Cloud Hosting

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Register today!

Carbon emissions, as a key driver of environmental change, are coming increasingly under scrutiny by government regulators and in the court of investor opinion. Recent moves by the Biden administration to limit greenhouse gasses and by the SEC to force all public companies to disclose even low levels of carbon footprint impact have garnered significant media attention reporting and compliance trends that are only likely to accelerate over time as the effects of climate change become more visible and pronounced.

The two most popular public blockchains, Bitcoin and Ethereum, employ a proof-of-work algorithm that consumes vast amounts of processing power, with Bitcoin alone using around 136 Terawatt-hours of electricity per year, more than the Netherlands or Argentina. Not only are these public chains massively inefficient on a per-transaction basis, but their power-hungry algorithms have inevitably led to block construction known as mining migrating to countries where environment laws are weaker and electrical power is produced from dirty sources, such as coal. This environmentally destructive footprint is inconsistent with the environmental stance of most U.S. public companies, the U.S. governments focus on carbon footprint reduction, and in the court of public opinion.

Private chains such as Hyperledger Fabric rely on 1990s era scale to peak capacity approaches that do not support auto-scaling or other dynamic capacity mechanisms. While more efficient than Ethereums proof-of-work protocol, they suffer from massive under-utilization of data storage mechanisms and their need for heavy, always on compute capacity drains power (and produces a carbon footprint) 24x7x365 regardless of actual transaction rates.

More modern approaches, such as Vendias blockchain, rely on more efficient serverless technologies and sustainable public cloud services. By exploiting these cloud-native technologies, modern blockchains offer tight cost enveloping and a carbon footprint that is actually lower than conventional (centralized) IT approaches to sharing data through hosted databases and APIs. Features designed to minimize file redundancy further enhance the ability of IT teams to improve storage efficiency without compromising functionality or security. Enterprises and companies of all sizes can benefit from both the speed of delivery and the improved cost and carbon footprint outcomes derived from SaaS-delivered blockchain capability using these newer approaches, allowing them to build cost-effective cross-cloud data fabric, partner data sharing and operational data service solutions while simultaneously improving their carbon footprint stance.

Signs of climate change routinely make headlines media attention that is increasingly shared with government and private industry attempts to control greenhouse gas emissions. Steps by the current U.S. administration to reduce carbon footprints and their resulting environmental damage include a variety of programs targeting supply chains, power production, and most recently SEC reporting requirements for public companies. While lowering greenhouse emissions and improving IT efficiency has been on the minds of CIOs for some time, this increased transparency and accountability is just the beginning of a push for compliance that will eventually rival SOC and PCI in its impact on R&D, business operations and investor reporting. Companies, especially larger enterprises, need to begin planning now for the inevitable impact of exposing their IT portfolio choices to the broader public.

Blockchain technologies offer companies a promising new platform for building everything from operational data store (ODS) systems that can span public cloud providers to secure partner data sharing that replaces conventional API-based solutions with blockchain-powered smart APIs. However, leveraging first generation blockchain technologies comes with unacceptable environmental costs:

As a result, blockchain technology has become associated in public opinion with a high, and largely unacceptable, carbon footprint. Thats unfortunate, because blockchains can actually improve carbon footprint, when implemented correctly. More modern approaches to blockchain protocols have focused not just on improving cost effectiveness and ease of use but also improving compute and storage efficiency, making it possible to actually decrease carbon emissions relative to conventional IT approaches.

In cryptocurrencies and other public blockchains, proof of stake has largely replaced proof of work in more modern implementations. Although proof of stake has occasionally been criticized as another form of centralization, it does avoid the high carbon footprint required by the Sybil attack-resistance proof-of-work approach. Public chains also serve a large, worldwide ecosystem, so at least the more popular ones enjoy a reasonable level of utilization.

Public chains still suffer from other forms of inefficiency: even when employing proof of stake, they are required to expend a large percentage of their computational resources maintaining Byzantine and denial-of-service attack resistance, rather than using those same resources to actual compute results. They also need to maintain a least common denominator approach to data modeling and storage that can serve anyone in their community, and cannot rely on optimizations based on data models or access patterns.

Worse, public chains are, well, public by construction, every node needs to maintain a copy of all information and updates from all sources, regardless of access patterns. So even experimental or test data from a no-longer-existent startup will have to be copied and maintained by every node in the network, in perpetuity. Similarly, if two companies want to use a public chain to communicate but dont necessarily need (or perhaps even want) others to participate in the exchange, every other node (and all auditing clients listening for updates) still has to be informed, making both data distribution and data storage vastly inefficient over time due to what the intentionally access pattern-agnostic approach of public chain design. Techniques designed to ameliorate these problems, such as sharding and L2 caches have their own drawbacks, usually including the fact that they are both more centralized in their approaches and that they place the burden of picking a subcommunity with which to communicate on every client.

These public chain drawbacks dont improve over time or with technology; in fact, as the throughput of streamed data and the total volume of stored data increase, they actually get worse. For all of these durable structural reasons, private chains will remain a more efficient and greener technology for applications such as partner data sharing, cross-cloud operational data stores, and real-time data fabrics than public chains.

First generation private chains, such as Hyperledger Fabric and Quorum, rely on known identities for node operators that do not require either Proof of Work or Proof of Stake to safely mint a block. However, as data sharing and data storage platforms go, they are woefully less efficient than modern, cloud-based approaches to storing and sharing data, such as Amazon DynamoDB or Azure CosmosDB. Cloud-based solutions such as these make more efficient use of infrastructure and electricity for several reasons:

Given that public cloud services have solved many of these challenges for centralized data sharing solutions, its natural to wonder if they couldnt be similarly applied to decentralized data sharing solutions, i.e. blockchains. And indeed, second generation blockchain approaches have done just that.

Numerous public cloud services are now described as serverless. While the term may seem somewhat ironic (given that they are, obviously, running on servers), the label conveys some important elements of both developer experience and implementation efficiency:

These multiple advantages of serverless technologies pass through into platforms built from them, as is the case with serverless blockchains technologies such as Vendias. Whats more, they not only improve on older private blockchain technologies that are always on, they actually improve on most conventional (centralized) approaches to building data sharing platforms, as the next section explores.

Conventional data center and commercial IT server utilization is notoriously low, with estimates ranging from 5-15% (i.e., 85-95% waste). Thats not surprising because any individual companys applications and solutions have typical usage patterns. Trying to fill in the low spots with their own or outsourced third-party workloads is tantamount to building their own version of a hosted serverless compute platform a challenge unreachable for all but the largest and most well staffed IT centers of the Fortune 50. For everyone else, their independent and isolated workloads effectively doom them to low server utilization rates, even when those servers are running in the public cloud.

Companies that need to build public APIs to share data across departments or organizations internally, to share data with business partners (in supply chains and other multi-company arrangements), or to create multi-cloud solutions find themselves in a predicament here: Building custom implementations to host the APIs, connect the APIs to the data, apply data integrity and constraint checks, create connectors to cloud and application data streams, implement event hooks and other notification solutions, and so on face an uphill battle. Not only are these implementations complex distributed systems that require high caliber engineering talent to develop and deploy, they require ongoing 247 operations support. And because they allow data to transit between companies, clouds, or organizations with differing compliance regimes, they face the highest levels of risk and scrutiny with respect to security, regulations, and policy enforcement. And because they are single use applications, they also suffer from low utilization. In the aggregate, owning a large portfolio of poorly utilized IT solutions, combined with upcoming reporting and transparency requirements, will be a significant liability for CIOs and CEOs to manage.

Modern blockchains offer a unique solution to these problems: By making it easy and secure to share real-time, operational data both internally and with partners, they lower time to market, remove project and security risks, and minimize the undifferentiated heavy lift of creating redundant data- and code-sharing platforms. By using modern, serverless blockchains, companies can simultaneously shift from 10% utilization in homegrown solutions to 100% utilization, because serverless solutions are only active when actual work is being performed, by construction. By leveraging the SaaS-style delivery of these blockchains, companies can also dramatically reduce the levels of staffing required to both develop and then operate the resulting systems, effectively shifting much of that burden onto the public cloud and blockchain service providers themselves, lowering IT costs even further. Finally, companies benefit from the massively multi-tenanted nature of the underlying cloud infrastructure, combined with the security and safety of having professionally managed fleets and software systems that are fully outsourced and staffed 24x7x365 around the globe. In short, adopting serverless blockchains allows companies to achieve higher utilization, lower environmental impact, faster time to market, and lower costs versus conventional approaches to building data-sharing solutions such as public APIs.

While databases may be the stars of enterprise data storage and sharing applications, the bulk of data owned and managed by companies is actually in the form of files. Thus, how files are shared, stored, exchanged, duplicated, and governed ends up having a larger effect on greenhouse gas emissions than database storage. Files are also key to partner data sharing solutions, as they often form the basis for both de jure and de facto industry data exchange standards.

The best modern blockchains manage files on chain along with scalar (database-held) data, treating them as native data types. But that alone isnt enough: To avoid the environmental impact of duplicating large volumes of (often large) data files, its also necessary to avoid creating unnecessary duplicates in the form of redundant copies of the data in every partners IT stack.

To accomplish this, blockchains such as Vendia also include sharing controls and dynamic file exchange. These features allow customers to set the dial anywhere from fully redundant copies (maximum operational isolation but also maximum environmental impact from redundant storage) to fully dynamic, where only a single copy is stored and then fetched on demand when other users with appropriate permission request it. In between are hybrid strategies, such as caching (fetch on first use) and quorum (maintain a small number of copies in strategic locations, such as one per public cloud). Without these critical operational controls, along with conventional governance and access controls, redundant file storage would quickly balloon out of control, invalidating any gains made from improved sharing of scalar data. This is one of the reasons that public chain file sharing solutions, such as IPFS and FileCoin, have not grown to be even a small fraction of a percent of cloud data storage solutions such as Amazon S3 the high cost, high latency, and low throughput of such systems blunts their decentralized advantages for all but the smallest size (and highest valued) files, making them a poor choice for most IT file sharing needs, such as partner data exchange.

Because blockchain technology ranges from the environmentally destructive (Bitcoin, Ethereum) to merely low utilization (Hyperledger Fabric, Quorum) to guarantees of perfect application utilization (serverless solutions such as Vendias), IT professionals facing technology choices need to be careful to ensure they are adoption technologies that will be both cost-effective and present their companies in the best possible light when carbon footprint reporting goes fully into effect. The following list will help identify technologies that improve a companys carbon footprint stance, rather than damaging it:

In a few short years, saving the environment has gone from a fringe movement to one of the top concerns of nations, influencing domestic and international policy. With new reporting requirements already present and the high likelihood of increased corporate compliance and reporting requirements likely, now is the time for CIOs, CEOs, and others to evaluate their IT choices and put strategies in place to lower carbon emissions over the long haul. Focusing on data and compute the two key drivers of cost and power consumption will enable companies to identify areas of improvement. With the increasing role of blockchains as mechanisms to share both code and data across companies and clouds, understanding and identifying which blockchain technologies and providers can help improve carbon footprint versus worsen it is an important question facing IT decision-makers and architects at all levels of an organization. The checklist provided in this article can serve as a vendor selection tool to help make informed decisions and guide a company towards a carbon and cost efficient solution.

Tim Wagner is a co-founder of Vendia, the inventor of AWS Lambda and a former general manager of AWS Lambda and Amazon API Gateway services. He has also served as VP of Engineering at Coinbase.

Welcome to the VentureBeat community!

DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.

If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.

You might even considercontributing an articleof your own!

Read More From DataDecisionMakers

Link:
Greenchains: Can blockchains save the environment? - VentureBeat

Digitization has transformed the way people meet, greet, and transact. However, it has increased the risks of cyber threats and data privacy breaches. As per reports, India ranks third in terms of the number of data breaches globally. The number of user accounts impacted has quadrupled since 2020. This is primarily due to the accelerated digitization since the pandemic.

Financial Services Sector is most prone to Cybercrime

As per the Indian Computer Emergency Response Team (CERT-In), over 2.9 lakh cyber security incidents related to digital banking were reported in 2020. These include website hacking, network scanning and probing, viruses, and phishing attacks.

Fintech companies are on the radar of cybercriminals since they produce huge volumes of data. The rise in popularity of NBFCs and e-commerce has witnessed a significant spike in digital payments. The sector has sensitive customer data like Aadhaar, PAN, demographics, and transactional details stored on cloud servers, raising the associated risk impact of KYC leaks, cyber threats, frauds, and data privacy breaches. This valuable data can be used to commit frauds or sold for ransomware attacks.

There are also reports of fake loans disbursed in the customers names without their knowledge and consent by fintech apps. This negatively impacts their Cibil score as credit reports have listed loans as defaults they never availed for.

Many financial institutions are not cloud-native, and still struggle with building secure cloud infrastructure. The vulnerable sector needs a robust digital infrastructure and solutions to ensure data security and protect customers creditworthiness.

Data security through AI-enabled digital KYC

Back in the day, Know Your Customer (KYC) was a tedious process of signing and verifying documents that required multiple face-to-face meetings between customers and financial institutions agents/ employees. Fast forward to today, fintechs have created a revolution and introduced a new era of the digital KYC process and creating exceptional user experiences.

RBI approved the video KYC process in January 2020. The seamless online process authenticates the customer identity through smartphones, tablets, or laptops via a live video interface. In this process, a representative from the financial institution is online at the other end to undertake the first step of due diligence of customers before onboarding. The entire process has become cost and time-efficient for both parties. V-KYC agents are 15-20x more effective than an in-field agent in completing KYC processes, and building digitized and auditable records for future reference.

Though VKYC is inherently secured, it is essential to implement additional layers of security. RBIs guidelines have mandated financial institutions host the technological infrastructure in their in-house premises to adhere to the baseline cybersecurity framework. Also, industry experts suggest refraining from using third-party apps for recording the process.

RBI has revised the KYC norms and extended VKYC to small and medium enterprises (SMEs), and allowed limited KYC accounts to be converted to full KYC accounts through video KYC. This is a great initiative to scale up data security measures for large populations.

Regulatory authorities like the RBI, SEBI, IRDAI, and PFRDA have directed financial institutions to opt for plug-and-play video KYC solutions. The recommendation also suggests using AI-enabled digital KYC solutions to enhance integrity.

New-age video KYC

The platform-agnostic solutions are flexible enough to be integrated with the existing systems. The go-live for some of these solutions is as low as 2 weeks for a bank, which allows banks to innovate at rapid speed. They offer features like two-way video calling and one-way recording, concurrent auditing, location based geo-tagging for compliance, intelligent routing for managing agent productivity. The AI-enabled image processing softwares are used for facial recognition by comparing user images across various documents like photo id proofs, selfies, and studio photographs.

For additional security checks, each customer is validate through a liveliness check with customized live-action commands, records are confirmed against USs Office of Foreign Assets Control and other sanctions lists.

Way forward

Every single reported fraud sets the ecosystem back sometimes, in the form of archaic processes, or higher cost of service for other customers, and an overall let down of customers confidence. Digital lenders need to balance user experience and fraud checks to minimize losses and reputation risks by regularly examining their IT and risk management systems.

India is one of the first countries to introduce the video KYC option for the financial services sector; AI-enabled technology evolves each day to strengthen the security of fintech platforms, and creates opportunities for banks to go for improved experiences at reduced risk.

Views expressed above are the author's own.

END OF ARTICLE

Read more:
How Video KYC has strengthened the security of fintech platforms - Times of India

Where does connected vehicle data go, and how can its lifecycle be managed? Freddie Holmes speaks with Dell to find out

A single connected vehicle will produce and share a fair amount of data as it roams through a smart city. As vehicles add more features and become more autonomous, the amount of data created by each vehicle will increase significantly. Where that data goes, what it is used for and how long it persists varies by application, but one thing is clear: data lifecycle management is becoming increasingly important for the automotive industry, and how this service is consumed will be vital.

New vehicles are already highly connected today but are set to become even smarter in coming years, boosting the amount of data being created and consumed. At the same time, cities are being outfitted with 5G cell towers, sensors inside of multi-access edge computing (MEC) units, roadside units (RSUs) and compute and storage servers to help enable the communication between a large number of disparate devices and workloads. For cars to speak with the city and vice versa, data must be shared rapidly, reliably and often in high volumes. As such, edge computing has become a hot topic for the automotive industry and those working on smart cities.

Edge servers allow data that is gathered from different connected devices around the city to be processed more closely than if the server was in the cloud, for example. Upload and download speeds and latencies are greatly improved by having a local edge server, and this will become invaluable in coming years as more smart vehicles hit the road. Autonomous vehicles (AVs) will push data demands even higher.

In todays automotive industry, edge computing is used primarily in a controlled test and development environment outside of a primary data centre. As more connected vehicles hit public roads, the role of edge computing will skyrocket.

When we start to talk about these vehicles being released into production, thats when the edge gets very large, very quickly, explained James Singer, a Technologist in the Infrastructure Solutions Group at Dell Technologies. Edge Infrastructure is required to send data to where it needs to go; today, much of it goes to the cloud or on-premises data centres. Because of the expected volumes of data, there will be many use cases that will need to be processed on the edge.

For example, there may not be enough time or bandwidth to send lumps of data to a data centre or to the cloud for it to be cleaned, tagged, trained and sent back to the car in the form of an over the air (OTA) update. There will need to be some kind of edge compute where data can be sent to servers that are close to where the vehicle resides, explains Singer. That kind of infrastructure doesnt exist at scale yet, but it will as the industry continues to improve vehicle functionality.

An important question the automotive industry may ask or is already asking, says Singer, is how the data gets from the vehicle to the cloud or to a hosted data centre. The industry is also trying to flesh out who will guarantee that the data makes it to its final destination securely, as well as who gets to see the data once it leaves the car. Then there is the question of whether the data persists on an edge server or if all data must be sent to one location. Since the data is mobile and disaggregated, how will the data be gathered and find its way home? asks Singer. Will automakers or Tier 1/Tier 2 suppliers be required to build out their own edge compute, networking and storage? These are all valid questions.

One thing is for certain, the automotive industry will consume compute and storage functionality as a service

Questions such as these centre around one key consideration: how will the automotive industry consume edge computing? Dell believes that Edge as a Service (EaaS) is the answer and is currently investigating what is required to make this vision a reality.

The idea is that EaaS will allow automakers to leverage the skills and resources of end-to-end edge infrastructure providers. In effect, it will provide a turnkey edge solution for automakers as they look to bring new connected and autonomous features to the mass market. It follows similar trends around Software as a Service (SaaS) and Platform as a Service (PaaS), which have both accelerated the industrys move toward digitalisation.

Dells technologists and engineers are investigating numerous variables that will influence how EaaS is offered. These include everything from environmental factors such as power and cooling requirements to physical and data security, how the compute and storage will be serviced, and whether certain data will persist at one particular location or eventually make it back to the cloud. There are many unknowns about how data will flow in the automotive pipeline, Singer emphasises. But one thing is for certain, the automotive industry will consume compute and storage functionality as a service.

In theory, this mobility sensor data will be put to good use, but as Singer explains, it is about prioritising what data leaves the car, what data is stored and perhaps even what data is no longer needed. In a fully-fledged production environment, we will need to be more judicious about what data leaves the car, what is deleted, what is stored and what can be processed locally in the vehicle, he says.

Recent advances around cellular vehicle-to-everything (C-V2X) will make things slightly more complex on the data management front. With C-V2X, there will be a huge amount of chatter between RSUs, cell towers, local and cloud infrastructure and other vehicles. This is where the volume of data starts to become a real challenge, and surrounding resources that are aware will not only be the creators but also the consumers of data, he adds.

A vehicles on-board sensors are constantly gathering information. A vehicle might spot that a crash has caused a road block, for example, or that a group of nearby school children could be at risk as they approach a pedestrian crossing. A section of road might be icy or damaged, and the safety driver or passengers (if fully autonomous) could send a distress signal to emergency services. When video data starts being shared in high volumesand in higher qualitythis is when the edge will become invaluable.

Basic data being transferred from vehicle to vehicle and vehicle to infrastructure might be in the realm of kilobytes, explains Singer. But when were talking about data streaming from the video cameras on these fleets of AVs, that will accumulate a huge amount of data. Even if it is only 10% of what is being created by the AVs various sensors, that is then multiplied by thousands of cars. The scale becomes tremendous. While LiDAR generates more data than RADAR, GPS, Ultrasonic and IMU, he explains, it does not come close to the amount of data coming from a video camera. Many vehicles already use 1K cameras, but that will transition to 4K and in the future maybe even 8K, Singer observes.

Pushing data back to a core data centre would be a long journey emphasises Singer, and thus the general trend over the next few years will be to locate compute power and storage closer to where data is being created. As edge servers will be in a different environment compared to that of a secure core data centre, the next challenge will be ensuring this infrastructure does not fall prey to cyber attacks. There are many potential attack vectors, and in this environment the idea of a firewall is no longer going to be good enough, Singer warns.

It will require a robust partnership between many different companies to make this happen

As the megatrends of 5G, autonomous driving and smart cities converge, an end-to-end edge infrastructureprovided to automakers through EaaSwill prove invaluable. This ecosystem will extend from the edge, to core data centres, and to the cloud, helping to manage the increasingly complex data lifecycle of next-generation mobility.

The benefits of edge computing to the automotive industry and smart city developers are clear, but individual players cannot approach all this on their own. Singer urges that stakeholders across the ecosystem work together if this application of the edge is to become a reality. Dell will not be able to build out all of this edge infrastructure on its own, he concludes. It will require a robust partnership between many different companies to make this happen.

Go here to see the original:
'Edge as a service' to play vital role in automotive - Automotive World