Sessions I’m Looking Forward to at MongoDB World 2017
February 21, 2017
Back in 2014, while I was working for BuzzFeed, the CTO asked if I wanted to head to MongoDB World. I had some basic understanding of MongoDB and how it made the lives easier for those who studied the information captured when users visited the BuzzFeed website, but that was it.
I’ve always enjoyed attending conferences. They enable me to learn new technology while meeting the people who create and implement it. So I took Mark up on his offer and headed to my first MongoDB World.
I even documented my attendance:
That nifty guidebook, which was also available as a mobile app, sent me on a journey to learn more about MongoDB. It steered me towards sessions on scaling, the benefits of sharding, and hardware selection for MongoDB that prepared me for future changes in technology I couldn’t have predicted at the time.
A few months later, a thing with a dress made my life very interesting. We used MongoDB to collect the data as the event occurred. Having attended MongoDB World, I felt prepared for this record traffic. While our front end web servers may have buckled under some of the pressure, our data layer was rock solid. Rather than feel the pressure, I allowed my training to take control to work alongside my team.
In 2016, after taking a journey further into Cloud Hosting, an opportunity arose for me to become a member of the MongoDB team as they launched MongoDB Atlas. I made sure that one of my primary tasks as part of this was to take part in MongoDB World as a presenter and give my first talk as a member of MongoDB.
Fast forward to MongoDB World 2017, and my name is listed in the session catalogue for the second year straight. I’ll be presenting a Jumpstart Session on MongoDB Operations. Being part of MongoDB World, initially as an attendee and eventually as a member of the MongoDB staff, has been an extraordinary experience. I often think back to my tweet to @MongoDB. The sessions I attended in 2014 lead me to where I am today.
Sessions I’m looking forward to
At MongoDB, we recently released the session catalogue for MongoDB World 2017, June 20-21 in Chicago. As a presenter, I’m always excited to see who my peers are, so I get a chance to attend some of their sessions and meet with them to chat about our experience. We have quite a lineup this year. As a person who's attended this from both sides, I wanted to share a few that are already on my calendar:
AWS Lambda and MongoDB Atlas
A newcomer to MongoDB, Raphael Londner will discuss the important details when developing an application using the AWS Lambda platform along with MongoDB Atlas, MongoDB's DBaaS (Database as a Service). Raphael is taking a really cool step that I did myself. As soon as I joined MongoDB, I shared my operations, AWS, and MongoDB skills. Similarly, Raphael joined our team in 2017 with the goals of helping developers build new applications in easier ways.
ETL for Pros: Getting Data Into MongoDB
As a person who's trained me in the past, Andre Spiegel continues to impress me. He excels at explaining how to cut to the core of your problem and providing you with better ideas to solve it. Extract, Transform, Load (known as ETL) is a method to work with your data warehouse. Andre will cover how traditional methods of dealing with rows and columns can be modernized by using complex documents. He'll also discuss tuning of the bulk loading process. When you're dealing with hundreds of GBs to TBs of data, that loading process is a big deal; luckily Andre's session will help you best prepare and execute.
How ThermoFisher Is Reducing Mass Spectrometry Experiment Times from Days to Minutes with MongoDB
In 2016, Joseph Fluckinger from Thermo Fisher had a conversation on stage with Eliot Horowitz, MongoDB’s CTO, to discuss much of his team's success with using MongoDB at AWS Re:Invent. I missed this talk and only saw some video clips. Later that night, I had dinner with Joseph and other colleagues. We spoke for hours about how much he enjoyed working with our team to build his talk, and how much the software made a difference to Thermo Fisher.
Hearing how his team replaced so many older SQL technologies with MongoDB to integrate with their tools – including a mass spectrometer – is something I’m really looking forward to.
So as June approaches, I have a ton of work to do to ready myself to present at MongoDB World. But the work is worth it. I look forward to meeting the MongoDB engineers, open-source developers, masters and rookies that will attend. Regardless of skill level, you can build something big for you, your company or your career if you attend MongoDB World. I can't wait to see you there!
What about you?
Take a look at our full list of presenters – anyone standing out you just HAVE to see? Like game designer Jane McGonigal? What's the most interesting subject you have seen in our sessions catalogue? There are three (count em… 1 - 2 - 3) sessions on Kubernetes. We have workouts, yoga, and even an international craft beer tasting.
I hope you and possibly the rest of your team make it. We’d love to have you join us for our biggest event of the year. For more information on MongoDB World sessions, visit mongodbworld.com.
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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 .