Continued Excellence: MongoDB Receives Fourth Consecutive Google Cloud Partner of the Year Award

John Murray and Melissa Smith
August 29, 2023 | Updated: September 8, 2023
#Partners

MongoDB and Google Cloud have closely partnered since 2018 to enable customers to build innovative applications through deep integrations and just reached another notable milestone. For the fourth year running, MongoDB has been honored as Google Cloud's Technology Partner of the Year, specifically in the category of Data & Smart Analytics. Over the past six years, the two companies have combined their strengths in advanced analytics and best-in-class database technology to drive innovation on behalf of customers.

Throughout 2022, customer demand for our combined offerings became more pronounced, as evidenced by a surge in customers purchasing MongoDB on the Google Cloud Marketplace. MongoDB's integration with Google Cloud's products and services, like BigQuery and Google Application Integration, reached new levels, bringing customers more value through deepened integration. Furthermore, the collaborative endeavors expanded into domains such as Google Cloud’s foundation models and the emerging field of generative AI.

Google & MongoDB focused on helping Startups especially those for Generative AI

To make it easier for startups to embrace this joint innovation, earlier this year MongoDB announced the AI Innovators Program. Through the program, startups gain access to additional MongoDB Atlas Credits, accelerated partnership and marketing opportunities, and more. Early-stage companies can opt into this program when applying to MongoDB for Startups via the Google for Startups Cloud Program or our joint landing page, Startups can use these programs to develop and launch the AI capabilities that will set their business apart and launch them from ideation to IPO.

BigQuery Partner Center

Since 2017, MongoDB and Google Cloud have partnered to make BigQuery and MongoDB integration seamless. Most recently, Google designated MongoDB as Google Cloud Ready for BigQuery after validating the integration using a three-part process, including data integration tests and analysis of benchmarks. This validates that MongoDB Atlas has met a core set of functional and interoperability requirements when integrating with BigQuery, making it easier for customers to choose MongoDB Atlas in Google Cloud’s BigQuery Partner Center.

Google Cloud Application Integration

In the rapidly evolving realm of digital transformation, enterprises must deliver seamless and scalable solutions for their business operations in order to maintain a competitive edge. To fulfill these requirements, organizations frequently employ robust integration platforms like Google Clouds Application Integration. Functioning as an iPaaS (Integration Platform as a Service) solution within the Google Cloud ecosystem, Application Integration offers the capacity to construct integrations that link with numerous third-party applications through Integration Connectors.

The MongoDB connector allows native operations such as insertion, updating, and deletion of document objects in MongoDB. The Google Cloud Application Integration simplifies the complex task of connecting data and applications for customers looking to build new applications.

To get started with Google Cloud's Application Integration and MongoDB Atlas, read the documentation page.

Summary

Since partnering together MongoDB and Google Cloud have collaborated on many integrations to help companies achieve their goals and customers are taking notice. “Working with the right technology partners has helped us to avoid analysis paralysis that can happen when developer teams spend a lot of time trying to understand and manage every detail,” says Sethu Madhav Vure, IT Architect for Ulta Beauty. “Instead, we convert a proof of concept into a working solution, and quickly bring it to market. It’s been a major shift in our IT culture as we try out new things weekly and see incredible support from leadership,” Vure said.

Ready to get started with MongoDB Atlas on Google Cloud? Check out our Google Cloud Marketplace listing to get started today. You can also learn more about our partnership on our Google integrations page.

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MongoDB Database Observability: Integrating with Monitoring Tools

This post is the final in a three-part series on leveraging database observability. Welcome back to our series on Leveraging Database Observability! Our previous post showcased a real-world use case highlighting how MongoDB Atlas’s observability tools effectively tackle database performance challenges. Whether you’re a developer, DBA, or DevOps engineer, our mission is to empower you to harness the full potential of your data through our observability suite . Integrating Atlas metrics with your central enterprise observability tools can simplify your operations. By seamlessly working with popular observability tools, our approach helps teams streamline workflows and enhance visibility across systems. Integrating MongoDB Atlas with third-party monitoring tools MongoDB’s developer data platform combines all essential data services for building modern applications within a unified experience. Our purpose-built observability tools for Atlas environments offer automatic monitoring and optimization, guiding diagnostics tailored specifically for MongoDB. Additionally, we extend Atlas metrics into your existing enterprise observability stack, enabling seamless integration without replacing your current tools. This creates a consolidated, single-pane view that unifies Atlas telemetry with other tech and application metrics, ensuring comprehensive visibility into both database and full-stack performance. This integration empowers you to monitor, receive alerts, and make data-driven decisions within your existing workflows, driving greater efficiency. Below is a quick guide to modifying integration settings through the Atlas UI and the popular integrations we support: Navigate to the Project Integrations page in Atlas. Choose the organization and project you want to configure from the navigation bar. On the Project Integrations page, select the third-party services you’d like to integrate. Configure the chosen services with the required API keys and regions. Critical integrations for your observability platform With Atlas’s Datadog and Prometheus integrations, you can send critical MongoDB metrics to these platforms, empowering detailed, real-time monitoring. Through Datadog , you can track database operation counts, query efficiency, and resource usage, ideal for pinpointing bottlenecks and managing resources. Similarly, Prometheus enables you to monitor essential metrics like query times, connection rates, and memory usage, supporting flexible tracking of database health and performance. Both integrations facilitate proactive detection of issues, alert configuration for resource thresholds, and a cohesive view of Atlas data when visualized in Grafana. Atlas’s integration with PagerDuty streamlines incident management by sending metrics like performance alerts, billing anomalies, and security events directly to PagerDuty. This integration records incidents automatically, notifies teams upon alerts, and supports two-way syncing, ensuring resolved alerts in Atlas are reflected in PagerDuty. It enables efficient incident response and resource allocation to maintain system stability. With Atlas integrations for Microsoft Teams and Slack, you can route key metrics—such as query latency, disk usage, and throughput—to these channels for timely updates. Teams can use these insights for real-time performance monitoring, incident response, and collaboration. Notifications through these platforms ensure your team stays informed on database performance, storage health, and user activity changes as they occur. Use case: Centralized observability with MongoDB Atlas, Datadog, and Slack Let’s walk through a hypothetical scenario for ShopSmart, an e-commerce company that leverages MongoDB Atlas to manage its product catalog and customer data. As traffic surges, the DevOps team faces challenges in monitoring application performance and database health effectively. To tackle these challenges, the team leverages MongoDB Atlas’ integration with Datadog and Slack, creating a powerful observability ecosystem. Integrating MongoDB Atlas with Datadog: The team pushes key MongoDB Atlas metrics into Datadog, such as query performance, connection counts, and Atlas Vector Search metrics. With Datadog, they can visualize these metrics and correlate overall MongoDB performance with their other applications. Out-of-the-box monitors and dedicated dashboards allow the team to track metrics like throughput, average read/write latency, and current connections. This visibility helps pinpoint bottlenecks in real time, ensuring optimal database performance and improving overall application responsiveness. Setting up alerts in Datadog: The team configures alerts for critical metrics like high query latency and increased error rates. When thresholds are breached, Datadog instantly notifies the team. This proactive approach allows the team to address potential performance issues before they impact customers. Integrating Datadog with Slack: To ensure fast communication, alerts are sent directly to the dedicated Slack channel, “ShopSmart-Alerts.” This integration fosters seamless collaboration, enabling the team to discuss and resolve issues in real-time. With these integrations, ShopSmart’s engineering team can monitor performance quickly and address issues efficiently. The unified observability approach enhances operational efficiency, improves the customer experience, and supports ShopSmart’s competitive edge in the e-commerce industry. By leveraging MongoDB Atlas, Datadog, and Slack, the team ensures scalable performance and drives continuous innovation. Conclusion MongoDB Atlas empowers developers and organizations to achieve unparalleled observability and control over their database environments. By seamlessly integrating with central enterprise observability tools, Atlas enhances your ability to monitor performance metrics and ensures you can do so within your existing workflows. This means you can focus on building modern applications confidently, knowing you have the insights and alerts necessary to maintain optimal performance. Embrace the power of MongoDB Atlas and transform your approach to database management—because your applications can thrive when your data is observable. And that wraps up our Leveraging Database Observability series! We hope you learned something new and found value in these discussions. Sign up for MongoDB Atlas , our cloud database service, to see database observability in action. To dive deeper and expand your knowledge, check out this learning byte for more insights on the MongoDB observability suite and how it can enhance your database performance.

November 14, 2024