Atlas Data Federation and Online Archive Can Now Be Deployed in Azure

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Exciting developments are on the horizon for users of Microsoft Azure, marking a significant leap in data management capabilities. First off, Atlas Data Federation is now Generally Available on Azure. This means you can now deploy it directly within Azure and even query data from Microsoft Azure Blob Storage. And that's not all. We've also launched the General Availability of Atlas Online Archive on Azure. These advancements usher in a new era of efficient archiving solutions for Azure-based data solutions.

Both updates are big steps forward in making data management on Azure more powerful and flexible. Let's dive into what this means for you!

Azure support in Atlas Data Federation (General Availability)

With Atlas Data Federation, users can seamlessly query, transform, and create views across multiple Atlas databases and cloud object storage solutions, such as Amazon S3 and now Microsoft Azure Blob Storage. This feature, previously exclusive to AWS, is a game-changer, allowing direct deployment within Azure and the ability to tap into Microsoft Azure Blob Storage for data insights.

Figure 1: Tap into Azure Blob Storage easily from the Atlas UI

Key features of Atlas Data Federation

  • Cloud flexibility: Choose between AWS and Azure for hosting federated database instances.
  • Diverse data sources: Incorporate MongoDB Atlas clusters or Azure storage solutions (Azure Blob Storage and Azure Data Lake Storage Gen2) as data sources for comprehensive queries, including cross-region.
  • Advanced aggregation: Comprehensive aggregation capabilities with operators inclusive of $match, $lookup, $queryHistory, $merge, $out, etc.
    • Direct $out support for Azure Blob Storage and Azure Data Lake Storage Gen2.
  • Atlas SQL queries on Azure: Execute SQL queries on Azure, integrating MongoDB data for a unified analysis experience.

Atlas Data Federation simplifies accessing and analyzing complex data sets by combining data across multiple sources into a single, federated view, providing valuable insights for more informed business decisions.

Explore Atlas Data Federation on Azure Today.

Azure support in Atlas Online Archive (General Availability)

Atlas Online Archive's expansion to Azure ensures that data tiering is not only efficient but also integrated, keeping archival data within the Azure ecosystem. This integration addresses the previous limitation of defaulting to AWS for storage, even for Azure-hosted clusters.

Figure 2: Seamlessly select Azure when choosing a region

Key features of Atlas Online Archive

  • Provider choice: Opt for AWS or Azure to align with your cloud strategy.
  • Automatic archiving: Set rules to move older data to cost-effective cloud storage automatically, eliminating manual offloading.
  • Unified querying endpoint: Access all data through a single endpoint, ensuring quick insights without compromising data availability.
  • Integrated MongoDB Atlas UI management: Manage your data tiering and archiving within the familiar Atlas interface, streamlining operations and maintenance.

Seamlessly manage your MongoDB Atlas data tiering at scale with Atlas Online Archive. Atlas Online Archive empowers you to manage your data lifecycle efficiently, balancing cost and accessibility with ease.

Finally, here are a few points to consider:

  • Any newly created archive on an Azure cluster on or after 02/28 will default to Azure regions. Note that storage regions for Online Archive will default to Azure clusters only if there are no pre-existing AWS archives on that specific Azure cluster
  • If there are any pre-existing AWS Online Archives on Azure clusters, then all newly created archives on that specific cluster will remain on AWS.
  • Cloud providers or storage regions cannot be edited or modified once configured

Embrace the Full Potential of Atlas Online Archive on Azure Today.

We're thrilled to support your data management journey, offering enhanced control and flexibility over your data through these new Azure capabilities. As MongoDB Atlas continues to expand as a multi-cloud solution, we're here to ensure your data strategy is as dynamic and versatile as your business needs.

For guidance on getting started, check out our documentation on Atlas Data Federation or Atlas Online Archive.

Thank you for trusting MongoDB Atlas as your Developer Data Platform. Welcome to the future of multi-cloud data management!

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They Asked, We Answered: A Q&A on Joining MongoDB’s Remote Solutions Center

Our Remote Solutions Center (RSC) team offers those with technical backgrounds interested in working with customers an opportunity to jumpstart a career in pre-sales. We asked Soheyl Rafi, Solutions Architect and former Remote Solutions Center team member, some common questions candidates have about joining the team. What is the day-to-day like on the Remote Solutions Center team? Working in the Remote Solutions Center is a dynamic and ever-changing experience, with each day bringing unique challenges and opportunities. You can expect a blend of calls, hands-on activities, customer interactions, and problem-solving. The variety keeps the role super interesting. Part of the diverse work environment comes from the collaboration that this role inherently entails. Throughout the day, you’ll engage in various customer interactions such as discussing project requirements and challenges to proposing tailored solutions. Another aspect could be your involvement in Technical Feasibility Workshops with customers. This is where your deep technical knowledge comes into play. You’ll be addressing intricate technical questions, providing insights, and ensuring that our solutions align with the customer’s needs. Enablement also plays a pivotal part in the day-to-day. You will spend a lot of time learning new technologies and features released by our Product team, understanding the competition, and staying abreast of the market as a whole. All in all, the day-to-day work is extremely diverse, and you’ll need to both enjoy and be comfortable wearing multiple hats. What can I expect during the onboarding phase? When you join the RSC, you can expect a comprehensive onboarding experience that covers both technical and sales aspects. Our onboarding plan is designed to provide hands-on training, ensuring that you become familiar with MongoDB technology and business processes. From a technical standpoint, you’ll have access to detailed training sessions and resources. You’ll be guided through the intricacies of our products and services, allowing you to build a strong foundation in your technical knowledge. On the sales front, we have a tailored onboarding plan that focuses on honing the skills required for successful client engagement. This includes understanding our market positioning, customer needs, and effective sales strategies. You will be exposed to real-world scenarios and practical exercises to enhance your sales acumen. To complement your onboarding experience, each new team member is paired with a more senior peer within the RSC. This mentorship helps you begin to build relationships within the team and provides valuable insights and guidance on navigating the role effectively. In addition, RSC leadership recognizes the importance of learning from industry veterans. That’s why each new hire is also paired with a seasoned professional from outside the RSC who acts as a Solution Architecture buddy. This experienced mentor with tenure in the industry will offer a unique perspective and share valuable insights to accelerate your learning. To gain practical exposure, you will have the opportunity to shadow calls and workshops conducted by experienced team members. This hands-on approach allows you to observe firsthand how we conduct business, manage client interactions, and collaborate within the team. In summary, our onboarding program within the RSC is a holistic approach that combines technical training, sales development, mentorship, and practical experience. How often can I expect to collaborate with Solutions Architects (SAs) in the field? As an SA within the RSC, collaboration with SAs in the field is consistently high. We are strategically positioned around account activities and proactively engage with our counterparts in the field teams. Depending on the opportunity during an engagement, you might assist in the early stages of the sales cycle, such as discovery and demos, before passing the deal onto the field SA. Collaboration in these engagements is pivotal, requiring alignment to ensure a seamless handover to the field teams. What internal career development opportunities are there for me? Upon joining the RSC team, you’ll immerse yourself in a dynamic learning environment. Unlike traditional career structures, the RSC team fosters an environment where you are in the driver’s seat, dictating the pace of your internal career development. No artificial roadblocks hinder you from taking on more challenging and senior-level tasks. Your dedication, skills, and initiative are the primary determinants of how quickly you progress. While there are specific tasks you’ll work on in your day-to-day, you’ll also have a wide range of internal projects available to enhance your skill sets and advance your career within MongoDB. In a team with diverse interests and skills, you can choose projects that align with your passion and interests. You’ll find yourself in a situation with structured learning paths, mentorship programs, project leadership opportunities, and a career trajectory limited only by your aspirations. In my career journey, I’ve achieved my goal of growing from an Associate SA to being promoted to a Solutions Architect for our enterprise customers. I am now a dedicated Solutions Architect to one of our biggest financial customers, helping them in their digital transformation and expanding their MongoDB footprint. What new things will I learn if I join the team? The question should be, “What will you not learn?” Databases are at the center of every tech stack. You will be exposed to and gain an understanding of the entire tech stack, including the underlying infrastructure and the application that will be built on top of MongoDB. In your role, you’ll find yourself engaging with customers to discuss the various technologies used in application development, the infrastructure decisions made, and other database solutions that are either part of their tech stack or under consideration. Each customer employs different methodologies for developing software and utilizes various programming languages and solutions. It is pivotal as an SA in the RSC to comprehend these diverse solutions and effectively communicate them to our customers. Beyond the technical aspects, you will start to see things from a macro perspective. Understanding your customer’s business is crucial. You will need to learn how to align technical solutions with business objectives, considering factors such as budget, timelines, and return on investment. Learn more about applying your technical skills and engaging with customers as part of our Remote Solutions Center.

February 28, 2024
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The Converged AI and Application Datastore for Insurance

In the inherently information-driven insurance industry, companies ingest, analyze, and process massive amounts of data, requiring extensive decision-making. To manage this, they rely on a myriad of technologies and IT support staff to keep operations running smoothly but often lack effectiveness due to their outdated nature. Artificial intelligence (AI) holds great promise for insurers by streamlining processes, enhancing decision-making, and improving customer experiences with significantly less time, resources, and staff compared with traditional IT systems. The convergence of AI and innovative application datastores is transforming how insurers work with data. In this post, we’ll look at how these elements are reshaping the insurance industry and offering greater potential for AI-powered applications, with MongoDB at the heart of the converged AI and application datastore. Scenario planning and flexible data layers One of the primary concerns for IT leaders and decision-makers in the insurance industry is making smart technology investments. The goal is to consolidate existing technology portfolios, which often include a variety of systems like SQL Server, Oracle, and IBM IMS. Consolidation helps reduce inventory and prepare for the future. But what does future-proofing really look like? Scenario planning is an effective strategy for future-proofing. This involves imagining different plausible futures and investing in the common elements that remain beneficial across all scenarios. For insurance companies, a crucial common thread is the data layer. By making data easier to work with, companies can ensure that their technology investments remain valuable regardless of how future scenarios unfold. MongoDB’s flexible developer data platform offers a distinct architectural advantage by making data easier to work with, regardless of the cloud vendor or AI application in use. This flexibility is vital for preparing for disruptive future scenarios, whether they involve regulatory changes, market shifts, or technological advancements. Watch now: The Converged AI and Application Datastore: How API's, AI & Data are Reshaping Insurance The role of AI and data in insurance Generative AI is revolutionizing the insurance sector, offering new ways to manage and utilize data. According to Celent's 2023 Technology Insight and Strategy Survey, 33% of companies across different industries have AI projects in planning, 29% in development, and 19% in production (shown in Figure 1 below). This indicates a significant shift towards AI-driven solutions by insurers actively experimenting with gen AI. Figure 1: Celent Technology Insight and Strategy Survey 2023 However, there's tension between maintaining existing enterprise systems and innovating with AI. Insurance companies must balance keeping the lights on with investing in AI to meet the expectations of boards and stakeholders. The solution lies in integrating AI in a way that enhances operational efficiency without overwhelming existing systems. However, data challenges need to be addressed to achieve this, specifically around access to data. According to a Workday Global Survey , only 4% of respondents said their data is fully accessible, and 59% say their enterprise data is somewhat or completely siloed. Without a solid data foundation, insurers will struggle to achieve the benefits they are looking for from AI. Data architectures and unstructured data When adopting advanced technologies like AI and ML, which require data as the foundation, organizations often grapple with the challenge of integrating these innovations into legacy systems due to their inflexibility and resistance to modification. A robust data architecture is essential for future-proofing and consolidating technology investments. Insurance companies often deal with a vast amount of unstructured data, such as claim images and videos, which can be challenging to manage. By leveraging AI, specifically through vector search and large language models, companies can efficiently process and analyze this data. MongoDB is ideal for managing unstructured data due to its flexible, JSON-like document model, which accommodates a wide variety of data types and structures without requiring a predefined schema. Additionally, MongoDB’s flexibility enables insurers to integrate seamlessly with various technologies, making it a versatile and powerful solution for unstructured data management. For example, consider an insurance adjuster assessing damage from claim photos. Traditionally, this would require manually reviewing each image. With AI, the photos can be converted into vector embeddings and matched against a database of similar claims, drastically speeding up the process. This not only improves efficiency but also enhances the accuracy of assessments. The converged AI and application datastore with MongoDB Building a single view of data across various systems is a game-changer for the insurance industry. Data warehouses and data lakes have long provided single views of customer and claim data, but they often rely on historical data, which may be outdated. The next step is integrating real-time data with these views to make them more dynamic and actionable. A versatile database platform plays a crucial role in this integration. By consolidating data into a single, easily accessible view, insurance companies can ensure that various personas, from underwriters to data scientists, can interact with the data effectively. This integration allows for more responsive and informed decision-making, which is crucial for staying competitive in a rapidly evolving market. This can be achieved with a converged AI and application datastore, as shown in Figure 2 below. This is where operational data, analytics insights, and unstructured data become operationally ready for the applications that leverage AI. Figure 2: Converged AI and application datastore reference architecture The convergence of AI, data, and application datastores is reshaping the insurance industry. By making smart technology investments, leveraging AI to manage unstructured data, and building robust data architectures, insurance companies can future-proof their operations and embrace innovation. A versatile and flexible data platform provides the foundation for these advancements, enabling companies to make their data more accessible, actionable, and valuable. The MongoDB Atlas developer data platform puts powerful AI and analytics capabilities directly in the hands of developers and offers the capabilities to enrich applications by consolidating, ingesting, and acting on any data type instantly. Because MongoDB serves as the operational data store (ODS)—with its flexible document model—insurers can efficiently handle large volumes of data in real-time. By integrating MongoDB with AI/ML platforms, insurers can develop models trained on the most accurate and up-to-date data, thereby addressing the critical need for adaptability and agility in the face of evolving technologies. With built-in security controls across all data, whether managed in a customer environment or through MongoDB Atlas, a fully managed cloud service, MongoDB ensures robust security with features such as authentication (single sign-on and multi-factor authentication), role-based access controls, and comprehensive data encryption. These security measures act as a safeguard for sensitive data, mitigating the risk of unauthorized access from external parties and providing organizations with the confidence to embrace AI and ML technologies. If you would like to learn more about the convergence of AI and application datastores, visit the following resources: Video: The Converged AI and Application Datastore: How API's, AI & Data are Reshaping Insurance Paper: Innovation in Insurance with Artificial Intelligence The MongoDB Solutions Library is curated with tailored solutions to help developers kick-start their projects

July 18, 2024