MongoDB & Bosch: Discussion on AIoT

MongoDB
August 11, 2021

For more than a decade, the digital transformation of industry has been focused on the technologies that make up the Internet of Things (IoT). As AI and machine learning tech mature, a new field has appeared that combines these trends: AIoT, the Artificial Intelligence of Things, which applies AI to the data collected by IoT devices. Among the firms pioneering this space is the engineering and industrial giant Bosch, which has long been a leader in IoT.

The move to AIoT has allowed for Bosch to create smart products that either have intelligence built in, or have “swarm intelligence” in their back end that allows for the collection of data that is used to improve the products.

In April 2021, Mark Porter, CTO at MongoDB, and Dirk Slama, VP of Co-innovation and IT/IoT Alliances at Bosch, sat down to discuss AIoT. Their conversation saw them touch on what MongoDB and Bosch are working on around AIoT, and where they see the future of AIoT heading.

Bosch’s new focus on AIoT has enhanced their need for a flexible, modern data platform such as MongoDB. IoT devices collect enormous amounts of data; as Bosch adds sensors and new types of data to their products, MongoDB has allowed it to adapt quickly without having to go through a schema redesign whenever they need to implement a change to their products.

As part of their efforts to progress AIoT technology, Bosch and other companies recently created the AIoT User Group, an initiative open to anyone. The group’s goal is to bring end users working on AIoT business and use cases together with technology experts to share best practices around AIoT solutions. This co-creation approach allows for the rapid utilization of best practices to try out and develop new ideas and technologies.

Porter and Slama’s conversation covered many AIoT topics — and a glimpse at the technology’s next steps. For instance, Slama wants to see agility added to AIoT without losing control. In AIoT, there are many features that must be perfect on day one; but there are also a lot of features where you want to continuously improve system performance, which requires an agile approach.

For Mark Porter and Dirk Slama's full conversation, check out the video below!

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Intern Series: Finding Community While Owning Production - Meet Carolina Obregon

Carolina Obregon is a rising senior at Tecnológico de Monterrey in Mexico who is interning in our New York City office. She’s spent the summer with the DevRel Platform/Education team building a quiz widget for the guides found on docs.MongoDB.com. Carolina has been excited to gain exposure to start-to-finish software development cycles, and in this interview, you’ll get to hear how she has found meaningful support both in her professional circle and from her membership in MongoDB’s Underrepresented Genders in Tech (UGT) Affinity Group. Alex Wilson: Hey Caro, it’s so good to see you! Can you tell me more about how you found out about MongoDB’s internship program? Carolina Obregon: I first applied to MongoDB's Women in Computer Science Summit all the way back in 2019 and while I wasn't accepted to attend that year, I kept receiving emails from MongoDB about blogs and future openings! When the next recruiting season came, I remembered MongoDB's openings and decided to take the chance and apply to the internship program! I was really happy to even get the first interview and even happier when I received the offer. AW: Why did you choose MongoDB for your internship? CO: As a software engineer, it's very important to me to be in a company that has an engineering centric culture so that I'm working with exciting technological challenges, a modern stack, and teammates that I can learn a lot from. Additionally, I really wanted to be part of a company that really cares about their employees, diversity, and company culture, and throughout the recruiting process and talking with past interns and current employees, I found that MongoDB really checked all the boxes I was looking for. AW: That’s great! What has your day-to-day looked like since you’ve been here? CO: The team I work on is part of the greater Developer Relation Platform/Education organization, which is key for all our developers to learn MongoDB from basics to advanced topics required to run MongoDB in production systems. My team specifically is responsible for developing the systems which run MongoDB documentation's website (docs.mongodb.com). Documentation is crucial for MongoDB since the core of the product is essentially targeted at developers. My intern project is creating a quiz widget that is going to be displayed throughout the docs.mongodb.com guides and will ask our users key multiple choice questions about the content that they’re currently reading on. It's exciting that I've gotten to work on this project from start to finish and really experience how the software development cycle works in the industry, from working with the product manager to the product designer and receiving support from the other engineers on my team to make this all happen. AW: Awesome! Anything particularly interesting that you’ve learned? CO: I've gotten to work on a lot with Javascript's React. I had done previous personal projects using this framework, but it has been very interesting getting to work on it in a real life production environment and receiving guidance and feedback from my teammates on how to keep improving my skills. AW: It must be so gratifying to do work with such tangible results and have clear growth opportunities—and that sounds fascinating. Has your team given you much support in this work? CO: They were really good at ramping me up and making me feel comfortable with the work and tech stack from the beginning. Giving me small tasks to start off and after I was comfortable enough, assigning me my own project to develop on my own. The whole team has been super attentive and helpful throughout the whole summer, and making sure that I'm constantly challenged, learning, and getting help in my work! AW: Fantastic! Is there anywhere else you’ve been finding support? CO: Getting the chance to be part of UGT (Underrepresented Genders in Tech) was a very fulfilling and meaningful experience. The Campus Team assigned a UGT mentor for each of us and prepared many events throughout the summer that ranged from talking about our personal experiences to fun game nights. I really enjoyed getting to know other interns and full timers who are also part of the affinity group. In the short time that I spent here, I’ve found MongoDB to be very supportive of underrepresented genders. Taking in the fact that women make up 46% of the intern class, I always felt that I was in a very comfortable and open work environment everytime I came to the office. AW: It’s been so nice to hear that you’ve had such a meaningful summer. There’s one last thing I’d love to hear: you talked about the company culture as part of the reason why you came to MongoDB—what have you found out about the culture since you’ve been here? CO: One of MongoDB's core values is Build Together, and I think that the company culture really stems from that. It is a very collaborative, friendly work environment where your teammates and co-workers legitimately care about your wellbeing both personally and professionally. Interested in interning at MongoDB? Our 2021/2022 Software Engineering Summer Internship for the US is now live and accepting applications for students

August 6, 2021
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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