AI and machine learning disruption for Enterprises started happening in the areas such as IT operations management (ITOPs) and Cloud management and SaaS apps.
In 2019 CIOs will see disruptive solutions for Cloud & Devops, AI/ML driven IT Ops and Cloud Ops.
Customers want AI-driven multi-cloud operations for monitoring, detection, prevention of disruptions. Disruptions cause revenue loss, unhappy users, impacts brand reputation etc.
Over the past year, I’ve had the good fortune of sitting down with leading enterprises to speak with CIOs, enterprise architects, database engineering leaders, and more. Many of these discussions centred on the evolving world of business applications and databases and the challenges of digital transformation initiatives (customer experience, digital banking experience, data-as-a-service, real-time analytics).
In these discussions, I gained insight into why enterprises are embracing NoSQL databases, and several enterprise data management trends stood out to me. Here are the top three that I believe are shaping the market and CIO digital transformation initiatives the most in 2019:
Non-relational NoSQL databases are no longer stepchildren of the relational database space but hold their own prominent place in the enterprise data architecture strategy. In recent years, NoSQL has become critical for building cloud-native applications, given that traditional relational databases cannot deliver the same agility, flexibility, and performance that these modern applications need.
NoSQL started with data stores such as MongoDB and Apache Cassandra but is now evolving to include in-memory database stores like Redis and search products like ElasticSearch and Splunk, which are fast developing as cornerstones for operational and analytical use cases. Organisations are throwing caution to the wind and embracing NoSQL data stores, a stark contrast to previous years in which they onboarded NoSQL databases alongside their relational counterparts.
Here are some real-life examples of how enterprises are unlocking serious business value with these new, modern infrastructures:
However, the rise of NoSQL adoption also presents operational challenges, and many leaders I spoke to stressed the need for data protection between their traditional and new environments. We at Rubrik are proud to be on the forefront of this trend and have made significant investments to address the growing demand for NoSQL in the enterprise.
NoSQL providers have targeted developers and open source contributors to seed themselves into the enterprise (after all, “developers are the new kingmakers”). An easily downloadable and installable NoSQL cluster allows developers to quickly prototype next-generation apps and determine their viability.
For example, MongoDB states that its Community Server “freemium” offering has been downloaded over 30 million times, a number that continues to grow year over year. Similar statistics are available for other NoSQL databases, and it’s clear that targeting developers is a strategic way to acquire mindshare and become well-positioned as the data store of choice for the next-generation of enterprise applications. Compare and contrast this new world with the world of heavy-metal, scale-up only, relational databases.
The developer-driven acceleration in the NoSQL market combined with the common goal of realising new business applications at a much faster pace explains the urgent need for enterprise-grade operational tooling. There are a lot of point products tailored for each individual data store and use case, but there is no leader that can handle a large, critical mass of unstructured data.
Case in point: MongoDB is positioned as a document-based repository that’s highly represented in verticals such as healthcare, financials, etc., while Apache Cassandra and DataStax are geared for high-volume based data sets for verticals such as IoT and eCommerce. Similar themes apply to data stores such as ElasticSearch, Redis, MemSQL, others — they all co-exist in enterprise environments. As a result, organisations crave a centralised solution for use cases such as reporting, monitoring, and analytics to use across their heterogeneous environment and across SQL and NoSQL databases. The key to winning here is to bring the same simplicity to NoSQL Data Management that NoSQL vendors brought to databases.
We’ve seen an accelerated migration of applications and data to the cloud (AKA the “lift and shift” mode of cloud adoption) and massive investments in building modern cloud-native applications. While lift and shift primarily revolves around maintaining the application fidelity with traditional cloud SQL datastores, cloud-native applications are primarily based on cloud-native NoSQL (AWS DynamoDB) and non-native NoSQL data stores (MongoDB, MongoDB Atlas, DataStax).
These modern applications are distributed, highly scalable, and very forgiving of their infrastructure. However, despite all of these advances, large investments are still being made into on-premises data centres. The hybrid cloud model is where we will see modern, next-gen applications and databases that run in private clouds converge with on-premises data centres. As a result, there will be a growing need for products and tools that can help customers migrate data to the cloud, thus enabling use cases such as data mobility, independence, and repatriation for compliance and governance needs.
Regardless of where organisations are in their digital transformation journey, the duo of SQL and NoSQL power some of the most critical customer experiences. The emerging theme is that SQL alone is not the answer for today’s organisations that want to realise digital transformation initiatives. Speaking with leaders across some of the world’s biggest enterprises proves both SQL and NoSQL are here to stay and organisations are hungry for enterprise-grade products that can help them solve end-customer needs and meet business objectives across their entire infrastructure. That’s why Rubrik is committed to giving customers the choice and flexibility to build hybrid cloud and multi-cloud architectures for their non-relational and relational data stores.
Interested in hearing industry leaders discuss subjects like this and sharing their experiences and use-cases? Attend the Cyber Security & Cloud Expo World Series with upcoming events in Silicon Valley, London and Amsterdam to learn more.
Amazon Web Services (AWS) and Microsoft have been selected to continue competing for the Pentagon’s cloud computing contract, the US Department of Defence said on Wednesday.
The highly sought after Joint Enterprise Defense Infrastructure (JEDI) contract is worth $10 billion and is part of a broad modernisation of Pentagon information technology systems that could take up to 10 years.
«I can confirm that AWS (Amazon Web Services) and Microsoft are the companies that met the minimum requirements outlined,» department spokeswoman Elissa Smith said in a statement to Reuters.
AWS, Microsoft, IBM and Oracle have been the front runners for the contract for a while, particularly after Google pulled out in October 2018, citing a clash of ethical values. But this latest decision is a snub to both IBM and Oracle.
Oracle has stayed in contention for the contract, despite repeatedly opposing its single-vendor specifications. In December, the cloud and database business launched a second bout of legal proceedings over the contract, filing a suit against the Department of Defence in the US Court of Federal Claims. The company’s original legal action was dismissed by the Government Accountability Office (GAO).
Oracle questioned the «propriety» of the procurement process after obtaining communications in which an official called colleagues voicing support for AWS rivals «dum-dums.» The tech giant alleged that two people who helped lead the JEDI project, Deap Ubhi, who served as JEDI project manager at the DoD, and Anthony DeMartino, chief of staff for the Deputy Secretary of Defense, were conflicted because of their relationship with AWS.
Ubhi, the lawsuit states, worked at AWS until joining the Defense Digital Service in the summer of 2016. He returned to AWS as general manager in November 2017.
The GAO has always maintained that the single vendor approach does not violate any laws and that for issues of national security the process is in the government’s best interests. IBM issued a similar legal challenge against the single-vendor process, which is said to violate procurement regulations, but that case was also blocked.
But with IBM and Oracle out of the picture, it falls to two of the industry’s biggest cloud providers, Microsoft and AWS, to battle it out.
Google has unveiled a whole suite of updates to its G Suite, including productivity boosting features, connected sheet support, Hangouts chat to email and new integrations with Google Assistant.
G Suite Add-ons make it easier for users to switch between different apps in Google’s lineup. For example, if you’re in email and want to view a document, you can switch to Docs via the side panel. As well as those Add-ons already available, the company has now added integrations with Copper, Workfront and Box.
Connected Sheets brings the power of pivot tables and shared data to Google Sheets. Connected Sheets allows you to connect up to 10 billion rows of BigQuery data without using SQL and then translate the data into tables easy-to-digest information for the rest of the organisation.
You can now also edit Microsoft Office documents, whether spreadsheets in Excel, Word documents or presentations in PowerPoint directly from G Suite, without having to convert to Docs, Sheets or Slides.
If you need to share any of these documents with others not in your organisation, you can do so using the new Visitor Sharing in Drive function, allowing others to collaborate on files without gaining full access, but using a pin code.
For those that use Hangouts for live messaging and video calling, Google has debuted Google Hangouts Chat into Gmail, so teams can view all communications from the Gmail pane. At the bottom left corner, you’ll see people, rooms and bots. Open up rooms to see conversation streams and threads. While in Hangout Meet video calls, users can now opt to have on screen captions display, powered by the company’s speech recognition tech.
The extension of Google Assistant to enterprise environments makes it much easier to keep your work life organised. Your calendar will sync with Assistant so you can make sure you get to meetings on time, know where you’re going and stay ahead of any schedule changes.
Google has launched a beta version of its AI platform, allowing developers, data scientists, and data engineers with an end-to-end development environment in which to collaborate and manage machine learning (ML) projects.
While ML is already employed in many cloud instances to sift through logs looking for data that could indicate malicious activity, Google announced a range of additional capabilities for its AutoML product – the same one introduced last year which aimed to get companies with limited ML know-how building their own business-specific ML products.
«We believe AI will transform every business and every organisation over the course of the next few years,» said Rajen Sheth, director product management at Google Cloud AI.
«We have focussed on building an AI platform that provides a very deep understanding of a number of fundamental types of data: voice, language, video, images, text and translation,» added Thomas Kurian, CEO Google Cloud. «On top of this platform, we have built a number of solutions to make it easy for our customers and analysts around the world to build products».
Infrastructure diagram of Google’s new AI platform
When AutoML launched last year, non-experienced workers could build ML-driven tools using image classification, natural language processing and translation specific for their businesses and the data they hold with little-to-no training.
Now Google has announced three new AutoML variations called AutoML Tables, AutoML Video and AutoML Vision for the edge. Tables allows customers to take massive amounts of data, hundreds of terabytes were cited, ingested through BigQuery and use that to create actionable insights into business operations such as predicting business downtime.
It’s all codeless, too. Data can be ingested and then fed through custom ML models created in days instead of weeks by developers, analysts or engineers using an intuitive GUI.
With Video, Google is targeting any organisation that hosts videos and needs to either categorise them automatically using automatic labelling such as cat videos or furniture videos. It can also help automatically filter explicit content and help broadcasters, much like it did with ITV recently, detect and manage traffic patterns on live broadcasts.
Vision was announced last year to help developers with image recognition. With Vision Edge for devices such as connected sensors or cameras, the challenge was that these device struggle with latency issues. Vision Edge harnesses edge TPUs for faster inference and LG CNS, an outsourcing arm of LG uses the tool to create manufacturing products that detect issues with things like LCD screens and optical films on the assembly line.
The new AutoML tools will have the ability to take visual data and turn it into structured data, that’s according to Sheth speaking at a press conference.
«One example of this is FOX Sports in Australia – they’re using this to drive viewer engagement – they’re putting in data from a cricket game and using that to predict when a wicket will fall with an amazing amount of accuracy and then it sends a notification out via social media telling followers to come and see it,» he said.
Sid Nag, research director at Gartner, said that while Google has effectively admitted to being the second best cloud provider with the introduction of Anthos, what it is doing well is leading the AI charge.
«They’re (Google Cloud) very strong in AI and ML, no-one’s doubted that,» Nag said in an interview with Cloud Pro. When asked if customers would choose Google Cloud specifically based on AI as its USP, Nag said: «yeah I think so, that and big data and analytics, you know, they’ve always been very strong in that area».
Binu Mathew, senior vice president and global head of digital products at Baker Hughes, came on stage after Sheth to talk to us about how his team of developers use Google’s AI tools in the oil and gas industry specifically.
He said, when an offshore oil platform goes down, it costs the company about $1m per day. However, by using ML, the oil company can teach its ML tools the signs of normal business function so when these figures start to go awry, the issue can be fixed before any costly downtime occurs.
Since using Google’s AI tools, Baker Hughes has experienced a 10x improvement in model performance, a 50% reduction in false positive predictions and a 300% reduction in false negatives.
Sheth said that AI will also be part of Kurian’s and Google Cloud’s hybrid cloud vision, you can deploy ML across GCP, on-prem, on other cloud platforms and at the edge. This is because it runs off Kubeflow, the open-source AI framework that runs anywhere Kubernetes runs too and it can all be managed by Anthos, Google’s new multi-cloud platform which «simply put, is the future of cloud», said Urs Hölzle, Google’s senior vice president of technical infrastructure.
Speaking at a subsequent and more intimate session compared to the keynote, Marcus East, CTO at National Geographic, told the crowd of the company’s cloud transformation and the quick mission-critical turnaround of migrating the company’s 20-year-old legacy on-prem photo archive system to a GCP-based archive in just eight weeks.
He also briefly mentioned the company’s work with AutoML so Cloud Pro caught up with East and a few of the engineers behind the company’s AI work after the event to hear more about the company’s vision for cloud AI implementation for the future, specifically with AutoML Vision.
Speaking exclusively to Cloud Pro, Melissa Wiley, vice president of digital products at National Geographic, said that one of the ideas it is exploring is that of advanced automated tagging of metadata and how it will be able to assign labels of not just specific animals, but specific species to animals that appear in the circa two million images it stores in its archive.
That starts by using AutoML Vision’s automatic image recognition. Using machine learning, Nat Geo can train its industry-specific ML tool to learn one species of tiger and apply that to identify the same species in all the other photos in which that species appears, according to Wiley.
«When our photographers are out in the field, they might be up to their waist in mud, avoiding mosquitos and being chased by wild creatures – they don’t have time to take a great photo and then turn to their laptop and fill in all the metadata,» said East. «So this idea that we could somehow use AutoML and the BroadVision API to really [make those connections] and enrich the metadata in those images is the starting point. Once we’ve done that, we can give our end consumers a better experience.»
«That’s the next stage for us; we can see the potential to harness the power of these cloud-native capabilities, to build personalised experiences for consumers. For example, we could say we know Connor likes snakes and videos of animals eating animals, let’s give him that experience,» he added.
Wiley also mentioned the enterprise potential for this too, perhaps offering the technology to schools, libraries or even other companies so Nat Geo can help them identify animals too. «There are a million ideas we could talk about,» she said.
Hewlett Packard Enterprise (HPE) has been busy on the partnership front of late. The company has announced deals with Nutanix, to deliver an integrated ‘hybrid cloud as a service’ to market, as well as with Google Cloud around simplifying hybrid cloud adoption.
Both partnerships will utilise HPE GreenLake, the company’s consumption-based IT model. Nutanix’s Enterprise Cloud OS software will be delivered through GreenLake ‘to provide customers with a fully HPE-managed hybrid cloud that dramatically lowers total cost of ownership and accelerates time to value’, as the companies put it.
The deal with Google Cloud, the next step in the companies’ collaboration, will also offer a migration path for Anthos, Google’s newly-rebadged cloud services platform. HPE customers can use Anthos to manage public cloud and on-premises resources, with the overall aim by the company of providing customers with a consistent experience across all environments.
“By partnering with Google Cloud and leveraging a container-based approach, HPE can offer a seamless hybrid cloud experience with the unique option to do it all as-a-service,” said Phil Davis, president of hybrid IT and chief sales officer at HPE. “This approach, powered by Anthos and HPE GreenLake, gives our customers the freedom to modernise at their own pace with the HPE infrastructure of their choice.”
The Nutanix deal is of interest primarily because the two companies were previously vehement opponents. In 2017 Nutanix announced a string of partner agreements, notably with IBM around aligning Nutanix’s enterprise cloud with IBM’s Power Systems server line. Alongside this, the company separately said the same software would be available on HPE ProLiant systems, as well as Cisco UCB B-series blade servers, as reported by ZDNet.
This came as news to HPE, who two days later put out a since-deleted blog post (Wayback link here, screenshot here), attributed to VP marketing Paul Miller, titled ‘Don’t be misled… HPE and Nutanix are not partners.”
“HPE values support with unambiguous accountability. Something you won’t get from Nutanix software on third party infrastructure,” wrote Miller. “They’ve set up a three-vendor decision tree – hardware, software and hypervisor – with a third party agency to deliver support SLAs. This model requires formal agreements from all parties. HPE has not entered to this agreement and we do not support their software on our hardware.”
All change now, however – although one could potentially infer the balance of power based on the canned quotes in the press materials. HPE CEO Antonio Neri said the company was “expanding its leadership in [the as-a-service consumption market] by providing an additional choice to customers seeking a hybrid cloud alternative that promises greater agility at lower costs.” Nutanix chief executive Dheeraj Pandey said: “We are delighted to partner with HPE for the benefit of enterprises looking for the right hybrid cloud solution for their business.”
As far as Google is concerned, this is one of many partnerships coming out during the company’s Next event in San Francisco this week. Of most interest during the keynote yesterday, as this publication explored, were proposed deals with seven leading open source software vendors.
Interested in hearing industry leaders discuss subjects like this and sharing their experiences and use-cases? Attend the Cyber Security & Cloud Expo World Series with upcoming events in Silicon Valley, London and Amsterdam to learn more.
As technology continues to advance, so does the amount of data generated on a daily basis, both internally – through marketing, sales, production, and finance, among others – and externally, from sources like the internet of things.
Storing and analysing all this data requires a dedicated system that can integrate a variety of data types, as well as provide information and insight. Not all traditional, on-site data warehouses are still up to the task. Because of this, cloud data warehousing has emerged, which has opened doors for organisations of all sizes and types.
‘Cloud data warehousing for dummies’ is a must-read whitepaper for any organisation looking for tips on migrating, considerations for choosing a new system, data trends, and more.
Like a traditional data warehouse, a cloud data warehouse is a computer system dedicated to storing and analysing data to find patterns and correlations that lead to information and insight. Data warehouses also store and integrate data from multiple sources in varying formats. However, cloud data warehousing is based in the cloud, not in a traditional, on-premise location, and as such can be bought from and managed by a vendor in an as-a-service product.
With that in mind, here are four business benefits of cloud data warehousing.
Flexibility is an important factor of cloud data warehousing. Organisations will have the ability to scale compute and storage independently, pending the company’s needs. So, if a business needs more storage today, they won’t also be forced to add more compute. But if their situation changes in the future, they can adjust however needed.
With the help of data analytics, semi-structured data has the capability to provide next-level insights beyond what traditional data can provide. But semi-structured data must be loaded and transformed before an organisation can analyse it—this is a process most traditional data warehouses can’t handle, but one that cloud data warehouses can.
This ability to support diverse data without performance issues ensures all of an organisation’s data can be loaded and integrated in one location. This not only increases flexibility, but it also means all data can be managed and maintained in one system, reducing costs.
Between licensing fees, hardware, set-up, management, securing and backing up data, and more, conventional data warehouses can cost millions. Not to mention building one that can hold the variety and volume required by today’s standards ups the cost even more.
However, using cloud data warehousing as a service (as it is commonly used today) can cut costs significantly, while keeping all the same features. Relying on service providers to maintain systems and only purchasing the amount of support needed helps organisations stretch their budgets further and avoid paying for unnecessary features.
Explore how your organisation can easily and affordably harness massive amounts of data and transform it into valuable insights in this comprehensive guide to cloud data warehousing.
An important aspect to analysing and storing data is keeping that data safe. In addition to the use of vendor-conducted penetration tests to check for vulnerabilities in the system, modern data warehouses do this through confidentiality and integrity measures.
Confidentiality practices prevent unauthorised access to data, and are usually done through role-based access control, which only allows those permitted to access the data to do so, and multi-factor authentication, which requires users to enter a code (usually one sent to a mobile phone) and ensures a stolen username and password can’t be used to access the system.
Integrity measures guarantee data isn’t modified or corrupted, and entails the use of encryption practices and encryption keys to protect data from unauthorised prying eyes.
Businesses can now up their data centre management game, thanks to the launch of Schneider Electric’s EcoStruxure IT Advisor, an easy to deploy data centre management platform.
IT Advisor combines cloud-based planning and modelling to uncover where businesses can make savings and improve uptime through optimising their facilities.
It can also analyse the business impact that decisions are having on the entire environment, automating workflows to ensure the data centre is running at its optimum.
“Hybrid data centre architectures are driving the industry to rethink the way their data centre infrastructure is managed and operated” said Kim Povlsen, vice president and general manager of Digital Services and Software at Schneider Electric.
“EcoStruxure IT Advisor addresses this need by offering customers a powerful cloud-based or on-premise data centre planning and modelling software, accessible from anywhere, and delivered with a flexible subscription model.”
Schneider Electric’s EcoStruxure IT Advisor features asset management, laying out data in each environment and enabling teams to view device details and asset attributes in a logical way.
In-depth risk planning models potential incidents and demonstrates the impact they may have on devices and infrastructure, while change management is supported by automated workflows, reducing the possibility of human error and ensuring best practices are out in place.
Schneider Electric has also integrated features to help co-location facilities understand how data is distributed.
It maps out areas, cages and racks with assets in a “floor view”, displaying how racks are being utilised so organisations know where there is space and make sure they’re using their resources in the most logical and efficient manner.
The IT Advisor system is an expansion of Schneider Electric’s EcoStruxure IT platform, which also includes EcoStruxure IT Expert, software that allows for the monitoring of physical IoT assets, and EcoStruxure Asset Advisor, a 24/7 monitoring service provided through its partner network.
HPE and Nutanix have expanded their partnership with the launch of an integrated hybrid cloud-as-a-service platform, combining HPE’s GreenLake and Nutanix’s Enterprise Cloud OS software.
The companies said that offering their products together will serve up a hybrid infrastructure fully-managed by HPE, at a lower cost than on-premise solutions. It also offers more flexibility in both customer data centres or a co-location facility.
The offering has been designed for businesses wanting to scale-up their infrastructure to operate mission-critical workloads and big data applications. It supports SAP, Oracle, and Microsoft environments, plus virtualised big data applications, such as Splunk and Hadoop.
The announcement is in response to a problem of overcomplexity from legacy hardware, and concerns over vendor lock-in when attempting to move to a hybrid model, according to the companies.
“HPE created the modern on-premises, as a service consumption market with HPE GreenLake. Hundreds of global customers now leverage HPE GreenLake to get the benefits of a cloud experience combined with the security, governance, and application performance of an on-premises environment, while paying for the service based on actual consumption,” said Antonio Neri, president and CEO, HPE.
“Today, HPE is expanding its leadership in this market by providing additional choice to customers seeking a hybrid cloud alternative that promises greater agility at lower costs.”
As part of the agreement, Nutanix’s channel partners will gain access to HPE’s servers, giving them the opportunity to sell the hardware alongside Nutanix’s software, offering customers a fully-integrated solution.
“Our customers tell us that it’s their applications that matter most. Our partnership with HPE will provide Nutanix customers with another choice to make their infrastructure invisible so they can focus on business-critical apps, not the underlying technology,” said Dheeraj Pandey, founder, CEO and chairman of Nutanix.
“We are delighted to partner with HPE for the benefit of enterprises looking for the right hybrid cloud solution for their business.”
Google has revealed its Cloud Services Platform has been rebranded to Anthos, a vendor-neutral app development platform that will work in tandem with rival cloud services from Microsoft and AWS.
It was developed as a result of customers wanting a single programming model that gave them the choice and flexibility to move workloads to both Google Cloud and other cloud platforms such as Azure and AWS without any change.
The news was announced during Thomas Kurian’s first keynote speech at a Google Cloud Next event as the company’s new CEO, succeeding Diane Greene’s departure in November last year.
The announcement was met with the loudest cheer of the day from the thousands-strong crowd in attendance who seemed to share the same enthusiasm as the industry analysts who have been trying to convince Google that 88% of businesses will undergo a multi-cloud transformation in the coming years.
That could be some way off though, considering global market intelligence firm IDC said last year less than 10% of organisations are ready for multi-cloud, with most sticking to just one vendor.
Anthos will allow customers to deploy Google Cloud in their own datacentres for a hybrid cloud setup and also allow them to manage workloads within their datacentre, on Google Cloud or other cloud providers in what’s being described as the world’s first true cloud-agnostic setup.
«The only way to reduce risk is by going cloud-agnostic», at least that’s according to Eyal Manor, VP engineering at Anthos. He said that managing hybrid clouds is too complex and challenging, and the reason why as much as 80% of workloads are still not in the cloud.
As it’s entirely software-based and requires no special APIs or time spent learning different environments, Manor said you can install Anthos and start running it in less than 3 hours.
It became generally available Tuesday both on GCP with Google Kubernetes Engine (GKE), and in customers’ datacentres with GKE On-Prem.
The announcement marks Google’s apparent move to make managing infrastructure much simpler for its customers so they can focus on improving their business.
By using Anthos, enterprises can depend on automation so they can «focus on what’s happening further up the stack and take the infrastructure almost for granted», said Manor. «You should be able to deploy new and existing apps running on-premise and in the cloud without constantly having to retrain your developers – you can truly double down on delivering business value».
Some of the world’s leading businesses have been given early access to the platform already such as HSBC which needs a managed cloud platform for its hybrid cloud strategy.
«At HSBC, we needed a consistent platform to deploy both on-premises and in the cloud,» says Darryl West, group CIO, HSBC. «Google Cloud’s software-based approach for managing hybrid environments provided us with an innovative, differentiated solution that was able to be deployed quickly for our customers.»
GCP customers have already invested heavily into their infrastructure, forging relationships with their vendors too which is why Google has launched Anthos with an ecosystem of leading vendors so users can start using the new platform from day one.
Cisco, VMware, Dell EMC, HPE, Intel and Atos are just a few that have committed to delivering Anthos on their own hyperconverged infrastructure for their customers.
