Infosys Media Platform & MongoDB: Metadata Management and Workflow Orchestration Across Media Supply Chain
Capitalize on current and innovative technologies in the media supply chain with the Infosys Media Platform (IMP). As a part of the cloud and cloud-based Infosys Cobalt ™ portfolio, Infosys’ unifying framework, built on MongoDB Atlas and MongoDB Enterprise Advanced , helps you facilitate creative collaboration, enable productions on an industrial scale, and monetize customer relationships. How? By integrating the various ecosystems involved and providing a common platform to connect you to services and technology solutions for the media content value chain. Infosys’ intelligently-woven media and metadata management framework, leveraging MongoDB’s document model, enables smart workflows and incorporates ML/AI to create, manage and moderate content metadata. This allows the orchestration workflows across different business functions. Additionally, the platform delivers the benefits of productivity, scalability, and agility via the cloud and streamlines collaboration among the ecosystem of partners and technology solutions. Why Infosys Media Platform (IMP)? The Infosys Media Platform consists of various modules that serve critical business functions, such as: The Curation & Digitization Module -- provides the master workflow and ingests content from internal archives and multiple sources using AI/ML to create a composite index of frame level and time-coded metadata of recognized elements (such as celebrities/known personalities, objects, brands, text, and images). It also enables intelligent ad spot identification and includes functions like automated QC, editing, review, and approval, and censor editing The Custom AI Module -- ensures that newly introduced elements such as celebrities, brands, etc., can be continuously trained and recognized. This can also be used to custom-train the AI models to recognize specific content as per customer’s needs The Localization Module -- enables collaboration across multiple locations and global vendors through automatic generation of closed captions and subtitles in multiple languages Metadata Management and Distribution Module -- enables global distribution to digital platforms at scale through standard workflow models and a state-of-the-art dashboard by orchestrating the accumulation of asset level and descriptive time-based metadata from production to delivery With the above modules, Infosys Media Platform can attain the following capabilities: Content Enrichment -- leverages AI models to process video files and generate time-coded metadata for post-production and distribution process Closed Captioning, Subtitling and Localization -- processes audio (dialogs from a video, lyrics from a song, speech from a podcast) and converts it into closed captions and subtitles Content Moderation -- recognizes the presence of mature content (profanity, violence, gore etc.) using the video content and speech detection capabilities Image Processing -- identifies various attributes of an image file, similar to the capabilities on video/music content Metadata Packaging & Distribution -- manages end-to-end supply chain of digital metadata creation, updates, packaging and distribution NLP Based Analytics -- using natural language processing capabilities of the platform, users can review any string of text (dialogs, lyrics, conversations) to determine the context of the conversation as well as the sentiment Why MongoDB for Infosys Media Platform? What company wouldn’t want a database platform that increases developer productivity and data-driven operational efficiency? MongoDB offers both. With MongoDB Atlas , you can reduce the time developers spend managing data and databases, so they can focus on value-added tasks like developing new apps. MongoDB’s document model and query language provide easier access to data, allowing developers to work quickly and efficiently to support new data structures and data types, as well as leverage database-supported roll-ups for analysis. Additionally, MongoDB Atlas introduces 100+ metrics and monitoring capabilities with its complete data platform built to improve operational productivity, so you can work smarter, not harder. A main feature of Infosys Media Platform is its cloud-agnostic nature; and as a cloud-agnostic and multi-cloud data platform, MongoDB is the only platform that satisfies IMP with its ability to run seamlessly across the globe. Through a mixed workload of real-time and transactional analytics, IMP also offers a roadmap on analytics, text search and data visualization capabilities--and MongoDB provides all these features. How MongoDB powers the data platform for Infosys Media Platform (IMP) Data for all the modules previously described is powered by the MongoDB data platform Details like profile data, accounts, ratings, translations, country/region details are stored in MongoDB Audit transactional data are currently running on SQL and there is a roadmap for moving to MongoDB data platform . In the future, MongoDB’s core capabilities will further enhance the Infosys Media Platform and customer experience. Our roadmap includes utilizing MongoDB ACID transactional capabilities to store audit details, as well as using MongoDB functions and triggers for creating cloud agnostic serverless functions. Additionally, MongoDB Atlas may be leveraged for full-text search capabilities applied to media data, and to create charts for dashboarding and real-time analytics of user subscriber data. Download the Modernization Guide
Appy Pie & MongoDB’s Seamless, No-Code Business Solutions for Mobile & Web Apps
The tech industry’s ceaseless and exponential growth is no longer a surprise. As long as clients and end-users remain interested in faster, more efficient services, then tech companies will continue to improve business processes to meet the demand. Simultaneously, these improvements will reduce costs and maximize revenue. It’s a win-win--if, of course, it’s done correctly. So, what’s behind most success stories? How do some companies launch and maintain applications at such rapid, expansive scale? Often, the key to success lies in fostering core business processes that are driven by automation. For many tech-based organizations, Appy Pie Connect has been the go-to seamless integration platform that helps them get started. And now, with MongoDB Realm , it’s about to get even easier. Users build best in-class-apps across Android, iOS, and web with MongoDB Realm’s mobile database, sync solution, and application development services. Why use Appy Pie & MongoDB Realm? Together, Appy Pie and MongoDB are driving seismic operational change. Originally, Appy Pie AppMakr product moved to MongoDB Realm for local storage. But after experiencing the immense ease and advantages offered by Realm--specifically, its offline-first database that supports cross-platform app development-- we decided to extend its benefits to the customers of Appy Pie Connect. As an automation platform, Appy Pie Connect helps businesses automate manual tasks through smart integrations, allowing for intuitive, instant sharing between apps less commonly connected like MailChimp and LinkedIn or Stripe and Gmail, and so on. By integrating MongoDB and MongoDB Realm with Appy Pie Connect, customers can easily store or retrieve data within multiple database sources. This enables the storage of flexible schemas and maintains consistency and integration. This unique “no code” technology allows organizations to extract and work with data from MongoDB and then apply that data to desired software through triggered-based actions. For example, users can set up a trigger for every event on their Google Calendar so that their Slack status corresponds and is updated at the start and end of each meeting. This way, data concurrency is maintained without any manual effort. Realm is a particularly great choice for the customers at Appy Pie Connect because of its effortless data syncing. View some of the common use cases below. Example 1 In the Meter Billing example below, cost is calculated in real time based on usage (e.g. video viewing time), resulting in a transparent “pay as you go” model. Example 2 With real-time data sync, any updates or changes to the application are immediately reflected without requiring users to update or reinstall. Example 3 All API failure logs are conveniently displayed to the admin on the Appy Pie dashboard so that immediate troubleshooting actions can be taken. Benefits of MongoDB Realm and MongoDB Atlas Appy Pie Connect already uses MongoDB Atlas, so moving to Realm -- a MongoDB product offered through Atlas -- was a natural choice. Realm allows mobile users to sync data quickly and seamlessly between mobile devices and backend systems, even if they go offline (sync will occur when they are connected) -- and Atlas enables it all.. Some benefits of using Atlas are as follows: Scalability flexible data schema Document oriented storage Ad hoc queries, indexing, and real-time aggregation Powerful tools for data analysis Serverless function and GraphQL support Easy hosting and quickly able to built rest API Ultimately, Appy Pie Connect helps businesses convert MongoDB into a central data store by pulling in and replicating data from all its sources. This allows customers to create new MongoDB documents automatically from new Typeform entries, new files on Dropbox, new posts on WordPress, or other resources. Similarly, Appy Pie Connect can also send MongoDB data to other third-party apps, including WordPress, Salesforce, Slack, Mailchimp, Google Drive, and many more. This makes enterprise-wide communication and collaboration much more efficient. When data is pulled from MongoDB through automation, it can help streamline other areas of the business. For example, when you pull MongoDB data into MailChimp, you can automatically add a new subscriber on Mailchimp. This ensures that your lists grow automatically, as fast as your business does. Ex. Appy Pie Connect seamlessly sends MongoDB data to third-party apps Use cases Send data from MongoDB to LinkedIn (without any code!) to quickly post accurate job-related content Extract retail product data into Google Sheets to record valuable data in an organized manner in one place Post enterprise-related content from MongoDB to Twitter to streamline social media presence How it works Appy Pie Connect employs a trigger-action based function that allows you, as a platform user, to choose the two apps you want to connect. The process is very straightforward. Once you choose the apps you wish to integrate, you will be presented with multiple options to connect them. Simply click on the “Connect” button. To integrate with the selected applications accounts, simply allow API access for Appy Pie Connect. Next, design the workflows by mapping all of your data synced from the applications you are connecting. Once complete, you are ready to test your brand new Connect with your Trigger and Action apps. And, that’s it! It is time to experience the magic of Appy Pie Connect at work. Let the automation workflows take over the mundane, repetitive tasks, and move on to more innovative, exciting tasks. As the efficiency of an organization improves through automation, one of the most direct advantages is a marked reduction in cost. These integrations help save hundreds of hours of manual effort, thereby freeing up talented resources to instead focus their energy and intellect on more critical, innovative issues. With Appy Pie Connect and MongoDB Realm, businesses can ensure that their workforce is not only optimized but also inspired, a key factor to employee satisfaction and overall company success. Watch this demo to learn how to integrate MongoDB with Google Sheets using Appy Pie Connect to help you automate data exchange between MongoDB and Google Sheets with ease. Click here to learn more about MongoDB Realm
Accelerating Mainframe Offload to MongoDB with TCS MasterCraft™
Tata Consultancy Services (TCS), a leading multinational information technology services and consulting company, leverages its IP-based solutions to accelerate and optimize service delivery. TCS MasterCraft™ TransformPlus uses intelligent automation to modernize and migrate enterprise-level mainframe applications to new, leading-edge architectures and databases like MongoDB. In this blog, we’ll review the reasons why organizations choose to modernize and how TCS has made the process easy and relatively risk-free. Background Legacy Modernization Legacy modernization is a strategic initiative that enables you to refresh your existing database and applications portfolio by applying the latest innovations in development methodologies, architectural patterns, and technologies. At the current churn rate, about half of today’s S&P 500 firms will be replaced over the next 10 years $100T of economic value is ready to be unlocked over the next decade via digital transformation Source Legacy System Challenges Legacy technology platforms of the past, particularly monolithic mainframe systems, have always been challenged by the pace of disruptive digitalization. Neither the storage nor the accessibility of these rigid systems is agile enough to meet the increasing demands of volume, speed, and data diversity generated by modern digital applications. The result is noise between the legacy system of record and digital systems of engagement. This noise puts companies at a competitive disadvantage. It often manifests as a gap between customer service and user experience, impeding the delivery of new features and offerings and constraining the business from responding nimbly to changing trends. Operational costs of mainframe and other legacy systems have also skyrocketed. With each million instructions per second (MIPS) costing up to $4,000 per year, these older systems can create the equivalent of nearly 40% of an organization’s IT budget in technical debt, significantly increasing the overall annual run cost. And as qualified staff age and retire over the years, it’s becoming harder to find and hire people with the required mainframe skills. To manage MIPS consumption, a large number of our customers are offloading commonly accessed mainframe data to an independent operational data layer (ODL), to which queries are redirected from consuming applications. IT experts understand both the risk and the critical need to explore modernization options like encapsulation, rehosting, replatforming, refactoring, re-architecting, or rebuilding to replace these legacy systems. The key considerations when choosing an approach are familiar: risk of business disruption, cost, timelines, productivity, and the availability of the necessary skills. MongoDB + TCS MasterCraft™ TransformPlus = Transformation Catalyst To stay competitive, businesses need their engineering and IT teams to do these three things, among others: Build innovative digital apps fast Use data as a competitive moat to protect and grow their business Lower cost and risk while improving customer experience Some customers use a “lift and shift” approach to move workloads off the mainframe to cloud for immediate savings, but that process can’t unlock the value that comes with microservice architectures and document databases. Others gain that value by re-architecting and rewriting their applications, but this approach can be time consuming, expensive, and risky. More and more, customers are using a tools-driven refactoring approach to intelligently automate code conversion. What TCS MasterCraft™ TransformPlus Brings to the Table TCS MasterCraft™TransformPlus automates the migration of legacy applications and databases to modern architectures like MongoDB. It extracts business logics from decades-old legacy mainframe systems as a convertible, NoSQL document data model for deployment. This makes extraction faster, easier, and more economical, and reduces the risk that comes with rewriting legacy applications. With more than 25 years of experience, TCS’s track record includes: 60+ modernization projects successfully delivered 500M+ lines of COBOL code analyzed 25M+ lines of COBOL code converted to Java 50M+ new lines of Java code auto-generated What MongoDB Brings to the Table MongoDB’s document data model platform can help make development cycles up to 5 times faster. Businesses can drive innovation faster, cut costs by 70% or more, and reduce their risk at the same time. As a developer, MongoDB gives you: The best way to work with data The ability to put data where you need it The freedom to run anywhere Why is TCS collaborating with MongoDB for Mainframe Offload? Cost. Redirecting queries away from the mainframe to the ODL significantly reduces costs. Even cutting just 20%-30% in MIPS consumption can save millions of dollars in mainframe operating costs. Agility. As an ODL built on a modern data platform, MongoDB helps developers build new apps and digital experiences 3—5 times faster than is possible on a mainframe. User Experience. MongoDB meets demands for exploding data volumes and user populations by scaling out on commodity hardware, with self-healing replicas that maintain 24x7 service. More details can be found here . How TCS MasterCraftTM Accelerates Mainframe Offload to MongoDB Data Migration Configures target document schema to corresponding relational schema Automatically transforms relational data from mainframe sources to MongoDB documents Loads data to MongoDB Atlas with the latest connector support Application Migration Facilitates a cognitive code analysis-based application knowledge repository Ensures complete, comprehensive application knowledge extraction Automates conversion of application logic from COBOL to Java, with data access layer accessing data from MongoDB Splits monolithic code into multiple microservices Automates migration of mainframe screens to AngularJS-based UI Together, TCS MasterCraft™ TransformPlus and MongoDB can simplify and accelerate your journey to the cloud, streamlining and protecting your data while laying the foundation for digital success. Download the Modernization Guide to learn more.
1Data - PeerIslands Data Sync Accelerator
Today’s enterprises are in the midst of digital transformation, but they’re hampered by monolithic, on-prem legacy applications that don’t have the speed, agility, and responsiveness required for digital applications. To make the transition, enterprises are migrating to the cloud. MongoDB has partnered with PeerIslands to develop 1Data, a reference architecture and solution accelerator that helps users with their cloud modernization. This post details the challenges enterprises face with legacy systems and walks through how working with 1Data helps organizations expedite cloud adoption. Modernization Trends As legacy systems become unwieldy, enterprises are breaking them down into microservices and adopting cloud native application development. Monolith-to-microservices migration is complex, but provides value across multiple dimensions. These include: Development velocity Scalability Cost-of-change reduction Ability to build multiple microservice databases concurrently One common approach for teams adopting and building out microservices is to use domain driven design to break down the overall business domain into bounded contexts first. They also often use the Strangler Fig pattern to reduce the overall risk, migrate incrementally, and then decommission the monolith once all required functionality is migrated. While most teams find this approach works well for the application code, it’s particularly challenging to break down monolithic databases into databases that meet the specific needs of each microservice. There are several factors to consider during transition: Duration. How long will the transition to microservices take? Data synchronization. How much and what types of data need to be synchronized between monolith and microservice databases? Data translation in a heterogeneous schema environment. How are the same data elements processed and stored differently? Synchronization cadence. How much data needs syncing, and how often (real-time, nightly, etc.)? Data anti-corruption layer. How do you ensure the integrity of transaction data, and prevent the new data from corrupting the old? Simplifying Migration to the Cloud Created by PeerIslands and MongoDB, 1Data helps enterprises address the challenges detailed above. Migrate and synchronize your data with confidence with 1Data Schema migration tool. Convert legacy DB schema and related components automatically to your target MongoDB instance. Use the GUI-based data mapper to track errors. Real-time data sync pipeline. Sync data between monolith and microservice databases nearly in real time with enterprise grade components. Conditional data sync. Define how to slice the data you’re planning to sync. Data cleansing. Translate data as it’s moved. DSLs for data transformation. Apply domain-specific business rules for the MongoDB documents you want to create from your various aggregated source system tables. This layer also acts as an anti-corruption layer. Data auditing. Independently verify data sync between your source and target systems. Go beyond the database. Synchronize data from APIs, Webhooks & Events. Bidirectional data sync. Replicate key microservice database updates back to the monolithic database as needed. Get Started with Real-Time Data Synchronization With the initial version of 1Data, PeerIslands addresses the core functionality of real-time data sync between source and target systems. Here’s a view of the logical architecture: Source System. The source system can be a relational database like Oracle, where we’ll rely on CDC, or other sources like Events, API, or Webhooks. **Data Capture & Streaming.**Captures the required data from the source system and converts them into data streams using either off-the-shelf DB connectors or custom connectors, depending on the source type. 1Data implements data sharding and throttling, which enable data synchronization at scale, in this phase. Data Transformation. The core of the accelerator, when we convert the source data streams into target MongoDB document schemas. We use LISP-based Domain Specific Language to enable simple, rule-based data transformation, including user-defined rules. Data Sink & Streaming. Captures the data streams that need to be updated into the MongoDB database through stream consumers. The actual update into the target DB is done through sink connectors. Target system. The MDB database used by the microservices. Auditing. Most data that gets migrated is enterprise-critical; 1Data audits the entire data synchronization process for missed data and incorrect updates. Two-way sync. The logical architecture enables data synchronization from the MongoDB database back to the source database. We used MongoDB, Confluent Kafka and Debezium to implement this initial version of 1Data: The technical architecture is cloud agnostic, and can be deployed on-prem as well. We’ll be customizing it for key cloud platforms as well as fleshing out specific architectures to adopt for common data sync scenarios. Conclusion The 1Data solution accelerator lends itself to multiple use cases, from single view to legacy modernization. Please reach out to us for technical details and implementation assistance, and watch this space as we develop the 1Data accelerator further.