Sahir Azam

8 results

Introducing the MongoDB 5.1 Rapid Release

Arriving just a few months after the General Availability of 5.0, MongoDB 5.1 is our first Rapid Release which brings more native time series enhancements, richer analytics, new security options, and overall improvements to platform resilience and developer productivity. Launching alongside MongoDB 5.1 are new capabilities in Atlas Search which will make it easier for users to build fast and rich application search experiences. MongoDB 5.1 marks our accelerated release cadence designed to get new database features and improvements into your hands faster than ever before. MongoDB 5.1 and all future rapid releases will be fully supported on MongoDB Atlas and are available as development releases from our Download Center. Native Time Series Enhancements With optimized time series collections, clustered indexes, and window functions, MongoDB 5.0 made it faster, easier, and lower cost to serve the industry’s fastest growing, data intensive use cases such as IoT platforms and real-time financial analytics. Now with MongoDB 5.1, you can globally distribute your time series applications and further simplify their development: More developer velocity Time series collections can now take advantage of MongoDB’s native sharding to horizontally distribute massive data sets and co-locate nodes with data producers to support local write operations and to enforce the data sovereignty controls. It is common for time series data to be uneven, for example a sensor goes offline and several readings are missed. But in order to perform analytics and ensure correctness of results data needs to be continuous. With densification you can now handle missing data better and build time series apps and analytics faster putting less burden on the developer. Time series collections now also support delete operations . While most time series applications are append-only, users need to be able to invoke their right to erasure so we are giving developers an easy way to comply with modern data privacy regulations. Complete data lifecycle From medical sensors to market data fluctuations, time series means hundreds of millions data points per day. You need to process these massive volumes fast, distill valuable insights then continue to retain the full data set for regulatory purposes - possibly for years - all without incurring skyrocketing costs and data movement complexity. With Atlas Online Archive support for time series, now available in preview, you can do exactly that and seamlessly and economically manage your entire time series data lifecycle. Simply define your own archiving policy, and Atlas handles all data movement for you by tiering aged time series data out of your database into lower cost, fully managed cloud object storage. Rather than delete anything, you can retain all your time series data, preserving the ability to query it at any time alongside your live data for long term trend analytics and machine learning, or for compliance purposes. Support for online archiving is available for MongoDB 5.0 and above. Broader platform support for Time Series Data Our native time series capabilities are supported across the entire MongoDB data platform making it easy to work with time series data in any context. You can now create time series collections directly from Atlas Data Explorer, MongoDB Compass or MongoDB for VS Code. With support for date binning, date filtering options, and value comparison, Atlas Charts lets you create graphs and dashboards from any Atlas times series collection, easily share insights, and embed visualizations into your applications for a rich user experience. Richer and More Flexible Analytics and Full-Text Search Many developers start out with MongoDB for their operational use cases, and then expand to leverage our platform's versatility in powering analytics and search as well. MongoDB 5.1 includes new features and enhancements that make it easier to unlock insights from your data and improve user experience. Cross-shard joins and graph traversals For most transactional and operational workloads, the document data model largely eliminates the need to join data from different collections. This is because related data can be embedded in sub-documents and arrays within a single, richly structured document – following the principle that what is accessed together is often best stored together. However analytical applications can sometimes require joins to be executed – for example bringing together customers and orders from separate collections. Through the $lookup aggregation pipeline stage, you can have the database join collections for you. The $graphLookup stage gives you the ability to traverse related data, performing “friend-of-friend” type queries to uncover patterns and surface previously unidentified connections in your data. In MongoDB 5.1 we now allow you to use $lookup and $graphLookup to combine and analyze data that is distributed across shards which was not previously possible. Our design gives you even more precision in your code by enabling you to target individual shards as needed. However you don’t need to understand sharding or even know your collection is sharded to run these queries as there is no new syntax for developers to learn. Materializing results for operational analytics The $merge and $out aggregation stages can be used to write the results of an aggregation pipeline in order to create a new collection or create/update an on-demand materialized view . These stages enable users to reduce processing overhead by reading pre-computed results instead of re-running the aggregation each time, and by writing only incremental results when the aggregation results change. Users often want to run resource-intensive analytical queries on secondary nodes in order to avoid performance impacts on the primary — but since only primaries can serve writes, aggregations including $out or $merge could not previously run on a secondary node. Soon, such pipelines will run, performing their query execution work on a secondary node, then automatically directing any writes to the primary. This allows you to offload computationally expensive analytics work to secondary nodes while still being able to materialize the results of that work. This will be accessible via drivers in their upcoming releases. Full-Text Search Facets: now in public preview Faceted search allows users to filter and quickly navigate search results by categories and see the total number of results per category for at-a-glance statistics. With our new facet operator , facet and count operations are pushed down into Atlas Search’s embedded Lucene index and processed locally, taking advantage of 20+ years of Lucene optimizations. This makes workloads such as ecommerce product catalogs, content libraries, and counts run up to 100x faster . Learn more from our Atlas Search facets blog post . New and Enhanced Security Options End-to-end encryption for confidential computing Extending beyond cloud provider Key Management Services (KMS), MongoDB’s unique Client-Side Field Level Encryption will support any KMIP-compliant KMS . This functionality is being released in new versions of drivers that will be available soon. Client-Side FLE delivers some of the strongest privacy and security controls available anywhere today. By using the MongoDB drivers to encrypt the most sensitive fields in your documents before they leave the application you can do three things that are not possible with in-flight or at-rest encryption alone: Protect data while it is in-use, in the memory of your active database instance. The database never sees plaintext, but data remains queryable. Make data unreadable to anyone running the database for you, or who has access to the underlying database infrastructure — this includes MongoDB SREs running the Atlas services as well as cloud provider personnel. Simplify the process of enforcing right to erasure (sometimes called right to be forgotten) mandates in modern privacy regulations such as the GDPR or the CCPA. This is because you simply destroy the key encrypting a user’s PII, and their data is rendered unreadable and unrecoverable — in-memory, at-rest, in backups, and in logs. Google Cloud Private Service Connect We’ve also added a new network security option to MongoDB Atlas with the availability of Google Private Service Connect (PSC). Private Service Connect allows you to create private and secure connections from your Google Cloud networks to MongoDB Atlas. It creates service endpoints in your VPCs that provide private connectivity and policy enforcement, allowing you to easily control network security in one place. Along with VPC Peering, Google Cloud PSC makes it easy to connect your applications and services in Google Cloud to Atlas. Platform Resilience MongoDB 5.1 continues to build out controls for reliability and availability with the following enhancements: We've made a number of changes to WiredTiger internals that improve backups, including minimizing the checkpoints pinned while a backup cursor is open and improving handling of backup cursors that are open for long periods. These improvements will reduce both the operational overhead and storage consumption on the replica node from which the backup is taken. This improvement is available for backups taken from MongoDB Atlas and from self-hosted deployments controlled by Ops Manager or Cloud Manager, and has been backported to MongoDB 4.2 and above. In addition to enhancements affecting backups, WiredTiger checkpointing and locking have been improved to enhance performance when MongoDB is managing many concurrently active collections in a single instance. This is especially useful to multi-tenant applications built on MongoDB. We'll also be adding improvements in upcoming versions of our drivers that support mongos controls to mitigate connection storms in sharded clusters, especially during failover events. These include preferentially connecting to nodes that have existing idle connections that can be reused, improving the matching of connection pool sizing across replica set members, limiting the rate of new connections, and adding a mechanism to limit the number of mongos servers used when connecting to sharded clusters via SRV records. Improved Productivity for C# Developers Making it easier for developers to query and manipulate data is at the core of our mission. For C# developers the LINQ API serves as the main gateway between the language and database. In MongoDB 5.1 we are improving developer productivity for our C# community with a completely redesigned LINQ interface that lets developers write all of their MongoDB queries as well as build sophisticated aggregation pipelines natively in C#. Getting Started with MongoDB 5.1 You can learn more about all of the new features and enhancements in MongoDB 5.0 and 5.1 from our Guide to What’s New . MongoDB 5.1 is available now. If you are running Atlas Serverless instances or have opted in to receive Rapid Releases in your dedicated Atlas cluster, then your deployment will be automatically updated to 5.1 starting today. For a short period after upgrade, the Feature Compatibility Version (FCV) will be set to 5.0; certain 5.1 features will not be available until we increment the FCV. MongoDB 5.1 is also available as a Development Release for evaluation purposes only from the MongoDB Download Center. Consistent with our new release cadence announced last year, the functionality available in 5.1 and the subsequent Rapid Releases will all roll up into MongoDB 6.0, our next Major Release scheduled for delivery in 2022. I really look forward to hearing what you think about MongoDB 5.1, and can’t wait to tell you what’s new in the 5.2 Rapid Release scheduled for next quarter. Safe Harbour Statement The development, release, and timing of any features or functionality described for our products remains at our sole discretion. This information is merely intended to outline our general product direction and it should not be relied on in making a purchasing decision nor is this a commitment, promise or legal obligation to deliver any material, code, or functionality.

November 9, 2021

Re-Imagining What A Cloud-Native Database Can Be

COVID-19 has compelled companies of all sizes and industries to reinvent themselves. From the way they work to the way they interact with customers, the pandemic has forced an urgent shift to a digital-by-default customer experience and, as a result, has accelerated the move to the cloud. But as companies make the move, many are finding that the same data silos and operational complexity that thwarted innovation for decades is simply following them into the cloud. Developers responsible for building today’s apps have to work with a patchwork of technologies, data models, APIs, and languages across disparate systems to deliver the right data at the right time to power critical applications and services. To better serve these developers, we’ve expanded our capabilities outside of the core database into a robust data platform we call MongoDB Cloud . At its core is MongoDB Atlas, our fully managed global cloud database, which enables your developer teams to spend less time on undifferentiated work and more time writing code that adds business value. By adding capabilities such as Atlas Search , Atlas Data Lake , MongoDB Charts and MongoDB Realm , which provide a consistent experience for working with data in different ways, you’re drastically reducing the cognitive burden on development teams. Simply put, MongoDB Cloud allows you to easily deploy, manage, and scale data architectures designed to support the converging requirements of transactional and analytical systems within a single elegant platform. Any cloud, anywhere, anytime The pandemic has put a spotlight on resilience and agility and showcased the importance a data platform can have for your business. This has not only accelerated the migration to the public cloud, but also the move to multi-cloud environments. Many of our customers rely on more than one cloud provider, and 55 percent of organizations currently report using multiple public clouds . That’s why we designed our offerings to have the same great developer experience regardless of which cloud provider or providers you use. Since launching in 2016, MongoDB Atlas has always pushed the boundaries of what’s possible in cloud data management, with customers able to deploy their data from more than 75 regions worldwide across AWS, Azure, and Google Cloud. And with the recent launch of multi-cloud clusters on MongoDB Atlas, we’ve recast the cloud and development experience again. With this first-of-a-kind capability, companies gain the ability to distribute their data in a single cluster across multiple public clouds simultaneously, or move workloads seamlessly between them. This is true data portability, enabling the freedom and flexibility to use best-of-breed services across multiple platforms, and ensuring cross-cloud resiliency. But we’re not standing still. Introducing Online Archive on MongoDB Atlas Today, we are announcing more innovations that unleash the full potential of business data, beginning with the general availability (GA) of Online Archive for MongoDB Atlas. With Online Archive, you can seamlessly tier your data across fully managed databases and cloud object storage, all while retaining the ability to query it through a single endpoint. Users can create a rule to automatically archive infrequently accessed data in their MongoDB Atlas clusters onto their object store, eliminating operational complexity and transactional data storage costs. All users on dedicated clusters (M10+) can use Online Archive regardless of which cloud provider they are using to run Atlas. If you want to learn more or see if Online Archive could help your organization, watch our deep-dive technical session , which is available on demand and features a live Q&A on Wednesday, Dec. 2 from 3:30-4pm ET. Online Archive gives me the flexibility to store all of my data without inucrring high costs, and feel safe that I won't lose it all. It's the perfect solution. Ran Landau, CTO, Splitit The power of choice Empowered developer teams around the world turn to MongoDB Atlas on their preferred cloud to deliver mission-critical services to their businesses faster. Here are a few customer success stories that are near and dear to our hearts: Ludo King : The small but mighty team of developers behind India’s favorite mobile game, Ludo King, turned to MongoDB Atlas and MongoDB Realm on AWS. The results? They’ve been able to keep building new, revenue-generating features for the game’s half a billion players, while efficiently managing near instantaneous 1000% growth. Toyota Materials Handling Europe : While building the connected warehouses of the future, Toyota Material Handling needed a database as flexible and powerful as MongoDB Atlas, running on Azure, to break down their monolith and transition to a microservices architecture. Boxed : Grocery delivery wholesaler Boxed built its platform on MongoDB Atlas on Google Cloud to accommodate the soaring demand for goods and services due to the pandemic. As brick-and-mortar retailers struggled to keep up with demand, Boxed saw a 30x spike in demand, which they were able to handle because of MongoDB’s powerful data platform. Get started with MongoDB Atlas today. And make sure you take advantage of all the opportunities to explore MongoDB at AWS re:Invent 2020 .

November 30, 2020

Introducing Multi-Cloud Clusters on MongoDB Atlas

One of the core pillars of MongoDB is the freedom to run anywhere. Since 2017, organizations have been able to use MongoDB Atlas , our fully managed global cloud database, across 70+ regions on the cloud provider of their choice: AWS, Azure, or Google Cloud. We’re increasingly seeing customers run independent workloads on different clouds — a common practice among enterprises with different applications and business units. However, we believe the real power of multi-cloud applications is yet to be realized in our industry. So today, I’m proud to announce that multi-cloud clusters are generally available on MongoDB Atlas! With this groundbreaking capability, customers can distribute their data in a single cluster across multiple public clouds simultaneously, or move workloads seamlessly between them. Data — traditionally the hardest piece of an application stack to move — is now the easiest. A New Multi-Cloud Paradigm More organizations are moving towards a multi-cloud model , and they want the freedom and flexibility to use the best of each cloud provider for any and every application. The question is how engineering teams can do this efficiently and deliberately while dealing with challenges such as incompatible operations and the effects of data gravity . Read our eBook, Why the World is Going Multi-Cloud , for a high-level guide to today's fast-emerging cloud architecture. Download Now With multi-cloud clusters on MongoDB Atlas, customers can realize the benefits of a multi-cloud strategy with true data portability and a simplified management experience. Developers no longer have to deal with manual data replication, and businesses can focus their technical resources on building differentiated software. This opens up a whole new set of possibilities that were previously difficult ― if not impossible ― to achieve, from being able to use best-of-breed services across multiple platforms to data mobility and cross-cloud resiliency. Use best-in-class technology across multiple clouds in parallel Developer productivity is critical to a company’s success, and CTOs know that enabling their teams to choose the best technology available is a major contributing factor. With MongoDB Atlas, developers get more freedom in deciding what building blocks to use, regardless of which cloud is storing application data. Some examples of popular cloud services that our customers like to use include AWS Lambda , Google Cloud AI Platform , and Azure Cognitive Services. With multi-cloud clusters, developers can now run operational and analytical workloads using different cloud tools on the same dataset, with no manual data replication required. Migrate workloads across cloud environments seamlessly Data mobility is another reason companies want a multi-cloud strategy. The world is constantly changing, and businesses never know if, or how, their cloud requirements are going to change. They may face mergers and acquisitions, be subject to new regulatory controls for data portability, find themselves in direct competition with a cloud provider, or find significant cost savings on another platform. With MongoDB Atlas, organizations can future-proof their applications and have the option to move them from one cloud to another if needed, without undergoing a costly data migration. Our built-in automation seamlessly handles cross-cloud data replication on a rolling basis so applications stay online and available to end-users. Improve high availability with cross-cloud redundancy Any business with a mission-critical or user-facing application knows that downtime is unacceptable. Cloud disruptions vary in severity, from temporary capacity constraints to full-blown outages, and organizations need to mitigate as much risk as possible. By distributing data across multiple clouds, they can improve high availability and application resiliency without sacrificing latency. MongoDB Atlas extends the number of locations available by allowing users to choose from any of the nearly 80 regions available (with more coming) across AWS, Azure, and Google Cloud — the widest selection of any cloud database on the market. This is particularly relevant for businesses that must comply with data sovereignty requirements , but have limited deployment options due to sparse regional coverage on their primary cloud provider. In some cases, only one in-country region is available, leaving users especially vulnerable to disruptions in cloud service. For example, AWS and Google Cloud each offer only one region in Canada. With multi-cloud clusters, organizations can take advantage of both regions, and add additional nodes in the Azure Toronto and Quebec City regions for extra fault tolerance. With MongoDB Atlas, customers no longer need to make a trade-off between availability and compliance. Reach more users with flexible deployment options In order to deliver a world-class application experience, organizations must at a minimum meet end-user requirements for their products and services. For SaaS providers and B2C businesses, this may include cloud provider preferences or regional availability. While each of the cloud providers offer a large and growing list of regions globally, their data centers are still heavily concentrated in the USA, Europe, and eastern Asia. If multinational enterprises want to reach local users in other areas, they may not always find coverage on a single cloud. For example, AWS is the only provider to offer a cloud region in Bahrain, Azure Oslo is the only option in Norway, and only Google Cloud has data centers in Indonesia. To capture more global market share, companies may need a multi-cloud strategy to meet customers where they are. An Integrated, More Secure Cloud Data Platform MongoDB has consistently delivered innovations in the data management experience, including automated data tiering with Atlas Online Archive , integrated full-text search with Atlas Search , and Client-Side Field Level Encryption (FLE) for some of the strongest levels of data privacy available today. Client-Side FLE currently works with AWS Key Management Service (KMS), and will soon offer beta support for Azure Key Vault and Google Cloud KMS. With this expansion, it will be easier for organizations to further enhance the privacy and security of sensitive and regulated workloads across all major public cloud platforms. Read our guide to learn more about how Client-Side Field Level Encryption protects data in MongoDB. Download Now Multi-Cloud Data Management Made Easy Multi-cloud distribution can be enabled for both new and existing clusters starting today via the Atlas UI. Multi-cloud clusters come with all the features that our customers know and love, including built-in security defaults , fully managed backup and restores , automated patches and upgrades , intelligent performance advice , and more. While multi-cloud clusters are generally available, we are planning on releasing more capabilities in the coming months to deliver even more value to you. Whether you’re a startup just getting off the ground or a global enterprise in the midst of a multi-year cloud transformation initiative, our multi-cloud database solution abstracts away the toughest roadblock to unlocking your multi-cloud strategy. When your data can travel across clouds, there’s no limit to what you can build. Let us know where multi-cloud clusters on MongoDB Atlas take you - or tell us what you need to get there .

October 20, 2020

Announcing MongoDB 4.4 and MongoDB Cloud

Today at, we’re announcing a number of new products and services that expand what you can do with MongoDB. Join the event (free and entirely virtual) to learn more, or read about the news on our announcements page . At MongoDB, our mission is to free the genius within everyone by making data stunningly easy to work with. For many years, that’s meant building a database with an intuitive and flexible document model, plus a distributed systems architecture for resilience and horizontal scale-out. Of course, the modern data architecture isn’t limited to only the transactional database. Many applications also require analytics and search functionality, which often requires teams to learn, deploy, and manage additional systems. If you’re building mobile apps, you’ll need to deal with data on the device and syncing it to the backend. You may also find yourself building data visualizations, writing a lot of glue code to move data between data services, or creating and operating custom data access APIs. We want to make all of that easier. Today, alongside a new version of MongoDB and improvements to MongoDB Atlas, we’re announcing new products that go beyond the database and deliver a consistent experience for developers, wherever data resides. These are all part of MongoDB Cloud , a unified data platform for modern applications. MongoDB 4.4 MongoDB 4.4 , the latest version of the database, is now available in beta; you can try it out in MongoDB Atlas or download the development release. We think of MongoDB 4.4 as “user-driven engineering”, delivering a number of the features and improvements that have been most requested by the MongoDB community. Headline features of MongoDB 4.4 include: Aggregation enhancements: use the new Union stage to combine data from multiple collections into a single result set, define your own Custom Aggregation Expressions, and use new operators for array handling, string manipulation, and more. Refinable shard keys: as you scale, modify data distribution by adding suffixes to your shard key. Hedged reads: submit read requests to multiple replicas returning results from the fastest node. Mirrored reads: mirror a configurable subset of reads to secondaries, keeping their caches warm . The latest release also includes other features such as compound hashed shard keys, resumable initial sync, streaming replication, global read and write concerns, and more. To learn more about what’s coming, read our guide to what’s new in MongoDB 4.4 . MongoDB Cloud The best way to use MongoDB is with MongoDB Atlas , our fully-managed global cloud database. Atlas now makes it even easier to manage and optimize MongoDB with new functionality that allows you to run the database on auto-pilot: Atlas Auto-Scale , previously beta, is now Generally Available: Atlas monitors metrics in real time and adjusts cluster compute and storage to meet the needs of your workload. Atlas will now proactively give you advice on how to model your data for the best performance. Schema suggestions , available in both the Atlas Performance Advisor and Data Explorer , use database metadata and logs to flag common anti-patterns when working with the document data model. This includes having documents that are too large, having too many collections or indexes, using unbounded arrays, and more. Atlas is the core of MongoDB Cloud, a unified data platform for modern applications. MongoDB Cloud provides a data foundation, unifying different data services with a common developer experience from cloud to edge. We’re excited to launch many of these data services today. Atlas Search , now GA, is built into Atlas. Instead of deploying a separate search technology and coordinating data synchronization with your transactional database, you can create search indexes right in Atlas and access them with the same MongoDB aggregation framework you’re already familiar with. Atlas Data Lake , also generally available today, helps realize the value of your data lake faster by querying data in any format on Amazon S3 using the MongoDB Query Language (MQL). You can query your existing S3 data or even enable automated tiering of data between the Atlas Cloud Database and Data Lake. Atlas Online Archive , available today in beta, automatically moves older data into Data Lake while preserving query access across both tiers with federated queries. This data foundation reaches to the edge with the Realm Mobile Database , compatible with both iOS and Android. Mobile apps need local access to data, and Realm makes it happen without taking up too much space or draining your battery. Realm Sync , available in beta, automates the process of syncing bi-directionally with a backend Atlas cluster, with built-in conflict resolution. Beyond the data foundation, MongoDB Cloud offers application services that simplify building apps with MongoDB. MongoDB Realm’s application development services include serverless functions, which execute application logic based on real-time database changes or on a schedule, and a GraphQL Service that makes it easy to expose a GraphQL API for MongoDB Atlas. MongoDB Charts is the best way to build visualizations of MongoDB data and now makes accessing and sharing those visualizations even easier, whether directly or a part of an application. The new embedding SDK makes it easier to build charts into your applications and control them directly from application code. Dashboard filtering lets users define a data filter to be applied across all charts on a dashboard, customizing it according to their needs; each user of a shared dashboard can have a different, personalized filter. Dashboards can now also optionally be shared with a public link, giving view-only access to unauthenticated users. Tools and Integrations We’ve also announced a number of tools and integrations that make working with the database easier. A new MongoDB shell is now available in beta, and improves on the existing shell with autocomplete, syntax highlighting, contextual help messages, and more. You can also work with MongoDB in your IDE of choice with new integrations for VS Code and Jetbrains products. A new CLI for MongoDB Cloud adds an easily scriptable way of provisioning and controlling cloud resources. Alongside the UI and the API, you can now manage your cloud environments from your command line. If you’re managing MongoDB yourself, two new Kubernetes announcements make the process easier. If you’re an Enterprise customer using our Enterprise Kubernetes Operator with Ops Manager, you’re now able to run Ops Manager itself in Kubernetes , simplifying the setup process. If you’re using the community version of MongoDB, a new MongoDB Community Kubernetes Operator enables you to deploy simple containerized MongoDB clusters. Two new GA drivers expand our language support . The Rust driver , previously available in alpha, is now generally available, supporting this fast-growing language. Expanding the mobile development capabilities we bring with MongoDB Realm, we’re also announcing a new driver for Swift . Get Building in the Cloud We’re very excited about everything we’ve announced today. If you are too, you can get started with some of the new functionality by creating a free MongoDB Atlas account in minutes. We can't wait to see what you build! Safe Harbor Statement The development, release, and timing of any features or functionality described for MongoDB products remains at MongoDB's sole discretion. This information is merely intended to outline our general product direction and it should not be relied on in making a purchasing decision nor is this a commitment, promise or legal obligation to deliver any material, code, or functionality. Except as required by law, we undertake no obligation to update any forward-looking statements to reflect events or circumstances after the date of such statements.

June 9, 2020

New to MongoDB Atlas: Performance Advisor, Auto-Expand Storage Capacity, Teams

MongoDB Atlas includes a set of monitoring capabilities that give your teams complete visibility into the performance of your databases, allowing you to anticipate issues and proactively take the necessary steps to ensure an optimal experience for your end customers. Important historical metrics are automatically highlighted in optimized dashboards. It’s easy to create and customize alerts that ping the endpoints you want when key metrics go out of range. You can also see what’s happening in your cluster as it happens with the real-time performance panel, which displays memory usage, network I/O, operations in flight, the hottest collections, and the slowest operations. This panel even allows you to kill slow-running operations with just a few clicks. Real-time performance panel Automated index suggestions with the new Performance Advisor But what if instead of killing off those operations, you wanted a quick and easy way to see how to improve their runtime? That’s now easy with the new Performance Advisor, available for all dedicated MongoDB Atlas deployments. The Performance Advisor shows the different collections in your database that are experiencing suboptimal performance. Click on a specific collection and it will display existing indexes, examples of slow-running queries and relevant metrics, and most importantly, automatically generated index suggestions to help improve their performance. New Performance Advisor, available for all dedicated MongoDB Atlas deployments This new feature runs in the background with no impact to your existing deployments and ensures that you’re getting the most performance out of MongoDB with the resources you’ve provisioned. Automatically expanding storage capacity When you do need additional resources, MongoDB Atlas now makes that process easier to manage with automatic scaling for storage capacity. Enabled by default for all dedicated clusters (M10 instance size and above), auto-scaling for storage detects when your disks hit 90% utilization and provisions additional storage such that your cluster reaches a disk utilization of 70% on AWS & GCP, or a maximum of 70% utilization on Azure. This automated process occurs without impact to your database or application availability. Simplified user management with Teams MongoDB Atlas makes it easy to manage your database footprint with a simple hierarchy optimized for organizations made up of multiple business units. Projects contain MongoDB clusters; clusters in a project do not necessarily have to be in the same region. Organizations are made up of different projects that share the same billing settings. And today, we’re introducing teams , which will help simplify database user management. All users in a team will share the same access to a project . Teams can have access to multiple projects and users can belong to multiple teams . Changelog New disk size options for customers running on Microsoft Azure. 32GB, 64GB, 256GB, 512GB, 2TB, and 4TB disk sizes are now available. Free tier is now also available in AWS Frankfurt (EU-Central-1) Have feedback about a new feature or MongoDB Atlas? As always, we’d love to hear it at . Not an Atlas user yet? Get started with a 512MB database for free.

October 31, 2017

New to MongoDB Atlas: More Azure Regions, Monitoring Metrics via the API, Cross-Project Restores, Test Failover

Earlier this year, we announced the availability of our cloud database service, MongoDB Atlas, with global support for Amazon Web Services, Microsoft Azure and Google Cloud Platform. And since then, we’ve been humbled by the overwhelming reception from the global community of MongoDB users. Customers like Ticketek — Australia’s largest ticketing company in sports and entertainment — which now uses MongoDB Atlas to support the core transactional systems needed to power their multi-channel ticket sales and distribution network. “Everyone knows Ticketek from an A/NZ perspective, but we’re also delivering tickets in the US and UK and we recently bought the largest ticketing company in Malaysia,” explained Matt Cudworth, CTO of TEG, Ticketek’s parent company, in an interview with . “Atlas became an obvious choice for us to be able to deliver [services] in most regions. We can use different cloud providers, and you can’t go past [a managed service by] the vendor that makes the software. There’s no better expert in that technology.” More Atlas Regions on Microsoft Azure Today, we’re excited to announce that MongoDB Atlas now supports 23 Azure regions across the world. This will grant the increasing number of MongoDB users looking for a cloud database service global low latency connectivity and the ability to meet data sovereignty requirements. New MongoDB Atlas regions on Microsoft Azure You can now deploy clusters with MongoDB Atlas in 41 regions across AWS, Azure, and GCP. Log in to your account to see the full region list. New MongoDB Atlas Features We’ve also been working on adding features based on user feedback. Here are just a few quick highlights: Support for monitoring metrics and logs via Atlas API You can now obtain fine-grained monitoring metrics on database processes and the underlying instances via the MongoDB Atlas API . In addition, the API will allow you to retrieve log files for a particular host. Cross-project restores You can now perform backup restores into a different Project (formerly Group) than the backup snapshot source. This allows you to easily execute tasks such as creating multiple staging or test environments that match recent production data with different user access privileges or in different regions. Test failover / “Chaos” button Modern cloud applications should be designed for high availability despite instance failures. With the new “Test Failover” button — available for all dedicated clusters — MongoDB Atlas will trigger a replica set failover and subsequent election, helping you test redundancy and ensure that your application connection handling is resilient. All of these new features are now live in MongoDB Atlas. As always, we’d love to hear your feedback at . Not an Atlas user yet? Get started with a 512MB database for free.

September 14, 2017

New — Live Migrations, More AWS Regions, Queryable Backups & More in MongoDB Atlas

Last month we announced the Free Tier in MongoDB Atlas and the availability of MongoMirror, a downloadable utility that makes migrating live MongoDB replica sets easy. We’ve since incorporated the same live migration functionality into MongoDB Atlas, our database as a service, and updated the platform with some new features. Live Migration Live migration allows us to automate the import of any pre-existing MongoDB 3.0+ replica set into MongoDB Atlas. It works by performing an initial sync between a source database and a target database in Atlas, and then tailing the source oplog to keep the database in Atlas in sync with live updates from your application. To use live migration, we’ll first need to create a dedicated (M10 or above) Atlas cluster. In the example below, we’ve created a cluster with M30-size instances in US-EAST-1. You can see from the screenshot below that we now have a new option, “Migrate Data to this Cluster”. We’ll need the following for the migration: Hostname: Port of the primary of our source replica set Username/password (if authentication is enabled) CAFile (if running MongoDB with SSL enabled and the --sslCAFile option) Once we have this information, we’re ready to select “I’M READY TO MIGRATE”. We’ll then be brought to a new window that asks for the location of our source replica set and credentials. The “VALIDATE” button at the bottom of the window checks to make sure that MongoDB Atlas can tail our source oplog to make sure that new operations are captured. Clicking the “START MIGRATION” button kicks it off. We’ll get an email notification when it’s time to cut over to MongoDB Atlas; all we have to do to finalize the migration process is modify the database connection string in our app. For a more detailed walkthrough of Live Migration in MongoDB Atlas, click here . Now in (almost) all AWS regions MongoDB Atlas is now available in most AWS regions, which means users around the world can leverage the database service with minimal geographical latency. As a reminder, MongoDB Atlas’ support for VPC Peering means teams can easily and securely connect their own VPCs to a new Atlas cluster in one of the new regions. AWS Regions (Americas) AWS Regions (APAC) AWS Regions (EMEA) us-east-1 (N. Virginia) ap-southeast-2 (Sydney) eu-west-1 (Dublin) <tr> <td>us-west-2 (Oregon)</td> <td>ap-southeast-1 (Singapore)</td> <td>eu-west-2 (London)</td> </tr> <tr> <td>us-east-2 (Ohio)</td> <td>ap-northeast-1 (Tokyo)</td> <td>eu-central-1 (Frankfurt)</td> </tr> <tr> <td>us-west-1 (N. California)</td> <td>ap-northeast-2 (Seoul)</td> </tr> <tr> <td>ca-central-1 (Canada)</td> <td>ap-south-1 (Mumbai)</td> </tr> <tr> <td>sa-east-1 (São Paulo)</td> </tr> Queryable backup snapshots Also new in MongoDB Atlas is the ability to query backup snapshots and restore data at the document level in minutes. No longer do we need to restore an entire cluster when all we really need is a small subset of our data. Within the Atlas UI, we can now select a backup snapshot and click on the new “Query” option. We can opt to use a downloadable Backup Tunnel, which handles the security for connecting to our backup instance, and use the mongo shell or a MongoDB driver to connect to our backup via the tunnel. For a walkthrough of using queryable backups in Atlas, click here . Explore your databases from the Atlas UI Finally, the new Data Explorer in MongoDB Atlas allows us run queries, view metadata about our databases and collections, and see index usage statistics without resorting to the mongo shell. We can access the Data Explorer for dedicated Atlas clusters by selecting the new “DATA” button associated with our databases. This will bring us to a new view, shown below. All of these new features are now live in MongoDB Atlas . As always, we’d love to hear your feedback at ! Discuss on Hacker News Get started on the Atlas free tier

April 18, 2017