• A developing technology called quantum networking may one day enable data transmission with higher security than is currently possible.
• Data can only move a relatively small distance when transmitted as light over a network before errors start to appear.

According to a recent report, Amazon Web Services Inc. has partnered with De Beers PLC to produce diamonds for quantum networks.

According to a recent Bloomberg report, a De Beers subsidiary named Element Six is involved in the partnership. The subsidiary has opened a facility in Oregon that can produce millions of artificial diamonds annually, meant for networking purposes. Element Six will work with an AWS division called the Center for Quantum Networking, which debuted last year, as part of the partnership.

A developing technology called quantum networking may enable data transmission with higher security than is currently possible one day. AWS intends to integrate the technology into its infrastructure, according to Bloomberg. For tasks like connecting cloud data centers together, quantum networking hardware might be used.

In a data center network, information is encoded to light and then transmitted over fiber optic cables to its final location. Quantum networks also use light to transmit data. However, they go about it in a way that makes it much more difficult for hackers to eavesdrop on data traffic secretly.

The observer effect, a phenomenon, causes observing subatomic particles to change some of their characteristics. The state of the photons passing through the fiber optic cables of a quantum network is altered when a hacker observes those photons. Therefore, the ensuing interference enables the network operator to identify a breach right away.

Quantum networks also make it difficult for hackers to copy traffic, which is another advantage. This lowers the possibility of data exfiltration, further enhancing security. Nevertheless, one of the biggest challenges to putting the technology into practice is how challenging it is to copy information in quantum networks.

Data can only move a relatively small distance when transmitted as light over a network before errors start to appear. The reason is that as light signals carrying data travel farther and farther from their source, they weaken.

Conventional networks have a repeater component as a solution to that problem. To prevent errors, it gathers information-carrying light pulses before they begin to fade, makes a new copy, and then sends the copy in place of the original. However, in quantum networks, copying data in this way is impossible, making it impossible to use conventional repeaters.

Quantum networks are unsuitable for connecting geographically dispersed systems because long-distance data transmission calls for repeaters. This limits the technology’s applicability to cloud service providers. The new alliance between AWS and De Beers aims to overcome this difficulty.

As part of the collaboration, the cloud behemoth is creating a novel repeater operating in quantum networks. According to reports, AWS intends to produce components using artificial diamonds grown by De Beers’ Element Six division. A significant step toward creating commercial-grade quantum networks would be the creation of a working quantum repeater.

According to Bloomberg, Antia Lamas-Linares, AWS Center for Quantum Networking head, expects the technology to be used in “years rather than decades.”

Competitors of AWS are also investing in cutting-edge networking technologies. Microsoft Corp. purchased the networking startup Lumenisity Ltd. in December of last year. The startup has created a new fiber optic cable to transmit data more securely and quickly than existing hardware.

Lumenisity’s cables differ from regular fiber optic links as they are hollow. Before being acquired by Microsoft, the startup claimed that data could move through the hollow core 50% more quickly than with standard network hardware. Additionally, the technology enables traffic protection using quantum encryption algorithms, which are more secure than the software used today.

• Oracle includes support for anomaly detection, recommendation, and multivariate time series forecasting in the engine along with some well-known machine learning apps.
• For efficient monitoring and workload planning, ML can be integrated with MySQL Autopilot.

Oracle Corp. enhanced the MySQL HeatWave product with latest automation features, ML capabilities, and enhanced performance on the cloud of Amazon Web Services Inc., capitalizing on its growing market share for hybrid transactional/analytical database management systems.

HeatWave, an in-memory analytical accelerator that was unveiled in late 2020, expands to thousands of cores, supports both real-time analytics and online transaction processing, and has made waves with its outstanding price-performance. Developers don’t need to extract data from another database to fill training models thanks to the embedded machine learning features.

As compared to AWS’ SageMaker managed machine learning service, which is priced independently from AWS’ Redshift cloud data warehouse, training is offered free for customers. According to Oracle, MySQL HeatWave is up to 99% less expensive and 25 times quicker than Redshift.

Oracle includes support for anomaly detection, recommendation, and multivariate time series forecasting in the engine along with some well-known machine learning apps. Anomaly detection is widely used in financial services to watch machinery and manufacturing environments as well as to find out why a credit card is being declined. Customers or viewers of videos can receive personalized recommendations from recommendation algorithms. Using numerous variables, multivariate time-series forecasting can resolve complex issues.

HeatWave AutoML can integrate models based on the Open Neural Network Exchange standard without the need for a machine learning framework. Nipun Agarwal, Sr. Vice President for MySQL database and HeatWave at Oracle, added that a large portion of the training procedure was also automated by the company.

He mentioned, “Not only do we now offer machine learning processing inside the database, but the training process, which is the more complicated part of machine learning, is fully automated as well.” This involves a voluntary choice of features, algorithms, and parameters. Oracle stated that other cloud services suggest only algorithms that require users to choose the most suitable one and tune it manually.

Agarwal reported, “All models can be explained because we use model diagnostic techniques. Users can run explanations directly from the console, which means no ML expertise is required. We have also introduced this notion of what-if scenarios where the user can toggle various attributes to see if it changes the outcome of the machine learning model.”

For efficient monitoring and workload planning, ML can be integrated with MySQL Autopilot. The feasibility of OLTP workloads provided by the Auto Shape Prediction can “make it very easy to see why autopilot is making the decisions does,” said Agarwal. Moreover, it recommends tables that can be purged or unloaded from the memory to lower the pricing. The suggestions are backed by visual analytics of archived performance trends that include buffer pool hit rate and throughput.

Oracle is also enhancing the integration of S3 object storage, CloudWatch, and PrivateLink into HeatWave to optimize it for use on the Amazon cloud. For mixed columnar representation, HeatWave now offers an optimized storage layer based on S3 object storage.

HeatWave copies the data it receives from MySQL to its scale-out data management component, which is based on S3. If reloading is necessary, Oracle said, the data can be loaded without the requirement for transformation, leading to noticeably quicker availability and recovery periods. Data never departs the AWS cloud, so egress fees are not applicable.

Agarwal commented that HeatWave on AWS works 10X faster than Snowflake Inc.’s namesake data warehouse and 20X as compared to Redshift. “HeatWave is designed from the ground up for distributed scale-out query processing. It has been designed for commodity hardware and since we use machine learning-based automation the system learns and improves on the fly,” he added.

Finally, Oracle is extending HeatWave nodes and altering their design and cost. For an additional USD 16 per month, a 32-gigabyte shape will be added to the current 512-gigabyte option. A standard 512-gigabyte node can now handle up to 1 terabyte of data, up from its previous limit of 800 gigabytes. According to Oracle, this results in a total price performance improvement of 15%.

• Customers get access to Value-Driven AI through the DataRobot AI Platform, a unique and team-based methodology that enhances how businesses are managed, expanded, and optimized.
• To help organizations maximize their current investments, DataRobot also unveiled a recently established cooperation with SAP.

This year, DataRobot Inc. is riding the tide of interest in artificial intelligence with the introduction of a significant upgrade to its AI development platform.

DataRobot AI Platform 9.0 is the most recent version, and it is currently accessible. New partner integrations, revised service offerings, and AI Accelerators are all included to assist businesses in realizing meaningful returns on their AI investments.

The DataRobot AI Platform offers tools for all of the crucial coding and software deployment processes required in developing machine learning applications and is intended to serve as the focal point of a company’s AI initiatives. DataRobot stands out because it caters to both corporate customers and data scientists. It offers a straightforward point-and-click AI builder for the latter group, enabling people to develop AI models without writing code.

It operates by first analyzing the task that the customer wants to automate using AI, and then it searches its library of pre-packaged algorithms for the best relevant neural network. Following that, the chosen neural network is fully automatically taught to complete that task.

Yet, data scientists frequently want to design their own unique neural networks, and DataRobot offers a feature called Composable ML to support this customer base. Customers can create a neural network using DataRobot’s no-code AI builder and customize it to their specifications using custom code; the business claims this method is quicker than starting from scratch.

With recent launch, DataRobot is introducing several new features to its platform, such as Workbench, a new user interface that the company claims will facilitate more collaborative experimentation and speed up the discovery of insights. To remove production obstacles and lower corporate risk, it also provides additional safeguards to guard against AI bias and automate AI model compliance.

Another feature is the new AI Accelerators and AI services, which, according to DataRobot, will assist clients in launching new AI projects and achieving results much more quickly than in the past.

In addition, DataRobot stated that its platform now has a brand-new connection with SAP SE and an improved Snowflake integration that will expedite data preparation, model creation, and monitoring. Clients may now build unique machine learning models in DataRobot and integrate them into the SAP application stack using business data from the SAP HANA cloud and other non-SAP sources.

According to Andy Thurai, principal analyst and vice president of Constellation Research Inc., AI, and machine learning are rapidly moving from experimentation to implementation. As a result, once a model has demonstrated its capacity to generate feasibly practical business value, it must be quickly implemented in production. DataRobot is enabling users to do this with today’s version.

“DataRobot is moving the conversation up the value chain. AI used to be model-driven, then later it was data-driven, and now with this push, DataRobot is making it business value-driven. If this works, it can sell to different personas at different ticket prices and a different value proposition than its competitors.” Thurai said.

Thurai clarified that one of DataRobot’s key advantages is that it employs more than 250 data scientists who collaborate closely with clients to advance their projects. DataRobot can also compete with hyper scalers like Amazon Web Services Inc. and Google Cloud because most of its new clients are cloud-based, according to the analyst.

Andy Thurai added, “The CI/CD, API, governance, and compliance improvements introduced today mean that DataRobot can easily plug and play with large enterprises, especially in regulated industries. The integrations with Snowflake and SAP mean enterprises can do their ML model work where the data resides without moving it around. In this way, DataRobot has created a true enterprise model based on business value, enabling it to sell at higher prices and longer terms than the competition.”

Ritu Jyoti, an analyst at International Data Corp., said the agreements are favorable since businesses require an AI solution that integrates effectively with their current investments and infrastructure. Ritu Jyoti further said, “With its platform and integration enhancements that make it easy for customers to deploy in their preferred environment, DataRobot has demonstrated leadership within a crowded market. Their compliance and governance is also uniquely positioned to drive value for customers today.”

With today’s release, DataRobot AI Platform, according to the company, is now accessible as a “Single-tenant SaaS” on Google Cloud, Microsoft Azure, and Amazon Web Services, enabling customers with the most strict security and compliance requirements to make use of a managed AI service. Red Hat OpenShift is now supported by DataRobot AI Platform’s on-premises version.

Debanjan Saha, Chief Executive of DataRobot, said, “Since our founding, we have been 100% focused on helping enterprises realize measurable value from AI by offering an AI lifecycle platform designed to solve business problems, and the applied AI expertise to help customers envision what’s possible – and achieve it,”

• PerfectScale provides tools that allow teams to optimize the performance of hundreds of Kubernetes clusters that are the foundation of their most critical applications.
• PerfectScale platforms can aid any flavor of Kubernetes, consisting of Google LLC’s GKE, Microsoft Corp.’s Azure AKS, Amazon Web Services Inc.’s EKS, and bare-metal deployments.

PerfectScale Inc. announced the general availability of its constant optimization platform for Kubernetes recently, giving enterprises a new option to automate the solidity of their information technology environments.

The software-as-a-service platform is directed at companies that control distributed, large-scale Kubernetes environments that manage modern, containerized applications. As PerfectScale clarifies, optimizing these environments is a manual, time-consuming, and challenging task that’s important to avoid spiraling cloud costs and application performance affairs.

To help with this, PerfectScale furnishes tools that permit teams to optimize the performance of numerous Kubernetes clusters that serve as the basis of their most critical applications. Its software engages advanced, artificial intelligence-based algorithms that assist in evaluating usage patterns and performance and cost metrics, empowering it to optimize its environments constantly to ensure resilience and stability at the minimum possible cost.

Amir Banet, Chief Executive and co-founder of PerfectScale, said system resilience and cost optimization are the biggest priorities for any firm that depends on Kubernetes to strengthen their applications. He explained, “Ineffectively allocating Kubernetes resources may cause performance and overspending problems today, and the problems will persist and get exponentially worse as the application scales. Our mission at PerfectScale is to help organizations get the most out of Kubernetes in an effortless manner by continuously and automatically optimizing each layer of the K8s stack.”

PerfectScale says its platform can aid any flavor of Kubernetes, consisting of Google LLC’s GKE, Microsoft Corp.’s Azure AKS, Amazon Web Services Inc.’s EKS, and bare-metal deployments with no operating software installed on the servers. Its prime features include resiliency risk detention to remove issues affecting the Kubernetes cluster’s performance, waste detection to remove not-so-important cloud costs and issue prioritization, to find and remediate the most pressing issues. It also furnishes analysis tools that assist teams in understanding better how system changes will affect their Kubernetes environments’ durability and cost-effectiveness, plus reports that track optimization progress.

The platform is aimed at businesses that manage distributed, large-scale Kubernetes environments. It is used to manage modern, containerized applications. Optimizing these environments, according to PerfectScale, is a complex, manual, and time-consuming task required to avoid spiraling cloud costs and application performance issues.

The platform was made available in the beta test last October and has been well-received by early adopters. Qwilt Inc., a provider of Open Edge technologies, said it was able to reduce its cloud costs using PerfectScale’s platform significantly.

Tomer Tcherniak, a senior site reliability engineer at Qwilt, said, “PerfectScale has removed critical blindspots we had in our Kubernetes environment. We found out many of our workloads and services were wasting nearly 90% of the resources we allocated. Not only are we significantly reducing costs, but we are also improving system performance to ensure we are giving our customers the best possible experience.”

• The new partnership will allow developers to deploy neural networks on SageMaker in just a few clicks.
• Amazon SageMaker and AWS-designed chips will let the team and larger machine learning community turn the latest research to reproducible models that anyone can build on.

Hugging Face Inc., the operator of a well-known platform that hosts machine learning models, is collaborating with Amazon Web Services Inc. to streamline the development of its artificial intelligence projects.

There was an existing collaboration going on since early 2021 which got expanded when the companies announced the partnership on February 21, 2023.

Adam Selipsky, AWS Chief Executive Officer, said, “Generative AI has the potential to transform entire industries, but its cost and the required expertise puts the technology out of reach for all but a select few companies. Hugging Face and AWS are making it easier for customers to access popular machine learning models to create their own generative AI applications with the highest performance and lowest costs.”

New York-based Hugging Face has received over USD 160 million in a recent funding round. It operates a platform that resembles GitHub, which helps developers to host open-source AI models plus technical assets such as training datasets. It allows storing code for over 100,000 neural networks.

Additionally, Hugging Face will use AWS as its preferred public cloud in accordance with the new collaboration. The business is also launching a new integration with the machine learning platform Amazon SageMaker. Developers can use the platform’s more than six cloud services to train, deploy, and create AI models.

With just a few clicks, developers will be able to deploy neural networks hosted by Hugging Face on SageMaker thanks to the new integration. After uploading an AI model in SageMaker, it can be trained by using AWS Titanium chips-powered cloud instances. The chips are curated exclusively for AI training tasks.

Neural networks deployed from Hugging Face to AWS work with many types of cloud instances, including the ones powered by AWS Inferentia accelerator series. These are basically the chips optimized to perform inference, or the tasks of running AI models right after the training phase gets completed.

Clement Delangue, CEO of Hugging Face, said, “The future of AI is here, but it’s not evenly distributed. Amazon SageMaker and AWS-designed chips will enable our team and the larger machine learning community to convert the latest research into openly reproducible models that anyone can build on.”

It adds essence to Hugging Face AWS Deep Learning Containers that the company already offers to developers as a part of the partnership. The containers make Hugging Face’s AI models available in prepackaged format which is easy to deploy in public cloud environments.

• Node infrastructure that connect with current blockchains and protocols and can link into the network with the right access is required to access this network for reading, writing, and computation.
• fm intends to use the additional cash to expand its engineering team and quicken the development of its current solutions to develop enhanced staking services.

Gateway.fm, a provider of decentralized blockchain infrastructure nodes, recently said it acquired USD 4.6 million in early funding. The money will give developers tools to access scalable Web3 infrastructure to create decentralized applications.

Lemniscap, an investment company specializing in blockchain businesses and cryptoassets, led the round. Several well-known cryptocurrency investors participated, including the Fantom Foundation, CMT Digital Ventures, Unstoppable Domains Ventures, and the LAO DAO.

Node infrastructure is necessary to operate blockchain and web3 technologies because nodes, rather than a single authority, validate and store data in decentralized networks. Nodes are devices that conduct all of the computing on the network and record the complete blockchain transaction history, such as computers, servers, or specialized machines.

Node infrastructure that connects with current blockchains and protocols and can link into the network with the right access is required to access this network for reading, writing, and computation. Gateway.fm’s solutions provide decentralized connectivity to blockchains without depending on centralized services like Amazon Web Services (AWS).

Co-founder and CEO of Gateway.fm, Cuautemoc Weber said, “I’ve felt that the spirit of decentralization at the heart of the Web3 movement has been undermined by limited access to scalable infrastructure. No more. We want to provide reliable node infrastructure, best-in-class validators and robust dev tooling to help Web3 projects scale at pace, while enticing financial institutions and enterprises to explore blockchain technology with confidence.”

By using its services, Web3 businesses can bypass any middlemen and access nodes directly using remote procedure calls, enabling it to offer a highly decentralized service.

The business offers access to free Public RPC calls on the Ethereum mainnet for up to 30 queries per second to test the service. Additionally, the company provides corporations with an enterprise solution that includes elastic pricing, unlimited requests, and comprehensive analytics.

Customers may easily create node networks for Ethereum staking, a method of using the ether cryptocurrency to support the blockchain’s security and receive rewards, using Gateway Grow. Those who stake a cryptocurrency and lock it up for a while to demonstrate that they have a “stake” in the blockchain, receive a reward after transaction validation. Proof-of-stake chains like Ethereum, Gnosis, and IXO can link to Grow.

The business offers Gateway Access, a fast, scalable Web3 RPC node service for customers looking for decentralized blockchain access. Now, it is accessible in Singapore, Switzerland, Sweden, and Germany, offering 3,000 procedure calls each second or 260 million per day. Ethereum, Gnosis, Fantom, and NEAR are now supported by access.

Finally, by offering decentralized, scalable decentralized node access for early development, Gateway Jumpstart enables engineers to create new blockchains and protocols to quickly get their projects off the ground and spur user adoption.

Many major players fill in the market of blockchain infrastructure solutions, including well-known firms like Alchemy, Infura, and Blockdaemon. Large cloud service providers Google Cloud and Amazon Web Services Inc. have recently started offering nodes-as-a-service options. Node, a blockchain node infrastructure solution, was introduced by crypto exchange Coinbase Inc. as a part of Coinbase Cloud.

According to Gateway.fm, it intends to use the additional cash to expand its engineering team and quicken the development of its current solutions to develop enhanced staking services.

• Procyon Inc., a provider of secure access management for multi-cloud enterprise infrastructure, announced that it has raised USD 6.5 million in funding for the launch of its privileged access management platform.
• The Procyon Multi-Cloud Privilege Access Management platform is a solution that gives developers instant access to what they need, with sufficient privileges to perform what they need, and without requiring passwords.

Procyon Inc., a provider of secure access management for multi-cloud enterprise infrastructure, announced that it has raised USD 6.5 million in funding for the launch of its privileged access management platform, which, according to the company, will revolutionize how DevOps teams and developers access cloud services.

Lobby Capital led the financing round, with GTM Capital and First Rays Venture Partners also participating.

As multicloud environments become the norm, said Procyon co-founder and CEO Sukhesh Halemane and Chief Business Officer Akash Agarwal, accessing them securely has gotten more complex and challenging for developers. At the same time, cybersecurity teams have been strengthening their defences since many people with access to cloud environments have the power to compromise important data.

Sukhesh Halemane stated, “One of the biggest worries is highly privileged users having access to the crown jewels getting compromised, and if you think about it in the cloud every user who has access to the database account is a privileged user. A second problem is that either developers are struggling to get access to something, meaning they’re sending email or Slack messages and two days later they finally get access, or they have too much access, such as they have too many privileges assigned.”

The Procyon Multi-Cloud Privilege Access Management platform is a solution that gives developers instant access to what they need, with sufficient privileges to perform what they need, and without requiring passwords.

On the developer access end, the platform eliminates passwords by leveraging the Trusted Platform Module present in computing environments – such as PCs, laptops, and mobile devices – to authenticate devices in conjunction with an identity management provider such as Okta Inc. Procyon attaches user identities cryptographically to the resources they will access via TPM.

The business claims that the credential itself is safe and eliminates the need for password managers or vaults, hence removing everything that can be readily stolen. For more sensitive functions, TPM can also be integrated with biometrics such as fingerprint readers and FaceID on laptops and mobile devices for even greater protection.

The average cost of a data breach is USD 4.35 million, according to the 2022 cost of data breach research by IBM Corporation and the Ponemon Institute. The most prevalent cause of data breaches was stolen or compromised credentials, which required the greatest time to discover. Some breaches of major corporations in 2022 were the result of stolen credentials, such as the September hack of Uber Technologies Inc.

In conventional cloud systems, developers may have perpetual access to cloud resources that provide them credentials to sensitive systems. This renders them vulnerable to social engineering attacks like phishing, in which a hacker attempts to deceive a victim into divulging their password and other information.

To prevent this, Procyon provides a self-service portal where developers may request access to the precise resources they require, along with the duration of their requirement, and obtain access via a password-free method. The security team may design approval policies based on a variety of parameters, including compliance requirements, resource, identity, and approver. The rights can also be programmed to expire after a certain period of time, indicating that they are temporary.

This is known as “zero standing privileges” and “just-in-time access” in the industry, because it helps avoid the possibility of an attacker gaining access to overprivileged resources or a user account.

Akash Agarwal, Chief Business Officer at Procyon said, “In olden systems, you’d be given a password and access to these systems that you would retain for some period of time, in many cases forever. And you left the company and your email is being disbanded and maybe your access to corporate, but we’re discovering that other access that you shared over Slack still remains with you. Unless the company has a super-comprehensive system to know who was given access to what, they can’t revoke that. That’s what leads to compromises and the sale of credentials on secondary markets.”

The self-service portal is compatible with all major cloud providers, including Google Cloud, Microsoft Azure, and Amazon Web Services, and keeps track of all administrative rights and responsibilities. Procyon refreshes these roles whenever they are modified on these services so that business procedures do not fail.

If anything does go wrong, such as an account or service being accessed maliciously, Procyon’s platform provides a “kill switch” that can terminate sessions, devices, and accounts from accessing the system immediately. According to the firm, this is made simple since the platform stands between the developer and every service with which they connect and has a complete view of every authentication transaction and session. Agarwal highlighted that as the complexity of multicloud systems increases, so does the value of Procyon for corporate organisations.

Akash Agarwal further said, “With businesses with large engineering teams can’t manage this. They have full-time identity management teams where it’s someone’s job to provide you identity and access and that person is just overwhelmed trying to manage it. If you think about it, Procyon’s value proposition becomes compelling because we give that person automation. We give the entire DevOps team automation to manage privileges and eliminate potential compromises with what we do.”

• The launch comes almost a year after Akamai bought Linode LLC, a provider of infrastructure-as-a-service, for about USD 900 million.
• Akamai claims that all cloud services will adhere to ISO, SOC 2, and HIPAA standards and that introducing the Akamai Qualified Computing Partner Program would increase their utility.

Akamai Technologies Inc., which provides content delivery network and offers cloud services, recently, announced that it is launching a huge distributed edge and cloud platform called Akamai Connected Cloud.

It is made to work with cloud computing, content delivery, and security in a way that brings experiences and applications closer to end users and protects them better from security threats. The launch comes almost a year after Akamai bought Linode LLC, a provider of infrastructure-as-a-service, for about USD 900 million.

Linode was a competitor to cloud services like Amazon Web Services Inc. and Google Cloud, but it was much smaller and less complicated. It was made for small developers who didn’t want to be stuck with big companies or get nasty surprises when they got their bills. At the time of the purchase, Akamai said it would use Linode’s features to make itself the “world’s most distributed compute platform.”

The result is Akamai Connected Cloud, and the company is adding core and distributed sites to the same infrastructure backbone that powers its existing edge network. This is a huge step forward for the company’s cloud capabilities. It is meant to offer developers a distributed platform for building, running, and securing next-generation applications.

Akamai says its Connected Cloud service is available in 4,100 locations in 134 countries. This puts compute, storage, database, and other essential cloud services closer to large populations, industries, and IT centers. It said that as a result, developers can now build and deploy more efficient cloud workloads with a latency of fewer than ten milliseconds and global reach.

The company wants to work with customers in the media, gaming, software-as-a-service, retail, and government industries. It hopes to win them over not only with the features of Akamai Connected Cloud but also with low prices.

It said that it has been able to use the power of its existing network to bring CDN-like economics to cloud data transfer and lower the cost of cloud egress. Because of this, it can offer much lower egress rates than other cloud service providers, the company said.

Tom Leighton, co-founder, and CEO of Akamai, claimed that because of his company’s expertise in edge computing, anything from content to cybersecurity could be scaled, bringing customers’ digital experiences closer to them while keeping threats farther away. He said, “Our customers know us and trust us for this scale. Now we plan to scale cloud computing, to provide customers with better performance at a lower cost.”

Eleven primary cloud computing facilities are already part of Akamai’s cloud infrastructure, dispersed around the United States, Europe, and Asia. Three additional sites will be added and ready to use by the end of the second quarter. After constructing ten additional core locations the following year, they will offer all of Linode’s cloud computing services. At the same time, Akamai intends to establish new “distributed” sites in more than 50 cities around the world this year, providing essential cloud computing services to more “difficult-to-reach” areas that conventional cloud providers currently neglect.

Akamai Chief Operating Officer and General Manager Adam Karon defined Akamai Connected Cloud as a “continuum of computation” that extends from the core to the edge, along with security, CDN, and round-the-clock support, in a blog post.

He added, “With Linode’s developer-friendly DNA, you’ll find it simpler to deploy distributed applications. Developers will be able to use these capabilities for applications, workloads, and use cases that haven’t been imagined yet.”

Akamai claims that all cloud services will adhere to ISO, SOC 2, and HIPAA standards and that introducing the Akamai Qualified Computing Partner Program would increase their utility. According to the statement, this is to provide customers with various services from third-party compatible with the Akamai Connected Cloud.

To deliver workloads across a broader range of computing and geography, the next generation of cloud computing, according to International Data Corp. analyst Dave McCarthy, will require changing how enterprises and developers think about bringing their applications and data closer to customers.

McCarthy said, “Akamai’s innovative rethinking of how this gets done — and how it is architecting Akamai Connected Cloud — puts it in a unique position to usher in an exciting new era for technology and to help enterprises build, deploy and secure distributed applications.”

• ThreatModeler planned to introduce 50 new threat models every month to address industry needs, wide use cases, and regulatory requirements.
• ThreatModeler affirms that companies will attain security in a fraction of the time.

The startup, ThreatModeler Inc., provides an automated threat modeling solution. It recently inaugurated the Threat Model Marketplace which will work as a cybersecurity asset marketplace, which will provide pre-built, field-tested threat models.

The enterprises are allowed to prioritize steps to reduce threats, understand the security requirements, and speed up their efforts to know the actuality of attack surfaces. These free features are provided by Threat Model Marketplace for a limited time to enterprises. The models have a thick coverage of different environments such as Google Cloud Platform, Amazon Web Services Inc., and Microsoft Corp.’s Azure.

As per ThreatModeler, there is a skill gap or talent shortage among workers in the cybersecurity field, so enterprises are facing complex cybersecurity mandates and grappling with new threats. The toughest part is cybersecurity compliance, keeping pace with new executive orders and legislation is becoming difficult for companies. An example would be the Quantum Security Preparedness Act, which is newly introduced to the counter-threat landscape.

Chief technology officer of ThreatModeler, John Steven states “Threat modeling is so valuable for maintaining secure systems that Executive Order 14028 makes threat modeling activities a compliance demand for many organizations. With organizations eager for help to overcome the persistent challenges that modeling can entail, Threat Model Marketplace is the right platform at the perfect time and represents a significant step forward in facilitating access to this important security resource.”

Threat Model Marketplace is being launched with 50 pre-built threat modeling templates that are industry compliant and are aligned with best practices. Not only this, after launch, the company targets to launch 50 new threat models every month. It will help in addressing industry needs, regulatory requirements, and ever-expanding use cases.

The company affirms that businesses can effectively become secure with less time and cost usually required to design, create, and verify secure designs from scratch.

The company has update plans for the marketplace in the near future, like enabling third parties to upload self-designed threat models that can be download with low or no cost. The access to and development of pre-built and reviewed cybersecurity assets is open to all, as the platform is designed to “democratize”.

• Airbus SE is reportedly discussing purchasing a minority stake in Atos SE’s new cybersecurity branch, which caused shares of the French information technology major Atos SE to rise.
• Atos indicated it would split into two. Evidian will include its cybersecurity, big data, and supercomputing services, while the second spinoff will consist of its declining IT infrastructure management firm.

Airbus SE is reportedly discussing purchasing a minority stake in Atos SE’s new cybersecurity branch, which caused shares of the French information technology firm Atos SE to rise.

The report originated from Les Echos through Reuters and was based on unnamed sources with knowledge of the conversations. Airbus declined to comment on the claim but told Reuters that it often engages in private discussions with its business partners, clients, and suppliers.

Atos, for its part, declined to comment but disclosed in December that it had already begun “exploratory discussions with potential future minority shareholders in the scope of Evidian-related activities.”

Atos referred to its proposed spinoff firm, which is anticipated to include its cybersecurity division and other business segments. The spinoff was announced in June 2022 after an internal assessment of Atos was conducted in response to the company’s share price falling by more than 50%. That month, Atos informed investors that it deals with a fragmented portfolio, many “red contracts,” high reliance on subcontractors, low productivity, and an insufficient skill set for commercial personnel.

In response to these issues, Atos said the company would split into two smaller parts. Evidian will be comprised of its cybersecurity division, big data services, and supercomputing services, while the second spinoff will be formed of its waning IT infrastructure management business.

According to Les Echos, a minority share in Evidian would be strategically important to Airbus, a major defense contractor. Airbus would ensure access to the encrypted communications systems it puts in the military vehicles it manufactures by acquiring a share in Evidian. Airbus has a well-established position in the cybersecurity market, and in 2022 it integrated its cyber activities under the name Airbus Protect.

They are still being determined how far the negotiations have advanced, but the recent improvement in Atos’s finances may push it to play hardball. In October, the company’s third-quarter financial figures showed a return to sales growth. In addition, it has entered into an eight-year agreement with the Union of European Football Associations and has just formed a strategic alliance with Amazon Web Services Inc.

Atos recruited a new chief executive officer in June. Nourdine Bihmane is the fourth CEO of Atos since 2019 and the third in the past year.