Dana Groce

16 results

How Legacy Modernization with WeKan and MongoDB Atlas Helps Meet Evolving Consumer Demands

COVID-19 has accelerated the growth and adoption of digital economies across the globe, and the businesses best positioned to keep pace with related changes in consumer behavior and demand will continue to gain a competitive advantage in the marketplace. According to a consumer study by FIS Global that surveyed participants to understand changes in recent buying behaviour and patterns, consumers have spent 58% more money online since the pandemic started. What’s more, 42% of respondents stated an increase in purchases from local/independent small businesses, and 27% of consumers have subscribed to one new online streaming platform. Large institutions and household brands can not risk complacency if they want to maintain market share. The customer loyalty of today will be captured by the companies that act with agility and optimize data to deliver the most seamless, custom experience for consumers. Unsurprisingly, business models that have prioritized and directed resources towards aligning their processes with digital transformation are better placed to deal with customer behaviour shifting into the digital realm. And yet, innumerable businesses are plagued by the limitations of their legacy IT systems when trying to modernize their digital experience. For many organizations, legacy systems are seen as holding back the business initiatives and business processes that rely on them...when a tipping point is reached, application leaders must look to application modernization to help remove the obstacles Stefan Van Der Zijden, VP Analyst, Gartner Continued use of these systems holds back businesses’ potential for revenue generation and building customer-facing credibility; but modernizing them reaps worthy rewards. Luckily, you don’t have to go it alone. This post will detail how organizations can undertake this modernization process, often termed “legacy modernization,” so as to leverage the speed, agility, and responsiveness required to succeed in a digital-first marketplace. What is legacy modernization? Legacy modernization refers to the process of updating an organization’s antiquated IT stack to align with new-age business goals and workflows. To drive innovation, business leaders need to be supported by technology that can help implement their goals in the real world. They need fast-paced, highly connected systems with minimal-to-zero downtime, and platforms or dashboards that provide cohesive and easily comprehensible views of the entire ecosystem. Generally, legacy IT stacks are incapable of meeting these standards which is where legacy modernization comes in. Defining legacy systems and 4 major drawbacks Essentially, a legacy system is any software or technological system that slows down an organization’s business growth and its ability to shift and adapt to changing market forces. If a software setup is unable to integrate with newer systems, workflows or processes, it qualifies as “legacy.” Generally the incompatibility of legacy technologies, and the bottlenecks that come with them, lead to major issues related to maintenance, support, updates, integration and overall user experience. Think of it this way: using a legacy system in 2021 is comparable to driving a Prius with an engine made in 2000. Legacy solutions lack flexibility and carry a significant technology debt due to dated languages, databases, architectures, and a limited supply of aging baby-boomer programmers. a Deloitte Study on Legacy Systems and Modernization The business impact of legacy systems are varied, but often adverse. They include: 1. Inability to act with agility and meet demand Generally, legacy systems can only be accessed from office computers. But in a digital-first world, mobile devices are at the core of digital transformation. If employees cannot access necessary software from anywhere at any time, their productivity and operational capacity is severely limited. The link between software and employee performance has, in fact, been well-documented . For instance, in 2015 , a computer running a 23 year-old operating system (Windows 3.1) caused planes to be grounded at Paris’ Orly airport for several hours. Needless to say, customers were not happy. 2. Decreased employee productivity and customer satisfaction Everyday people are at the heart of digital transformation. If a business wants to attract and retain customers who are increasingly reliant on their internet-powered mobile devices for day-to-day activities and transactions, they have to meet them online. And if they want to attract top talent, they need to equip their employees with the tools and agility needed to innovate. Being saddled with legacy systems will prevent companies from using newer apps and providing the best possible customer service, support and experience. Additionally, sub-par employee performance and customer service will inevitably cause financial loss due to unsatisfied customers and missed opportunities for expansion. 3. Scalability issues and security risks Legacy software is usually incapable of scaling up, which poses major obstacles to business growth. In a competitive marketplace, businesses must be able to shift strategy and optimize according to market forces, for which they need the support of their IT stack. An excellent example of this is how companies have had to adapt to remote work becoming the ‘new normal’ due to the global pandemic. The IBM 2020 Cost of a Data Breach Report puts the average cost of a data breach at USD 3.92 million. Legacy software almost always has glaring flaws in its security mechanisms for multiple reasons: withdrawal of manufacturer support, lack of updates and regular maintenance, difficulties in fixing vulnerabilities within outdated systems. Issues like security breaches will significantly harm brand credibility and repel customers from entrusting the business with their data. 4. Higher costs Administrative, support and maintenance costs are unnecessarily high when companies have to work with legacy software. Additionally, hiring and training new employees, especially developers, is difficult since there is a shortage of coders trained in legacy languages like COBOL and Natural. Most legacy systems are hosted on premise, which translates to enormous and unnecessary overhead related to maintenance and upgrades. These costs are easily eliminated by leveraging cloud computing platforms like AWS, Google Cloud, or Microsoft Azure. Despite these glaring inadequacies, the pandemic has revealed how far too many organizations continue to rely on aging IT systems. In a 2020 AppDynamics Report , 66% of technologists say “the pandemic has exposed weaknesses in their digital strategy, driving an urgent need to push through initiatives which were once a part of multi-year digital transformation programs.” A roadmap for legacy modernization The journey to legacy modernization can be an intensive one, but there are proven best practices and expert guidance to help you get started. Galvanize the key players in your organization and get started by asking the right questions: What resources can be assigned to the modernization endeavour? Do your employees possess the skills to operate the new systems? What are the specific competitive advantages that modernization needs to provide for your organization? Is there a separate support and retirement schedule in place for your legacy system? Should modernization occur in a single shift or in phases? How will this affect our business? Escaping the pressures imposed by unwieldy tech stacks has become possible with microservices and cloud-based application development and/or usage. The trick lies in decentralizing business tech offerings by migrating them from Relational Database Management Systems (RDBMS) to the Cloud via scalable solutions like MongoDB Atlas , MongoDB's hosted database-as-a-service offering. Moving from monolith to microservices architecture can be complex, but offers multiple long-term advantages across multiple parameters. Refactoring monolithic systems requires carefully constructed strategies, the most successful of which are drawn from the Strangler Pattern approach . How do we modernize from existing legacy systems? Initiate new functionalities as microservices: Every time a business has to implement a new functionality or feature, they can incorporate it as a microservice instead of adding it to the existing monolith architecture. Not only does this prevent the legacy stack from expanding, but allows stakeholders to become acquainted with the advantages of microservice ecosystems. Dismantle the monolith: Once microservices have been introduced into an organization’s ecosystem, monolith structures need to be deconstructed for eventual elimination. Companies like FedEx and CitiBank have attested to the success of a microservices-based strategy with real world implementation. To quote FedEx CIO Rob Carter , “We began to build out the services and microservices that represent the less complex, more flexible, faster-to-market capabilities that we have today.” CitiBank, too, opted for migrating its monolith system to a microservices-based architecture so as to accelerate digital transformation. How WeKan and MongoDB Atlas can help Implementing successful, sustainable and scalable legacy modernization requires expertise in executing on the process itself, as well as the right tools that can understand and adapt to an organization’s unique needs and business goals. Databases and platforms like MongoDB and its tool suite help address the challenges of replatforming from monolith to microservice. MongoDB Atlas is the leading choice of general purpose databases for modernization. As a document-based, distributed database, MongoDB reduces time spent on development cycles and empowers developers with flexible schema and the tools they need to maintain productivity. A leap forward from traditional RDBMS, MongoDB Atlas's smart infrastructure helps organizations scale effortlessly and maintain business-critical reliability while driving lower TCO, reducing security risk, and remaining ACID compliant. Complementary to MongoDB, WeKan’s Modernization process is composed of 5 phases that aim to scope an optimal modernization journey for any business operating on legacy systems and looking for a better return on their technology investment: Diagnosis phase – The first step is to understand the current state of the business, its most critical pain points and identify major inefficiencies that can be solved through technology modernization. Prescription phase – With a good understanding of the business’ state, we propose reference solution architectures that can address most critical pain points and enhance overall performance of their technology ecosystem with a focus on always reducing the total cost of ownership (TCO) and increasing ROI on their technology spend. Validation phase – After gathering potential solutions, we then validate through POCs their tech viability, expected outcomes and leverage results from these efforts to narrow down and select the option that is best suited to the business’ needs. Requirements definition phase – With a target solution in hand, we work on defining the technical requirements and specifications of the proposed solution to ensure seamless integration to the overall technology ecosystem. Execution and Implementation phase – With the right solution architecture, technical requirements in place, and a proposed modernization plan, our modernization consultants work hand-in-hand with internal stakeholders on the development, testing, delivery and implementation of the proposed modernized solution. According to the World Economic Forum, digital transformation could generate more than $100 trillion by 2025 . Without legacy modernization, businesses will miss out on tapping into revenue streams offered by the digital economy. It is integral for organizations to leverage the many advantages of modernization so that they may gain and retain a competitive edge in a constantly connected and perpetually online marketplace. To learn more about WeKan and MongoDB Atlas's efficacy in organization-centric digital transformation, refer to our case study with RideKleen. After migrating operations to AWS, WeKan chose MongoDB Atlas, Atlas Data Lake and MongoDB Realm as their central data platform. Atlas offers a fully managed cloud database service with built-in automation, Atlas Data Lake provides federated query capabiliites to natively data query across MongoDB and AWS S3, while MongoDB Realm simplifies the critical edge-to-cloud sync and provides backend services to speed development work, including triggers, functions, and GraphQL. RideKleen case study Watch how MongoDB’s industry-best modernization services helped OTTO, Germany’s #2 global e-commerce provider and #1 site for e-commerce, fashion and lifestyle. Learn more about our Modernization Program Learn more about WeKan

July 1, 2021

Build Better Mobile Apps -- Running MongoDB Realm and Google Cloud

We’re partnering with Google Cloud to offer MongoDB Realm as part of the MongoDB Cloud stack with Google Cloud to service users globally whether you’re building a new mobile app or modernizing an existing one. Realm’s integrated application development services make it easy for developers to build industry leading apps on mobile devices and the web. With MongoDB Atlas running as a service with Google Cloud, it’s easy to connect your mobile database to Google services. Customers choose Google Cloud to: avoid vendor lock-in by running multi-cloud and hybrid cloud deployments take advantage of Google Cloud’s machine learning and advanced analytics abilities stay secure with the same protections Google Cloud itself uses to guard their data, applications, and infrastructure. Why MongoDB Realm for Mobile? Realm comes with 3 key features: Cross-platform mobile database Cross-platform mobile sync solution Time-saving application development services Mobile Database Realm’s mobile database is an open source, developer-friendly alternative to CoreData and SQLite. With Realm’s open source database, mobile developers can build offline-first apps in a fraction of the time. Supported languages include Swift, C#, Xamarin, JavaScript, Java, ReactNative, Kotlin, and Objective-C. Realm’s Database was built with a flexible, object-oriented data model, so it’s simple to learn and mirrors the way developers already code. Because it was built for mobile, applications built on Realm are reliable, highly performant, and work across platforms. Sync Solution Realm Sync is an out-of-the-box synchronization service that keeps data up-to-date between devices, end users, and your backend systems, all in real-time. It eliminates the need to work with REST, simplifying your offline-first app architecture. Use Sync to backup user data, build collaborative features, and keep data up to date whenever devices are online - without worrying about conflict resolution or networking code. Powered by the Realm Mobile Database on the client-side and MongoDB Atlas on the backend, Realm is optimized for offline use and scales with you. Building a first-rate app has never been easier. Application Development Services With Realm app development services, your team can spend less time integrating backend data for your web apps, and more time building the innovative features that push your business initiatives forward. Services include: GraphQL Functions Triggers Data access controls User authentication Use these products from Google to accelerate the development and deployment of backend services: Google Kubernetes Engine (GKE) Google Cloud Functions (FaaS) Google App Engine (PaaS) Realm and MongoDB Atlas with Google Cloud and Android As Realm is a MongoDB product offered through Atlas, and Atlas is used by Realm to sync data between the database and clients, Google Cloud and Atlas abilities are key to the Realm user experience. Figure 1: Screenshot of Realm offered through MongoDB Cloud UI MongoDB Atlas and Google Cloud MongoDB Atlas delivers a fully managed service on Google Cloud’s globally scalable and reliable infrastructure. Atlas allows users to manage their MongoDB databases easily through the UI or an API call. It’s simple to migrate to, and offers sophisticated features such as Global Clusters that offer low-latency read and write access anywhere across the globe. 3 Key Abilities with MongoDB Atlas and Google Cloud Geographic Presence All Google Cloud regions have at least 3 availability zones, providing higher availability, resiliency and geographic availability. Other public clouds do not have the same reliability guarantees. Network Offering — Cost and Customer Benefits Global VPC - global resources that reduce complexity in networking implementation Performance - premium tier leverages performance of the Google Cloud network improving application performance and latency across tiers Price - better pricing ratio for network egress costs Native Integrations Security -- Atlas offers native integrations to Google Auth through Realm, support for Google Cloud KMS for additional encryption at rest or MongoDB Client-Side Field Level Encryption, and OAuth flow based console integration Billing -- pay as you go billing on Google Cloud Marketplace (Realm is purchased through Atlas credits similarly on Marketplace) Realm and Android With Realm, you can create mobile applications for Android devices. Realm supports all versions of the Android API after level 9 (Android 2.3 Gingerbread). Below is a sample reference architecture which shows how to leverage MongoDB Atlas with Google Cloud as an Operational Data Layer (ODL) / Operational Data Store (ODS) and build mobile applications using MongoDB Mobile and Realm Sync. Figure 2: Reference Architecture for ODL on MongoDB Atlas and Realm with Google Cloud Realm Customer Story — A Leading New York Healthcare Payer MongoDB has partnered with Exafluence to deliver a COVID employee self-assessment health checker app for a leading healthcare payer in New York since the onset of the pandemic, they’ve needed to quickly adapt to new operational standards, as the situation with COVID evolves. MongoDB Atlas, Realm, Google Cloud, and Exafluence have all been a key part of allowing their onsite operations to continue. The CDC and New York State require organizations to keep track of which of their employees reporting to a physical office for work. As a result, the organization must monitor their New York based employees who still come onsite in order to support their members. They needed an app that would capture their employees’ health, and ask a series of questions to determine if the associate was able to enter the facility. Exafluence -- a MongoDB Global Strategic Partner working with the healthcare payer’s HR team and business team -- was able to deliver a complete solution in only three weeks from start to go-live. This rapid deployment was made possible using MongoDB Atlas, Realm, and Google Cloud. The completed app includes: support for mobile devices a web Portal to aggregate information use of QR Scans to confirm access on iPads deployed in facility entrances integration with Active Directory and alerts to the funds email system This rapid deployment was made possible using MongoDB Atlas and Realm. The organization and Exafluence chose Realm because it’s application development services make it easy to work with data across both web and mobile applications. Realm works with React js, provides offline sync and is Atlas cloud ready. MongoDB Atlas and Realm also make it easy to rapidly develop new features when the next stage of the pandemic changes app requirements. Exafluence will be able to quickly add app features tied to vaccination, like the ability for employees to disclose and share immunization certification via MongoDB’s FHIR API. Prior to the Covid App, this healthcare payer chose to use Atlas on Google Cloud because the fully managed, global DBaaS accelerates development and allows them to manage both structured and unstructured data. They also needed a solution for analytics involving geocoding, machine learning, and dashboarding. With Atlas and Google Cloud, their teams get agility while with elastic scaling and provision on-demand resources. Additional differentiators that drove the organization to select Google Cloud include: Maps API Air flow for scheduling Cloud identity Kubernetes deployment and seamless integration with MongoDB and Realm for mobile development Scalable VM environments Meeting CISO requirements They were able to automate and offload operational tasks while taking advantage of built-in security best practices, and this in turn reduced regulatory risk. With Atlas and Google Cloud, their teams can also elastically scale and provision on-demand resources to build more microservices, in-line with their agile development requirements. Click here to learn more about MongoDB Realm

February 2, 2021

MongoDB Atlas Connector for Apache Spark is Certified for Azure Databricks

We are happy to announce that the MongoDB Connector for Apache Spark is now officially certified for Microsoft Azure Databricks . Databricks, founded by the original creators of Apache Spark, provides the Databricks Unified Analytics platform . MongoDB Atlas users can integrate Spark and MongoDB in the cloud for advanced analytics and machine learning workloads by using the MongoDB Connector for Apache Spark which is fully supported and maintained by MongoDB. The MongoDB Connector for Apache Spark exposes all of Spark’s libraries, including Scala, Java, Python, and R. MongoDB data is materialized as DataFrames and Datasets for analysis with machine learning, graph, streaming, and SQL APIs. The MongoDB Connector for Apache Spark can take advantage of MongoDB’s aggregation pipeline and rich secondary indexes to extract, filter, and process only the range of data it needs – for example, analyzing all customers located in a specific geography. This is very different from simple NoSQL data stores that do not offer secondary indexes or in-database aggregations and require the extraction of all data based on a simple primary key, even if only a subset of that data is needed for the Spark process. This results in more processing overhead, more hardware, and longer time-to-insight for data scientists and engineers. Additionally, MongoDB’s workload isolation makes it easy for users to efficiently process data drawn from multiple sources into a single database with zero impact on other business-critical database operations. Running Spark on MongoDB reduces operational overhead as well by greatly simplifying your architecture and increasing the speed at which analytics can be executed. MongoDB Atlas, our on-demand, fully-managed cloud database service for MongoDB, makes it even easier to run sophisticated analytics processing by eliminating the operational overhead of managing database clusters directly. By combining Azure Databricks and MongoDB, Atlas users can make benefit of a fully managed analytics platform, freeing engineering resources to focus on their core business domain and deliver actionable insights quickly. What's Next? Get started now with MongoDB Atlas on Azure Download the connector from Maven Central Take a deep dive into the project on GitHub Learn more about the Spark Connector in our documentation

October 17, 2018

MongoDB Radio: Our New Podcast Project

This is for our previous Podcast series. We've launched a new one since this post went live. Find out more information here: https://www.mongodb.com/blog/post/mongodb-podcast-has-launched . Welcome to the inaugural post of MongoDB Radio, our new podcast project. We’re very excited to bring you great content about MongoDB, the people who build it, and the people who use it. Throughout this series we will feature interviews with MongoDB engineers, experts in the field of distributed computing and databases, stories from our community and trends in technology, and much more. The world of distributed systems and next generation applications is a fascinating place, and we can’t wait to share it with you. In episode one we spent time with Luke Lovett, a software engineer on the driver’s integration team at MongoDB. Among many things, Luke is responsible for maintaining one of our most popular projects – the Hadoop connector for MongoDB. The connector allows you to plug MongoDB into the Hadoop ecosystem of tools and perform sophisticated processing against the data within MongoDB. We spoke with Luke during our developer conference in San Jose, where he was delivering a talk on some of the new features available on the connector. We discussed the connector in depth, what it’s like to work on an open source project with the community, and how he got started at MongoDB. Join us for two days of GIANT thinking. Learn more about MongoDB World About the Author - Bryan Reinero Bryan is US Developer Advocate at MongoDB fostering understanding and engagement in the community. Previously Bryan was a Senior Consulting Engineer at MongoDB, helping users optimize MongoDB for scale and performance and a contributor to the Java Driver for MongoDB. Earlier, Bryan was Software Engineering Manager at Valueclick, building and managing large scale marketing applications for advertising, retargeting, real-time bidding and campaign optimization. Earlier still, Bryan specialized in software for embedded systems at Ricoh Corporation and developed data analysis and signal processing software at the Experimental Physics Branch of Ames Research Center.

April 18, 2016

Parse Shutdown: How to Seamlessly Continue Operations with Azure and MongoDB Cloud Manager

It has now been a few months since Parse announced their shutdown, and we at MongoDB are working to develop resources and options for users interested in migrating to other environments. We previously announced our guide to migrating from Parse to AWS and MongoDB Cloud Manager and are now adding a comprehensive guide to migrating a Parse backend to Azure with Cloud Manager . Along with Parse’s moving on announcement , they released Parse Server, an open source replacement for their hosted backend. Along with Parse Server, they have provided a practical migration path from their hosted solution to a private one. To use this solution, a team needs to provision a private MongoDB database, migrate their Parse data to that MongoDB, deploy the Parse Server into a hosting environment of their choosing, and update their client to issue API calls to their new Parse Server. MongoDB Cloud Manager’s tight integration with Azure makes it easy to setup a MongoDB deployment. This guide is for mobile developers and does not assume any prior experience with MongoDB, Node.js, or Azure. Each section provides a complete, high-level checklist with detailed, step-by-step directions. In addition, there are great jumping-off points to the specific MongoDB documentation relevant to those migrating from Parse, such as how to manage indexes and set up monitoring. Migrate from Parse to MongoDB and Azure

March 31, 2016

Announcing MongoDB's Giant of the Month, Doug Duncan of Alteryx

MongoDB customers and community members are the people who realize GIANT ideas. We are excited to begin highlighting some of our community members, our MongoDB Giants, who are tackling challenging problems and bringing solutions to life with MongoDB. This month’s MongoDB Giant is Doug Duncan, a DBA at Alteryx , who is making a meaningful impact to the MongoDB community. Alteryx is a leader in data preparation, blending, and advanced analytics. Doug has worked with RDBMSs for longer than he cares to admit, focusing in both development and administration. Through his experience, Doug grew to embrace new data storage technologies. He began working with MongoDB several years ago (starting with the MongoDB 1.8 release in early 2011) both professionally and recreationally. Doug acted as an online TA the first two years following MongoDB University’s founding, working closely with the team by answering students’ questions about the M101J , M101JS and M202 courses, as well as providing questions used in the courses. For his contributions to the education team Doug was awarded the first ever MongoDB DBA certification back in November of 2013. Doug also periodically answers questions on the MongoDB Google group . This year he will increase his participation in the community by delivering talks at the Denver MongoDB User Group . In his spare time, if Doug’s not reading up on MongoDB, Hadoop, or other distributed data stores, you can find him walking around the foothills of Colorado with his wife, two boys and two dogs. Become an important part of the MongoDB community. Join our Advocacy Hub and start getting involved today. Join the Advocacy Hub

January 27, 2016