We released another round of UI beautification for MMS on September 9th, and we wanted to make sure our customers knew about all of the changes:
- An overhaul of the settings page. This is now named “Administration” and has tabs within it for billing, API keys, personal settings, group settings, user administration, and more. Billing has also been moved from the backup tab to this tab, along with invoice history.
- The Billing and Payment History page itself received a UI refresh as well.
- A new agent widget, located in the top right hand corner, will give tips about the status of all the agents along with a shortcut to their logs.
- The Monitoring Icon was renamed to “Deployment”, and a “Servers” icon was added. Clicking the servers icon will show all the information we currently have about the servers hosting your MongoDB deployment.
We also added a new alert - customers who are backing up a sharded cluster can now be notified if that cluster does not have a MongoS.
Both the monitoring agent and backup agent received fixes and new functionality for authentication using MongoDB 2.4 style client certificates. See the release notes for the agents here for more details.
Intern Spotlight: Josh Clapper
This summer, MongoDB welcomed 33 university students to our intern program in Engineering, Marketing, and Education. In this series, we'll introduce you to the talented students who are helping us transform development and operations for how we run applications today. I had the chance to sit down with Josh Clapper who spent the summer working with the Marketing team! Where do you go to school, what is your major, and what year are you in? I go to Yale University, majoring in Global Affairs and American Studies. I’m a rising junior, planning to graduate in 2016. What is your role at MongoDB? I work in Corporate Marketing, especially focusing on our partner ecosystem. How did you find out about the internship program at MongoDB? Why did you choose to come to MongoDB? I worked last summer at Crowdtap, a collaborative marketing platform based here in New York, and heard about MongoDB through some of my coworkers who knew about the company. When I was looking at where to work this summer, I submitted an application to MongoDB because the company had had a lot of success but was still small; I wanted to learn more about that environment. What’s your hometown? My hometown is Coronado, CA. Bike or public transportation to work? Subway or walking, depending on how much time I have and the weather. What’s a typical day (or week) for you? Typically I’ll get to work and see what projects I’m involved in for that particular day. I’ve been helping in product marketing, corporate communications, and community. What do you love most about MongoDB? I love the family of people who work here and the global sense of that family within the company and in the broader community of MongoDB users. What’s the most challenging aspect of your job? I think the most challenging part is getting up to speed with everything MongoDB does. There’s a unique challenge every department works with. I've felt challenged every week I've been here, and it's been a big professional growth experience. What’s your favorite Seamless lunch order? Getting sandwiches from any of the American restaurants that cycle through the list, maybe with a little barbecue sauce mixed in. Name one secret skill you have, unrelated to work. I’m really good at remembering scenes from movies or TV shows. It’s a pretty useful secret skill. How do you like New York City? As someone from Southern California, the high usage of public transit is definitely something to get used to. The scene for technology companies here is really interesting; I’ve enjoyed learning and growing up in it. There’s also a kind of classic experience to the city, where each neighborhood comes to represent a phase of life. Kindle or book? What’s your favorite book? Book but the Kindle is growing on me. My favorite book is Joan Didion’s essay collection “Slouching Towards Bethlehem,” and right now I’m reading Duty: Memoirs of a Secretary at War, by former Secretary of Defense Robert Gates. Describe your perfect weekend. The perfect weekend would probably start with dinner at a friend’s apartment, maybe a party afterwards. I would get a run in, have a long brunch the next day and do some reading in Central Park. Want to help build the next revolution in database technology? MongoDB offers summer internships and new graduate opportunities to foster computer science talent across the country. Learn more about the MongoDB University Relations program . Or apply to be one of our 2015 Summer Engineering Interns!
MongoDB Query API Webinar: FAQ
Last week we held a live webinar on the MongoDB Query API and our lineup of idiomatic programming language drivers. There were many great questions during the session, and in this post, what I want to do is share the most frequently asked ones with you. But first - here is a quick summary of what MongoDB Query API is all about if you are unfamiliar with it. What is MongoDB Query API? MongoDB is built upon the document data model . The document model is designed to be intuitive, flexible, universal, and powerful. You can easily work with a variety of data, and because documents map directly to the objects in your code, it fits naturally in your app development experience. MongoDB Query API lets you work with data as code and build any class of application faster by giving you extensive query capabilities natively in any modern programming language. Whether you’re working with transactional data, looking for search capabilities, or trying to run sophisticated real-time analytics, MongoDB Query API can meet your needs. MongoDB Query API has some unique features like its expressive query, primary and secondary indexes, powerful aggregations and transformations, on-demand materialized views, and more — enabling you to work with data of any structure, at any scale. Some key features to highlight: Indexes To optimize any workload and query pattern you can take advantage of a large set of index types like multi-key (for arrays), wildcard, geospatial, and more and index any field no matter how deeply nested it is within your documents. Fully featured secondary indexes are document-optimized and include partial, unique, case insensitive, and sparse. Aggregation Pipeline Aggregation pipeline lets you group, transform, and analyze your data to support any class of workload. You can choose from dozens of aggregation stages and over 200 operators to build modular and expressive pipelines. You can also use low-code tools like MongoDB Compass to drag and drop stages, examine intermediate output, and export to your programming language of choice. On-Demand Materialized Views The powerful $merge aggregation stage allows you to combine the results of your aggregation pipeline with existing collections to update and enrich data without having to recompute your entire data set. You can output results to sharded and unsharded collections while simultaneously defining indexes on each view Geospatial and Graph Utilize MongoDB’s built-in natively ability to store and run queries against geospatial data Use operators like $graphLookup to quickly traverse connected data sets These are just a few of the features we highlighted in the MongoDB Query API webinar. No matter what type of application you are thinking of building or managing, MongoDB Query API can meet your needs as the needs of your users and application change. FAQs for MongoDB Query API Here are the most common questions asked during the webinar: Do we have access to the data sets presented in this webinar? Yes, you can easily create a cluster and load the sample data sets into Atlas. Instructions on how to get started are here . How can I access full-text search capabilities? Text search is a standard feature of MongoDB Atlas. You can go to cloud.mongodb.com to try it out using sample data sets. Does VS code plugin support Aggregation? Yes, it does. You can learn more about the VS code plugin on our docs page. If you need to pass variable values in the aggregation, say the price range from the app as an input, how would you do that? This is no different than sending a query - since you construct your aggregation in your application you just fill in the field you want with value/variable in your code. Is there any best practice document on MongoDB query API to have stable performance and utilize minimum resources? Yes, we have tips and tricks on optimizing performance by utilizing indexes, filters, and tools here . Does MongoDB support the use of multiple different indexes to meet the needs of a single query? Yes, this can be accomplished by the use of compound indexes. You can learn more about it in our docs here . If you work with big data and create a collection, is it smarter to create indexes first or after the collection is filled (regarding the time to create a collection)? It is better to create the indexes first as they will take less time to create if the collection is empty, but you still have an option to create the index once the data is there in the collection. There are multiple great benefits of MongoDB’s indexing capabilities: When building indexes, there is no impact on your app’s availability since the index operation is online. Flexibility to add and remove indexes at any time. Ability to hide indexes to evaluate the impact of removing them before officially dropping them. Where do I go to learn more? Here are some resources to help you get started: MongoDB Query API page MongoDB University MongoDB Docs You can also check out the webinar replay here .