics) | Additional Custom Metrics per hour (per 100 Metrics) | $0.008 |
APM Hosts per hour | APM Hosts per hour | $0.06 |
APM Analyzed Spans per hour - 15 Day Retention (Per 1 Million) | APM Analyzed Spans per hour - 15 Day Retention (Per 1 Million) | $2.55 |
Indexed Log Events per hour - 15 Day Retention (Per 1 Million) | Indexed Log Events per hour - 15 Day Retention (Per 1 Million) | $2.55 |
Ingested Logs per hour (Per 1 GB) | Ingested Logs per hour (Per 1 GB) | $0.10 |
Synthetics API Tests per hour (Per 10K test runs) | Synthetics API Tests per hour (Per 10K test runs) | $7.20 |
Synthetics Browser Checks per hour (Per 1K test runs) | Synthetics Browser Checks per hour (Per 1K test runs) | $18.00 |
Serverless Functions per hour (no longer offered) | Serverless Functions per hour (no longer offered) | $0.012 |
Dimensions summary
You pay per hour based on what you actually use, with no upfront commitment. Each dimension bills a different resource independently, so you only add what you monitor. Host-based dimensions cover infrastructure, application performance (APM), network, and profiled hosts. Volume-based dimensions bill logs, spans, custom metrics, synthetic tests, user sessions, and serverless activity in set units like per GB or per million events. Containers, custom metrics, and analyzed spans act as usage add-ons beyond included allotments. A separate consumption unit covers additional Datadog usage. Dimensions combine freely to match your monitoring needs.
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. A billable APM host is one actively generating traces submitted to Datadog. Uninstrumented hosts like databases or load balancers do not count, even with APM enabled.
Each host license includes an allotment, such as containers per host and custom metrics per host. Usage above these allotments bills through the separate add-on dimensions like Additional Containers per hour or Additional Custom Metrics per hour. Metrics and containers are averaged across your whole account, not per host.
Ingested Logs bill per GB for processing and archiving all your logs. Indexed Log Events bill separately per million events for the logs you keep searchable during a 15-day retention window. Both charges apply at once, so ingesting everything while indexing selectively controls cost.
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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
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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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Sentiment is AI generated from actual customer reviews on AWS and G2
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AI generated from product descriptions
Multi-Source Data Integration
Collects and correlates data from more than 600 vendor-backed technologies and APM libraries in a single unified interface
Infrastructure and Application Monitoring
Monitors underlying infrastructure, supporting services, applications, and security data simultaneously within a single observability platform
Unified Observability Dashboard
Provides full visibility into the health and performance of each layer of the environment through a single pane of glass
Rapid Deployment and Setup
Enables quick deployment through turn-key integrations and easy-to-install agent for monitoring servers and resources
Security and Threat Mitigation
Integrates security data and threat detection capabilities to identify and mitigate security threats across the monitored environment
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
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Customer reviews
Courtney S.
Effortless Integration, Powerful Observability
Reviewed on Sep 30, 2026
Review provided by G2
What do you like best about the product?
I like Datadog for its ease of platform integration and the library of predefined dashboards that are incredibly useful.
What do you dislike about the product?
My main complaints with Datadog are its high, rigid pricing structure and the limitations of their customer support workflow.
What problems is the product solving and how is that benefiting you?
Datadog eliminates manual server checks and error guessing, reducing human overhead.
Rubene R.
Unmatched Observability with Pricing Caveats
Reviewed on Sep 29, 2026
Review provided by G2
What do you like best about the product?
I rely on Datadog as my primary all-in-one observability platform every single day. Out of all the modules built into the platform, I find the APM distributed tracing combined with the log explorer to be the most invaluable feature set for my daily workflow.
What do you dislike about the product?
My biggest frustration with Datadog comes down to its pricing model and how fast ingestion costs can spiral completely out of control if you aren't hypervigilant.
What problems is the product solving and how is that benefiting you?
Datadog eliminates guesswork during production incidents and saves time by allowing trace of user requests across microservices seamlessly.
Anshuman S.
All-in-One Observability with Great Cloud Integrations and a User-Friendly UI
Reviewed on Sep 10, 2026
Review provided by G2
What do you like best about the product?
It is an all-in-one Observability tool which is a combination of infrastructure metrics, application logs, application performance monitoring, real user monitoring, and security monitoring. It has very good integrations with almost all cloud providers. The User Interface is very user-friendly.
What do you dislike about the product?
It's very costly. Sending application logs to Datadog can lead to unpredictable costs. Providing add-on features is a very complex task. It's difficult to learn for new users.
What problems is the product solving and how is that benefiting you?
Despite the cost, I love this tool. It helps in identifying real-time issues very quickly. We can easily identify slowness using APM metrics or which API is taking more time. Identifying 5xx errors becomes very easy using this tool.
Zaid K.
Comprehensive Monitoring with Easy Integration
Reviewed on Jul 21, 2026
Review provided by G2
What do you like best about the product?
I use Datadog for monitoring, and it helps me in a lot of ways. It shows in-depth logs of the systems and provides a comprehensive view of metrics. There are lots of metrics, and the integration is very simple, especially with Terraform. It offers a good view of metrics, which is really valuable for me. I appreciate being able to create my own dashboards and metrics. The setup was quite easy, and we received support from the data ops team to integrate it with the systems.
What do you dislike about the product?
I think Datadog's anomaly detection is quite basic in alerting me. I would like it to be enhanced to provide more detailed warning alerts.
What problems is the product solving and how is that benefiting you?
I use Datadog for monitoring, providing in-depth logs and metrics. It simplifies integration, especially with Terraform, and offers a good view of metrics, making it easier to handle multiple instances and identify issues like memory leaks.
Aditya J.
Enterprise Observability and Monitoring at Scale with Datadog
Reviewed on Jul 17, 2026
Review provided by G2
What do you like best about the product?
What I like best about Datadog is its ability to provide deep observability across infrastructure, applications, logs, cloud services, and identity platforms from a single pane of glass. Having used Datadog for an extended period, I've found its dashboards, alerting capabilities, and correlation between metrics, logs, and traces to be extremely valuable for both proactive monitoring and incident response.
As an administrator, I appreciate the flexibility in creating custom dashboards, configuring monitors, and tuning alerts to reduce noise while ensuring critical issues are detected early. The platform's extensive integration ecosystem makes it easy to onboard new services, and features such as anomaly detection, log analytics, and service mapping significantly improve troubleshooting efficiency.
Overall, Datadog has helped streamline operations, reduce mean time to resolution (MTTR), and provide actionable insights that support both day-to-day monitoring and long-term platform optimization.
As an administrator, I appreciate the flexibility in creating custom dashboards, configuring monitors, and tuning alerts to reduce noise while ensuring critical issues are detected early. The platform's extensive integration ecosystem makes it easy to onboard new services, and features such as anomaly detection, log analytics, and service mapping significantly improve troubleshooting efficiency.
Overall, Datadog has helped streamline operations, reduce mean time to resolution (MTTR), and provide actionable insights that support both day-to-day monitoring and long-term platform optimization.
What do you dislike about the product?
While Datadog is a mature and feature-rich platform, one area that can be challenging is cost management at scale. As environments grow and more teams onboard services, log ingestion, custom metrics, and data retention costs require ongoing optimization and governance. I've also found that in large enterprise deployments, alert tuning and monitor management need regular review to avoid alert fatigue and maintain signal-to-noise quality.
Another area for improvement is that some advanced configurations and cross-product features can have a learning curve for newer administrators. While the platform offers tremendous flexibility, fully leveraging its capabilities often requires experience and a well-defined monitoring strategy.
That said, these challenges are common for enterprise observability platforms, and the operational benefits Datadog provides generally outweigh the drawbacks.
Another area for improvement is that some advanced configurations and cross-product features can have a learning curve for newer administrators. While the platform offers tremendous flexibility, fully leveraging its capabilities often requires experience and a well-defined monitoring strategy.
That said, these challenges are common for enterprise observability platforms, and the operational benefits Datadog provides generally outweigh the drawbacks.
What problems is the product solving and how is that benefiting you?
Datadog solves the challenge of maintaining visibility across complex, distributed environments by bringing infrastructure metrics, application performance, logs, traces, security signals, and cloud services into a single observability platform. Prior to adopting Datadog, troubleshooting often required switching between multiple tools and manually correlating data from different sources.
As a long-time user and administrator, I've found that Datadog significantly improves operational efficiency by enabling teams to quickly identify performance bottlenecks, detect anomalies, and investigate incidents from a centralized interface. The ability to correlate metrics, logs, and traces has greatly reduced troubleshooting time and improved root cause analysis.
Datadog has also helped us implement a more proactive monitoring approach through intelligent alerting, anomaly detection, and service health visibility. This has contributed to faster incident response, reduced downtime, improved system reliability, and better overall user experience. From an operations perspective, it has become a critical platform for maintaining service health and supporting informed decision-making across teams.
As a long-time user and administrator, I've found that Datadog significantly improves operational efficiency by enabling teams to quickly identify performance bottlenecks, detect anomalies, and investigate incidents from a centralized interface. The ability to correlate metrics, logs, and traces has greatly reduced troubleshooting time and improved root cause analysis.
Datadog has also helped us implement a more proactive monitoring approach through intelligent alerting, anomaly detection, and service health visibility. This has contributed to faster incident response, reduced downtime, improved system reliability, and better overall user experience. From an operations perspective, it has become a critical platform for maintaining service health and supporting informed decision-making across teams.