Ashley Kuhwilm

9 results

Introducing Auto-Index Creation for Atlas Serverless Instances

Atlas serverless instances now offer auto-index creation, a new capability that automatically generates indexes to help optimize performance and reduce the cost of your queries. Auto-index creation is now available in public preview and enabled by default for all serverless instance deployments - allowing developers to worry less about needing to manually optimize their serverless database. Simplify development with Atlas serverless instances Developers love serverless technology primarily because of its unparalleled ease of use. By abstracting away infrastructure management, serverless allows developers to focus on what they do best: writing code and building amazing applications. It’s expected that any great serverless offering just works out of the box, without a large learning curve or emphasis on implementation and setup. Atlas serverless instances, first announced as generally available in June 2022, deliver on this promise by allowing you to deploy a database that seamlessly scales with demand in seconds with minimal configuration and a consumption-based pricing model that only charges for what you use. The addition of auto-index creation now further reduces management overhead by automating index creation for common queries to ensure fast response time. How auto-indexing works Indexes are special data structures that store a small portion of the collection's data set in an easy-to-traverse form. Without indexes, MongoDB must perform a collection scan—i.e., scan every document in a collection—to select those documents that match the query statement. By adding an index to appropriate queries, you can dramatically reduce the number of documents the query engine must inspect in order to return a result and in turn benefit from improved query performance and a reduction in the read operations you are charged for. With auto-index creation enabled, Atlas will analyze your recent query workload and automatically create high-impact indexes based on index suggestions in the Performance Advisor . This helps promote good index hygiene for your data by creating high-impact indexes without requiring you to regularly check for suggestions or create indexes manually. You can view newly created indexes in the Atlas UI in the Collections tab of the Data Explorer. You can also continue to manually add additional indexes in the Collections tab or via the Performance Advisor at any time. To learn more about auto-index creation, visit our documentation . Create a serverless instance in Atlas today.

December 18, 2023

View and Analyze Your Monthly MongoDB Atlas Usage with Cost Explorer

In today's macroeconomic climate, knowing where your money's going is a big deal. From optimizing costs to boosting efficiency, understanding your software expenses can be a total game-changer for your business. That’s why we’re excited to announce the release of Cost Explorer in MongoDB Atlas. Cost Explorer is a new visual interface available in the Billing section of the Atlas UI that is meant to help you view and analyze your monthly MongoDB Atlas usage in one convenient location. How can Cost Explorer help you? Cost Explorer allows you to easily filter your Atlas usage data by what’s most important to you and your business, with filters to segment your view by organization (if you have cross-org billing enabled), projects, clusters, or services, within a time window of up to 18 months. With Cost Explorer, you can now quickly pinpoint trends or outliers in your month-over-month usage to identify opportunities to potentially improve or optimize your Atlas usage going forward. If you’re looking for additional customization beyond what is available in Cost Explorer, you can also create your own billing dashboards in Atlas Charts that are fully tailored to your needs. Cost Explorer is viewable for any Atlas user assigned the Organization Owner, Billing Admin, or Organization Billing Viewer roles. To learn more about Cost Explore and how to manage your Atlas billing, view our documentation on managing billing .

September 13, 2023

Understanding the Costs of Serverless Architecture: Will it Save You Money?

As the digital landscape evolves, developers are constantly on the lookout for innovative ways to optimize their applications and deliver seamless user experiences. One approach that has gained popularity over the years is serverless architecture. By abstracting away server management and scaling concerns, serverless promises increased development efficiency, reduced operational overhead, and potential cost savings. However, before diving headfirst into this paradigm shift, it's crucial to understand the tradeoffs and costs associated with serverless architecture to know if it’s the right fit for your use case and budget requirements. What is serverless architecture? Let's first briefly review what serverless architecture entails. In traditional setups, developers manage servers, infrastructure provisioning, and scaling. By contrast, serverless architecture allows developers to focus solely on the business logic for their applications without worrying about the underlying infrastructure. Instead, the service providers handle the server provisioning and scaling dynamically based on the application's demand. There are a variety of technologies and services that now fit the serverless model, including function-as-a-service (FaaS), API gateways, object storage, and even databases. Understanding the cost model of serverless When it comes to pricing, serverless solutions follow a usage-based pricing model where you “only pay for what you use”. This means, instead of fixed monthly fees for maintaining servers, you only pay for the actual computing resources used during the execution of your code. The primary cost factors for serverless solutions can vary slightly by service but they all typically meter on some form of the following: Compute resources: The compute needed to execute and service your application workload. Memory or storage allocation: The amount of memory allocated or overall data size being stored. Data transfer: The data is transferred in and out. Cost comparison: Serverless vs. provisioned infrastructure To determine whether serverless will save you money, you must evaluate your application's specific requirements and usage patterns. Serverless architecture can be cost-effective in certain scenarios, but it might not be the optimal choice for every use case. Generally, with traditional provisioned infrastructure, you are going to have to deal with initial upfront costs even before there is traffic to your application. Which means you will likely have much more capacity than you need to operate. The same cycle is repeated over time as your application grows and requires more resources to scale – you scale up to a server that is much more than you actually need. Serverless on the other hand removes the upfront cost and the risk of over-provisioning for your workload requirements, since it will simply scale as needed and you will only pay for what you use. However, not all applications scale linearly, so for both new and more established applications where you may be considering using serverless, it’s important to think about your usage patterns and requirements before going down this path. Here's a breakdown of cost considerations depending on your applications requirements and traffic patterns: Low and Variable Workloads: If your application experiences irregular traffic patterns or low user demand, serverless can be highly cost-effective. You won't have to pay for idle server time, as the service provider automatically scales down to zero when there's no traffic. High Burst Traffic: Serverless excels in handling sudden spikes in traffic. Provisioned infrastructure may require overprovisioning to handle peak loads, incurring unnecessary costs during normal usage. Predictable Workloads: In cases of steady, predictable workloads, provisioned infrastructure with reserved instance capacity might be more cost-effective than serverless. Short-Lived Tasks: For tasks that execute quickly and don't require significant resources, serverless can be more cost-efficient. provisioned servers might incur higher costs due to minimum capacity or billing requirements. Long-Running Tasks: If your application frequently executes tasks that run for extended periods, serverless may end up being more expensive in the long run. In these scenarios, provisioned infrastructure may be the more cost-effective option. Optimizing costs in serverless architecture Because serverless solutions are charged based on usage, ensuring you have proper optimizations in place is not only important for performance but also to keep costs as low as possible. It’s important to make sure you are considering best practices for implementation so the service runs smoothly and can scale as efficiently as possible. This can mean different things depending on the type of serverless service you are using. If you are using a function-as-a-service platform like AWS Lambda that may mean allocating the right amount of memory for your function or controlling the invocation frequency to minimize invocations. Or if you are using a serverless database like MongoDB Atlas, that may mean modeling your data and structuring your queries in a certain way to minimize the size of the data being read from or written to the database. Regardless of the service, you should familiarize yourself with any best practices before jumping right in. Choosing the right solution for your needs Serverless architecture offers developers a powerful way to streamline development and focus on building applications without worrying about infrastructure management - providing benefits far beyond cost savings alone. For certain use cases with varying workloads and short-lived tasks, serverless can indeed be an option to save you money. However, it's crucial to assess your application's specific requirements and usage patterns to determine if serverless is the right fit for your needs. By understanding the cost model, comparing it with provisioned infrastructure, and implementing the proper cost optimization strategies, you can make an informed decision that aligns with your development goals and budget. Get started with MongoDB Atlas MongoDB Atlas gives developers flexibility with both serverless and provisioned database deployments available to address your workload requirements, regardless of your app's traffic patterns or budget constraints. Try Serverless on MongoDB Atlas today .

August 21, 2023

Improving Building Sustainability with MongoDB Atlas and Bosch

>> Announcement: Some features mentioned below will be deprecated on Sep. 30, 2025. Learn more . Every year developers from more than 45 countries head to Berlin to participate in the Bosch Connected Experience (BCX) hackathon — one of Europe’s largest AI and Internet of Things (AIoT) hackathons. This year, developers were tasked with creating solutions to tackle a mix of important problems, from improving sustainability in commercial building operations and facility management to accelerating innovation of automotive-grade, in-car software stacks using a variety of hardware and software solutions made available through Bosch, Eclipse, and their ecosystem partners. MongoDB also took part in this event and even helped one of the winning teams build their solution on top of MongoDB Atlas. I had the pleasure of connecting with a participant from that winning team, Jonas Bruns, to learn about his experience building an application for the first time with MongoDB Atlas. Ashley George: Tell us a little bit about your background and why you decided to join this year's BCX hackathon? Jonas Bruns: I am Jonas, an electrical engineering student from Friedrich Alexander University in Erlangen Nürnberg. Before I started my master’s program, I worked in the automotive industry in the Stuttgart area. I was familiar with the BCX hackathon from my time in Stuttgart and, together with two friends from my studies, decided to set off to Berlin this year to take part in this event. The BCX hackathon is great because there are lots of partners on site to help support the participants and provide knowledge on both the software and hardware solutions available to them — allowing teams to turn their ideas into a working prototype within the short time available. We like being confronted with new problems and felt this was an important challenge to take on, so participation this year was a must for us. AG: Why did you decide to use MongoDB Atlas for your project? JB: We started with just the idea of using augmented reality (AR) to improve the user experience (UX) of smart devices. To achieve this goal, we needed not only a smartphone app but also a backend in which all of our important data is stored. Due to both limited time and the fact that no one on our team had worked with databases before, we had to find a solution that would grow with our requirements and allow us to get started as easily as possible. Ideally, the solution would also be fully managed as well to eliminate us having to take care of security on our own. After reviewing our options, we quickly decided on using MongoDB Atlas . AG: What was it like working with MongoDB Atlas, especially having not worked with a database solution before? JB: The setup was super easy and went pretty fast. Within just a short time, we were able to upload our first set of data to Atlas using MongoDB Compass . As we started to dive in and explore Atlas a bit more we discovered the trigger functionality (Atlas Triggers), which we were able to use to simplify our infrastructure. Originally, we planned to use a server connected to the database, which would react to changed database entries. This would then send a request to control the desired periphery. The possibility to configure triggers directly in the database made a server superfluous and saved us a lot of time. We configured the trigger so that it executes a JavaScript function when a change is made to the database. This evaluates data from the database and executes corresponding requests, which directly control the periphery. Initially, we had hit a minor roadblock in determining how to handle the authentication needs (creating security tokens), which the periphery needs and expects during a request. To solve for this, we stored the security tokens on an AWS server which listens to an HTTP request. From Atlas, we then just have to call the URL and the AWS instance does the authentication and control of the lights. After we solved this problem, we were thrilled with how little configuration was needed and how intuitive Atlas is. The next steps, like connecting Atlas to the app, were easy. We achieved this by sending data from Flutter to Atlas over HTTPs with the Atlas Data API . AG: How did Atlas enable you to build your winning application? JB: By the end of the challenge, we had developed our idea into a fully functional prototype using Google ARcore, Flutter, MongoDB Atlas, and the Bosch Smart Home Hardware (Figure 1). We built a smartphone application that uses AR to switch on and off a connected light in a smart building. The position and state of the light (on or off) are stored in the database. If the state of the light should change, the app manipulates the corresponding value in the database. The change triggers a function that then sets the light to the desired state (on or off). The fact that we were able to achieve this within a short time without sufficient prior knowledge is mainly due to the ease and intuitive nature of Atlas. The simple handling allowed us to quickly learn and use the available features to build the functionality our app needed. Figure 1: Tech stack for the projects prototype. AG: What additional features within Atlas did you find the most valuable in building your application? JB: We created different users to easily control the access rights of the app and the smart devices. By eliminating the need for another server to communicate with the smart devices and using the trigger function of Atlas, we were able to save a lot of time on the prototype. In addition, the provided preconfigured code examples in various languages facilitated easy integration to our frontend and helped us avoid errors. Anyone who is interested can find the results of our work in the GitHub repo . AG: Do you see yourself using Atlas more in the future? JB: We will definitely continue to use Atlas in the future. The instance from the hackathon is still online, and we want to get to know the other functionalities that we haven't used yet. Given how intuitive Atlas was in this project, I am also sure that we will continue to use it for future projects as well. Through this project, Jonas and team were able to build a functional prototype that can help commercial building owners have more control over their buildings and take the steps to help reduce CO₂ emissions.

January 12, 2023

Introducing Snapshot Distribution in MongoDB Atlas

Data is at the heart of everything we do and in today’s digital economy has become an organization's most valuable asset. But sometimes the lengths that need to be taken to protect that data can present added challenges and result in manual processes that ultimately slow development, especially when it comes to maintaining a strict backup and recovery strategy. MongoDB Atlas aims to ease this burden by providing the features needed to help organizations not only retain and protect their data for recovery purposes, but to meet compliance regulations with ease. Today we’re excited to announce the release of a new backup feature, Snapshot Distribution. Snapshot Distribution allows you to easily distribute your backup snapshots across multiple geographic regions within your primary cloud provider with the click of a button. You can configure how snapshots are distributed directly within your backup policy and Atlas will automatically distribute them to other regions as selected—no manual process necessary. How to distribute your snapshots To enable Snapshot Distribution, navigate to the backup policy for your cluster and select the toggle to copy snapshots to other regions. From there, you can add any number of regions within your primary cloud provider—including regions you are not deployed in—to store snapshot copies. You can even customize your configuration to copy only specific types of snapshots to certain regions. Copy snapshots to other regions Restore your cluster faster with optimized, intelligent restores If you need to restore your cluster, Atlas will intelligently decide whether to use the original snapshot or a copied snapshot for optimal restore speeds. Copied snapshots may be utilized in cases where you are restoring to a cluster in the same region as a snapshot copy, including multi-region clusters if the snapshots are copied to every cluster region. Alternatively, if the original snapshot becomes unavailable due to a regional outage within your cloud provider, Atlas will utilize a copy in the nearest region to enable restores regardless of the cloud region outage. Perform point in time restore Get started with Snapshot Distribution Although storing additional snapshot copies in varying places may not always be required, this can be extremely useful in several situations, such as: For organizations who have a compliance requirement to store backups in different geographical locations from their primary place of operation For organizations operating multi-region clusters looking for faster direct-attach restores for the entire cluster If you fall into either of these categories, Snapshot Distribution may be a valuable feature addition to your current backup policy, allowing you to automate prior manual processes and free up development time to focus on innovation. Check out the documentation to learn more or navigate to your backup policy to enable this feature. Enable Snapshot Distribution

September 29, 2022

Embrace the Benefits of Serverless Development With MongoDB Atlas

>> Announcement: Some features mentioned below will be deprecated on Sep. 30, 2025. Learn more . Today’s applications are expected to just work, regardless of time of day, user traffic, or where in the world they are being accessed. To achieve this level of performance and scale, developers need to ensure they have the proper infrastructure resources in place to handle user demand, which often leads to time wasted on non-differentiating work. Organizations that want to stay competitive and rapidly innovate must look for solutions that simplify the process and enable them to speed time to development. Enter serverless. What’s the big deal with serverless? Serverless technologies allow developers to build applications without thinking about resource provisioning and scaling. As a result, developers are increasingly adopting a serverless-first approach to application development as a means to move fast, optimize costs, and eliminate the operational overhead of deploying and managing infrastructure. With application demand and user expectations growing faster than ever, serverless is becoming an essential component of application modernization strategies for both emerging startups and enterprises alike, with more and more organizations beginning to adopt function-as-a-service (FaaS) solutions, popular serverless frameworks, and now even serverless databases. Atlas serverless instances now generally available With MongoDB Atlas , our mission is and always has been to empower developers to move fast and simplify how they build with data for any application. Newer developers don’t have time to learn the intricacies of deploying and managing databases, nor should they have to. Recognizing this shift, we have been focused on building a developer data platform that minimizes this challenge. We started by launching services like Atlas Functions and Atlas Triggers and then moved to the data layer, first adding auto-scaling, then releasing Atlas serverless instances, our serverless database deployment option, in public preview in July 2021. Today, we are excited to announce that serverless instances are now generally available (GA). With serverless instances, you can quickly deploy a database with minimal configuration—just choose your cloud provider and region, and get the full power of MongoDB with the benefits of the serverless model . Once you’ve deployed your database, the serverless instance will take care of the scaling for you, with the ability to scale up or down from zero without any cold starts, and will only charge you for the operations you run. What’s new in serverless instances With this GA release, serverless instances will now offer additional features, such as private networking with AWS PrivateLink, enhanced monitoring and alerting capabilities, and extended backup retention with point-in-time recovery. Also, serverless instances are now compatible to use with our other serverless cloud services, such as the Atlas Data API and Atlas Functions, making building end-to-end serverless applications even easier. We’ve also dropped our prices (up to 60% in certain regions), to improve usage costs, with tiered pricing for reads that gives you automatic discounts on your daily usage without any up-front commitments or the need to talk to a sales rep. With this model, you can scale your usage without the fear of surprises. Develop modern serverless applications of any scale with Atlas The MongoDB Atlas data platform lets you build modern applications of any scale. Unlike other serverless databases, Atlas provides the full power and flexibility of the document model, so you can structure data for a variety of different use cases, instead of being limited to only simple key/value workloads. Additionally, our unified query API allows you to run MongoDB anywhere with a consistent experience—whether it’s on your laptop, a dedicated cluster, or a serverless instance—without ever changing your app code. Already using other serverless solutions in your application stack today? Atlas connects seamlessly with other leading serverless tools—from FaaS, to app development platforms, and frameworks—so you can continue working with the solutions you already know and love. And, most importantly, serverless instances are hosted on the same reliable Atlas foundation that is already trusted by organizations of all sizes today, from disruptive startups to some of the world's largest enterprises. Get started today Serverless databases are incredibly flexible and we’ve seen them perform well for lightweight or infrequent application workloads, such as application development and testing, or QA environments, event-driven applications, and periodic cron jobs. Are you ready to give serverless instances a try? Deploy your first serverless database today to see just how easy it is to get a cloud data endpoint for your application. Create your first serverless database

June 7, 2022

Accelerate App Development by Integrating MongoDB Atlas with Vercel: Now Available on the Vercel Marketplace

We’re excited to announce that MongoDB Atlas is now available on the Vercel Integrations Marketplace . If you are already using Vercel to develop and ship applications, or considering it for an upcoming project, this integration enables you to add a fully managed MongoDB Atlas database to your Vercel application in a matter of minutes. Build new web experiences with ease Vercel is known for making it easy for frontend developers to deploy Next.js applications instantly with no configuration and seamless scale through built-in CI/CD, analytics, serverless functions, and content delivery at the edge. MongoDB Atlas complements Vercel with a fully managed multi-cloud database service built on an intuitive and flexible document data model that provides a frictionless getting started experience. Atlas offers several database deployment types, ranging from a free shared cluster that is great for exploring MongoDB, to serverless instances that are ideal for app development and lightweight workloads, to our dedicated clusters that offer advanced functionality and customizations to power the most mission-critical applications. When using Atlas with Vercel, developers can build new web experiences quickly and with ease. Deploy on Vercel with zero configuration and instantly start building with documents that map directly to objects in your code. Scale without limits with Atlas and Vercel As your application grows, Atlas is built to grow with you, allowing you to modify data schemas if requirements change, and to scale confidently with built-in defaults and best practices that ensure your application is performant and secure. Our developer data platform makes expanding to meet new workload requirements easy, with embedded capabilities for full-text search, real-time analytics, data visualization, and more, so you can get the most out of your data without the added complexity of additional tools. And if you’re planning to have users all over the world, that’s no problem. Atlas and Vercel make delivering first-class experiences easier, regardless of where your users are located. Take advantage of Vercel’s edge network and the ability to distribute your data globally on Atlas with the click of a button, with access to nearly 100 regions and features for data partitioning, multi-region, and multi-cloud deployments designed for resiliency and responsiveness. Get started today If you’re ready to start building your next application with MongoDB Atlas and Vercel, getting started is simple. Select MongoDB Atlas on the Vercel Integrations Marketplace and automatically create and link your Atlas database with your Vercel app project in just a few clicks. We’re excited to see what you build! Join our community forums to share your project, leave feedback, ask questions, and connect with other developers using MongoDB Atlas. Try the integration today

June 7, 2022

Real Apps Built with a MongoDB Atlas Serverless Database

Serverless application development is quickly gaining popularity as a preferred way of building and running modern applications. With developers looking for solutions to speed development and provide even greater abstraction from the underlying infrastructure supporting those applications, it’s no surprise that the concept of serverless is extending beyond compute services to now databases as well. To continue delivering a modern developer experience for our users, MongoDB has recently introduced serverless databases in Atlas, currently available in preview. This new deployment option eliminates the process of capacity sizing and management altogether, and instead provides an on-demand endpoint that seamlessly scales based on workload demand and only charges for the resources used. If that sounds compelling, you might be wondering what can I build with a serverless database? The scalability and cost model naturally make them a great option for workloads that are infrequent and have cycles of usage combined with longer idle periods - like CRON jobs that run weekly or monthly. Because of this, we challenged users in a recent Atlas hackathon to use serverless databases as the backend to automate a weekly task - and some of the end results were pretty cool! Track your weekly fitness goals If you’re looking for a way to hold yourself accountable for your fitness goals, why not use an app to track your progress? This app uses Atlas to store and automate the weekly data aggregation and analysis - so you know if you’re meeting your goals. Automate the collection and delivery of your favorite web content Want to stay up to date on all the latest developer content from your favorite sites like Dev and Hashnode? This web app automatically compiles the latest articles from developer sites once a day and delivers up to 5 titles to your inbox based on keywords you’ve provided. It uses an Atlas database to store all the data and is hosted on Netlify using Netlify Serverless Functions as the backend service. Track your productivity for better work/life balance Finding the right work/life balance can be difficult without a true understanding of how you're spending your time - something a KanBan board is great at helping with. This submission uses an Atlas database along with Azure functions to automate the process of creating monthly reports from a Notion kanban board - eliminating the manual task and freeing up more time to get work done. If you’re interested in what else is possible with Atlas check out the other submissions here . Are you ready to try serverless? These are just a few of the ways you can use a serverless database in MongoDB Atlas but by no means the only use case. If you’re in the early stages of building a new application and aren’t sure of the level of scale to expect, serverless may be a great choice - enabling you to start quickly without the added cognitive load of worrying about infrastructure requirements. Or maybe you already have an app up and running but need a more effective dev/test environment - consider trying serverless as a way to optimize your resource spend. Are you ready to build your next app? Give Atlas serverless databases a try today and share your experience with us in our community forums ! Create your first serverless database

April 8, 2022

Serverless Instances Now Offer Extended Regional and Cloud Provider Support

Today’s applications are expected to just work, regardless of time of day, user traffic, or where in the world they are being accessed from. But in order to achieve this level of performance and scale, developers have to meticulously plan for infrastructure needs, sometimes before they even know what the success of their application may be. In many cases, this is not feasible and can lead to over provisioning and over paying. But what if you could forgo all of this planning and the database would seamlessly scale for you? Well, now you can - with serverless instances on MongoDB Atlas. Since we announced serverless instances in preview at MongoDB.live we have been actively working toward implementing new functionality to make them more robust and widely available. With our most recent release, serverless instances now offer expanded cloud providers and regions, and support MongoDB tools. Deploy a serverless instance on the cloud provider of your choice With our dedicated clusters on MongoDB Atlas, you have the flexibility to run anywhere with global reach on the cloud provider of your choice, so you can deliver responsive and reliable applications wherever your users are located. Our goal is to provide this same flexibility for serverless instances. We’re happy to announce that you can now deploy a serverless instance in ten regions on AWS, Google Cloud, and Azure. You’ll see when deploying a serverless instance there are now more regions supported on AWS, as well as two available regions on both Google Cloud and Azure - so you can get started with the cloud provider that best suits your needs or the region that’s closest to you. We will be continuing to add new regions over time to ensure coverage where you need it most. Easily import your data with MongoDB tools With this release, we have also made it easier to work with your data. You can now easily import data from an existing MongoDB deployment using the MongoDB Tools including mongodump, mongorestore, mongoexport , and mongoimport . In order to use MongoDB tools with serverless instances, you will need to be using the latest version . If you have additional feature requests that would make your developer experience better, share them with us in our feedback forums . Database deployment made simple With serverless instances, you can get started with almost no configuration needed - MongoDB Atlas will automatically scale to meet your workload needs, whether you have variable traffic patterns or you’re looking for a sandbox database for your weekend hobby project. If you haven’t yet given serverless instances a try, now is a great time to see what they can offer. If you have feedback or questions, we’d love to hear them! Join our community forums to meet other MongoDB developers and see what they’re building with serverless instances. Create your own serverless instance on MongoDB Atlas. Try the Preview .

September 16, 2021