• The Google Cloud Consulting portfolio will initially feature more than a dozen professional services, according to the Alphabet Inc. division.
• Optimizing current cloud environments is the subject of a second group of Google Cloud Consulting services.

The professional service products of Google LLC’s cloud division are being reorganized into a new, centralized portfolio dubbed Google Cloud Consulting.

It follows a year in which Google Cloud increased its financial commitments to expand its professional services business significantly. With the help of the firm’s services, companies may more easily adopt Google Cloud products, train staff members to use them, and create new apps.

Lee Moore, Vice President of Google Cloud Consulting, reported, “The Google Cloud Consulting portfolio provides unified services capability, bringing together offerings, across multiple specializations, into a single place. This includes services from learning to technical account management to professional services and customer success.”

According to the company, the introduction of the Google Cloud Consulting portfolio has two primary objectives.

Its first goal is to make it simpler for businesses to hire experts from the search engine giant. The company claims that customers will have access to a thorough explanation of each service in Google’s catalog and illustrations of how to utilize it. The objective is to streamline the procurement procedure for business customers.

According to the search engine titan, Google Cloud Consulting will make it simpler for partners to collaborate with its professional service teams. Google has a vast ecosystem of associates dedicated to providing consulting services to its clients. A business launching a complex cloud initiative could hire both Google and a third-party consulting firm to assist.

According to the Alphabet Inc. division, the Google Cloud Consulting portfolio will initially feature more than a dozen professional services. The products fall under various categories.

Some services are designed to make it easier for businesses to implement Google Cloud products. The process of implementing Google Workspace is made more accessible by one such service. Another is made to make it simpler to transfer on-site corporate records to BigQuery, the search engine giant’s cloud-based data repository.

Optimizing current cloud environments is the subject of a second group of Google Cloud Consulting services. For instance, company employees can work with an organization to determine whether its cloud environment has weak security settings.

Training options are also part of the Google Cloud Consulting portfolio. It can give administrators at a company the know-how to set up and control Google Cloud environments. More specialized topics are also covered in the training programs, such as how to create applications for artificial intelligence using the Vertex AI toolkit.

Moore stated, “As we look forward to 2023, we’ll continue to expand the service catalog and focus on making it even easier to find and transact these services and further streamline the experience of engaging with our services.”

• Google LLC recently unveiled Med-PaLM 2, a neural network capable of answering medical test questions, and presented a cloud-based automation toolbox for healthcare businesses.
• According to Google, the AI obtained a score of 85%, 18% higher than a prior-generation neural network dubbed Med-PaLM.

Google LLC recently unveiled Med-PaLM 2, a neural network capable of answering medical test questions, and presented a cloud-based automation toolbox for healthcare businesses.

The innovations were unveiled during the company’s annual The Check Up healthcare event.

Advances in AI

The announcement of Med-PaLM 2 was the first significant highlight of Google’s healthcare event. Med-PaLM 2 is a novel artificial intelligence model developed internally by Google. It can accept medical queries as input and provide comprehensive responses in natural language. Google claims that AI can also elucidate the reasoning behind its answers.

Med-PaLM 2’s accuracy was evaluated by having it answer a succession of questions like the United States Medical Licensing Examination. According to Google, the AI scored 85%, 18% higher than a prior-generation neural network dubbed Med-PaLM. According to the company, the efficacy of Med-PaLM 2 “far surpasses” comparable AI models from other companies.

In the coming weeks, Google’s cloud division intends to make Med-PaLM 2 available to a limited number of customers. According to the search behemoth, the objective is to determine how the model could be implemented in the medical field.

Aashima Gupta and Amy Waldron, Google Cloud executives, stated that Google hopes to “understand how Med-PaLM 2 might be used to facilitate rich, informative discussions, answer complex medical questions, and find insights in complicated and unstructured medical texts. They might also explore its utility to help draft short- and long-form responses and summarize documentation and insights from internal data sets and bodies of scientific knowledge.”

Med-PaLM 2 is one of various AI models developed by Google to assist medical professionals in their work. It collaborates with numerous healthcare organizations to improve its research in this field. In addition to announcing Med-PaLM 2, the company also announced four new healthcare partnerships.

The first collaboration is with an “AI-based organization” directed by the non-profit organization Right to Care. The focus of the collaboration is to make AI-powered tuberculosis screenings broadly accessible in Sub-Saharan Africa. Google reports that its partners have pledged to donate 100,000 complimentary screenings.

The three additional healthcare AI partnerships are with Kenyan non-profit Jacaranda Health, Chang Gung Memorial Hospital of Taiwan, and Mayo Clinic. The previous two collaborations focus on interpreting ultrasound images using machine learning. The partnership between Google and the Mayo Clinic seeks to develop an artificial intelligence (AI) model that can help physicians plan radiotherapy treatments faster.

The New Claims Acceleration Suite

In addition to its new partnerships and Med-PaLM 2 model, Google Cloud announced the Claims Acceleration Suite. It reduces administrative labor for healthcare organizations via the use of AI. The offering utilizes multiple existing Google Cloud services, including the Document AI API for document information extraction.

The Claims Acceleration Suite is intended to accelerate two frequent healthcare administration tasks. The first is claims processing, while the second is a prior authorization for health insurance. At launch, the offering only supports the second use case.

Health insurance prior authorization evaluates the medical necessity of a treatment plan. Examining medical records and other patient information that is frequently dispersed across multiple documents is required for the evaluation. According to Google, preparing this data for processing requires substantial manual labor.

The Claims Acceleration Suite is intended to accelerate the activity. It can transform medical data in unstructured files, such as PDFs, into a structured format more amenable to processing. In addition, the offering provides a search tool for medical professionals to peruse the collected data.

• According to Google, the Assured OSS collection includes the most well-known Python and Java packagers and popular artificial intelligence and machine learning tools.
• Google states it garnered an immensely positive response after releasing Assured OSS for public access the last year.

Google Cloud is making its Assured Open Source Software service generally available for Java and Python ecosystems to help enhance the security of the most popular open-source software.

Assured OSS, which was just announced and is free for consumers to use, enables organizations to utilize the same OSS packages that Google utilizes in its own developer workflows. Users can get extra security precautions that Google offers with those packages, enhancing their own security.

Given that the bulk of software programs and services in use today are based on open-source software, it might be an appealing offer. Even proprietary software applications rely on various open-source parts, but the security of these offerings from the community raises serious concerns. 17% of all security incidents in 2022 began with an attack on the open-source software supply chain, per the Mandiant M-Trends report. If hackers discover a flaw in an open-source component, it could be exploited by any application that employs it.

According to Google, organizations will gain a more secure open-source software supply chain by relying on Google’s comprehensive library of Assured OSS packages. With an Assured Software Bill of Materials offered in forms compliant with industry standards, they will better comprehend the components of the packages they employ. Because Google is continuously scanning and patching the components they utilize for vulnerabilities, their overall risk will also be decreased.

According to Google, the Assured OSS collection includes the most well-known Python and Java packages and popular artificial intelligence and machine learning tools such as TensorFlow, Pandas, and Scikit-Learn. The OSS packages are routinely scanned, analyzed, and fuzz-tested for vulnerabilities, are verifiably signed by Google, and are distributed from a company-protected artifact registry. ACCORDING TO GOOGLE, assured OSS has already demonstrated its value as it was the first to identify and resolve 48 percent of all newly discovered vulnerabilities in the first 250 Java applications it offered through the program.

Holger Mueller at Constellation Research Inc. reported that all the latest software is practically written with an open-source component, and its format indicates that it is open to all types of risks. “For many enterprises, checking software for bugs and vulnerabilities is an arduous and sometimes even impossible task. So it’s great to see that Google is letting others benefit from its own checks and due diligence,” Mueller added.

Google states it garnered an immensely positive response after releasing Assured OSS for public access the last year. Tech Fellow and N.A Managing Director of Citibank, Jon Meadows, mentioned that his company has been among the earliest adopters of this initiative. “Both Citi and Google see untrusted and unverified open source dependencies as a key risk vector. Assured OSS can help reduce risk and protect open-source software components commonly used by enterprises like us,” he added.

Organizations that want to begin using Assured OSS can use this self-service onboarding form. Then, they can attach the Assured OSS packages to their software development infrastructure in any desired environment, such as Artifact Registry, Artifactory, Nexus, and others.

Melinda Marks, an ESG analyst, stated that a reliable, secure open-source package is crucial for companies in the fast-growing cycles. “Without proper vetting and verification or metadata to help track OSS access and usage, organizations risk exposure to potential security vulnerabilities and other risks in their software supply chain. By partnering with a trusted supplier, organizations can mitigate these risks and ensure the integrity of their software supply chain to protect their business applications better,” she added.

• Google Cloud unveiled Cloud Armor Advanced Network DDoS Protection, which gives clients constant attack monitoring and mitigation for certain workloads.
• Customers can view the service’s archive of previous and ongoing DDoS attacks at any time.

To protect users in the gaming, telecoms, and other sectors that use workloads behind external network load balancers, virtual machines with public IP addresses, or protocol forwarding, Google Cloud is expanding its Cloud Armor network protection service’s features.

These clients were at a high risk of distributed denial-of-service and other types of attacks until now because they lacked a Google Cloud-native defensive capability to safeguard their workloads.

To address this, Google Cloud unveiled Cloud Armor Advanced Network DDoS Protection, which gives clients constant attack monitoring and mitigation for certain workloads. In particular, the so-called SYN flood, UDP flood, DNS reflection, and NTP amplification attacks as well as other volumetric DDoS and protocol DDoS attacks will be protected by the new service.

Lihi Shadmi, the Product Manager for Google Cloud, describes how Cloud Armor Advanced Network DDoS Protection operates in the background at the edge of Google’s network, where it passively monitors two different types of signals. The first concerns the health of the customer’s workload, while the second examines incoming traffic. When Cloud Armor notices early indications of workload duress or a sharp deviation from the expected baseline in traffic patterns, it will notify clients that an attack is underway. According to Shadmi, it is an always-on monitoring system with a low rate of false-positive attack detection and no latency added to network flows.

Cloud Armor checks the traffic to ascertain the attack signature using its well curated signature database when an attack is detected. It can then use this knowledge to deliver the best mitigation at the network’s edge.

“Cloud Armor stops the incoming attack before it reaches the customer’s workloads while allowing legitimate traffic to pass through. The mitigations are in effect only during an attack. Once Cloud Armor identifies the attack has ended, it will disable the mitigations. The whole process, from detection to mitigation, takes mere seconds,” wrote Shadmi.

Customers can view the service’s archive of previous and ongoing DDoS attacks at any time. Three different kinds of event logs are produced during an attack: the detection and beginning of mitigation, updates on the attack’s status every five minutes for as long as it is active, and finally the end of the attack and mitigation. Customers will also be able to see details like traffic volumes and attack categorization.

According to Google, customers can sign up for Cloud Armor’s Managed Protection Plus service to apply for Cloud Armor Advanced Network DDoS Protection. For all the Google Cloud regions they use, they must set up the service to offer security on a per-region basis.

Customers can access flexible cancellation conditions for the first 30 days to test Advanced Network DDoS Protection or any other premium feature they’re interested in using before committing to Cloud Armor’s Managed Protection Plus subscription, according to Shadmi.

• By dynamically scaling up and down to accommodate player counts, Google Cloud manages the underlying Kubernetes clusters with GKE Autopilot and Agones, ensuring the game server can function flawlessly.
• GKE Autopilot can integrate with other crucial cloud services, including analytics, matchmaking services, and customized network proxies.

According to Google Cloud, running worldwide multiplayer game servers on Google Kubernetes Engine Autopilot is now a fully automated experience for game developers.

Software containers, which host the elements of contemporary agile applications, including video games, are managed and orchestrated through GKE, a cloud-based service. It provides a platform for creating and sustaining massively multiplayer online games. With GKE Autopilot, developers can access a fully-managed, serverless version of GKE, where Google automates all the overheads.

Game developers can now use GKE Autopilot to serve players worldwide, according to a blog post by Google Kubernetes Engine’s Senior Product Manager, Ishan Sharma.

He clarified that most developers don’t want to be concerned with the underlying cloud infrastructure. They simply want it to grow with player traffic so they can concentrate on adding new features to their games.

Sharma wrote, “At Google Cloud, we are fixated on making game launches boring by making GKE Autopilot the platform-of-choice for running game workloads for scalability, reliability, and automation.”

With the help of the brand-new, open-source game server orchestrator Agones, Google Cloud has made it possible to run dedicated game servers on GKE Autopilot.

The game server, which acts as the definitive source of the game’s state and to which players must connect to interact with the game, is one of the most important components of multiplayer games.

As a result, game servers must continue to function flawlessly at all times and connect thousands of players without any interruptions.

By dynamically scaling up and down to accommodate player counts, Google Cloud manages the underlying Kubernetes clusters with GKE Autopilot and Agones, ensuring the game server can function flawlessly. Developers are no longer required to worry about setting up the underlying infrastructure.

Sharma explained, “With traditional Kubernetes, this scaling requires resources and time for planning, rightsizing and bin-packing. You might overprovision node pools much earlier in anticipation of scaling up and keep those node pools running longer before scaling down. All this costs money.”

According to analyst Holger Mueller of Constellation Research Inc., gaming is a key cloud application because it necessitates elasticity to provide gamers with the best experience, leading to unpredictably high and low usage.

He added, “Running the infrastructure for these gaming workloads manually quickly becomes an expensive endeavor, and mistakes are often made, leading to higher costs or a poorer gaming experience. So automated infrastructure, which Google Cloud now offers with GKE Autopilot, is critical. Combine this with Google’s super-fast network, and you have a very compelling platform for game workloads.”

Google made a number of justifications for why game designers ought to think about hosting their games on GKE Autopilot. Developers only pay for the CPU, memory, and storage their servers use with GKE Autopilot.

Therefore, there is no risk of incurring charges for unused capacity or operating system overheads and components. Google quotes a Forrester study demonstrating how GKE Autopilot can cut infrastructure costs by as much as 85% and boost developer productivity by as much as 45%.

Google emphasized that developers won’t be forced into using its cloud if they use GKE Autopilot. Sharma noted that many game developers use multiple-region cluster fleets, on-premises settings, and other cloud platforms to run workloads.

He noted that games remain portable and flexible because Agones is open source and GKE Autopilot is based on open-source Kubernetes.

Multitarget parallel deployment, a feature of Google Cloud that enables developers to roll out new features or updates in a particular area, is another advantage.

Therefore, before releasing the new feature to a larger audience, developers can build a new GKE cluster for a small area, deploy it, and gauge user reaction.

Finally, Sharma noted that GKE Autopilot could integrate with other crucial cloud services, including analytics, matchmaking services, and customized network proxies.

• 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,”

• Google LLC continues its journey with generative artificial intelligence by incorporating the emerging technology’s benefits into its products via Google Cloud for developers and Workspace for corporate customers.

Google LLC continues its journey with generative artificial intelligence by incorporating the emerging technology’s benefits into its products via Google Cloud for developers and Workspace for corporate customers.

Due to its capacity to produce new content based on basic word descriptions, Generative AI has been a subject of contention, resulting in chatbots that can have conversations, compose emails, generate code, and create artwork. This contrasts with traditional AI, which can simply evaluate and classify data.

The Google Cloud team recently unveiled various generative AI tools to assist developers in experimenting with the new technology. These updates include support for Vertex AI, the company’s managed machine learning platform, and a generative AI app builder that puts the power of AI in the hands of business users.

With complete support for generative AI in Vertex AI, data science and machine learning teams can build and deploy AI applications at scale utilizing Google’s core models. The company stated that these models would initially be used to generate text and images but would eventually be expanded to generate audio and video. With this system, developers can investigate models, customize them with their data, adjust prompts, and integrate them into their applications.

The new Generative AI App Builder will enable corporate users and developers to swiftly create new AI experiences, such as bots, chat interfaces, search engines, and smart assistants. With the app builder, users will obtain direct application programming interfaces to Google’s own models and may utilize prebuilt templates to begin the development of their apps.

Google said it would provide access to the Generative AI App Builder and aid for Vertex AI assistance to a limited number of testers, including Toyota, Mayo Clinic, HCA Healthcare, Deutsche Bank, and Automation Anywhere.

To make it easier to experiment with Google’s generative AI large language models, Google Cloud is introducing the PaLM API, which is aimed to allow developers immediate access for developing text generation quickly, such as chat, summarization, and categorization. PaLM, or the Pathways Language Model, is a very effective AI for comprehending and creating language on a massive scale for various applications.

Following the introduction of PaLM API, the Google Cloud team also announced the availability of MakerSuite, a tool that enables developers to fine-tune custom models, review data and generate relevant prompts for making the necessary replies from the AI. With MakerSuite, developers may alter the text they give the AI initially until they obtain the response they seek and output it as code.

The Google Cloud team has been investigating AI processes for several years, including the development of apps utilizing the large language model LaMDA in the AI Test Kitchen and the MUM to Search model. Using MakerSuite, the team used what it had learned about fragmented workflow development. The technology allows developers to fine-tune their models directly in the browser, saving them considerable time and effort.

Generative AI in Google Workspace for business users

Google is also adding the power of generative AI for Workspace users by releasing the first set of AI-powered writing functionalities for Google Docs and Gmail to a select group of users.

Smart Compose, which provides autocomplete recommendations for typed sentences, and Smart Reply, which provides suggested email responses, have given AI-related experiences to many Gmail users. Yet, for a subset of Workspace testers, the full capabilities of generative AI will become available during the year.

Soon, Workspace users will be able to compose emails or text by simply expressing what they want in a single sentence and have the AI develop a prospective draft based on their writing style and then fine-tune it based on tone. The same may be done in Docs for proofreading, writing, and rewriting in Docs.

Future functions Google wants to push out are auto-generated graphics, audio, and video for Slides, getting insights and analysis via auto-completion and formula creation in Sheets, capture notes in Meet, and processes for getting things done in Chat.

Kurian underlined the importance of data privacy for the new services, stating that data would not be used to train the company’s algorithms and that client data would be segregated to achieve this.

• Ballistic Ventures LLC, TLV Partners Management Ltd., Lightspeed Venture Partners L.P and some famous cybersecurity professionals actively participated in the funding
• Oligo claims to be different from existing solutions because of its behavior-monitoring technology and dynamic library-level analysis to swiftly identify vulnerabilities in a running package.

Oligo Security, an Israeli cybersecurity startup, recently launched out of stealth mode. It also declared that it had closed USD 28 million for its runtime application security and observability solution.

The investors who participated in funding consisted of Ballistic Ventures LLC, TLV Partners Management Ltd., Lightspeed Venture Partners L.P, and some famous cybersecurity professionals. Other members include Snyk Inc. Chief Technology Officer Adi Sharabani, former Google Cloud Vice President Eyal Manor, now chief product and engineering officer at Twilio Inc., and Eyal Waldman, founder and chief executive of Nvidia Corp. subsidiary Mellanox Technologies.

It is founded by CTO Gal Elbaz (previously with Check Point Software Technologies Inc.), CEO Nadav Czerninski, and Chief Product Officer Avshalom Hilu, all previous officers in the Israel Defense Force’s cyber units. Oligo provides a runtime application security and observability solution that authorizes enterprises to first detect and prevent open-source code vulnerabilities in their applications without affecting performance.

Open source code comprises 80% to 90% of modern software and delivers an attractive attack vector for cybercriminals and nation-states. Oligo claims that current software composition analysis solutions fail and organizations are exposed. It’s argued that existing solutions are noisy, cause large volumes of false positives, and don’t provide runtime application context for prioritization.

That’s the time when Oligo comes into play. It argues to be different from existing solutions because of behavior-monitoring technology and dynamic library-level analysis to identify vulnerabilities in a running package quickly. The company’s platform sets a priority on the basis of the application context. It saves development time by concentrating on the exact attack surface.

The solution makes users aware only if there is a deviation from a library’s permission policy with an indication of suspicious activity. Oligo argues that its solution is quick and efficient by design. It uses a proprietary eBPF- based engine to detect vulnerabilities accurately and prevent an attack while maintaining application stability.

Czerninski explained, “After Oligo’s co-founder, Gal Elbaz, discovered that a widely used app like Instagram could be easily compromised by misusing an open-source library, we realized that there is a significant gap in the way the market currently addresses open source security. We zeroed in on a protection method that inspects each library in runtime or staging, allowing us to precisely identify attacks in cases of deviations and to fix the vulnerabilities that matter.”

Oligo’s technology profiles the acceptable behavior of each library, forming a knowledge base of libraries’ profiles and blocking or alerting whenever a library activity is not up to mark. At the library level, its platform allows effective and quick performance while maintaining the high stability of the application, Oligo says.

• 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.”

• Uber believes that the new cloud deal will help it channelize the resources toward strategic initiatives and core strengths while the company continues to expand and explore new markets.
• Uber deal is significant for both Google Cloud and Oracle as they compete against their cloud infrastructure market rivals, Microsoft Corp. and Amazon Web Services.

Uber Technologies Inc., a ride-hailing company, announced its multicloud strategy, the latest seven-year strategic cloud collaboration with Oracle Corp. With this development, Uber will shift a major chunk of its crucial workloads to Oracle Cloud Infrastructure.

Meanwhile, the company also disclosed expanding its partnership with Google Cloud, its existing partner. Uber mentioned it has been working with Google to “reimagine the customer experience for Uber users, drivers and merchants and modernize its cloud infrastructure.”

Uber believes that the new cloud deals will help it channelize the resources toward strategic initiatives and core strengths while the company continues to expand and explore new markets. As per the company, the way to its profitability will be catalyzed by working in conjunction with Google and Oracle.

Analysts stated that the deals are victorious for both Google and Oracle, perceiving Uber’s brand recognition. However, Oracle received considerably larger share in the contract worth over a billion dollars.

JP Morgan’s analyst Mark Murphy reported to investors, “Our sense is that Oracle’s portion of the contract likely includes a broader footprint than just Uber Freight, and Oracle may be handling 60-80% of the direct infrastructure/economics in this arrangement. We believe this is one of the 10-figure wins that Oracle had already booked and announced during its recent October quarter, and we are just learning of the logo today.”

It is evident that Uber will shut its own on-premises data centers and shift entire IT workloads to Google Cloud and Oracle.

Uber’s Chief Executive Dara Khosrowshahi said, “Uber is revolutionizing the way people, products, and services move across continents and through cities. To deliver on that promise for customers while building value for shareholders, we needed a cloud provider that will help us maximize innovation while reducing our overall infrastructure costs. Oracle provides an ideal combination of price, performance, flexibility, and security to help us deliver incredible customer service, build new products and increase profitability.”

Oracle announced that collaborating with Uber will also penetrate to other areas of collaboration. It has chosen Uber as the ride-hailing partner for employees to eat and travel globally. Oracle is also planning to continue with Uber for miscellaneous delivery and retail services.

Derrick Wood, analyst Cowen Inc., said, “This is a net new win for Oracle OCI and a notable competitive win over AWS, reinforcing the growing momentum and market share gains it has been driving over the last several quarters and giving us confidence that this momentum should continue.”

Uber deal is significant for both Google Cloud and Oracle as they compete against their cloud infrastructure market rivals, Microsoft Corp. and Amazon Web Services.

Martin Peers from a renowned media company, analyzed that AWS could have been a better choice for Uber, from a technical point of view. This is because AWS knows the business better as it has already served Lyft Inc., Uber’s rival for years. However, Uber’s decision is a function of pricing structure, as Google Cloud and Oracle are estimated to provide service at a cost lower than AWS’ offerings.

Despite receiving a smaller share of the deal, Google Cloud is keen on playing a major role in modernizing Uber’s customer experience. This can be accomplished by “technical investments” in Google Ads, Maps, and Cloud to help Uber reduce the price per trip, explore new revenue channels, and enhance in-house analytics. Besides, it assured to assist Uber in augmenting the mobile application performance.

Khosrowshahi said, “Our partnership with Google centers around a shared commitment to putting customer experience at the forefront of everything we do.”