Datadog has announced the release of new and enhanced observability products for Google Cloud users, with a focus on expanded monitoring capabilities for BigQuery, Gemini and Vertex AI.
These new capabilities are designed to assist teams in identifying costs, optimising queries, and detecting data quality issues specific to BigQuery. Enhanced features for large language model (LLM) observability will allow users to monitor, troubleshoot, and secure applications that utilise Gemini and Vertex AI. Additionally, other offerings include Google Cloud Storage Monitoring and Cloud Cost Management, further strengthening Datadog's suite of tools for Google Cloud.
Datadog's expanded BigQuery monitoring capabilities, currently in preview, provide users an ability to view BigQuery usage by user and project. This functionality helps teams identify high-cost areas, target long-running queries for optimisation, and detect data quality issues. Yasmeen Ahmad, Managing Director of Strategy & Outbound Product Management for Data, Analytics & AI at Google Cloud, stated, "BigQuery is an integral part of Google Cloud users' tech stacks, enabling them to unlock insights from their proprietary datasets. With Datadog's new monitoring capabilities, Google Cloud customers can more granularly track usage, attribute costs to users and teams, and ensure their BigQuery data is up to date for accurate insights."
Yrieix Garnier, Vice President of Product at Datadog, commented on the complexities faced by their clients: "Today, it takes significant time to pinpoint where the largest BigQuery usage is coming from across projects and drill into the problematic queries to optimise. With our new BigQuery monitoring capabilities, which complement our existing 35+ Google Cloud integrations, Datadog customers can identify cross-project BigQuery cost centres, high-impact optimisation opportunities, and the stakeholders that need to be involved. Customers can also improve data quality by detecting data freshness and volume anomalies so they can fix issues quickly and ensure their business has accurate and up-to-date insights."
Beyond BigQuery, Datadog has introduced several other products. These include LLM Observability for monitoring and securing Gemini and Vertex AI applications, Cloud TPU Integration for detecting resource bottlenecks, and Private Service Connect for enhanced data security and reduced costs. Each of these tools aims to provide deep operational visibility for Google Cloud environments.
Datadog's offerings extend further with GKE Autoscaling, currently in preview, that offers workload scaling recommendations and automation, as well as Storage Monitoring which provides visibility into Google Cloud Storage performance at various levels. The Google Cloud Cost Recommendations feature identifies inefficiencies and offers optimisation advice specifically for services like Cloud Run and Cloud SQL.
As companies in various industries depend on Google Cloud infrastructure, Datadog aims to centralise their data streams through its observability platform. This approach has earned Datadog three Google Cloud Partner of the Year awards across categories including Technology – Global and Application Development – CloudOps.
Kevin Ichhpurani, President, Global Partner Ecosystem at Google Cloud, expressed the company's satisfaction with Datadog, noting: "We're pleased to recognise Datadog as our Global Technology Partner of the Year. Datadog has consistently helped Google Cloud customers gain deep operational visibility and improve application performance by delivering innovative monitoring solutions that drive customer success."
