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Adopting Edge Computing for Web Apps – 4 Key Enablers – ReadWrite



Adopting Edge Computing for Web Apps - 4 Key Enablers - ReadWrite

In the last few years, the uptake of internet-connected devices has grown exponentially, and it will not slow down in the coming years. According to Gartner, by 2023, the average CIO will be responsible for more than three times the endpoints they managed in 2018. However, supporting such a surge would require scaling-up of the cloud infrastructure and substantial provision of network capacity, which may not be economically feasible.

In such cases, edge computing could emerge as a solution as the required resources, such as computing, storage, and network can be provided closer to the data source for processing.

Businesses are looking for insights that are near-real-time and actionable, which is fueling edge computing’s uptake across industries. Edge computing’s benefits are well known, and in a previous article, I illustrated the benefits and some use cases.

Adopting Edge Computing in Web Application Development

It is only a matter of time before edge becomes mainstream, as demonstrated by a recent IDC survey that found 73% of respondents chose edge computing as a strategic investment. The open-source community, cloud providers, and telecom service providers are all working towards strengthening the edge computing ecosystem, accelerating its adoption and the pace of innovation.

With such tailwinds in favor, web app developers should focus on having an edge adoption plan in place to be more agile and leverage edge’s ability to improve user engagement ratio.

Benefits like near real-time insights with low latency and reduced cloud server bandwidth usage bolster the uptake of edge computing across industries for web applications. Adopting an edge-computing architecture for website applications can increase productivity, lower costs, save bandwidth and create new revenue streams.

I have found there are four critical enablers for edge computing that help web developers and architects get going.

1. Ensure application agility with the correct application architecture

The edge ecosystem comprises multiple components like devices, gateways, edge servers or edge nodes, cloud servers, etc. For web applications, edge computing workload should be agile enough to run on edge ecosystem components, depending on the peak load or availability.

However, there could be specific use cases like detecting poaching activity via drone in a dense forest with low or no network connectivity, which demands developing applications native to the edge devices or gateways.

“Adopting cloud-native architectural patterns like microservice or serverless provide application agility. Cloud native’s definition as explained by the Cloud Native Computing Foundation (CNCF) supports this argument: ‘“Cloud native technologies empower organizations to build and run scalable applications in public, private, and hybrid clouds.’”

Features such as containers, service meshes, microservices, immutable infrastructure, and declarative application programming interfaces (APIs) best illustrate this approach. These features enable loosely coupled systems that are resilient, manageable, and observable. They allow engineers to make high-impact changes frequently and with minimal effort.”

The foremost step in edge computing adoption would be to use a cloud-native architecture for the application or at least for the service that is to be deployed at the edge.

2. Get benefits of edge infrastructure and services by adopting CSPs

Cloud Service Providers (CSPs) offer services like computing and storage local to a region or zone, which act like mini/regional data centers managed by CSPs. Applications or services adhering to the “develop once and deploy everywhere” principle can be easily deployed on this edge infrastructure.

CSPs like AWS (outpost, snowball), Azure (edge zones), GCP (Anthos), and IBM (cloud satellite) have already extended some of their fully managed services to on-premises setup. Growth stage startups or enterprises can easily leverage these hybrid cloud solutions to deploy edge solutions faster and for greater security as they can afford the associated cost.

For an application running on wireless mobile devices that rely on cellular connectivity, new cellular 5G technology can provide a considerable latency benefit. In addition, CSPs are deploying their compute and storage resources closer to the telecom carrier’s network, which mobile apps like gaming or virtual reality can utilize to enhance the end-user experience.

3. Leverage custom code execution with CDNs

Content Delivery Networks (CDNs) have distributed Points of Presence (PoP) to cache and serve the web application content faster. They are evolving rapidly, and many PoPs now have language runtime like JavaScript (v8), which allows program execution closer to the edge. In addition, it increases security by migrating client-side program logic to the edge.

Web applications like online shopping portals can deliver a better customer experience with reduced latency when empowered with such services. For example, applications can benefit more by moving cookies manipulation logic to CDN edge processing instead of hitting the origin server. This move could prove effective when there is a heavy surge of traffic during events like Black Friday and Cyber Monday.

Moreover, such a method could also prove effective for running A/B testing. You can serve a fixed subset of users with an experimental version of the application while giving the rest of the participants a different version.

4. Use open deep learning model formats that provide ML framework interoperability

The diversity of neural network models and model frameworks has grown multifold in the last few years. This has encouraged developers to use and share neural network models on a broad spectrum of frameworks, tools, runtimes, and compilers. But before running a standard AI/ML model format on various edge devices, developers and entrepreneurs should look for some standardization to counter edge’s heterogeneity.

Open deep learning model formats like Open Neural Network Exchange (ONNX) is emerging as a solution as it supports interoperability for commonly used deep learning frameworks. It provides a mechanism to export models from different frameworks to the ONNX format. ONNX Runtime is available in other languages, including JavaScript. Both models and runtimes are compatible with various platforms, including low-ower-edge devices.

The conventional approach for machine learning applications is to generate AI/ML models in a compute-intensive cloud environment and use that model for inferencing. With AI/ML JavaScript frameworks, it is possible to execute inference on browser-based applications. Some of these frameworks also support training models in browser or JavaScript backend.

The right technology decisions secure better business values

In working with dozens of startups, I have found that the best business decisions sometimes depend on early adoption of emerging technologies like edge computing for better impact on customers.

However, adopting emerging technology takes forethought and planning to be successful. By following the enablers above, you are well-positioned for seamless and sustainable integration of edge computing to develop web-based applications.

Image Credit: Ketut Subiyanto; Pexels; Thank you!

Pankaj Mendki

Pankaj Mendki is the Head of Emerging Technology at Talentica Software. Pankaj is an IIT Bombay alumnus and a researcher who explores and fast-tracks the adoption of evolving technologies for early and growth-stage startups. He has published and presented several research papers on blockchain, edge computing, and IoT in several IEEE and ACM conferences.


Fintech Kennek raises $12.5M seed round to digitize lending



Google eyed for $2 billion Anthropic deal after major Amazon play

London-based fintech startup Kennek has raised $12.5 million in seed funding to expand its lending operating system.

According to an Oct. 10 report, the round was led by HV Capital and included participation from Dutch Founders Fund, AlbionVC, FFVC, Plug & Play Ventures, and Syndicate One. Kennek offers software-as-a-service tools to help non-bank lenders streamline their operations using open banking, open finance, and payments.

The platform aims to automate time-consuming manual tasks and consolidate fragmented data to simplify lending. Xavier De Pauw, founder of Kennek said:

“Until kennek, lenders had to devote countless hours to menial operational tasks and deal with jumbled and hard-coded data – which makes every other part of lending a headache. As former lenders ourselves, we lived and breathed these frustrations, and built kennek to make them a thing of the past.”

The company said the latest funding round was oversubscribed and closed quickly despite the challenging fundraising environment. The new capital will be used to expand Kennek’s engineering team and strengthen its market position in the UK while exploring expansion into other European markets. Barbod Namini, Partner at lead investor HV Capital, commented on the investment:

“Kennek has developed an ambitious and genuinely unique proposition which we think can be the foundation of the entire alternative lending space. […] It is a complicated market and a solution that brings together all information and stakeholders onto a single platform is highly compelling for both lenders & the ecosystem as a whole.”

The fintech lending space has grown rapidly in recent years, but many lenders still rely on legacy systems and manual processes that limit efficiency and scalability. Kennek aims to leverage open banking and data integration to provide lenders with a more streamlined, automated lending experience.

The seed funding will allow the London-based startup to continue developing its platform and expanding its team to meet demand from non-bank lenders looking to digitize operations. Kennek’s focus on the UK and Europe also comes amid rising adoption of open banking and open finance in the regions.

Featured Image Credit: Photo from; Thank you!

Radek Zielinski

Radek Zielinski is an experienced technology and financial journalist with a passion for cybersecurity and futurology.

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Fortune 500’s race for generative AI breakthroughs



Deanna Ritchie

As excitement around generative AI grows, Fortune 500 companies, including Goldman Sachs, are carefully examining the possible applications of this technology. A recent survey of U.S. executives indicated that 60% believe generative AI will substantially impact their businesses in the long term. However, they anticipate a one to two-year timeframe before implementing their initial solutions. This optimism stems from the potential of generative AI to revolutionize various aspects of businesses, from enhancing customer experiences to optimizing internal processes. In the short term, companies will likely focus on pilot projects and experimentation, gradually integrating generative AI into their operations as they witness its positive influence on efficiency and profitability.

Goldman Sachs’ Cautious Approach to Implementing Generative AI

In a recent interview, Goldman Sachs CIO Marco Argenti revealed that the firm has not yet implemented any generative AI use cases. Instead, the company focuses on experimentation and setting high standards before adopting the technology. Argenti recognized the desire for outcomes in areas like developer and operational efficiency but emphasized ensuring precision before putting experimental AI use cases into production.

According to Argenti, striking the right balance between driving innovation and maintaining accuracy is crucial for successfully integrating generative AI within the firm. Goldman Sachs intends to continue exploring this emerging technology’s potential benefits and applications while diligently assessing risks to ensure it meets the company’s stringent quality standards.

One possible application for Goldman Sachs is in software development, where the company has observed a 20-40% productivity increase during its trials. The goal is for 1,000 developers to utilize generative AI tools by year’s end. However, Argenti emphasized that a well-defined expectation of return on investment is necessary before fully integrating generative AI into production.

To achieve this, the company plans to implement a systematic and strategic approach to adopting generative AI, ensuring that it complements and enhances the skills of its developers. Additionally, Goldman Sachs intends to evaluate the long-term impact of generative AI on their software development processes and the overall quality of the applications being developed.

Goldman Sachs’ approach to AI implementation goes beyond merely executing models. The firm has created a platform encompassing technical, legal, and compliance assessments to filter out improper content and keep track of all interactions. This comprehensive system ensures seamless integration of artificial intelligence in operations while adhering to regulatory standards and maintaining client confidentiality. Moreover, the platform continuously improves and adapts its algorithms, allowing Goldman Sachs to stay at the forefront of technology and offer its clients the most efficient and secure services.

Featured Image Credit: Photo by Google DeepMind; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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UK seizes web3 opportunity simplifying crypto regulations



Deanna Ritchie

As Web3 companies increasingly consider leaving the United States due to regulatory ambiguity, the United Kingdom must simplify its cryptocurrency regulations to attract these businesses. The conservative think tank Policy Exchange recently released a report detailing ten suggestions for improving Web3 regulation in the country. Among the recommendations are reducing liability for token holders in decentralized autonomous organizations (DAOs) and encouraging the Financial Conduct Authority (FCA) to adopt alternative Know Your Customer (KYC) methodologies, such as digital identities and blockchain analytics tools. These suggestions aim to position the UK as a hub for Web3 innovation and attract blockchain-based businesses looking for a more conducive regulatory environment.

Streamlining Cryptocurrency Regulations for Innovation

To make it easier for emerging Web3 companies to navigate existing legal frameworks and contribute to the UK’s digital economy growth, the government must streamline cryptocurrency regulations and adopt forward-looking approaches. By making the regulatory landscape clear and straightforward, the UK can create an environment that fosters innovation, growth, and competitiveness in the global fintech industry.

The Policy Exchange report also recommends not weakening self-hosted wallets or treating proof-of-stake (PoS) services as financial services. This approach aims to protect the fundamental principles of decentralization and user autonomy while strongly emphasizing security and regulatory compliance. By doing so, the UK can nurture an environment that encourages innovation and the continued growth of blockchain technology.

Despite recent strict measures by UK authorities, such as His Majesty’s Treasury and the FCA, toward the digital assets sector, the proposed changes in the Policy Exchange report strive to make the UK a more attractive location for Web3 enterprises. By adopting these suggestions, the UK can demonstrate its commitment to fostering innovation in the rapidly evolving blockchain and cryptocurrency industries while ensuring a robust and transparent regulatory environment.

The ongoing uncertainty surrounding cryptocurrency regulations in various countries has prompted Web3 companies to explore alternative jurisdictions with more precise legal frameworks. As the United States grapples with regulatory ambiguity, the United Kingdom can position itself as a hub for Web3 innovation by simplifying and streamlining its cryptocurrency regulations.

Featured Image Credit: Photo by Jonathan Borba; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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