We update MongoDB Cloud Manager regularly so that we can make it better for our customers. The latest version of Cloud Manager that was released on 2/22/16 introduced some significant changes and improvements. Continue reading below to learn more about the changes:
- Release of optimized navigation structure UI, including simplified Servers & Processes view. Take a look at the new Deployment tab to see the re-styled Servers and Processes tabs.
- Completely retooled user and roles management, giving users more flexibility over what is managed and what is not managed. You can find the users and roles under the “More” menu on the Deployment tab.
- Ability to convert a replica set to a sharded cluster
If you have any feedback, feel free to send us an e-mail at email@example.com. Thanks for using Cloud Manager!
Derivitec’s Risk Analysis Platform Uses MongoDB to Give Any Trader Access to Big-Bank Computing Power
Understanding future risk is vital for every successful organisation. In the financial markets, gaining that understanding means processing a mountain of complex data. In previous generations that meant you needed big computers and proprietary software that only big banks could afford. Thanks to better open source software and commodity hardware, that is no longer the case. Derivitec uses powerful modern infrastructure like MongoDB and AWS to make it possible for traders to get streamlined, industry standard financial analytics in minutes, not months. This gives them an understanding of what a range of different future events could mean for their investments. Answering the vital questions: What could go wrong? What’s the worst-case scenario? How can I hedge that risk? To address these questions Derivitec needed to build a different, more modern, platform. In 2011, when the company started, the team knew it would be processing a large volume and wide variety of data. So the database layer was going to be a defining factor for success. For the core functionality of the platform something fast, reliable and, above all, flexible was needed. New data sources, constantly changing regulations, and variable customer requirements meant functionality would be continually evolving. For Derivitec the obvious answer was a non-relational database with a document-oriented data model . Then, as now, MongoDB was a good fit. It’s worth pointing out that other no-SQL solutions were evaluated for this functionality but, quite simply, the performance levels were nowhere near what was needed. There are dozens of non-relational databases, but the choice was still a simple one. The three reasons for deciding on MongoDB were: Tried and tested technology – it has all the modern functionality and performance but it’s also got a massive community, thousands of customers and a mature support network. Operational tooling – Cloud Manager provides monitoring, backup and automation of deployments from the beginning - reducing costs and eliminating risk Ease of use – If you’re building a platform that will be easy to use, it makes sense to use one that’s easy to use too. MongoDB was also proven to run efficiently in the cloud, which is a huge part of what makes Derivitec special. In the early days Derivitec used Microsoft’s Azure cloud, but as its usage of MongoDB increased, the decision was made to switch from Azure to Amazon Web Services . Azure’s cloud was still too focused on its own software and it wasn’t as simple as it should have been to use non-Microsoft software, whilst AWS proved to be more accommodating. With that underlying infrastructure in place the platform could now be scaled out. MongoDB’s flexibility enabled Derivitec to deliver a system that could have users calculating risk on their portfolios in minutes, compared to the months it would have normally taken. For example, you can simply drop your trades in from Excel, visualise them, rearrange your portfolios, set up new portfolios, and manage the whole booking cycle natively within the app. The playing field is far from level. A big financial institution can still call a Napoleon's army of resources - both personnel and technology. But with the right data, enough context and access to intuitive tools you might just be able to see what your multiple futures hold. It’s exciting to be working in a time that modern open source software architectures and the power of cloud computing is eliminating obstacles and liberating giant ideas from giant budgets. About Derivitec Derivitec Ltd is a privately owned, UK based independent software vendor specialising in high performance, cost effective analytics for the derivatives industry. Founded in Dec 2011, the company have been working intensively towards cloud based solutions for risk and portfolio management. The Derivitec Risk Portal has been designed to allow users to start analysing risk on their derivatives portfolios in a matter of minutes. With industrial standard models and sanitised market data as standard, customers can focus on the business of business, while Derivitec concentrates on the business of risk. For an overview of MongoDB and its implementation on the AWS cloud platform read our guide. MongoDB on AWS: Guidelines and Best Practices About the Author - George Kaye George is the CEO and founder of Derivitec.
MACH Aligned for Retail (Microservices, API-First, Cloud Native SaaS, Headless)
Across the Retail industry, MACH principles and the Mach Alliance are becoming increasingly common. What is MACH and why is it being embraced for Retail? The MACH Alliance is a non-profit organization fostering the adoption of composable architecture principles. It stands for Microservices, API-First, Cloud-Native SaaS and Headless. The MACH Alliance’s Manifesto is to: “Future proof enterprise technology and propel current and future digital experiences" The MACH Alliance and the creation of this set of principles originated in the Retail Industry. Several of the 5 co-founders of the MACH Alliance are technology companies building for retail use cases: for example commercetools is a composable commerce platform for retail (built completely on MongoDB). MongoDB has been a member of the MACH Alliance since 2020, as an “enabler” member, meaning use of our technology can enable the implementation of the MACH principles in application architectures. This is because a data layer built on MongoDB is ideal as the basis for a MACH architecture. Members of our Industry Solutions team sit on the MACH technology, growth and marketing councils, and actively are involved with furthering the adoption of MACH across the Retail Industry What is MACH, why is it important for retail? The retail industry has long been a fast adopter of technology and a forerunner in technology trends. This is because of the competitive nature of the business leading a drive towards innovation- its vital that retails are able to react quickly to new technologies (e.g. NFTs, VR, AI) to capture market share and stay ahead of the competitors. Retailers have realized that to be able to deliver new and value-add experiences to their customers, they have to cut back on operational overhead that leads to increased cost and build standard functionality that can either be bought or re-used. This is where the benefits of MACH comes in- it's all about increasing the ability to deliver innovation quickly while lowering operational costs & risk. Microservices: An approach to building applications in which business functions are broken down into smaller, self-contained components called services. These services function autonomously and are usually developed and deployed independently. This means the failure or outage of one microservice will not affect another and teams can develop in parallel, increasing efficiency. API-First: A style of development where the sharing and use of the data via API (application programming interface) is considered first and foremost in the development process. This means that services are designed to aid the easy sharing of information across the organization and simple interconnectivity of systems. Cloud-Native SaaS: Cloud-native SaaS solutions are vendor-managed applications developed in and for the cloud, and leveraging all the capabilities the cloud has to offer, such as fully managed hosting, built-in security, auto-scaling, cross-regional deployment and automatic updates. These are a good fit for a MACH architecture as adopting them can reduce operational costs and frees up developers for value-add work like new unique customer experiences. Headless: Decoupling the front end from the back-end so that front ends (or “heads”) can be created or iterated on with no dependencies on the back end. The fact that the layers are loosely coupled decreases time to market for new front ends, and encourages the re-use back-end services for multiple purposes. It also de-risks change in the long term as services can function independently. Where does MongoDB come in? MongoDB is an enabler for MACH, meaning that using MongoDB as your data layer helps retailers and retail software companies. achieve MACH compliance. Our data model, architecture and functionality empower IT organizations to build in line with these architecture principles. During a digital transformation, where a retailer is modernizing a monolith into a microservices based architecture, they're looking for a data layer which will enable speed of development & change. MongoDB is the "most wanted" database 4 years running on Stack Overflow's developer survey- this is because our document model maps to the way developers are thinking & coding, and the flexibility allows for iterative change of the data layer. When looking at API based communication, the standard format for APIs is JSON, which again maps to MongoDB's document model. The idea with API-first development is to develop with the API in mind- why not store the data the way you're going to serve it by API. This reduces complexity and increases performance. Cloud Native and SaaS products have become the norm as retailers wish to reduce maintenance and management work. MongoDB Atlas, provides a database-as-a-service, guaranteeing 99.995% uptime, automatic failover and self-healing and allowing DevOps engineers to spin up databases in minutes or by API/ script. Many retail software companies are also built on MongoDB Atlas- for example commercetools, which provides an ecommerce solution as a SaaS product. Headless architectures require a data layer that is able to adapt and change for new workloads. The ability to change the schema at runtime, with no downtime, makes MongoDB's document model ideal for this. Performance and the ability to scale for new "heads" is also important. MongoDB is known as a high performance database and can scale vertically automatically or scale out horizontally seamlessly. So MongoDB becomes a great choice for retailers choosing to adopt a MACH architecture (see figure 1 below). As a general purpose database with high performance, a rich expressive query language and secondary indexing, MongoDB is a really good fit as a data layer as it is capable of handling operational and analytical needs of the application. FIgure 1: Example of a MACH architecture Want to know more? Are you interested in a transition to MACH? Dive into our four part blog series exploring each topic in detail and how MongoDB supports each of these principles: Microservices API-First Cloud-Native SaaS Headless