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Datadog
Datadog is a cloud-based monitoring and analytics platform that provides a wide range of services for tracking the performance, availability, and security of applications and infrastructure. Datadog is widely used by organizations to gain insights into the performance of their technology stack, including servers, containers, databases, cloud services, and applications. It allows businesses to monitor their entire IT environment and gather data for analysis, troubleshooting, and optimization.
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What is Datadog and What services does it provide?
Datadog is a cloud monitoring and analytics platform that provides services for monitoring infrastructure, applications, and logs in real-time. It offers features such as dashboards, alerts, analytics, and integrations to help businesses optimize performance, troubleshoot issues, and ensure reliability.
Is Datadog a SIEM tool?
No, Datadog is not primarily a SIEM (Security Information and Event Management) tool. While it offers security monitoring capabilities, including threat detection and log management, it is primarily focused on performance monitoring and observability.
What types of data can be monitored with Datadog?
Datadog can monitor various types of data, including infrastructure metrics (e.g., CPU usage, memory usage), application performance metrics (e.g., response time, error rate), logs, traces, network traffic, and cloud services metrics (e.g., AWS, Azure, Google Cloud).
Does Datadog offer integrations with other tools?
Yes, Datadog offers extensive integration capabilities with over 400 third-party tools and services, including cloud providers, DevOps tools, databases, messaging systems, and collaboration platforms, allowing businesses to centralize monitoring and streamline workflows.
What are the pricing options for Datadog?
Datadog offers various pricing plans based on the services and features required, with pricing tiers for infrastructure monitoring, application performance monitoring (APM), log management, and other advanced features. Pricing is based on factors such as data ingestion volume, retention period, and additional features.
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