Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Rehydrate archived logs in any SIEM or logging vendor with Observability Pipelines

Security and observability teams generate terabytes of log data every day—from firewalls, identity systems, and cloud infrastructure, in addition to application and access logs. To control SIEM costs and meet long-term retention requirements, many organizations archive a significant portion of this data in cost-optimized object storage such as Amazon S3, Google Cloud Storage, and Azure Blob Storage.

Secure your APIs at the edge with Datadog App and API Protection

Modern applications are constantly exposed to various malicious activities, including credential stuffing, API abuse, and advanced injection attacks. Many of these threats can be stopped at the network edge, before they ever reach your application. That’s why Datadog App and API Protection offers real-time threat detection and blocking for popular edge proxies and load balancers, which include integrations for Envoy, Istio, NGINX, and Google Cloud Load Balancers (using Google Service Extensions).

Bits AI Security Analyst: Automate Cloud SIEM investigations

Datadog's Bits AI Security Analyst transforms the way security teams handle investigations by autonomously triaging Datadog Cloud SIEM signals. Built natively in Datadog, it conducts in-depth investigations of potential threats and delivers clear, actionable recommendations. With context-rich guidance for mitigation, security teams can stay ahead of evolving threats with greater efficiency and precision.

Control logging costs on any SIEM or data lake using Packs with Observability Pipelines

Rising log volumes are making it harder than ever for security and SRE teams to balance visibility with cost. Every network, CDN, and security layer generates continuous streams of telemetry, but deciding what to parse, retain, or drop often requires manual configuration, specialized knowledge, and extensive tuning.

Key learnings from the 2025 State of Cloud Security study

We have just released the 2025 State of Cloud Security study, where we analyzed the security posture of thousands of organizations using AWS, Azure, and Google Cloud. In particular, we found that: In this post, we provide key recommendations based on these findings, and we explain how you can use Datadog Cloud Security to improve your security posture.

How to monitor MCP server activity for security risks

The Model Context Protocol (MCP) is a popular framework for connecting AI agents to data sources, such as APIs and databases. Because this technology is still new and evolving, its security standards are also in the early stages. This means that MCP servers are susceptible to misuse, so teams building and running them internally need visibility into server interactions to keep their environments safe from attacks.