MongoDB Hackathon Winners Announced

MongoDB
January 28, 2022

Last December, the MongoDB Atlas Hackhaton on DEV was launched. A month has already passed by, and we are very excited to announce this edition’s winners.

Once again, the MongoDB judging panel was highly impressed by the quality of submissions they received and would like to thank everyone who participated in the hackathon. Over 210 submissions were received, and the choice was not easy.

The submissions were categorized into five categories, and each category winner will receive a grand prize worth $1500. In addition to the grand prize winners, ten runner-up projects were selected for prizes worth $250.

Action Star

In this category, the projects needed to create an event-driven application that used MongoDB Realm Functions and Triggers.

Plant Monitor - Using IoT, MongoDB and Flutter

Plant monitor is a complete plant health tracking device that uses MongoDB behind the scenes to store all the data from the IoT device. In addition to using the database to store the data, Souvik created a Realm function to have an HTTP endpoint for the device to send the data directly to MongoDB Atlas. He also went an extra step and used MongoDB Charts for excellent analytics of the plant health.



Automation Innovation

Here, the participants needed to automate a task performed every week using Atlas Serverless.

New Year Resolution Tracker with Weekly Automated Reports

New Year resolutions are hard to keep, but it will be easier this year, thanks to this application. New Year Resolution tracker is an application to log daily exercises and follow your progress with the established goal. A MongoDB Atlas Serverless instance was used to optimize the cluster usage. Alex decided to use the MongoDB JavaScript native driver to connect to the database, making the code easier to read.

E-commerce Creation

Searching through a catalog of products is now easier than ever with Atlas Search. In this category, the participants demonstrated the power of Atlas Search in an e-commerce demo application.

Groovemade - E-commerce app using MongoDB atlas search

Adding full-text search capabilities to an application can seem like a highly complex problem. However, Patrick proved this to be wrong in his project. Groovemade is an e-commerce website that uses MongoDB Atlas to store its catalog of products. The search bar uses Atlas search's auto-completion and fuzzy search features to deliver relevant results instantly to users.



Prime Time

This category was specifically for IoT and heavy analytics projects. Here, the participants used MongoDB Time Series collection to store large amounts of data.

Temperature Sensing with Raspberry Pi into MongoDB

IoT sensors produce a lot of data. This data needs to be stored efficiently to provide analytics to the end-users. With his fish tank temperature sensor, Kai demonstrated how to make the best use of MongoDB Time Series collection to handle the data coming from his sensor. With a new entry in the database every three seconds, Time Series is a great way to handle this type of data at scale.

Choose Your Own Adventure

For participants who got extra creative, this was the category for their projects. Anything that did not fit in the above categories was eligible here.

Asteria: Asteroids approaching Earth today

The MongoDB team received many creative and inventive submissions in this category. Still, this project stood out and was unanimously picked as the winner. In this project, Valeria uses many advanced MongoDB Atlas features such as Realm authentication, functions, and hosting, to warn us of possible asteroids colliding with our planet. Let's just hope we'll never have to actually use this website to track a potential collision!

Runner-Ups

In addition to those five grand prize winners, the jury also picked their ten favourite projects from all submissions. The 10 runner-ups, in no particular order, are:

Title of the document
Lotir - Share link and images between your phone and your computer Julien
RENT! e-commerce, submission for AtlasHackathon Matteo Bianchi
Metrics Monitoring App with Anomaly Detection using MongoDB madalinfasie
Explore Seattle City Bikes trips Benoît Durand
Recipe Cards Collection - Powered by MongoDB, Responsively Designed Roxioxx Studios
Watchkeeping: a timesheet compiling tool for Seafarers Chuong Tang
Atlas hackathon submission (Refactored waffles) Pranjal Jain
HeatSat yvesnrd
vaccineAvailability Application Bikram Bhusan Sinha
Manage webhooks with MongoDB Functions and Triggers Pubudu Jayawardana

See you next time!

That concludes our latest MongoDB Atlas and DEV hackathon. We would like to thank all the participants for their great ideas and unique submissions. This will most likely not be the last hackathon, so stay tuned to learn more about the future events coming up on Dev.to.

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Solving Complex Technical Challenges with MongoDB’s Technical Services Team

MongoDB's Technical Services team works with our customers to ensure that their MongoDB deployments are running at their best. From a query performance question on a test Atlas cluster to helping upgrade large self-hosted sharded clusters run by some of the world's best-known global enterprises, the Technical Services team is available 24/7 to help our customers with any MongoDB product or feature. This deeply technical team is distributed globally, with a variety of backgrounds and expertise to ensure that they can best address any new issue or question. In addition to solving these complex customer challenges, the team also works on internal projects such as software development of support tools for performance tuning, benchmarking, and diagnostics. Hear from three team members about their career journeys and role within Technical Services at MongoDB. Francisco Alanis , Senior Technical Services Engineer, Austin Tell me about your journey into tech. How did you get to where you are today? I've liked technology ever since I was a little kid. I grew up in a small border town in Mexico where my opportunities to learn more about technology were limited to books and magazines. However, I was fortunate enough to be able to visit the U.S. every once in a while. My favorite store to visit was Radio Shack, where I could be more hands-on with technology and inspired by what I found. I eventually started some more formal training in electronics when I did my junior high in a technical middle school, which offered the chance to get a technical degree by the time I started high school. Those days I was studying the basics of how computers worked as a side project, and I felt more attracted to that, but I didn't have access to an actual computer. After several months of savings, my dad was able to buy a computer at my insistence. From that moment on, I started to learn everything I could by poking and prodding and getting every computer magazine I could. I couldn't get access to the Internet until much later. During high school, I moved to the U.S. and started living on my own at about 17 years old. My main objective back then was to get into a college to study computer science or computer engineering. I still had to finish high school but was sent back to 9th grade due to my poor spoken English. I didn't let that stop me, though. I dropped out and got my GED a few months later, my Associates in Arts from a local community college two years later, then got accepted at the University of Texas - Pan American (now UT Rio Grande Valley) after that. There, I worked on projects specializing in networking, distributed systems to solve Physics problems (processing of LHC data), and later on, computer-assisted protein alignment. I completed my Master’s degree a few years later and graduated, married, and started working at IBM all in the same week. At IBM, I worked on Power VIOS Virtual Device Drivers, then AIX Network Device Drivers where I got experience in diagnosis, testing, and SR-IOV driver implementations, and finally at Watson Health where I worked as a DevOps engineer until 2017. In 2017 I started working at MongoDB as a Technical Services Engineer. What has your career path looked like at MongoDB? Before starting at MongoDB I had been working for almost 10 years as a developer, but I had no experience interacting directly with customers. In addition to that, my experience was deep in very specific types of technologies, but my breadth of knowledge wasn't great beyond what I could learn on my own from personal projects. Because of these limitations, my main goals when I started at MongoDB were to get better experience communicating with customers and to expand my breadth of knowledge. In these last four years, I can say I've done that and much more. I still feel a great sense of pride and accomplishment every time I start a call with a customer to assist in an emergency situation and end that call with either a crisis averted or with the customer confident that they are in good hands, knowing their problem will be handled not only by myself but by the full Technical Services team backing me up. Four years ago, I couldn't even imagine being able to offer that kind of service with the level of confidence I can today. In addition to that, it is a world of difference having experience in the design and development of applications versus actually seeing those applications used in the real world, especially the day-to-day consequences of design decisions that may seem inconsequential as a developer but that can profoundly affect customers' usage patterns and views of a product. It’s also interesting to see how different product stacks that include MongoDB can have different effects on the database, both positive and negative. What is the most enjoyable part of your role at MongoDB? Undoubtedly, the best part of MongoDB is the people I work with. I'm very grateful to have the opportunity to work daily with colleagues that are not only very smart but are also very passionate about technology and solving problems. On top of that, they are more than willing to share their knowledge. Our work in Technical Services is very collaborative since there's no single person that knows everything about the data platform. We are exposed to all kinds of different and sometimes unique issues. These issues frequently create learning opportunities that we then share with the team. Additionally, because MongoDB is being used in all kinds of use cases with both mature and emerging technologies, we get a lot of exposure to different solutions used in the field. This can give you accelerated experience in any well-known or new industry trends. Linda Qin , Staff Engineer, Sydney Tell me about your role as a Staff Engineer. My day-to-day job includes casework and project work. When I start my day, I first review the cases in both my own queue and the support queue, then work on the cases based on the urgency and severity. Normally my team responds primarily to the cases submitted by our customers on the MongoDB Support Portal. For critical issues, we’ll set up or join a call with the customer to resolve the issue. I am experienced in MongoDB core databases utilizing sharding, so I regularly help the team with questions in these areas. I am also the Named Technical Services Engineer (NTSE) for some customers. Our NTSE service is a premium enterprise support offering. MongoDB NTSEs work closely with designated customers and have a deep understanding of their environment in order to provide holistic, context-sensitive support. I join regular NTSE meetings with our customers to review opened issues, work on planned activities, and follow up on cases for them. Aside from the casework, I contribute to projects that help improve our productivity. For example, a colleague and I worked on a sharding analyzer to analyze the metadata in a sharded environment. Sharding is a method that MongoDB uses to distribute data across multiple machines. The sharding analyzer can be used to help us understand the data distribution and diagnose issues more efficiently. How do you collaborate with other teams and engineers in your role? Sometimes a case covers multiple areas and different subject expert teams work together to help our customers. For example, when an Atlas customer reports a performance issue, the issue could be caused by under-provisioning or could be related to the queries or indexing configuration. In those cases, I work with my colleagues from the Atlas support team on the investigations into the core database. Within the Technical Services team, we have technical experts with deep experiences and particular responsibilities surrounding their subject matter area. For example, we create a product report to highlight the main pain points and highly-demanded feature requests for the product team. We write Knowledge Base Articles to share internally and with our customers. Additionally, we are often involved in the early stage of new products to review the product description and scope documents and provide feedback based on our field experiences. I am a technical expert in sharding. Apart from the above contributions, I have been working on growing the Technical Services team's skills in this subject area. I have developed a sharding workshop that provides a real sharding deployment with many exercises. New hires or anyone on the support team can use this workshop to get hands-on experience with common issues related to sharding and to gain additional knowledge on the topic of sharding. I am currently working on adding functions to our internal diagnostics tool to automatically analyze MongoDB logs for issues on sharding. What are you most looking forward to in 2022? For MongoDB Technical Services, I am looking forward to more talented people joining our team. We currently have lots of openings in many different locations . For myself, I would like to continue working on projects related to sharding and issue diagnosis. I also plan to work with the other sharding experts to complete the next level sharding workshop, which includes some deeper exercises and knowledge on sharding. Emilio Scalise , Staff Engineer, Rome Tell me a bit about your career journey at MongoDB. I started working at MongoDB in 2015 as part of a small team of six Support Engineers in our Dublin office. The company grew considerably, and I had the opportunity to move back to my country (Italy) to work as a remote Technical Support Engineer in 2016. This role started as an undifferentiatedTechnical Services Engineer for any MongoDB product, but I then began to specialize in supporting our enterprise applications and integrations, a focus that was created the year after I started. This team specializes in supporting Ops Manager, Cloud Manager, and other applications that MongoDB provides in addition to MongoDB Enterprise Server. Over the years I became a Senior Technical Services Engineer, then a Technical Team Lead, and finally a Staff Engineer which is my current role. How has Technical Services leadership supported your career growth? The Technical Services leadership team supported me greatly through the years. I’ve been given the opportunity to take on increasing responsibility and lead many internal projects, teach and coach new team members, and work together with other teammates to continuously improve our MongoDB Support Service to match our growing company needs and expectations. All of these experiences helped me become the Staff Engineer I am today. What types of activities do you take part in as a Staff Engineer? Besides daily casework like all other Technical Services Engineers, as a Staff Engineer, I try to track and contribute to the resolution of major customer escalations and product issues. I’ve been coordinating training and internal tools efforts together with my teammates. Coaching, training, and collaborating with teammates is something that happens continuously over the day, every day. I am also involved with the Technical Experts Program in our organization as an “Expert Champion” (I help recruit new Experts) and as a member of the Ops Manager Experts Team. Within the Experts program, we collaborate with our Product and Development organizations by sharing feedback with them regarding product features and issues, and we also suggest and discuss future improvements in our products. Interested in a career in Technical Services at MongoDB? We have several open roles on our teams across the globe and would love for you to transform your career with us!

January 27, 2022
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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