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NCS-Core Nutanix Certified Services Core Infrastructure Professional

Exam Detail:
The NCS-Core exam, also known as "Nutanix Certified Services Core Infrastructure Professional," is a certification exam that validates the knowledge and skills of IT professionals in deploying and managing Nutanix solutions in a core infrastructure environment. Here are the details of the NCS-Core exam:

- Number of Questions: The NCS-Core exam typically consists of multiple-choice questions (MCQs) and may include scenario-based questions. The exact number of questions may vary, but it generally ranges from 60 to 70 questions.

- Time Limit: The time allocated to complete the NCS-Core exam is usually around 90 minutes. However, the duration may vary depending on the specific exam requirements and the exam delivery platform.

Course Outline:
The NCS-Core exam covers a wide range of syllabus related to deploying, managing, and troubleshooting Nutanix solutions in a core infrastructure environment. The exam assesses the candidate's knowledge in the following areas:

1. Nutanix Core Concepts and Architecture:
- Understanding the key concepts, components, and architecture of Nutanix solutions.
- Exploring the functionality of Nutanix Prism and the Nutanix Acropolis Operating System (AOS).
- Understanding the deployment options and considerations for Nutanix clusters.

2. Nutanix Cluster Deployment and Configuration:
- Deploying Nutanix clusters and nodes in different deployment scenarios.
- Configuring network and storage resources for Nutanix clusters.
- Performing initial cluster configuration and cluster expansion.

3. Nutanix Cluster Management and Operations:
- Managing Nutanix clusters using the Prism interface.
- Configuring and monitoring Nutanix resources, including virtual machines (VMs), storage, and networking.
- Understanding Nutanix cluster maintenance tasks and best practices.

4. Nutanix Data Services and High Availability:
- Configuring data services such as compression, deduplication, and erasure coding.
- Implementing Nutanix high availability mechanisms and disaster recovery solutions.
- Understanding data protection and backup strategies in Nutanix environments.

5. Nutanix Troubleshooting and Support:
- Identifying and resolving common issues and performance bottlenecks in Nutanix clusters.
- Understanding Nutanix support resources and troubleshooting methodologies.
- Utilizing Nutanix support tools and diagnostic utilities.

Exam Objectives:
The objectives of the NCS-Core exam are as follows:

- Evaluating the candidate's knowledge and understanding of Nutanix core concepts, architecture, and deployment models.
- Assessing the candidate's ability to deploy and configure Nutanix clusters, including network and storage resources.
- Testing the candidate's skills in managing and monitoring Nutanix resources using the Prism interface.
- Verifying the candidate's knowledge of Nutanix data services, high availability mechanisms, and disaster recovery solutions.
- Assessing the candidate's troubleshooting skills in identifying and resolving common issues in Nutanix clusters.
- Testing the candidate's understanding of Nutanix support resources and diagnostic tools.

Exam Syllabus:
The NCS-Core exam covers the following topics:

1. Nutanix Core Concepts and Architecture
2. Nutanix Cluster Deployment and Configuration
3. Nutanix Cluster Management and Operations
4. Nutanix Data Services and High Availability
5. Nutanix Troubleshooting and Support
Nutanix Certified Services Core Infrastructure Professional
Nutanix Infrastructure book

Other Nutanix exams

Nutanix-NCP Nutanix Certified Professional 5.10
NCP-MCI-5.15 Nutanix Certified Professional Multicloud Infrastructure (v5.15)
NCS-Core Nutanix Certified Services Core Infrastructure Professional
NCSE-Core Nutanix Certified Systems Engineer-Core (NCSE-Core)
NCSE-Level-1 Nutanix Certified Systems Engineer (NCSE): Level 1
NCP-MCI-6.5 Nutanix Certified Professional - Multicloud Infrastructure (NCP-MCI) v6.5

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Question: 59
An administrator needs to deploy an application with a large amount of data connected via Nutanix Volumes.
Which two actions should the administrator take when designing the Volume Group? (Choose two.)
A . Use multiple subnets for iSCSI traffic
B . Enable RSS (Receive Side Scaling)
C . Enable thick provisioning on the Volume Group(s)
D . Distribute workload across multiple virtual disks
Answer: B,D
Question: 60
A customer is running out of storage in an ESXi cluster. The customer wants to add storage without paying for an
additional hypervisor license.
Which option should the consultant recommend to meet the requirement?
A . Convert the cluster to AHV to support storage-only node requirements.
B . Select the storage-only checkbox during Foundation and then expand the cluster in Prism.
C . Buy a new node to meet the requirements of the storage-only node specifications.
D . Edit the factory_config.json file to configure the node as storage-only and then expand the cluster in Prism
Answer: C
Question: 61
An organization is running a Nutanix Cluster based on AOS 5.10.x and VMware vSphere 6.7. Currently, the CVM
network is segmented and Storage only nodes not present.
A new security project based on NSX is coming. VMware Distributed Virtual Switches are required. The administrator
needs to prepare the environment for the new project.
Which step should the administrator use to initiate the project?
A . Enable Nutanix Flow at the Prism Central Level
B . Manually disable CVM network Segmentation
C . Convert storage only nodes into vSphere nodes
D . Enable Jumbo Frames to accommodate network frames
Answer: D
Question: 62
An administrator is configuring software only. Data-at-Rest Encryption on their Nutanix cluster. They are planning to
deploy a third-party key management server (KMS).
Where should this server be hosted?
A . As a single VM on the Nutanix cluster
B . On hardware external to the Nutanix duster
C . As a clustered VM setup on the Nutanix cluster
D . As a single VM deployed on the host that contains the Prism leader CVM
Answer: B
Question: 63
An administrator needs to create and start five new VMs for a Data Analytics Project (OLAP).
The VM Profile is as follows:
vCPU:4
vRAM: 64 GB
vDisk: 1.5 TB
Each of the four nodes of the Nutanix cluster has the following:
24 vCPU. 20% overall usage
192 GB RAM, 60% overall usage
2xl920GBSSD
4x 2 TB HDD
At cluster level, there is a single RF2 container that is 30% utilized and has an extent store capacity of 13.5 TB.
Which component requires administrator attention?
A . Physical RAM, because it is not enough to power on all of the new VMs.
B . Physical Cores, because they are not enough to power on all of the new VMs.
C . Storage, because the capacity is not enough to create VMs.
D . Flash Tier because it is not enough to accommodate the workloads.
Answer: A
Question: 64
A VDI environment based on AHV Cluster is not performing well. The current environment is using only one bridge
(Bridge0). The administrator needs to verify if nodes are using all network cards associated to Bridge0.
Which two menus should be used to check the current configuration? (Choose two.)
A . Network Configuration item in Settings menu
B . Host view in Network menu
C . Host NICs tab in Hardware menu
D . I/O Metrics tab in VM menu
Answer: B,C
Question: 65
A consultant is onsite with a customer running Foundation VM (FVM) and discovers that there is no connectivity
between the FVM and their laptop.
The consultant verifies the following:
* The consultants laptop and Nutanix nodes are plugged into a flat switch.
* The laptop, switch and nodes are plugged into supported power supplies.
* The laptop network adapters and FVM are configured with their corresponding IP addresses.
What is the cause for the connectivity failure to the FVM?
A . The switch is not plugged into the power supply.
B . Desktop Firewall is blocking ping requests.
C . Network cables are not connected.
D . Laptop WiFi configured to use DHC
Answer: B
Question: 66
A customer with a four-node RF2 cluster is adding application VMs to their system. After adding these VMs, the
Prism dashboard shows 81% storage utilization.
What is the consequence of running the cluster at 81% storage utilization?
A . The customer has the ability to add more VMs up to the 100% storage utilization.
B . There is available capacity in the storage fabric and the cluster is resilient.
C . Node failure is imminent due to storage utilization.
D . The cluster is not resilient in the storage fabric
Answer: D
Explanation: https://next.nutanix.com/how-it-works-22/recommended-maximum-storage-utilization-37234
Question: 67
Refer to the exhibit.
After performing ESXi to AHV conversion on a cluster, the alerts shown in the exhibit display on Prism .
What should the administrator do to resolve this issue efficiently?
A . Remove the VMs. create a new Protection Domain, and add VMs to it
B . Remove VMs from the Protection Domain and add them back in.
C . Delete the Protection Domain, create a new Protection Domain, and add the VMs to it
D . Create a new Protection Domain and add the VMs to rt.
Answer: B
Question: 68
Refer to the exhibit.
An administrator notices a critical alert on the Metro Availability Protection Domain
What is causing this alert?
A . Metro Availability Protection domain is active on the remote site.
B . VMware Site Recovery Manager is handling a failover event
C . Metro Availability did not fail over and caused an outage.
D . vSphere moved VMs to the remote container, and the VMs must be moved back.
Answer: A
Explanation:
Ref: https://www.vvlsystems.com/wp-content/uploads/2016/11/BP-2009_Metro_Availability.pdf
Question: 69
A VM does not have enough resources for the demand, which leads to performance bottlenecks.
The VM is exhibiting one or more of following baseline values, based on the past 30 days:
CPU usage > 90% (moderate), 95% (high)
CPU ready time > 5%, 10%
Memory usage > 90%, 95%
Memory swap rate > 0Kbps (no moderate value).
Which type of VM is being described?
A . Constrained VM
B . Bully VM
C . Inactive VM
D . Over-provisioned VM
Answer: A
Question: 70
An administrator has a custom backup application that requires a 2TB disk and runs in Windows. Throughput is
considerably lower than expected.
The application was installed on a VM with the following configuration:
Four vCPUs with one core/vCPU
4GB of Memory
One 50GB vDisk for the Windows installation
One 2TB vDisk for the application
What is the recommended configuration change to Improve throughput?
A . Increase the number of cores per vCPU
B . Increase the vCPUs assigned to the VM
C . Span the 2TB disk across four vDisks
D . Add 4GB of memory to the VM
Answer: C
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Thu, 04 Jan 2024 18:29:00 -0600 en-US text/html https://yourstory.com/2024/01/nutanixs-mandy-dhaliwal-shape-tech-future-focusing-innovation
LLM series - Nutanix: Boxed for builders, how to forge & create developer AI tools

This is a guest post for the Computer Weekly Developer Network written by James Sturrock in his position as director of systems engineering, UK&I at Nutanix.

Sturrock writes as follows in full…

As we look out across the topographies that today describe modern enterprise software stacks, systems and solutions, we can clearly see that Artificial Intelligence (AI) – whether that be predictive, reactive or generative AI – has now become a core mandate.

With generative AI coming to the fore and now promising to bring accelerating automation advantages to every conceivable application we use, it may appear to be a case of boiling the ocean, drinking from a firehose and moving heaven and earth for IT departments that have yet to really embark on this journey. It can certainly seem like a daunting task, so where should we start?

Firstly, let’s remind ourselves how AI should be implemented.

AI use cases

Organisations in all industries now have the opportunity to recognise how AI can be used to amplify business security and reliability; many firms will find that AI can be applied to enhance data protection and Disaster Recovery (DR) as key cornerstones.

We can also remind ourselves how broad the application of AI can (and arguably should) be. This is because AI isn’t confined to one location, a large proportion of firms should think about how to boost their AI edge computing strategy investment as it exists in the Internet of Things (IoT).

But for AI to be truly effective, an organisation needs to be able to evidence a commensurate level of data management competency. In this age of cloud, it makes sense to identify platforms that can deliver integrated enterprise data services and security to protect the company’s AI models and data. It’s no good having bad data i.e. poorly parsed, deduplicated, unstructured or unsecured, but EVEN WHEN an organisation has good data, it’s no good if the business information streams are offline – this is a platform-level progression and it should be regarded as such.

A before AI

Getting AI running in an already-operational business is a team effort. This means working with both data scientists and developers (plus of course business stakeholders) to bridge the gap between their worlds and be able to use AI via platforms that deliver cloud-like operations to enable seamless access to workloads and data…

Nutanix’s Sturrock: Focus on key foundational structures at the infrastructure level for AI foundation models.

… and, as a secondary but no less fundamental point here, if we had to add another A before the AI in AI, it would be accessibility, adaptability and application applicability. This means that AI-empowered applications should be accessible and adaptable from the start. Organisations need to be able to buy, build, or modify AI models and data from any source; they should then be able to run them anywhere that their business requires the injection of AI to manifest itself.

But as much as we have said thus far (and to further validate our A for accessibility) we must also remember that using generative AI should not require a fully-blown subscription to a Cloud Services Provider (CSP) hyperscaler.

Our own CEO Rajiv Ramaswami reminds us that because many IT teams are still in a prototyping phase with AI, they are almost ‘playing’ with it in terms of discovering how its benefits can be captured, harnessed and indeed monetized. But we know that AI requires solid infrastructure and there is already a shortage of GPUs. It may be easy enough to build an AI model in the public cloud, but implementation is much more cost-effective in a hybrid cloud.

AI to go, carry out

There’s a packaging process happening here.

You could call it packaged generative AI, you could call it a compartmentalised intelligence services framework (if you wanted to make heads spin and over-jargonise it)… or you could just call it GPT-in-a-box – spoiler alert, we did call it that and it means that when software application developers are looking at the massive learning curve they face to gain competency with LLM data science techniques, there are shortcuts which help validate (there’s that word again, sorry) the use of these technologies in live production environments. This is a turnkey software-defined solution designed to seamlessly integrate generative AI and AI/ML applications into an organisation while keeping data and applications under your control.

When firms look at the consolidation factor that they can achieve in modern IT stacks, they can think about bringing together unified storage for data and their MLOps stack in one place.

As our own, VP of system engineering Paulo Perreira has previously explained, “Companies see the potential of generative AI and want to get the same results. But they wonder whether they want to bring their data to the cloud. Your internal data becomes part of the public domain. But models by themselves are worthless without data. GPT-in-a-box uses open-source models and trains them with private data. Users thus retain control over their data because it stays within the organisation. Companies see the potential of generative AI and want to get the same results. But models are worthless without your data.”

Underlying mechanics for developer AI

The goal of this discussion is to consider the environments required for developers to be able to work with Large Language Models (LLMs) and for that engineering to result in AI & ML models that are functional, bias-free, cost effective, safe and secure. For any of that to happen, software teams need to look at the underlying mechanics and supporting platforms that they execute these workloads with, on, through and over. That means looking for cloud substrate services that can cope with the model training and the resulting generative AI that is delivered.

We presume that a deep understanding of pre-trained model training leads to better decision-making for LLM system design, including model sizing, dataset sizing and compute infrastructure provisioning. Some customers might need to train a pre-trained model from the ground up because their datasets are very different. The compute infrastructure provisioning for LLM pre-training can be a complex endeavour, especially when we start to think about concerns related to data privacy, data sovereignty and data governance.

Once again, this is a platform play consideration and developers need to think about the back-end before they build the front-end.

MLOps is tops

As we move ahead in this space and start to enable an increasing number of tools for generative AI software development, we are already working to ensure we can balance the infrastructure services beneath.

Due to significant advancements in machine learning over the past few years, AI models can now be applied to a wide range of complex tasks. We will need to embrace MLOps as a key methodology to underpin the lifecycle of models and ensure that MLOps consists of workflows for the different pieces of the lifecycle including training, inference, hyperparameter tuning etc.

There is complexity here, but there is also key foundation support at the infrastructure level for the foundation models that we now drive into our LLM-empowered generative AI development. It’s time to look ahead, but make sure we have our ‘feet’ planted on the right infrastructure and cloud platform first.

Mon, 18 Dec 2023 16:16:00 -0600 en text/html https://www.computerweekly.com/blog/CW-Developer-Network/LLM-series-Nutanix-Boxed-for-builders-how-to-forge-create-developer-AI-tools
Nutanix .NEXT 2020: 7 Biggest Product Announcements

CRN breaks down the seven biggest launches Tuesday at Nutanix .NEXT—from new hyperconverged infrastructure software to Kubernetes and security offerings.

ARTICLE TITLE HERE

Nutanix .NEXT 2020

See the latest entry: Nutanix .Next 2021: 5 Huge Launches You Need To Know

Nutanix’s virtual .NEXT conference kicked off Tuesday as the hyperconverged and hybrid cloud software standout launched a slew of new products and as-a-service offerings ranging from hyperconverged infrastructure software to Kubernetes and security offerings.

“There’s a lot of room for growth in hyperconverged, and channel partners have a huge opportunity right now with Nutanix,” said Nutanix CTO Rajiv Mirani in an interview with CRN. “We’ve made significant investments in R&D to advance our core software stack as you can see with these releases. We’re continuing to set the bar for innovation.”

Thousands of people are expected to participate in Nutanix’s free .NEXT Digital Experience conference, which runs from Sept. 8 to Sept. 11.

CRN breaks down the seven biggest product news and announcements unveiled at Nutanix .NEXT.

Karbon Platform Services: Kubernetes PaaS

One of Nutanix’s biggest launches at .NEXT is its new Karbon Platform Services, a Kubernetes multi-cloud Platform as a Service (PaaS) with automated system-managed security. The new cloud-native PaaS gives software developers a turnkey managed services experience on-premises, in the public cloud or at the edge to build and run cloud-native applications. Karbon Platform Services also lets developers decouple applications from the underlying infrastructure.

“Our Karbon Platform Services is a full PaaS offering that essentially takes some of the most common cloud-native services and makes them available on-premises. So capabilities like Containers as a Service, but also Functions as a Service, serverless applications, support for monitoring with Prometheus, as well as advanced networking and data services,” said Mirani. “Few applications today are just self-contained inside a container, they do use all these other PaaS services as well. … We wanted to make Karbon very simple.”

Karbon Platform Services builds on the core Kubernetes life-cycle management capabilities with Karbon as an integrated component of the Nutanix HCI software. This new offering brings automated system-managed security and multitenancy to run a wide range of microservices-based applications across multiple cloud infrastructures, said Mirani.

“It’s a great opportunity for the channel because as people monetize their applications, they look for new ways to build them,” said Mirani. “This is something that could be a great value-added service that our partners can provide.

Nutanix Karbon Platform Services is now available.

HCI Software With New Blockstore Technology And Intel

Nutanix has revamped its flagship HCI architecture by injecting NVMe-based SSDs and Intel Optane SSDs, delivering up to 50 percent faster performance for I/O-intensive workloads such as large databases.

“It improves performance on some of the most complex workloads that we have by up to 50 percent. Things like latencies when you have sustained operations or IOPS [Input/Out Operations Per Second] when you have sustained operations. The way we did this was to rearchitect AOS,” Nutanix’s Mirani told CRN. “Obviously, it lets us go after the most critical applications like SAP HANA, Epic, etc. So that’s always extending the reach of what we can do.”

Nutanix’s new Blockstore technology self-manages storage with greater efficiency than traditional file systems. In addition, Nutanix HCI software adds support with the Storage Performance Development Kit, an open-source library developed by Intel that enables applications to access NVMe capacity directly in order to avoid any OS or kernel-level overhead and drive even faster workload performance.

“The net result is that with these improvements in performance, we continue to extend our lead,” said Mirani. “It really makes us well positioned for some of the newer hardware technologies that we just started working with.”

The enhanced Nutanix HCI software is now available.

Flow Security Central

Nutanix is launching a new centralized SaaS-based management plan, Flow Security Central, which provides compliance monitoring, network visibility and security operations across Nutanix-powered private clouds and public cloud environments. The offering also provides new micro-segmentation security planning as well as security audit and remediation.

“Flow Security Central is not just networking, it’s a lot more than that. It provides a view into your security posture, into your compliance requirements as well as doing networking monitoring. Think of it as single pane of glass from which you can monitor your Nutanix infrastructure, look for compliance violations, you can get recommendations on how to fix them—but on top of that, you can look into your network traffic, get recommendations on micro-segmentation rules and so on,” said Mirani.

Flow Security Central provides customers with a hub for their security operations so they can assess their overall security posture of Nutanix deployments and generate detailed recommendations to bring environments into compliance. In addition, it offers the network visibility and context needed to secure cloud networks and applications, according to Mirani.

Flow Security Central is now available.

Prism Ultimate

Nutanix is taking its infrastructure and hypervisor management offering, Prism, to the next level with the launch of Prism Ultimate, a cloud-based SaaS service.

Prism Ultimate adds advanced application insight and automation for troubleshooting application-related infrastructure bottlenecks. It also offers visibility into cloud IT resource consumption for targeted IT cost reductions and more accurate budgeting.

Nutanix Prism can also monitor non-Nutanix environments, including popular virtualization stacks, to supply Nutanix customers a single pane of glass for their entire infrastructure.

“Prism Ultimate is mainly based around analytics and monitoring, but instead of running on-premises this will run as a SaaS service in the cloud,” said Mirani. “We can apply a lot more resourcing in terms of CPU memory and so on, and provide even deeper insight into what’s happening. Plus, over time, you’ll be able to do cross-customer analytics.”

Prism Ultimate is currently available.

Nutanix Flow Networking, New VPC Technology

Built into Nutanix’s AHV virtualization, Nutanix Flow delivers advanced networking and security services to provide visibility into a virtual network as well as application protection and automation of common network operations.

At .NEXT, Nutanix introduced Flow Networking, aimed at simplifying the tasks of creating, isolating and managing software-defined networks that connect applications running in private data centers and in public clouds. The goal is to significantly simplify networking for hybrid and multi-cloud deployments. The new offering is based on virtual private cloud (VPC) constructs used by the leading public cloud providers and is a result of the company’s multiyear investment in Nutanix Xi Cloud that powers Nutanix’s cloud-based offerings.

“We have our own Xi offering, which lets you do disaster recovery as a service. We’ve developed the technology in the context of that so when people fail over to the Nutanix cloud, they don’t have to change their IP addresses to get their own virtual cloud which they can operate. We’re making that technology available on-premises,” said Mirani. “So people can now create on-premises multiple virtual private clouds completely isolated from each other and enable networking multitenancy within their on-premises infrastructure.”

The new software-defined networking capabilities of Nutanix Flow Networking are currently in development and will become available in late 2020, according to Mirani.

Calm as a Service

Nutanix also unveiled Calm as a Service, a hosted version of its application management and orchestration offering to support DevOps teams.

“Calm itself used to run only on a Nutanix AOS cluster. We’re now making it available as a service. You’ll be able to orchestrate and automate your environments from the cloud,” said Mirani. “So now there’s no dependency at all on Nutanix. Of course, you’ll still be able to orchestrate and automate Nutanix environments as well, but if you’re using it for VMware or cloud environments you can do that straight from the cloud.”

Nutanix Calm automates provisioning, scaling and life-cycle management for the cloud. Calm as a Service is now available.

New Elevate Partner Program

On the channel partner front, Nutanix launched its new Elevate Partner Program that for the first time brings together all of Nutanix’s partner ecosystem from VARs, systems integrators and distributors to service providers and hardware vendors.

Elevate includes new front-end margins, mechanisms to help deliver margin-rich services, better rebate levels for bringing in new business, and a new rebate that rewards Elevate Cloud Champion partners for selling across the entire Nutanix portfolio.

Nutanix also created a new partner portal with greater access to information and insight across the partner ecosystem through custom-branded marketing materials, training tools and personalized insight, allowing for more effective data-driven decisions. Another new enhancement is Nutanix’s new Performance+ Deal Registration, designed to increase incentive potential and opportunity protection. The deal registration program provides increased partner discounts, more predictable deal margins and enhanced opportunity protection.

Nutanix also launched a new Americas Partner Support Center – a team of dedicated channel sales, systems engineers and marketing resources—who will deliver an enhanced partner experience and will be available to usher the partner community through the transition along with ongoing presales support. The Elevate Partner Program emphasizes partner capabilities and competencies to sell and support Nutanix’s portfolio rather than revenue thresholds.

Tue, 08 Sep 2020 04:01:00 -0500 text/html https://www.crn.com/slide-shows/cloud/nutanix-next-2020-7-biggest-product-announcements
Nutanix, Google Partner To Bring Hyper-Converged Infrastructure Across On-Prem, Cloud Environments

A new strategic relationship between Nutanix and Google is aimed at making it easier for Nutanix-based hyper-converged infrastructure workloads to easily migrate to the Google cloud.

The relationship, unveiled at Nutanix's .NEXT conference, being held this week in Washington, D.C., builds a bridge between on-premise and cloud deployments, said Venugopal Pai, vice president of business development and alliances at San Jose, Calif.-based Nutanix.

It is part of a wider Nutanix effort to bring its hyper-converged infrastructure technology to hybrid clouds.

[Related: Nutanix Introduces Multi-Cloud Capabilities, Extends Hyper-Converged Infrastructure Across The Data Center To Cloud]

Nutanix Wednesday also unveiled Xi Cloud Services, which extends data center services to the cloud, either an upcoming Nutanix cloud or the Google Cloud Platform, via the company's Prism centralized data center infrastructure management software. The first service will be Xi Cloud Disaster Recovery.

Nutanix also unveiled the Nutanix Enterprise Cloud OS software, an application that extends the Nutanix hyper-converged infrastructure environment to the cloud.

In addition, the company introduced Nutanix Calm, a single software fabric that lets customers define and publish applications in the form of blueprints that can then be provisioned across different cloud environments.

Nutanix and Google are partnering in two ways to bridge the two worlds, Pai told CRN.

The first is Nutanix support for Kubernetes, the container technology pioneered by Google before being released to open source, Pai said. Nutanix customers can now run applications built in Kubernetes containers on-premise and in the Google Cloud Platform.

"So now we can bridge customers looking for Kubernetes in the cloud or on-prem," he said. "We allow the seamless transportation of containers to the Google Cloud Platform with a single click."

The other part of the Nutanix and Google relationship is the ability to run native Nutanix services and Kubernetes container applications both on-premise and in the Google Cloud Platform via the new Nutanix Xi Cloud Services, Pai said.

The first Nutanix Xi Cloud Service is disaster recovery. "With our new relationship, customers can easily move virtual machines for disaster recovery purposes to Google via Xi Cloud Services," he said.

The Nutanix and Google partnership is important as clients increasingly move part, but not all, of their IT to the cloud, said Jeff Guenthner, director of solutions architecture at CMI, a Mill Valley, Calif.-based solution provider and Nutanix channel partner.

"Every client we talk to has a cloud-first strategy, yet has legacy ties and is on a journey to being a hybrid enterprise," Guenthner told CRN via e-mail. "We understand the driving forces pushing this client paradigm. It was a main tenet in our decision to make them our [hyper-converged infrastructure] go-to market partner. Regardless of the current point [for] our clients on the hybrid enterprise journey, Nutanix is complementary."

Thu, 29 Jun 2017 01:27:00 -0500 text/html https://www.crn.com/news/cloud/300087966/nutanix-google-partner-to-bring-hyper-converged-infrastructure-across-on-prem-cloud-environments
Infrastructure Development and Ape Conservation

Crossref Citations

This Book has been cited by the following publications. This list is generated based on data provided by Crossref.

McLennan, Matthew R. Hintz, Benjamin Kiiza, Vicent Rohen, Jacqueline Lorenti, Georgia A. and Hockings, Kimberley J. 2021. Surviving at the extreme: Chimpanzee ranging is not restricted in a deforested human‐dominated landscape in Uganda. African Journal of Ecology, Vol. 59, Issue. 1, p. 17.


Andrasi, Balint Jaeger, Jochen A.G. Heinicke, Stefanie Metcalfe, Kristian and Hockings, Kimberley J. 2021. Quantifying the road‐effect zone for a critically endangered primate. Conservation Letters, Vol. 14, Issue. 6,


Galea, Benjamin and Humle, Tatyana 2022. Identifying and mitigating the impacts on primates of transportation and service corridors. Conservation Biology, Vol. 36, Issue. 1,


Ascensão, Fernando D’Amico, Marcello and Barrientos, Rafael 2022. No Planet for Apes? Assessing Global Priority Areas and Species Affected by Linear Infrastructures. International Journal of Primatology, Vol. 43, Issue. 1, p. 57.


Tue, 01 Jun 2021 12:28:00 -0500 en text/html https://www.cambridge.org/core/books/infrastructure-development-and-ape-conservation/C33D200CE87F1336C8BEF997BCE36BDD
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