Last June we introduced MongoDB Atlas, the database as a service for MongoDB. Atlas is designed in accordance with all of the best practices for managing MongoDB, so using it is like getting a professional MongoDB Ops team on your side. It is the easiest and most cost effective way to run MongoDB in the cloud, and it is already helping thousands of teams -- from innovative startups like Bond to established industry leaders like eHarmony and Thermo Fisher -- to build apps more efficiently by making database management as easy as possible.
We’re incredibly excited by the success our customers have had with Atlas so far, and today I’d like to share some updates to the service that will make it even easier to get started with Atlas.
Making Atlas data migrations simple with MongoMirror
It’s a cinch to spin up a MongoDB cluster with Atlas, but if you’re already running an application, you still have to migrate data, which until now has been a manual process. Today we’re introducing a new utility called MongoMirror that automates that process. MongoMirror will live migrate data to MongoDB Atlas from any pre-existing MongoDB 3.0+ replica set, making it even easier to get your existing applications migrated to Atlas.
Get MongoDB in the cloud for free with the new M0 tier
We’re also making it easier than ever to experiment with a real cloud environment for MongoDB. The new “M0” cluster type is a free cluster, ideal for learning MongoDB or building a prototype. Like our existing cluster types, the M0 tier has optimal security, availability, and managed upgrades by default.
More to come
The M0 tier and MongoMirror remove even more barriers between developers and execution of their ideas. Now you can get started with MongoDB Atlas for free, migrate without downtime, and scale up as you need, completely seamlessly. In the coming months, we’ll be bringing MongoDB Atlas to the Google Compute Engine and Microsoft Azure, and we’re actively working on even more tools to seamlessly migrate existing workloads to MongoDB Atlas, so stay tuned.
About the Author - Eliot Horowitz
Eliot Horowitz is CTO and Co-Founder of MongoDB. Eliot is one of the core MongoDB kernel committers. Previously, he was Co-Founder and CTO of ShopWiki. Eliot developed the crawling and data extraction algorithm that is the core of its innovative technology. He has quickly become one of Silicon Alley's up and coming entrepreneurs and was selected as one of BusinessWeek's Top 25 Entrepreneurs Under Age 25 nationwide in 2006. Earlier, Eliot was a software developer in the R&D group at DoubleClick (acquired by Google for $3.1 billion). Eliot received a BS in Computer Science from Brown University.
Leaf in the Wild: World’s Most Installed Learning Record Store Migrates to MongoDB Atlas to Scale Data 5x, while Reducing Costs
Learning Locker moves away from ObjectRocket to scale its learning data warehouse, used by the likes of Xerox, Raytheon and U.K. Universities. From Amazon’s recommendations to the Facebook News Feed, personalization has become ingrained in consumer experience, so it should come as no surprise that resourceful educators are now trying improve learning outcomes with that same concept. After all, no two students are identical in much the same way that no two consumers are exactly alike. Developing a truly personalized educational experience is no easy feat, but emerging standards like the xAPI are helping to make this lofty goal a reality. xAPI is an emerging specification that enables communication between disparate learning systems in a way that standardizes learning data. That data could include things like a student’s attendance in classes, or participation in online tools, but can also stretch to performance measures in the real-world, how students apply their learning. This data-led approach to Learning Analytics is helping educators improve learning practices, tailor teaching and take early intervention if it looks like a student is moving in the wrong direction. But the implications of this go far beyond the classroom, and increasingly companies are using these same techniques to support their employees development and to measure the impact of training on performance outcomes. Whilst educators are predicting the chances of a particular student dropping out, businesses can use these same tools to forecast organizational risk, based on compliance training and performance data, for example. We recently spoke with James Mullaney, Lead Developer at HT2 Labs a company that is at the forefront of the learning-data movement. HT2 Labs’ flagship product, Learning Locker , is an open source data warehouse used by the likes of the Xerox, Raytheon and a wide-range of universities to prove the impact of training and to make more informed decisions on future learning design. To continue to scale the project, better manage their operations and reduce costs, Learning Locker migrated from ObjectRocket to database as a service MongoDB Atlas . Tell us about HT2 Labs and Learning Locker. HT2 Labs is the creator of Learning Locker, which is a data warehouse for learning activity data (commonly referred to as a Learning Record Store or LRS). We have a suite of other learning products that are all integrated; Learning Locker acts as the hub that binds everything together. Our LRS uses the xAPI, which is a specification developed in part by the U.S. Department of Defense to help track military training initiatives. It allows multiple learning technology providers to send data into a single data store in a common format We started playing around with xAPI around four years ago as we were curious about the technology and had our own Social Learning Management System (LMS), Curatr. Today, Learning Locker receives learning events via an API, analyzes the data stored, and is instrumental in creating reports for our end customers. Who is using Learning Locker? The software is open source so our users range from hobbyists to enterprise companies, like Xerox, who use our LRS to track internal employee training. Another example is Jisc , the R&D organization that advances technologies in UK Higher & Further Education.. Jisc are running one of the largest national-level initiatives to implement Learning Analytics across universities in the UK and our LRS is used to ingest data and act as a single source of data for predictive models. This increased level of insight into individual behavior allows Jisc to do some interesting things, such as predict and preempt student dropouts. How has Learning Locker evolved? We’re currently on version two of Learning Locker. We’ve open sourced the product and we’ve also launched it as a hosted Software as a service (SaaS) product. Today we have clients using our LRS in on-premise installations and in the cloud. Each on-prem installation comes packaged with MongoDB. The SaaS version of Learning Locker typically runs in AWS supported by MongoDB Atlas , the managed MongoDB as a Service. Tell us about your decision to go with MongoDB for the underlying database. MongoDB was a very natural choice for us as the xAPI specification calls for student activities to be sent as JSON. These documents are immutable. For example, you might send a document that says, “James completed course XYZ.” You can’t edit that document to say that he didn’t complete it. You would have to send another document to indicate a change. This means that scale is very important as there is a constant stream of student activity that needs to be ingested and stored. We’ve been very happy with how MongoDB, with its horizontal scale-out architecture, is handling increased data volume; to be frank, MongoDB can handle more than our application can throw at it. In fact, our use of MongoDB is actually award-winning: Last year we picked up the MongoDB Innovation Award for best open source project. Beyond using the database for ingesting and storing data in Learning Locker, how else are you using MongoDB? As mentioned earlier, our LRS runs analytics on the data stored and those analytics are then using in reporting for our end users. For running those queries, we use MongoDB’s aggregation framework and the associated aggregation APIs. This allows our end users to get quick reports on information they’re interested in, such as course completion rates, score distribution, etc. Our indexes are also rather large compared to the data. We index on a lot of different fields using MongoDB’s secondary indexes. This is absolutely necessary for real-time analytics, especially when the end user wants to ask many different questions. We work closely with our clients to figure out the indexes that make the most sense based on the queries they want to run against the data. Tell us about your decision to run MongoDB in the cloud. Did you start with MongoDB Atlas or were you using a third party vendor? Our decision to use a MongoDB as a service provider was pretty simple — we wanted someone else to manage the database for us. Initially we were using ObjectRocket and that made sense for us at the time because we were hosting our application servers on Rackspace. Interesting. Can you describe your early experiences with MongoDB Atlas and the migration process? We witnessed the launch of MongoDB Atlas last year at MongoDB World 2016 and spun up our first cluster with Atlas in October. It became pretty clear early on that it would work for what we needed. First we migrated our Jisc deployment and our hosted SaaS product to MongoDB Atlas and we also moved our application servers to AWS for lower latency. The migration was completed in December with no issues. Why did you migrate to MongoDB Atlas from ObjectRocket? Cost was a major driving force for our migration from ObjectRocket. We’ve been growing and are now storing five times as much data in MongoDB Atlas at about the same costs. ObjectRocket was also pretty opaque about what was happening in the background and that’s not the case with MongoDB Atlas, which gives you greater visibility and control. I can see, for example, exactly how much RAM I’m using at any point in time. And finally, nobody is going to tell you that security isn’t important, especially in an industry where we’re responsible for handling potentially-sensitive student data. We were very happy with the native security features in MongoDB Atlas and the fact that we aren’t charged a percentage uplift for encryption, which was not the case with ObjectRocket. Do you have any plans to integrate MongoDB with any other technologies to build more functionality for Learning Locker? We’re looking into Hadoop, Spark, and Tableau for a few of our clients. MongoDB’s native connectors for Hadoop, Spark, and BI platforms come in handy for those projects. Any advice for people looking into MongoDB and MongoDB Atlas? Plan for scale. Think about what you’re doing right now and ask yourself, “Will this work when I have 100x more data? Can we afford this at 100x the scale?” The MongoDB Atlas UI makes most things extremely easy, but remember that some things you can only do through the mongo shell. You should ensure your employees learn or retain the skills necessary to be dangerous in the CLI. And this isn’t specific to just MongoDB, but think about the technology you’re partnering with and the surrounding community. For us, it’s incredibly important that MongoDB is a leader in the NoSQL space as it’s made it that much easier to talk about Learning Locker to prospective users and clients. We view it as a symbiotic relationship; if MongoDB is successful then so are we. James, thanks for taking the time to share your experiences with the MongoDB community and we look forward to seeing you at MongoDB World 2017 . For deploying and running MongoDB, MongoDB Atlas is the best mix of speed, scalability, security, and ease-of-use. Learn more about MongoDB Atlas
Transitioning from Teacher to MongoDB’s New Enterprise Modernization Team: Meet Gabriela Preiss
As a global company, MongoDB has amazing employees with interesting backgrounds and stories. I recently sat down with Gabriela Preiss, an Enterprise Modernization Consultant, to learn more about her journey across the globe from the U.S. to Barcelona, Spain, and her experience transitioning from teaching to becoming the first hire for MongoDB’s brand-new Enterprise Modernization Team, shifting enterprises toward innovation and generating a ton of compelling content along the way. Andrew Bell: Thank you for sharing your story, Gabriela. I’d love to know how you got to where you are today in your role. What skills are important for someone on your team to be successful? Gabriela Priess: My career journey has been from one end of the spectrum to the other. Originally, I studied English and education, and I was a high school teacher for four years. I loved teaching, and I encourage anyone who wants to pursue it to do just that, but eventually, I hit a block and craved more mobility. So I moved from the U.S. to Portugal and studied web and mobile development. Finding myself back as a junior in a new industry, I worked my way up by freelancing as a web developer, building a curriculum for a coding school, and then quickly finding my way into a lead tech support role with a popular web application organization, where I also led the QA process. So, how does all of this add up to working in and with data? I truly believe every professional experience is the chance to extract something positive — a learning takeaway. This diverse background has challenged me and shaped me, as well as helped me to be confident in my choices, to trust I’m taking steps in the right direction, because ultimately each career move has been better than the last and has led me to where I am now, with MongoDB, as an Enterprise Modernization Consultant. Ultimately a career risk led me to a job that didn’t even exist a year ago on a new team. So, we can never truly say what the future holds for us; we may be headed toward a killer career that hasn’t even been invented yet. When it comes to being successful on my team, I think this role is open to so much diversity. I’m trying to narrow down any specific skills, but I think anyone who is ambitious, independent, takes ownership with what they produce, and is curious will succeed here. Curiosity is a huge asset — someone who is open to learning and diving deep into what they don’t yet understand, eager to keep growing, and tech-curious. A big part of what we do involves us keeping our finger on the pulse of tech and data innovation, so we can confidently discuss, debate, or write about it. This means feeding ourselves with the right tech news content. AB: I’d love to know more about the modernization team. What’s your role and your day-to-day like? GP: Our reach is quite broad, but if I had to define it, I’d say the Enterprise Modernization Team (EMT) assists, educates, and helps inspire large enterprises to move toward modernization and innovation. Often, large enterprises have the most complex, costly legacies in their systems and need macro and micro aid and insights to not only modernize but also to visualize and tally the endpoint. EMT Principles and Consultants have the industry expertise and capability to translate our value proposition to senior executives and engineering management. This includes generating training content for internal teams; meeting with other teams for potential and ongoing accounts; delivering webinars, published content, and interactive exposition presentations; and meeting with clients so they have a stronger understanding of how MongoDB helps them to modernize from the most basic format, such as adopting the document model, to truly leading in innovation, such as data science, machine learning, and real-time analytics. So, EMT is a bridge between sales, technical sales, and marketing for complex industry use cases and solutions. These are the teams we collaborate most often with, working closely with sales reps and solutions architects, collaborating with solution providers, and closely aligning with the marketing team producing diverse content and product alignments. So, if you ask me what exactly is my role, I’d say it’s all of the above. Our team is small, although it’s growing quickly, and we have big plans to expand exponentially in the near future. That said, we have a democratic way of dividing the work. We’re made up of our Global Head, Boris Bialek, our Principal, Steve Dalby, and the two Consultants, including myself and Vanda Friedrichs. And we’re all expected to bring equally to the table, despite who has more seniority. This lets us all have an idea of what everyone is working on, and we frequently dip into each other’s projects either to help out or request aid. Each project is free roaming for all: as long as we’re aware of the objective and deadline, we can get creative with how we reach the endpoint. My projects are constantly evolving and regenerating, and I could joke that the only thing they have in common with each other is they all have to do with MongoDB. However, when I was hired, Boris was very clear and direct that each day would be different, and his promise has held true. I don’t have a day-to-day like most others might in regard to consistent projects, but the objective is always the same for each: how can we showcase MongoDB’s value in modernization and innovation in regards to data and tech? Because my projects are so diverse, and often more creative-oriented than anything else, I make up for what some may call a “lack of structure” by being very structured in how I plan my day. Before each day, I predetermine how my next day is going to be divided hourly by projects, tasks, and follow-ups, and I reserve some time for “self-learning,” where I take time to continue my training curriculum, since that’s an ongoing track. AB: Since this is a new role, what tools and resources (e.g., Sales Bootcamp) were you given to help you ramp up? GP: True, this was a new role when I first stepped in, so I didn’t totally know what to expect. There was a running joke I was learning by a fire hose, just having everything blasted at me, and something was bound to stick. MongoDB sets all employees up with boundless learning resources, so I created a curriculum for myself. I prioritized from the top down, based on what I needed to understand ASAP, such as MongoDB’s services and functions, and from there I had freedom to roam based on what interested me the most and what my weak spots were, and was given time to dive in deep technically. For example, I ran POVs to see the data in action from a locally set up database. I know other teams within the company have established curriculums for onboarding, but because this was a new role, I used the resources available and that worked for me. I was given a lot of liberty with my learning because it was mostly autonomous and self-driven, but that’s not to say my learning is over. The company really promotes a learning culture, and every week there are new resources with webinars, learning materials, training materials, and so on. Early into my onboarding, I participated in what’s called our Sales Bootcamp. It’s a two-week intensive training that dives deep into MongoDB’s services as a whole and lays a strong foundation to build on. It’s usually something that’s done in person at MongoDB’s headquarters in New York City, but since this is the COVID-19 era, it was done virtually, with a big cohort of new hires included from Europe and the Americas. This was a cool experience, because I got to meet a lot of new faces. Professionally, my background is originally in education, so I used to write my own curricula for my students, and I’ve been impressed with what I find the MongoDB enablement and Learning & Development teams generating. AB: What content have you and will you create? What is the purpose of this content? How is it leveraged? GP: Among many other roles, the EMT is a content-generating team, so we’re constantly working on creating something new, or collaborating with other teams to create new content. As of today, I’ve been with MongoDB for four months, and in that short time, I’ve been able to generate a lot of interesting, challenging pieces. Each project I’m given is a chance to dive deeper into that subject and expand my understanding of it — like data science or fintech, for example. One of the first projects I had was the chance to write a blog about MongoDB’s partnership with Iguazio , and how our data platform is the ideal persistence layer for Iguazio’s data science and MLOps platform, which is used to develop, deploy, and manage AI applications. Clearly, each project is a team effort, but this gave me the opportunity to dive into a topic I find personally interesting, while building connections with some of our most innovative partners. My first or second week I was introduced to an internal deck created by one of our Solutions Architects, Pascal Jensen. It was a sort of think piece on how data is being driven by the growing uncertainties of the world, in a political, social, and economic sense, and how the most innovative leading companies are responding. We decided to turn this into a more holistic, complete white paper to reach a wider audience. With that, after really digesting the deck that was available and multiple interviews with the Solutions Architects that contributed to it, I built an extensive paper around it, giving breath to the expression “digital by default.” This was something I was quite proud of, because it was so early on in my time with MongoDB, and it let me dive into truly interesting topics. I was able to build on the holistic elements of data and how it’s reshaping even the most mundane elements of the world, propelling us into the future with innovative technologies and solutions for some of the most crucial global concerns, such as hunger or healthcare. Last month, I presented my first corporate webinar with MongoDB, discussing transitioning from a relational database to MongoDB’s document model. It was a huge opportunity, because we were focusing on Spanish-speaking countries in Latin America. For me, this was almost a beta project, because I didn’t know what to expect in regard to reception. In the end, it was a massive success: overall, we had more than 6,500 registrants. That was a really exciting experience, because I knew as a team and a company we were clearly doing something right, engaging with the right audience, and connecting with the right people. There is a really positive response still outpouring from that webinar, and I was happy to be a part of it, especially as a rookie. Again, it just speaks to how much autonomy and freedom to create I’ve been given. My manager never holds me back from any opportunity and really encourages our success. In the spring, we’ll repeat the same endeavor with another webinar, covering a different topic I’m currently preparing in Spanish. AB: What was it like starting in a new role on a new team, especially during the pandemic? How do you stay connected to the team despite living in different countries? GP: Despite the pandemic, there was a lot to dive into because the company was running full speed ahead. It can be slightly intimidating being the new person on a fast-paced team, but I felt very included and seen from day one, and there was more than enough work and training to keep me busy. I haven’t really considered what it would’ve been like to work with MongoDB prepandemic, because at this point, this is all I’ve known. Staying connected with my direct team, though, has been the easiest part for me. I’ve never once felt disconnected despite never having met them in person. As of now, we’re dispersed across Dublin, London, Zurich, and Barcelona, and we’re growing. Plus, our backgrounds are even more diverse considering where we’ve lived, where we’re from, and the languages we speak. It’s refreshing to be part of a team that doesn’t feel limited to one geographic region, because it opens our minds and team discussions to diverse views and ideas. AB: How would you describe the team’s culture? And how do you maintain this culture during COVID-19? GP: The team culture is really positive, inclusive, and ambitious. Every team meeting feels like a brainstorming session, because part of our job is innovation. We’re all given a voice and are expected to use it as we shuffle through ideas and ongoing projects. But overall, our team culture is casual, in the sense that we engage with each other informally, but we all recognize what we need to be working on and by when. We’re each expected to take ownership of our work, and we’re given a lot of creative and structured autonomy. This means independently owning whatever it is we’re working on, and this goes for professional learning too. MongoDB creates a lot of resources internally that I take advantage of, from guided training and courses to reading material, interactive training, webinars, and so forth. I was paired up with one of our Solutions Architects, Benjamin Schubert, and he patiently made himself available to help guide me through some of the more technical aspects of our databases as I was learning how to maneuver through it myself, and I am eternally grateful. Of course, we have support any time we need it, and I can easily seek out resources or set up a Zoom call with an internal expert if I have any questions, but at the end of the day, the ticker moves forward only if everyone is doing their part, so each of us takes our part seriously. Interested in pursuing a career at MongoDB? We have several open roles on our teams across the globe , and would love you to build your career with us!