If you’ve attended a conference before, you know that large, multi-day events can be quite costly. The reason for this is that organizing a conference is expensive. Offering attendees an unforgettable experience complete with expert speakers, a memorable after party, and good food comes with a hefty price tag.
At MongoDB, our goal is to host events that are accessible to our community members. We want you to be able to attend MongoDB World, learn, develop new ideas, and connect with other contributors. We realized that by offering tickets that cost more than $1,000, we excluded part of our community, individuals or companies who were unable to afford to pay this ticket price.
The content at our events is not just tailored towards developers who work at large corporations. It’s also crafted with the open source community in mind. This includes independent consultants, academics, and government organizations, who are often priced out of large conferences.
For this reason, we’re excited to announce that we’ve created an accessible pricing model for MongoDB World 2017. You can now attend our annual two-day conference for as low as $224.25! The earlier you book, the lower your price. If you wait, a general admission ticket will still only cost you $499.
With this new pricing we hope MongoDB World 2017 will be accessible to more people in the community, whether they are students, freelancers, or startup and nonprofit employees. Even at a new price point we’ll still bring you a high-quality, community-centric conference, loaded with education, networking, and yes – an unforgettable after party.
Can’t wait to see you in Chicago on June 20-21!
What’s New in MongoDB 3.4, Part 3: Modernized Database Tooling
Welcome to the final post in our 3-part MongoDB 3.4 blog series. In part 1 we demonstrated the extended multimodel capabilities of MongoDB 3.4, including native graph processing, faceted navigation, rich real-time analytics, and powerful connectors for BI and Apache Spark In part 2 we covered the enhanced capabilities for running mission-critical applications, including geo-distributed MongoDB zones, elastic clustering, tunable consistency, and enhanced security controls. We are concluding this series with the modernized DBA and Ops tooling available in MongoDB 3.4. Remember, if you want to get the detail now on everything the new release offers, download the What’s New in MongoDB 3.4 white paper . MongoDB Compass MongoDB Compass is the easiest way for DBAs to explore and manage MongoDB data. As the GUI for MongoDB, Compass enables users to visually explore their data, and run ad-hoc queries in seconds – all with zero knowledge of MongoDB's query language. The latest Compass release expands functionality to allow users to manipulate documents directly from the GUI, optimize performance, and create data governance controls. DBAs can interact with and manipulate MongoDB data from Compass. They can edit, insert, delete, or clone existing documents to fix data quality or schema issues in individual documents identified during data exploration. If a batch of documents need to be updated, the query string generated by Compass can be used in an update command within the mongo shell. Trying to parse text output can significantly increase the time to resolve query performance issues. Visualization is core to Compass, and has now been extended to generating real-time performance statistics, and presenting indexes and explain plans. Figure 1: Real-time performance statistics now available from MongoDB Compass The visualization of the same real-time server statistics generated by the mongotop and mongostat commands directly within the Compass GUI allows DBAs to gain an immediate snapshot of server status and query performance. If performance issues are identified, DBAs can visualize index coverage, enabling them to determine which specific fields are indexed, their type, size, and how often they are used. Compass also provides the ability to visualize explain plans, presenting key information on how a query performed – for example the number of documents returned, execution time, index usage, and more. Each stage of the execution pipeline is represented as a node in a tree, making it simple to view explain plans from queries distributed across multiple nodes. If specific actions, such as adding a new index, need to be taken, DBAs can use MongoDB’s management tools to automate index builds across the cluster. Figure 2: MongoDB Compass visual query plan for performance optimization across distributed clusters Document validation allows DBAs to enforce data governance by applying checks on document structure, data types, data ranges, and the presence of mandatory fields. Validation rules can now be managed from the Compass GUI. Rules can be created and modified directly using a simple point and click interface, and any documents violating the rules can be clearly presented. DBAs can then use Compass’s CRUD support to fix data quality issues in individual documents. MongoDB Compass is included with both MongoDB Professional and MongoDB Enterprise Advanced subscriptions used with your self-managed instances, or hosted MongoDB Atlas instances. MongoDB Compass is free to use for evaluation and in development environments. You can get MongoDB Compass from the download center , and read about it in the documentation . Operational Management for DevOps Teams Ops Manager is the simplest way to run MongoDB on your own infrastructure, making it easy for operations teams to deploy, monitor, backup, and scale MongoDB. Ops Manager is available as part of MongoDB Enterprise Advanced, and its capabilities are also available in Cloud Manager , a tool hosted by MongoDB in the cloud. Ops Manager and Cloud Manager provide an integrated suite of applications that manage the complete lifecycle of the database: Automated deployment and management with a single click and zero-downtime upgrades Proactive monitoring providing visibility into the performance of MongoDB, history, and automated alerting on 100+ system metrics Disaster recovery with continuous, incremental backup and point-in-time recovery, including the restoration of complete running clusters from your backup files Ops Manager has been enhanced as part of the MongoDB 3.4 release, now offering: Finer-grained monitoring telemetry Configuration of MongoDB zones and LDAP security Richer private cloud integration with server pools and Cloud Foundry Encrypted backups Support for Amazon S3 as a location for backups Ops Manager Monitoring Ops Manager now allows telemetry data to be collected every 10 seconds, up from the previous minimum 60 seconds interval. By default, telemetry data at the 10-second interval is available for 24 hours. 60-second telemetry is retained for 7 days, up from the previous 48-hour period. These retention policies are now fully configurable, so administrators can tune the timelines available for trend analysis, capacity planning, and troubleshooting. Generating telemetry views synthesized from hardware and software statistics helps administrators gain a complete view of each instance to better monitor and maintain database health. Ops Manager has always displayed hardware monitoring telemetry alongside metrics collected from the database, but required a third party agent to collect the raw hardware data. The agent increased the number of system components to manage, and was only available for Linux hosts. The Ops Manager agent has now been extended to collect hardware statistics, such as disk utilization and CPU usage, alongside existing MongoDB telemetry. In addition, platform support has been extended to include Windows and OS X. Private Cloud Integration Many organizations are seeking to replicate benefits of the public cloud into their own infrastructure through the build-out of private clouds. A number of organizations are using MongoDB Enterprise Advanced to deliver an on-premise Database-as-a-Service (DBaaS). This allows them to standardize the way in which internal business units and project teams consume MongoDB, improving business agility, corporate governance, cost allocation, and operational efficiency. Ops Manager now provides the ability to create pre-provisioned server pools. The Ops Manager agent can be installed across a fleet of servers (physical hardware, VMs, AWS instances, etc.) by a configuration management tool such as Chef, Puppet, or Ansible. The server pool can then be exposed to internal teams, ready for provisioning servers into their local groups, either by the programmatic Ops Manager API or the Ops Manager GUI. When users request an instance, Ops Manager will remove the server from the pool, and then provision and configure it into the local group. It can return the server to the pool when it is no longer required, all without sysadmin intervention. Administrators can track when servers are provisioned from the pool, and receive alerts when available server resources are running low. Pre-provisioned server pools allow administrators to create true, on-demand database resources for private cloud environments. You can learn more about provisioning with Ops Manager server pools from the documentation. Building upon server pools, Ops Manager now offers certified integration with Cloud Foundry. BOSH, the Cloud Foundry configuration management tool, can install the Ops Manager agent onto the server configuration requested by the user, and then use the Ops Manager API to build the desired MongoDB configuration. Once the deployment has reached goal state, Cloud Foundry will notify the user of the URL of their MongoDB deployment. From this point, users can log in to Ops Manager to monitor, back-up, and automate upgrades of their deployment. MongoDB Ops Manager is available for evaluation from the download center . Backups to Amazon S3 Ops Manager can now store backups in the Amazon S3 storage service, with support for deduplication, compression, and encryption. The addition of S3 provides administrators with greater choice in selecting the backup storage architecture that best meets specific organizational requirements for data protection: MongoDB blockstore backups Filesystem backups (SAN, NAS, & NFS) Amazon S3 backups Whichever architecture is chosen, administrators gain all of the benefits of Ops Manager, including point-in-time recovery of replica sets, cluster-wide snapshots of sharded databases, and data encryption. You can learn more about Ops Manager backups from the documentation . MongoDB Atlas: VPC Peering The MongoDB Atlas database service provides the features of MongoDB, without the operational heavy lifting required for any new application. MongoDB Atlas is available on-demand through a pay-as-you-go model and billed on an hourly basis, letting developers focus on apps, rather than ops. MongoDB Atlas offers the latest 3.4 release (community edition) as an option. In addition, MongoDB Atlas also now offers AWS Virtual Private Cloud (VPC) peering . Each MongoDB Atlas group is provisioned into its own AWS VPC, thus isolating the customer’s data and underlying systems from other MongoDB Atlas users. With the addition of VPC peering, customers can now connect their application servers deployed to another AWS VPC directly to their MongoDB Atlas cluster using private IP addresses. Whitelisting public IP addresses is not required for servers accessing MongoDB Atlas from a peered VPC. Services such as AWS Elastic Beanstalk or AWS Lambda that use non-deterministic IP addresses can also be connected to MongoDB Atlas without having to open up wide public IP ranges that could compromise security. VPC peering allows users to create an extended, private network connecting their application servers and backend databases. You can learn more about MongoDB Atlas from the documentation . Next Steps As we have seen through this blog series, MongoDB 3.4 is a significant evolution of the industry’s fastest growing database: Native graph processing, faceted navigation, richer real-time analytics, and powerful connectors for BI and Spark integration bring additional multimodel database support right into MongoDB. Geo-distributed MongoDB zones, elastic clustering, tunable consistency, and enhanced security controls bring state-of-the-art database technology to your most mission-critical applications. Enhanced DBA and DevOps tooling for schema management, fine-grained monitoring, and cloud-native integration allow engineering teams to ship applications faster, with less overhead and higher quality. Remember, you can get the detail now on everything packed into the new release by downloading the What’s New in MongoDB 3.4 white paper . Alternatively, if you’d had enough of reading about it and want to get started now, then: Download MongoDB 3.4 Alternatively, spin up your own MongoDB 3.4 cluster on the MongoDB Atlas database service Sign up for our free 3.4 training from the MongoDB University
Built With MongoDB: FanPlay
Pritesh Kumar and Bharat Gupta co-founded FanPlay Technologies at the beginning of the pandemic that shook the world in 2020. With their real money gaming (RMG) product, they’ve joyfully brought thousands of people together across India in a safe way, while establishing the country’s leading gaming app. For this segment of #BuiltWithMongoDB, we spoke with Pritesh about their company’s business model, how MongoDB is working to their advantage, and what celebrities are already utilizing their platform. MongoDB: What prompted you to build FanPlay? Pritesh: The emergence of COVID-19 really prompted me into the startup world again. I’ve been a founder in the past, and I knew that at this time a lot of new companies would emerge, so I decided to be part of that. The idea for FanPlay came from observing Cameo . I was really impressed by its strong viral growth and its monetization of influencers. I think these micro influencers on the platform, although they don’t make a lot of money for a single video, can add massive value to any business. And at the same time, we were looking at the RMG industry, which was and still is the fastest-growing space in online gaming. But there is a real problem of very high customer acquisition cost. So, we put one and one together and started building an influencer-led, RMG platform. We get influencers to host real-money trivia games for the fans and followers on our platform. Typically these influencers promote their own shows on their social media platforms. They gather an audience from YouTube, TikTok, and various other channels, and then they come to our platform for the gaming experience. The audience usually pays a small entry fee. From that entry fee, a prize is created, that prize goes to the winner of the game, and from that prize we take a cut. So this is our business model. MongoDB: What was your initial vision for the product, and what does it look like today? Pritesh: The product has changed a lot from what we initially envisioned. We started with a web app initially because we thought that acquiring users on the web would be much easier, but then we launched our free Android app and it did very well. From there we launched our paid-entry model. So the product has gone through three iterations so far. In the beginning we worked a lot with Instagram influencers and realized that we needed to be working with influencers on YouTube, and specifically with people more regionally significant to India, where most of our business is at the moment. We have also expanded to hosting established faces from Instagram and YouTube. MongoDB: Can you tell us about the scale of the platform? Pritesh: Currently we work with about 500 influencers that have a lot of visibility, and we host roughly 20,000 active users daily, from India. Typically we run about 20 games per day, and we’re working to scale that to 100 per day. MongoDB: What does your tech stack consist of? Pritesh: The app is built in React Native, and the back end is Node.js. Then of course for a database we use MongoDB. MongoDB was a very clear choice for us. From a professional standpoint, as an early-stage startup, you don’t know what your product will eventually turn into, right? How will it evolve in the next six months or a year? So it’s difficult to stick to a schema. Therefore, you need a lot of flexibility. Because of our need for flexibility, SQL was out of the question, so we needed to go with NoSQL. Once we decided on NoSQL, MongoDB became the obvious choice because of the community support and documentation. As a founder, I believe in really fast execution and putting your product out there, rather than waiting for a pitch-perfect product. And that demands a lot of flexibility from the business, product, and tech sides, because we need to be able to make immediate changes based on the features that are demanded and that catch the users’ attention. With MongoDB, we are able to try a lot of product variations or tweaks very quickly. MongoDB: As you've scaled, is there a particular MongoDB feature you've benefited the most from? Pritesh: There are a few features of MongoDB Atlas that have benefitted us a lot. One is the performance metrics. It’s really really amazing, actually. You can get a very clear picture of the state of your database in a single snapshot. It helps you buy time to focus on shipping your core product and the technology behind it. It removes your focus on database management and cluster management and just does it for you right out of the box. Also, Atlas handles all of the sharding and scaling. And something that I didn’t foresee but found very useful is its scalability. Startups tend to start at a scale where the free version of any cloud product would be good enough, right? But then you quickly move into a very different kind of need and scale. It just keeps on changing! Atlas gives us that flexibility to scale up really quickly with a very minimal amount of effort. MongoDB: Have you used any of the MongoDB for Startups services? Pritesh: Yes! We had a session with a technical advisor. I found it really helpful for addressing the key features we are launching in the future, and the main challenges we are going to face when building them. I was able to discuss those and was very satisfied. The session was really good for us. MongoDB: Who is the most well-known celebrity to have hosted a game so far on FanPlay? Pritesh: The comedian Kumar Varun ! MongoDB: Who is your favorite TV or game show host? Pritesh: Amitabh Bachchan , who is a household name in India for his acting and for his role as host of Kaun Banega Crorepati (India’s Who Wants To Be A Millionaire). MongoDB: What is your favorite podcast or blog? Pritesh: The InfoQ Podcast . It goes deep into how organizations build challenging tech products. Looking to build something cool? Get started with the MongoDB for Startups program.