How Can Datadog’s New Tools Optimize Your Google Cloud Use?

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Datadog has been making waves in the tech world with the recent introduction of new and enhanced observability products tailored specifically for Google Cloud users. Focusing on influential tools like BigQuery, Gemini, and Vertex AI, these advancements are designed to help teams monitor costs, optimize queries, and identify potential data quality issues in BigQuery. Additionally, Datadog’s new features for large language model (LLM) observability support users in monitoring, troubleshooting, and securing applications that use Gemini and Vertex AI. This comprehensive array of new offerings includes Google Cloud Storage Monitoring and Cloud Cost Management, significantly broadening Datadog’s toolset for Google Cloud.

Expanded Monitoring Capabilities for BigQuery

The expanded BigQuery monitoring capabilities, currently in preview, allow users to track BigQuery usage by individual users and projects. This feature is instrumental in helping teams identify high-cost areas, optimize long-running queries, and detect data quality issues that may impede accurate insight extraction. Yasmeen Ahmad, Managing Director of Strategy & Outbound Product Management for Data, Analytics & AI at Google Cloud, emphasized the importance of BigQuery for Google Cloud users. BigQuery enables the extraction of valuable insights from proprietary datasets, and Datadog’s tools make the process even more efficient by enabling detailed tracking of usage, cost attribution, and data currency. Yrieix Garnier, Vice President of Product at Datadog, explained the difficulties clients face in identifying extensive BigQuery usage across different projects and drilling down to optimize problematic queries. Garnier pointed out that the new monitoring capabilities, alongside over 35 existing Google Cloud integrations, will help clients pinpoint cross-project BigQuery cost centers and find optimization opportunities. Moreover, this enhanced monitoring facilitates the identification of stakeholders responsible for high-cost projects and ensures better data quality by allowing quick detection of freshness and volume anomalies.

New Tools Beyond BigQuery

Beyond BigQuery, Datadog has introduced several other powerful products aimed at optimizing Google Cloud usage. These include LLM Observability tools for Gemini and Vertex AI applications, which provide comprehensive monitoring, troubleshooting, and security capabilities tailored for applications that rely on these models. Additionally, the Cloud TPU Integration aids in identifying resource bottlenecks, which can significantly enhance application performance and reliability. Datadog’s Private Service Connect offers improved data security and cost reduction by ensuring more secure connections between services.

Further enhancements include GKE Autoscaling, which is currently in preview, and promises workload scaling recommendations and automation to ensure efficient resource utilization. Storage Monitoring adds visibility into Google Cloud Storage performance, which can aid in identifying and resolving potential storage issues. Additionally, Google Cloud Cost Recommendations aim to detect inefficiencies and provide crucial optimization advice for services like Cloud Run and Cloud SQL. These tools underscore Datadog’s commitment to providing comprehensive operational visibility for complex Google Cloud environments.

Recognition and Partnership

Datadog’s strategy to centralize data streams for companies reliant on Google Cloud infrastructure has proven highly effective, earning the company recognition with three Google Cloud Partner of the Year awards. Categories of these awards include Technology – Global and Application Development – CloudOps, highlighting Datadog’s contributions to improving application performance and operational visibility through innovative monitoring solutions.

Kevin Ichhpurani, President of the Global Partner Ecosystem at Google Cloud, commended Datadog for its significant role in helping Google Cloud customers achieve deep operational visibility. Ichhpurani pointed out that Datadog’s advanced monitoring tools have consistently improved application performance, allowing businesses to maximize their use of Google Cloud services efficiently and securely.

Next Steps for Google Cloud Optimization

Datadog is making a significant impact in the tech world with the rollout of new and improved observability products geared specifically towards Google Cloud users. These upgrades focus on crucial tools such as BigQuery, Gemini, and Vertex AI. They are built to assist teams in monitoring costs, optimizing queries, and identifying potential data quality issues within BigQuery. Moreover, Datadog has introduced features for large language model (LLM) observability. These features aid users in monitoring, troubleshooting, and securing applications that leverage Gemini and Vertex AI. This suite of offerings is extensive, with additions such as Google Cloud Storage Monitoring and Cloud Cost Management. These enhancements broaden Datadog’s suite of tools for Google Cloud significantly, making it even more comprehensive for its users. This expansion demonstrates Datadog’s commitment to providing robust, versatile solutions to streamline operations and ensure the smooth functioning of applications.

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