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Tag: Metaverse

  • Four Technologies Transforming Data and Driving Change

    Four Technologies Transforming Data and Driving Change

    Data is getting a facelift in 2023 courtesy of event-driven architecture (EDA). These four technologies are set to transform DevOps and IT operations over the next year–whether it be how companies make use of data or the customer experience they offer.

    1. Applied Observability: A Powerful Source of Decision-Making

    Applied observability has been recognized by Gartner as a key 2023 strategic tech trend at its most recent Orlando Symposium. It ensures that the right data is delivered at the right time for rapid action based on confirmed stakeholder actions rather than intentions. “Observable” data include key digitized artifacts that appear when any stakeholder takes any kind of action. Applied observability feeds these observable artifacts back in a highly orchestrated and integrated approach to accelerate organizational decision-making and allows the business owner to track how long an action took to fully process at every point in the workflow.

    But unearthing these insights requires an event-driven approach to software architecture. Distributed tracing, for example, is a method of tracking application requests as they flow from front-end devices to back-end services and databases. By definition, and in contrast to traditional tracing, distributed tracing can be visualized to show a searchable, graphical picture of when, where and how a single event flowed through an enterprise, regardless of the number of hops the workflow took to fully process.

    Consider the potential traceability and end-to-end observability benefits across a payment ecosystem underpinned by EDA. Embedding distributed tracing into an event mesh emits trace events in OpenTelemetry format so banks can collect, visualize and analyze them in any compatible tool. This empowers them to not only confirm that a given message was published but easily understand exactly when and by whom, where it went, down to individual hops, who received it and when … or why not.

    2. Hyper and Intelligent Automation: Taking Automation to the Next Level

    Gartner and IDC identified both hyper and intelligent automation in their yearly technology trends for 2023. Hyperautomation moves automation up a level, adding more intelligence to automation and using a broader set of tools so that previously un-automatable tasks can be automated. Hyperautomation initiatives come in many different shapes and sizes and are being seen across a wide range of industries, from banking and insurance to manufacturing and health care.

    But hyperautomation requires an organization to be underpinned by an EDA and–more specifically, an event mesh–to maximize success. An event mesh is an interconnected network of event brokers that allows data to be pushed in real-time to parts of the organization where the data is needed. It does this dynamically, meaning that new event types can be added at any time and interest in events can be registered to allow a seamless interchange of data for the applications that are interested in using it.

    Take the aviation industry as an example. An event mesh streams information such as flight routes, delays, cancellations and mileage accruals between applications, connected devices and people anywhere in the world, instantly. With an event mesh, information about events can be continuously streamed to multiple systems; filtered so each system only receives the data it needs. This ultimately enhances the customer experience as passengers, pilots and crews are notified in real-time when something relevant occurs on each and every flight.

    3. The Acceleration of the Event-Driven API Economy

    The API economy has exploded. Research from MIT Initiative on the Digital Economy showed that over a four-year period, businesses using APIs saw 12.7% more growth in market capitalization compared to those that did not adopt APIs.

    But the API economy is changing as event-driven architecture and asynchronous event-driven APIs become increasingly important to companies striving to operate in real-time. Using both synchronous and asynchronous methods can result in an application environment in which system resources are most effectively used.

    AsyncAPI and RESTful APIs will be the next evolution of the API economy. API management platforms will need to adapt quickly to this new reality. As a prime example, Forrester recently spotlighted a global biotech company that is blazing a trail in the API-driven area. As the case study demonstrates, the organization understood that EDA is a complement to RESTful APIs–another tool in their digital business toolbox, filling in the gaps of a REST-only approach.

    As a result, they planned a unified event + REST approach from the outset. Both APIs and events are managed as enabling digital products, with the governance and life cycle of both unified as one process. A platform team builds a unified API + event platform for app dev teams rather than building each as a separate siloed platform. The results include faster speed to market and new business opportunities. The company also embraces FAIR data principles: Data that is findable, accessible, interoperable and reusable. A digital marketplace consisting of both events and APIs makes the data findable and machine-readable via Open API Spec (OAS) and AsyncAPI metadata. Data can then be accessed on demand via APIs and events push data in real-time.

    4. The Metaverse Continues at Pace

    Driven by technologies including digital twins, augmented reality and virtual reality, McKinsey estimates the metaverse will be worth $5 trillion by 2030. Data in real-time will be the vital common denominator to link the digital and physical divide and optimize the Metaverse. McKinsey lists real-time data as a vital element to facilitate adoption of the metaverse in several key industries including retail, banking/financial services and transportation.

    The metaverse cannot be static. It needs to be in real-time, in motion. It needs an EDA and a real-time event mesh to support it.

    For example, if an avatar visits a retailer in the metaverse, the retailer will need to keep track of countless user actions such as how long someone spent looking at a particular product, which products got the most interest, etc. The metaverse will produce a significant amount of data that companies will be interested in analyzing in real-time. This data can be used to make decisions from real-time adjustments to inventory to incentivizing commerce through real-time offers/discounts/coupons and even dynamically pricing products.

    Designing a Data-Driven Future With new Tech

    Together, these four predictions have the potential to revolutionize company operations, communications and decision-making–but to take advantage of their full potential and reap success, these four trends will need EDA by their side.

  • Meta Income Down by Half | Will Apple Make it Worse? | Linux Secure Boot Fix

    Meta Income Down by Half | Will Apple Make it Worse? | Linux Secure Boot Fix

    Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.

    This week: Meta’s latest results are very bad, Apple wants its cut of Facebook ads, and Lennart Poettering proposes a new Secure Boot for Linux. (more…)

  • Extreme Sports in the Metaverse

    Extreme Sports in the Metaverse

  • Augmented Reality

    Augmented Reality

  • Modern Morals

    Modern Morals

  • How to Visit the Metaverse

    How to Visit the Metaverse

  • Status in the Metaverse

    Status in the Metaverse

  • GraphQL as a Meta Layer

    GraphQL as a Meta Layer

    There’s a lot of interest in GraphQL lately. The query language is excellent for data retrieval, and it could act as a more usable mechanism to evolve the traditional REST API integration approach. But as adoption grows steadily, architects are now considering the implications of managing GraphQL at scale.

    Certain issues may hinder GraphQL in practice. To review, security concerns require a nuanced approach to authorization. This is because it wraps multiple data retrieval points into a single request. Without native caching, performance could also suffer. Changeability is also required to continually update the graph, which may ruffle feathers with those seasoned in the world of REST where a guiding tenet is to build for longevity using web-compliant methods.

    According to Jens Neuse, CTO, WunderGraph, there is a simple way to mitigate most of these issues and harmoniously work with various API styles. To Neuse, the core problem is that GraphQL is not meant to be exposed over the internet. Instead, he advocates for interacting through a gateway. Such an intermediary would enable more implicit calls and proper authentication and authorization for specific underlying functions and resources. Using GraphQL as an internal integration layer could also help combine disparate APIs into a similar language, exposing GraphQL-like usability for frontend developers while allowing them to hit any API style on the backend.

    Below, we’ll consider the drawbacks of exposing GraphQL directly and see how an intermediary layer could benefit development. We’ll also uncover what open source software is on the horizon that could power this setup.

    Why GraphQL Shouldn’t be Exposed Publicly

    Facebook, the creator of GraphQL, uses an internal GraphQL API to power all of its apps across Android, iOS and web browsers. (This is not to be confused with their public Graph API). Interestingly, if we look at Facebook’s use of GraphQL, we see these endpoints are not exposed to the public web at all.

    It’s true. Open up Developer Tools in Chrome, and you’ll see there is not a single mention of a root HTTP endpoint like https://api.graphql/. Functions name GraphQL, sure, but they call it more implicitly. Other companies, like Twitter and Airbnb, use a similar abstracted approach to interact with a private GraphQL.

    In fact, most GraphQL APIs are not public. APIs.guru only charts 35 public GraphQL APIs—notable services include GitHub’s GraphQL API, Shopify Storefront and GitLab. This number is minuscule compared to the total number of public APIs, at over 24,000 according to ProgrammableWeb.

    A Layer In Between

    If we treat it as Facebook intended (and how they use it in production today), it could reverse the issues above, said Neuse. “These problems come down to our core belief that GraphQL is not supposed to be exposed over the internet,” he said.

    But if clients do not access a GraphQL endpoint, what are they interacting with? According to Neuse, the ideal architecture involves a layer between the client and the server. Such a layer would validate queries and represent verbose calls with simple functions. The process would involve a handshake as follows:

    1. Take query, store it on a server.
    2. Validate it; make sure it’s not malicious.
    3. Send back a handle to the client.
    4. Then, execute the query.

    Such a process could also enact universal policies on a per-function basis, thus solving potential authorization issues when fetching data from multiple backend services with a single query.

    “The issue is that using the query language comes with a cost,” Neuse said. “Not exposing GraphQL directly but ‘compiling’ it to a JSON-RPC API when deploying solves these problems.”

    Thus, the scalability issue isn’t so much an issue of size but of access. “GraphQL can be very valuable, even in small environments,” said Neuse.

    The Next Evolution of a Virtual Graph

    Another potential benefit of using GraphQL as an intermediary is combining APIs; a “virtual graph,” as Neuse calls it. This virtual graph offers a common integration language to interact with various API styles, whether REST, GraphQL, gRPC or webhook, in a GraphQL-like manner.

    Consider the ease with which package managers like npm enable developers to instantly install dependencies. For example, installing a package like React.js is as simple as initiating the command npm install react within Terminal.

    On the other hand, the API integration is very cumbersome. Users must read through documentation, create an account on a third-party site and download an SDK to call the service in their preferred language. So, why isn’t looping in dependencies like APIs and cloud services as simple as other common dependencies?

    According to Neuse, one reason is that the REST paradigm is obsessed with the resource constraint—aside from HATEOAS, it lacks a concept of relationships between data and fields. A virtual graph could enable a straightforward process similar to package managers, said Neuse. Interestingly, the WunderGraph team plans to open source a project that allows just that ability.

    GraphQL as a Meta Layer

    Many folks assume that GraphQL and REST are mutually exclusive. However, as we’ve seen, there are ways to use them in combination. Plus, with an abstraction layer, the REST versus GraphQL comparison becomes just an underlying technical nuance.

    “If you compare GraphQL to other specifications, like OpenAPI spec, you see GraphQL has the fastest-growing community,” said Neuse. As of 2021, JSON Schema is the most popular, used by 75% of developers, followed by Swagger 2.0 (54%), OpenAPI 3.0 (40%) and GraphQL (31%) according to the Postman State of API Report. While this number may be small now, 35% of respondents also said they plan to use GraphQL in the coming year.

    “It’s a very, very interesting movement,” said Neuse. What began at Facebook as a framework for data fetching for React apps has now expanded into something much bigger. Within this second new movement, largely driven by companies like Apollo and Hasura, GraphQL becomes the new data layer, he said.

    “Still, everybody is looking at GraphQL thinking they must migrate from REST—this is the wrong direction,” said Neuse. Instead of migrating all existing REST APIs to GraphQL, he predicts the industry will coalesce on using GraphQL as the integration language for querying REST APIs. A meta layer, if you will.

    Of course, meta has been a bit co-opted lately with Facebook’s rebranding …