A public cloud is a platform that uses the standard cloud computing model to make resources, such as virtual machines, applications, or storage, available to remote users.  Public cloud services may be free or offered through several subscriptions or on-demand pricing schemes, including a pay-per-usage model.

Public cloud is an alternative application development approach to traditional on-premises IT architectures. In the basic public cloud computing model, third party hosts scalable, on-demand IT resources and provides them to users over a network connection, either the public internet or a dedicated network.

A low-code development platform is an app that provides the Graphical User Interface for Programming and develops the code at a fast rate, and reduces the traditional programming efforts. Therefore, many public clouds and big tech companies use low-code and no-code platforms to build internal workflow applications and rapidly develop customer-facing experience. Low-code and no-code platforms provide an alternative option when the business requirements matched the platform’s capabilities.

Many low-code platforms have been available in the market for more than a decade. And some of these support tens of thousands of business applications. Over time such platforms have enhanced capabilities, developer experience, hosting options, enterprise security, application integrations, and other competencies that allow rapid development and easy maintenance of the functionally rich application.

Why Public Clouds and machine learning, Target Low-code Platforms

There are two reasons why public clouds and big tech companies target low-code platforms.

First, public clouds companies target development and engineering teams that want to code apps, automate Continuous Integration/Continuous Deployment pipelines, and instantiate infrastructure as code—developing products for citizen developers and others who wish to build them with low-code requires different experiences, tools, and functionality.

Second, stand-alone-low-code platforms have evolved through multiple computing paradigms. Some go back to client-server days. Newcomers would offer matching capabilities and the strategies and motivations to remain relevant.

In some cases, the low-code platforms are woefully behind stand-alone platforms. On the other hand, they demonstrate how low-code can enable machine learning, chatbots, voice interfaces, spatial search, and more.

Low-code Development Platforms

monday.com

monday.com offers a low code development platform that helps to digitize processes and workflows. It increases employees’ productivity and engagement, helping with fast building functionality as per requirements.

The platform helps to automate the workflow without coding. It has interactive boards and custom forms that provide business data in a quick and standardize way. monday.com can be seamlessly incorporated with existing data and tools. It has over 50 prebuilt adapters to integrate it with in-house built systems through an open API.

Visual LANSA

Visual LANSA’s low-code platform stimulates and simplifies enterprise apps while making the development team more productive. It develops apps faster, easier, and at a lower cost than traditional methods. It can write code inside the IDE. It is the only platform that runs on IBMi, Windows, and Web.

Quixy

Quixy is a no-code BPM and Application Development Platform. It can be used by the business of any industry to create complex enterprise-grade apps. Application development will be 10X faster without writing any code. Quixy has dozens of prebuilt solutions for various use cases such as CRM and Project & Task Management.

KiSSFLOW

KiSSFLOW, BPM, and workflow software enables to create custom apps and automate business processes. It delivers more than 45 pre-installed apps to develop business apps. It provides a cloud-based solution that can be used by businesses of any size and from any industry.

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*Big Tech soon may be asking people to opt into a nationwide tracking and data collection scheme to help public health officials predict the next coronavirus hotspot.

Amid multiple reports of foreign states like China and Israel using surveillance to suppress the spread of COVID-19, some U.S. experts are divided over whether individuals should give up their privacy to help contain the virus.

The Chinese government began requiring Chinese citizens to download new tracking software on their phones in February, which they use to update their health status, according to the state-run Xinhua News Agency. A person who updated her status to the color red, indicating she was sick, would not be allowed in public areas like subways or grocery stores.

This data was shared with Chinese police and used to contain the spread of the novel coronavirus and pinpoint virus hotspots.

At the beginning of April, U.S. tech giants Apple and Google announced a similar initiative with a key difference: It’s opt-in only, and any data they share with public health officials or the federal government will be made anonymous, or “de-identified.”  

“Since COVID-19 can be transmitted through close proximity to affected individuals, public health officials have identified contact tracing as a valuable tool to help contain its spread,” Apple and Google said in a joint statement. “A number of leading public health authorities, universities, and NGOs around the world have been doing important work to develop opt-in contact tracing technology. To further this cause, Apple and Google will be launching a comprehensive solution that includes application programming interfaces (APIs) and operating system-level technology to assist in enabling contact tracing.”

Apple and Google plan to launch the APIs for iPhones and Android phones in May, and then launch “a broader Bluetooth-based contact tracing platform by building this functionality into the underlying platforms,” which they say will be more reliable than APIs.

Apple’s and Google’s tracing plan is legal and not mandatory.

A privacy-focused research and activism group, Electronic Frontier Foundation, said any and all surveillance tactics deter free speech and association. The group also pushed back on the idea that de-identified data protects individuals’ privacy.

“Re-identification of de-identified data is a constant infosec threat,” the foundation said. “De-identification of location data is especially hard, since location data points serve as identification of their own. Also, re-identification can be achieved by correlating de-identified data with other publicly available data like voter rolls, and with the oceans of information about identifiable people that are sold by data brokers. While de-identification might in some cases reduce privacy risks, this depends on many factors that have not yet been publicly addressed, such as the careful selection of what data to aggregate, and the minimum thresholds for aggregation.”

The foundation said governments need to prove the necessity of surveillance tactics to contain COVID-19 before they roll out these programs.

“Even if governments could show such efficacy, we would still need to balance the benefit of the government’s use of these powers against the substantial cost to our privacy, speech, and equality of opportunity,” the foundation said. “The population that carries a networked phone at all times is not representative of the overall population; for example, people without phones skew towards lower-income people and older people.”

Roslyn Layton, a visiting tech scholar at the American Enterprise Institute, thinks Apple’s and Google’s idea is a good one as long as it remains optional and not mandatory.

“The key difference with surveillance, is, it’s one thing when you agree to it, and that’s what these companies are offering, and we’ve been using Apple and Google for a long time so they’re trusted, and they’re also governed by the rule of law,” said Layton. “I’m a huge fan of (their plan), if we’ve learned one thing from this virus, it’s that the problem is not too much data, it’s too little. In this crisis, we need more data than ever. We need to agree for our data to be processed for a mutually beneficial reason. People like to use their data for social good.”

But the foundation worries that once this data is collected, it could easily be bartered and traded on a Big Data black market.

The foundation “has long opposed location surveillance programs that can turn our lives into open books for scrutiny by police, surveillance-based advertisers, identity thieves, and stalkers.”

Because the coronavirus is predicted to outbreak a second time in the U.S. later in the year, Layton thinks the opt-in tracking approach could be very valuable, and that individuals should consider it in the name of public health.

“Does that mean everyone has to participate and all your data becomes part of the state, no, it’s opt-in, you can opt-out, and it’s governed by laws which we have transparency about,” Layton said. “That, I’m personally comfortable with and can live with.”

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