Datadog, Inc. Stock Price, News & Analysis

Datadog (NASDAQ: DDOG) has announced a modern approach to Cloud SIEM (Security Information and Event Management) that addresses traditional SIEM challenges. The solution features risk-based insights, 15-months data retention, and security operational metrics, requiring no dedicated staff for activation. The platform leverages modern architectures and machine learning to ensure scalability, cost efficiency, and real-time threat detection.

The system includes pre-built integrations with over 30 new Content Packs added in the past six months, including partnerships with major security providers. Organizations like Lenovo, FanDuel, Carvana, and UAB are already utilizing this modern approach for improved threat detection and security investigations.

Datadog has expanded its Database Monitoring product to include MongoDB support, now covering the five most popular database types including Postgres, MySQL, SQL Server, and Oracle. The solution enables teams to troubleshoot and optimize database performance by providing comprehensive visibility into database clusters, query metrics, and application performance.

The platform helps teams ensure high database availability, optimize query performance, and resolve issues faster through integrated monitoring capabilities. Teams can track critical metrics like queries per second, replication details, and latency while receiving proactive recommendations for optimization.

Datadog (NASDAQ:DDOG) has announced its management's participation in three upcoming investor conferences. The company will present at the RBC Global TIMT Conference on November 19, 2024, at 10:00 a.m. ET, the UBS Global Technology Conference on December 3, 2024, at 10:55 a.m. ET, and the Barclays Global Technology Conference on December 11, 2024, at 12:50 p.m. ET. All presentations will be webcast live with replays available on the company's investor relations website.

Datadog (NASDAQ: DDOG) has launched Kubernetes Active Remediation, enhancing its automated troubleshooting capabilities for Kubernetes environments. The new feature provides curated remediation guidance, best practices, and end-to-end issue management. It offers a comprehensive overview of cluster-level resource problems, ranked by importance, along with consolidated troubleshooting information and root cause analysis.

The platform enables teams to directly trigger deployment patches for key issues within Datadog's unified platform, automating root-cause analysis and detection while improving troubleshooting speed. The solution is designed to help organizations overcome the challenges of Kubernetes expertise and resource-intensive diagnostics.

Datadog (NASDAQ: DDOG) announced its Q3 2024 financial results, reporting revenue of $690 million, a 26% year-over-year increase. GAAP operating income was $20 million with a 3% margin, while non-GAAP operating income was $173 million with a 25% margin. GAAP net income per diluted share was $0.14, and non-GAAP net income per diluted share was $0.46. Operating cash flow stood at $229 million, and free cash flow was $204 million. Datadog had $3.2 billion in cash and marketable securities as of September 30, 2024.

Datadog now has approximately 3,490 customers with ARR of $100,000 or more, a 12% increase from last year. The company was named a Leader in the 2024 Gartner Magic Quadrant for Observability Platforms and Digital Experience Monitoring. Additionally, Datadog announced the general availability of Datadog Monitoring for Oracle Cloud Infrastructure.

For Q4 2024, Datadog projects revenue between $709 million and $713 million, with non-GAAP net income per share between $0.42 and $0.44. For the full year 2024, the company expects revenue between $2.656 billion and $2.660 billion, and non-GAAP net income per share between $1.75 and $1.77.

Datadog (NASDAQ: DDOG) has been named a Leader in Gartner's first-ever Magic Quadrant for Digital Experience Monitoring (DEM), positioning highest in Ability to Execute. The company's DEM solution encompasses Synthetic Monitoring and Testing, Real User Monitoring (RUM), Product Analytics, Session Replay and Error Tracking capabilities for browser and mobile applications. This recognition highlights Datadog's success in providing comprehensive insights into user experience, performance, and security across the entire technology stack. The company's tools have proven valuable for organizations like Redzone QAD, which utilizes Datadog's Synthetic Monitoring for ensuring reliable digital experiences.

Datadog's State of Cloud Security 2024 report reveals significant security risks associated with long-lived credentials across major cloud providers. Key findings include:

- 46% of organizations use unmanaged users with long-lived credentials

- 62% of Google Cloud service accounts, 60% of AWS IAM users, and 46% of Microsoft Entra ID applications have access keys older than one year

- 79% of S3 buckets are covered by Public Access Block, up from 73% last year

- 18% of AWS EC2 instances and 33% of Google Cloud VMs have sensitive project permissions

- 10% of third-party integrations have risky cloud permissions

The report emphasizes the need for modern authentication mechanisms, short-lived credentials, and active monitoring of APIs to enhance cloud security.

Datadog (NASDAQ:DDOG), a cloud application monitoring and security platform provider, has announced its upcoming third quarter fiscal year 2024 earnings call. The company will release its financial results before U.S. markets open on Thursday, November 7, 2024. A conference call is scheduled for the same day at 8:00 a.m. Eastern Time to discuss the results and financial guidance.

Interested parties can access the conference call via phone by registering through a provided link. Additionally, a live webcast of the call will be available on the company's Investor Relations page, with a replay archived on the website for future reference.

Datadog (NASDAQ: DDOG) has announced the general availability of Datadog Monitoring for Oracle Cloud Infrastructure (OCI). This new offering enables Oracle customers to monitor both cloud-native and traditional workloads on OCI, providing comprehensive visibility across infrastructure, applications, and services. Key features include:

1. Integration with 20+ major OCI services and 750+ other technologies
2. Customizable dashboards and monitors for real-time performance visualization
3. Monitoring of AI/ML inference workloads, including GPU usage and performance
4. Code-level visibility into applications with real-time service maps and AI-powered synthetic monitors

The solution aims to help customers confidently migrate from on-premises to cloud environments, execute multi-cloud strategies, and monitor AI/ML workloads effectively.