Coming Soon - MongoDB Atlas as a native service on the Google Cloud

Leo Zheng
April 9, 2019 | Updated: June 26, 2020
#Releases#Cloud

Building and managing applications with MongoDB Atlas on Google Cloud is about to become even easier. That's because we are pleased to announce an expanded technical and business partnership with Google which will bring MongoDB Atlas into the Google Cloud Console.

As this change is deployed, customers will be able to provision, run, and scale their fully managed MongoDB clusters from the same user interface used to manage native GCP services. In other words, the experience of using Atlas on Google Cloud Platform will be similar to that of using Google’s native cloud services, with out-of-the-box integrations to Google StackDriver and Cloud IAM to start, and many more GCP service integrations such as GKE and Cloud Machine Learning Engine to follow. The integration will include unified billing — i.e., customers will receive one invoice from Google Cloud that includes their Atlas usage.

Finally, Atlas will also be made available as an offering on the GCP Marketplace, allowing customers to leverage their existing financial commitments to Google Cloud to cover their Atlas usage.

The deeper integration between Atlas and GCP elevates the user experience for joint customers and makes it frictionless to use the leading database for modern applications with the cloud service ecosystem driving the latest innovations in Kubernetes and AI/ML.

MongoDB Atlas, the fully managed global cloud database, is the best way to deploy, run, and scale MongoDB on the Google Cloud. Developed and run by the same engineering team that delivers the latest MongoDB database packages, Atlas automates time-consuming administration tasks such as deployment, configuration changes, and maintenance while providing best-in-class monitoring, data recovery, security, and performance optimization features out of the box.

Customers like Spoke, which provides a Google AI-powered chatbot to customers, migrated to MongoDB Atlas on GCP in 15 minutes, with zero impact to their application. Thanks to richer metrics and automated performance optimization suggestions, the team is already seeing a significant increase in productivity, with more time to focus on developing Spoke’s core features rather than performing database operations and management tasks.

“We used to spend eight engineering hours once a week or so trying to figure out what was going on, and that doesn't exist anymore.” : Roopak Venkatakrishnan, Software Engineer, Spoke

Atlas allows you to deploy clusters across 18 GCP regions in minutes.

Atlas allows you to deploy clusters across 18 GCP regions in minutes.

The new experience for Atlas on GCP will be available for joint customers beginning with the GCP marketplace integration this summer — stay tuned! If you’d rather not wait, you can create a free account and deploy a cluster on GCP in minutes.

← Previous

Countdown to MongoDB World 2019: T-10 Weeks - The Hackathon and The First Sneak Peeks

With ten weeks to go before we open the doors at MongoDB World, we wanted to give you a taste of what's going to be going on in some of the tracks. First, a quick reminder of when and where - the conference is running for three days, June 17th to the 19th, at the Hilton Midtown in New York City. Make sure you have that marked in your diary while we tell you about the Hackathon and what's going on at the conference.

April 8, 2019
Next →

How Edenlab Built a High-Load, Low-Code FHIR Server to Deliver Healthcare for 40 Million Plus Patients

The Kodjin FHIR server has speed and scale in its DNA. Edenlab, the Ukrainian company behind Kodjin , built our original FHIR solution to digitize and service the entire Ukrainian national health system. The learnings and technologies from that project informed our development of the Kodjin FHIR server. At Edenlab, we have always been driven by our passion for building solutions that excel in speed and scale. With Kodjin, we have embraced a modern tech stack to deliver unparalleled performance that can handle the demands of large-scale healthcare systems, providing efficient data management and seamless interoperability. Eugene Yesakov, Solution Architect, Author of Kodjin Built for speed and scale While most healthcare projects involve handling large volumes of data, including patient records, medical images, and sensor data, the Kodjin FHIR server is based on a system developed to handle tens of millions of patient records and thousands of requests per second, to ensure timely access and efficient decision-making for a population of over 40 million people. And all of this information had to be processed and exchanged in real-time or near real-time, without delays or bottlenecks. This article will explore some of the architectural decisions the Edenlab team took when building Kodjin, specifically the role MongoDB played in enhancing performance and ensuring scalability. We will examine the benefits of leveraging MongoDB's scalability, flexibility, and robust querying capabilities, as well as its ability to handle the increasing velocity and volume of healthcare data without compromising performance. About Kodjin FHIR server Kodjin is an ONC-certified and HIPAA-compliant FHIR Server that offers hassle-free healthcare data management. It has been designed to meet the growing demands of healthcare projects, allowing for the efficient handling of increasing data volumes and concurrent requests. Its architecture, built on a horizontally scalable microservices approach, utilizes cutting-edge technologies such as the Rust programming language, MongoDB, ElasticSearch, Kafka, and Kubernetes. These technologies enable Kodjin to provide users with a low-code approach while harnessing the full potential of the FHIR specification. A deeper dive into the architecture approach - the role of MongoDB in Kodjin When deciding on the technology stack for the Kodjin FHIR Server, the Edenlab team knew that a document database would be required to serve as a transactional data store. In an FHIR Server, a transactional data store ensures that data operations occur in an atomic and consistent manner, allowing for the integrity and reliability of the data. Document databases are well-suited for this purpose as they provide a flexible schema and allow for storing complex data structures, such as those found in FHIR data. FHIR resources are represented in a hierarchical structure and can be quite intricate, with nested elements and relationships. Document databases, like MongoDB, excel at handling such complex and hierarchical data structures, making them an ideal choice for storing FHIR data. In addition to supporting document storage, the Edenlab team needed the chosen database to provide transactional capabilities for FHIR data operations. FHIR transactions, which encompass a set of related data operations that should either succeed or fail as a whole, are essential for maintaining data consistency and integrity. They can also be used to roll back changes if any part of the transaction fails. MongoDB provides support for multi-document transactions , enabling atomic operations across multiple documents within a single transaction. This aligns well with the transactional requirements of FHIR data and ensures data consistency in Kodjin. Implementation of GridFS as a storage for the terminologies in Terminology service Terminology service plays a vital role in FHIR projects, requiring a reliable and efficient storage solution for terminologies used. Kodjin employs GridFS , a file system within MongoDB designed for storing large files, which makes it ideal to handle terminologies. GridFS offers a convenient way to store and manage terminology files, ensuring easy accessibility and seamless integration within the FHIR ecosystem. By utilizing MongoDB's GridFS, Kodjin ensures efficient storage and retrieval of terminologies, enhancing the overall functionality of the terminology service. Kodjin FHIR server performance To evaluate the efficiency and responsiveness of the Kodjin FHIR server in various scenarios we conducted multiple performance tests using Locust, an open-source load testing tool. One of the performance metrics measured was the retrieval of resources by their unique ids using the GET by ID operation. Kodjin with MongoDB achieved a performance of 1721.8 requests per second (RPS) for this operation. This indicates that the server can efficiently retrieve specific resources, enabling quick access to desired data. The search operation, which involves querying ElasticSearch to obtain the ids of the searched resources and retrieving them from MongoDB, exhibited a performance of 1896.4 RPS. This highlights the effectiveness of polyglot persistence in Kodjin, leveraging ElasticSearch for fast and efficient search queries and MongoDB for resource retrieval. The system demonstrated its ability to process search queries and retrieve relevant results promptly. In terms of resource creation, Kodjin with MongoDB showed a performance of 1405.6 RPS for POST resource operations. This signifies that the system can effectively handle numerous resource-creation requests. The efficient processing and insertion of new resources into the MongoDB database ensure seamless data persistence and scalability. Overall, the performance tests confirm that Kodjin with MongoDB delivers efficient and responsive performance across various FHIR operations. The high RPS values obtained demonstrate the system's capability to handle significant workloads and provide timely access to resources through GET by ID, search, and POST operations. Conclusion Kodjin leverages a modern tech stack including Rust, Kafka, and Kubernetes to deliver the highest levels of performance. At the heart of Kodjin is MongoDB, which serves as a transactional data store. MongoDB's capabilities, such as multi-document transactions and flexible schema, ensure the integrity and consistency of FHIR data operations. The utilization of GridFS within MongoDB ensures efficient storage and retrieval of terminologies, optimizing the functionality of the Terminology service. To experience the power and potential of the Kodjin FHIR server firsthand, we invite you to contact the Edenlab team for a demo. For more information On MongoDB’s work in healthcare, and to understand why the world’s largest healthcare companies trust MongoDB, read our whitepaper on radical interoperability .

May 31, 2023