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Cisco Data Intelligence Platform (CDIP) Solution Overview

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Updated:August 24, 2021

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The documentation set for this product strives to use bias-free language. For the purposes of this documentation set, bias-free is defined as language that does not imply discrimination based on age, disability, gender, racial identity, ethnic identity, sexual orientation, socioeconomic status, and intersectionality. Exceptions may be present in the documentation due to language that is hardcoded in the user interfaces of the product software, language used based on RFP documentation, or language that is used by a referenced third-party product. Learn more about how Cisco is using Inclusive Language.

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Updated:August 24, 2021
 

 

Modernizing your data lake to the evolving landscape

In today’s environment, voluminous amounts of data ends up being stored in data ecosystem. Enterprises are constantly evaluating new sets of data management for processing, transforming, and analyzing these large amounts of data leading to newer data pipelines evolving beyond the standard data lake.

The rapid advancement with artificial intelligence and machine learning has brought new a set of challenges for business and IT organization’s data strategy when it comes to implementing high-performance, scalable, and agile fashion cloud-scale architecture.

The next generation of distributed systems for big data analytics needs to address data silos between different tiers such as data lakes, data warehouse, AI/compute, and object storage. It is imperative to develop an infrastructure that sustains a healthy data pipeline between storage devices and computing devices (CPU, GPU, FPGA), reduces network bandwidth, and achieves overall low latency for parallel data processing is critical for supporting an organization’s goals.

Hadoop ecosystem has evolved over the years from batch processing (Hadoop 1.0) to streaming and near real-time analytics (Hadoop 2.0) and to Hadoop meets AI (Hadoop 3.0). Currently the capabilities of the technologies are evolved to enable the data lake as a private cloud with separation of storage and compute and, going forward, support of the hybrid cloud (and multicloud).

Cloudera released the following two types of software in the second half of 2020, both of which together enable the data lake as a private cloud:

      Cloudera Data Platform (CDP) Private Cloud Base, which provides storage and supports the tradition-al data lake environments and introduced Apache Ozone, the next-generation file system for data lake and

      Cloudera Data Platform Private Cloud Experiences, which provides different experiences or personas (data analyst, data scientist, data engineer) based on processing of workloads for data stored in CDP Private Cloud Base

Apache Ozone initiative provides the foundation for the next generation of storage architecture for HDFS, where data blocks are organized in storage containers for higher scale and handling of small objects in HDFS. The Ozone project also includes an object store implementation to support several new use cases.

Cisco® Data Intelligence Platform (CDIP) is a thoughtfully designed private cloud for data lake requirements, supporting data-intensive workloads with Cloudera Data Platform Private Cloud Base and compute-rich (AI/ML) and compute-intensive workloads with Cloudera Data Platform Private Cloud Experiences, while also providing storage consolidation with Apache Ozone on Cisco UCS® infrastructure fully managed through Cisco Intersight. Cisco Intersight simplifies management and moves management of servers from the network into the cloud.

CDIP as a private cloud is based on the Cisco UCS M6 family of servers, which support 3rd-Gen Intel® Xeon® Scalable family processors with PCIe Gen 4 capabilities. These servers include the following:

      The Cisco UCS C240 M6 Server for Storage (Apache Ozone and HDFS) and extends the capabilities of the Cisco UCS rack server portfolio with 3rd-Gen Intel Xeon Scalable Processors supporting more than 43 percent more cores per socket and 33 percent more memory when compared with the previous generation.

      The Cisco UCS X-Series with Cisco Intersight is a modular system managed from the cloud. It is de-signed be shaped to meet the needs of modern applications and improve operational efficiency, agility, and scale through an adaptable, future-ready, modular design.

We move management from the network into the cloud with Cisco Intersight so that you can respond at the speed and scale of your business and manage all of your infrastructure.

CDIP with Cloudera Data Platform enables the customer to independently scale storage and computing re-sources as needed while offering an Exabyte scale architecture with low total cost of ownership (TCO) and future-proof architecture with the latest technology offered by Cloudera.

Cisco Data Intelligence Platform

Cisco Data Intelligence Platform (CDIP) is a cloud-scale architecture and a private cloud primarily for a data lake, which brings together big data, AI/compute farm, and storage tiers to work together as a single entity while also being able to scale independently to address the IT issues in the modern data center. This architecture provides the following:

      Extremely fast data ingest and data engineering done at the data lake.

      AI compute farm allowing for different types of AI frameworks and compute types (GPU, CPU, FPGA) to work on this data for further analytics.

      A storage tier, allowing to gradually retire data that has been worked on to a storage-dense system with a lower $/TB providing a better TCO; next-generation Apache Ozone file system for storage in a data lake.

      Seamlessly scale the architecture to thousands of nodes with a single pane of glass management using Cisco Intersight and Cisco Application Centric Infrastructure (ACI®).

Cisco Data Intelligence Platform caters to the evolving architecture bringing together a fully scalable infra-structure with centralized management and a supported software stack (in partnership with industry leaders in the space) to each of these three independently scalable components of the architecture, including data lake, AI/ML, and object stores.

Cisco Data Intelligence Platform architecture

Figure 1.            

Cisco Data Intelligence Platform architecture

Cisco Data Intelligence Platform with Cloudera Data Platform

Cisco developed numerous industry-leading Cisco Validated Designs (reference architectures) in the area of big data, compute farm with Kubernetes (CVD with RedHat OpenShift Container Platform), and object store.

A CDIP architecture as a private cloud can be fully enabled by the Cloudera Data Platform with the following components:

      Data lake enabled through CDP private cloud base

      Private cloud with compute on Kubernetes can be enabled through CDP Private Cloud Experiences

      Exabyte storage enabled through Apache Ozone

Cisco Data Intelligent Platform with Cloudera Data Platform

Figure 2.            

Cisco Data Intelligent Platform with Cloudera Data Platform

Cloudera Data Platform (CDP)

CDP is an integrated data platform that is easy to deploy, manage, and use. By simplifying operations, CDP reduces the time to onboard new use cases across the organization. It uses machine learning to intelligently auto scale workloads up and down for more cost-effective use of cloud infrastructure.

Cloudera Data Platform (CDP) Data Center is the on-premises version of Cloudera Data Platform. This new product combines the best of both worlds such as Cloudera Enterprise Data Hub and Hortonworks Data Plat-form Enterprise along with new features and enhancements across the stack. This unified distribution is a scalable and customizable platform where you can securely run many types of workloads.

Cloudera Data Platform provides:

      Unified Distribution: Whether you are coming from CDH or HDP, CDP caters to both. It offers richer feature sets and bug fixes with concentrated development and higher velocity.

      Hybrid and On-Prem: Hybrid and multi-cloud experience, on-premises - it offers the best performance, cost, and security. It is designed for data centers with optimal infrastructure.

      Management: It provides consistent management and control points for deployments.

      Consistency: Security and governance policies can be configured once and applied across all data and workloads.

      Portability: Policies go with data, even when data moves across all supported infrastructure.

Cloudera Data Platform Private Cloud Base (CDP PvC Base)

CDP Private Cloud Base is the on-premises version of Cloudera Data Platform. This new product combines the best of Cloudera Enterprise Data Hub and Hortonworks Data Platform Enterprise along with new features and enhancements across the stack. This unified distribution is a scalable and customizable platform where you can securely run many types of workloads.

CDP Private Cloud Base supports a variety of hybrid solutions where compute tasks are separated from data storage and where data can be accessed from remote clusters, including workloads created using CDP Private Cloud Experiences. This hybrid approach provides a foundation for containerized applications by managing storage, table schema, authentication, authorization, and governance.

CDP Private Cloud Base is comprised of a variety of components such as Apache HDFS, Apache Hive 3, Apache HBase, and Apache Impala, along with many other components for specialized workloads. You can select any combination of these services to create clusters that address your business requirements and workloads. Several preconfigured packages of services are also available for common workloads.

Cloudera Data Platform Private Cloud Experiences (CDP PVC)

Cloudera Data Platform (CDP) Private Cloud is the newest on-prem offering of CDP that brings many of the benefits of the public cloud deployments to the on-prem CDP deployments.

CDP Private Cloud provides a disaggregation of compute and storage and allows independent scaling of compute and storage clusters. Through the use of containerized applications deployed on Kubernetes, CDP Private Cloud brings both agility and predictable performance to analytic applications. CDP Private Cloud gets unified security, governance, and metadata management through Cloudera Shared Data Experience (SDX), which is available on a CDP Private Cloud Base cluster.

CDP Private Cloud users can rapidly provision and deploy Cloudera Data Warehousing and Cloudera Machine Learning services through the Management Console and easily scale them up or down as required.

A CDP Private Cloud deployment requires you to have a Private Cloud Base cluster and a RedHat OpenShift Kubernetes cluster. The OpenShift cluster is set up on a bare-metal deployment. The Private Cloud deployment process involves configuring the Management Console on the OpenShift cluster, registering an environment by providing details of the data lake configured on the Base cluster, and then creating the workloads.

CDP PVC Base and CDP PVC Experiences

Figure 3.            

CDP PVC Base and CDP PVC Experiences

Cloudera Machine Learning

Machine learning has become one of the most critical capabilities for modern businesses to grow and stay competitive today. From automating internal processes to optimizing the design, creation, and marketing processes behind virtually every product consumed, ML models have permeated almost every aspect of our work and personal lives.

Cloudera Machine Learning (CML) is Cloudera’s new cloud-native machine learning service, built for CDP. The CML service provisions clusters, also known as ML workspaces, that run natively on Kubernetes.

Each ML workspace enables teams of data scientists to develop, test, train, and ultimately deploy machine learning models for building predictive applications all on the data under management within the enterprise data cloud. ML workspaces are ephemeral, allowing you to create and delete them on demand. ML work-spaces support fully containerized execution of Python, R, Scala, and Spark workloads through flexible and extensible engines.

Cloudera Machine Learning enables you to:

      Easily onboard a new tenant and provision an ML workspace in a shared OpenShift environment.

      Enable data scientists to access shared data on CDP Private Cloud Base and CDW.

      Leverage Spark-on-K8s to spin up and down Spark clusters on demand.

Cloudera Machine Learning (CML)

Figure 4.            

Cloudera Machine Learning (CML)

Apache Ozone

Apache Ozone is a scalable, redundant, and distributed object store for Hadoop. Apart from scaling to billions of objects of varying sizes, Ozone can function effectively in containerized environments such as Kubernetes and YARN. Applications using frameworks like Apache Spark, YARN, and Hive work natively without any modifications. Apache Ozone is built on a highly available, replicated block storage layer called Hadoop Distributed Data Store (HDDS).

Apache Ozone separates management of namespaces and storage, helping it to scale effectively. Ozone Manager manages the namespaces, while Storage Container Manager handles the containers.

Apache Ozone is a distributed key-value store that can manage both small and large files alike. While HDFS provides POSIX-like semantics, Ozone looks and behaves like an object store.

Apache Ozone brings the following cost savings and benefits due to storage consolidation:

      Lower infrastructure cost

      Lower software licensing and support cost

      Lower lab footprint

      Newer additional use cases with support for HDFS and S3 and billions of objects supporting both large and small files in a similar fashion

Data lake consolidation with Apache Ozone

Figure 5.            

Data lake consolidation with Apache Ozone

Highlights

Intelligent multidomain management with Cisco Intersight

Enabling IT to operationalize at scale heterogenous infrastructure and application platform to seamlessly function as a single cohesive unit through single-pane-of-glass management.

Powered by the latest generation in CPU from Intel, AMD, and NVidia

The latest generation of processors from Intel (Cascade Lake Refresh) and AMD (EPYC 7002 series) provides the foundation for powerful data center platforms with an evolutionary leap in agility and scalability.

Eliminate infrastructure silos with CDIP

A highly modular platform that brings big data, AI compute farms, and object storage to work together as a single entity, while each component can scale independently to address the IT issues in the modern data center.

Disaggregated Architecture

CDIP is a disaggregated architecture that brings together a more integrated and scalable solution for Big data analytics and AI. It is specifically designed to improve resource utilization, elasticity, heterogeneity, and failure handling and also be able to consume continuously evolving AI/ML frameworks and landscape.

Prevalidated and fully supported

Cisco Validated Designs facilitate faster, more reliable, and more predictable customer deployments by providing configuration and integration of all components into a fully working optimized design with scalability and performance recommendations.

Fully supported and prevalidated architectural innovations with partners

Pretested and prevalidated through industry-standard benchmarks, tighter integration, and performance optimization with industry-leading independent software vendor (ISV) partners in big data, AI, and object storage, Cisco Data Intelligence Platform offers best-of-breed, end-to-end validated architectures and reduces integration and deployment risk by eliminating guesswork.

For more information, see: www.cisco.com/go/bigdata_design

Managing from the cloud with Cisco Intersight

With Cisco Intersight, management is moved from the network into the cloud so that you can respond at the speed and scale of your business and manage all of your infrastructure.

Cisco Intersight delivers intuitive computing through cloud-powered intelligence. This platform offers a more intelligent level of management that enables IT organizations to analyze, simplify, and automate their environments in ways that were not possible with prior generations of tools. This capability empowers organizations to achieve significant savings in total cost of ownership (TCO) and deliver applications faster, so they can support new business initiatives.

Cisco Intersight is a software-as-a-service (SaaS) infrastructure management that provides single-pane-of-glass management of CDIP infrastructure in the data center. Cisco Intersight scales easily, and frequent up-dates are implemented without impact to operations. Cisco Intersight Essentials enables customers to centralize configuration management through a unified policy engine, determine compliance with the Cisco UCS Hardware Compatibility List (HCL), and initiate firmware updates. Enhanced capabilities and tight integration with Cisco TAC enable more efficient support. Cisco Intersight automates uploading files to speed trouble-shooting. The Intersight recommendation engine provides actionable intelligence for IT operations management. The insights are driven by expert systems and best practices from Cisco.

Cisco Intersight offers flexible deployment either as software as a service (SaaS) on Intersight.com or running on your premises with the Cisco Intersight virtual appliance. The virtual appliance provides users with the benefits of Cisco Intersight while allowing more flexibility for those with additional data locality and security requirements.

Cisco Intersight

Figure 6.            

Cisco Intersight

Reference architecture

Cisco Data Intelligence Platform reference architectures are carefully designed, optimized, and tested with the leading big data and analytics software distributions to achieve a balance of performance and capacity to address specific application requirements. You can deploy these configurations as is or use them as tem-plates for building custom configurations. You can scale your solution as your workloads demand, including expansion to thousands of servers through the use of Cisco Nexus® 9000 Series Switches. The configurations vary in disk capacity, bandwidth, price, and performance characteristics.

CDIP in a Rack

Figure 7.            

CDIP in a Rack

Data lake reference architecture

Table 1 lists the data lake, private cloud, and dense storage with Apache Ozone reference architecture for Cisco Data Intelligence Platform.

Table 1.        Cisco Data Intelligence Platform with CDP Private Cloud Base (Apache Ozone) configuration on Cisco UCS M6

 

Performance

Capacity

Servers

16 x Cisco UCS C240 M6 Rack Servers with small-form-factor (SFF) drives

16 x Cisco UCS C240 M6 Rack Servers with large-form-factor (LFF) drives

CPU

2 x 3rd-Gen Intel Xeon Scalable Processors 6330 processors (2 x 28 cores, at 2.0 GHz)

2 x 3rd-Gen Intel Xeon Scalable Processors 6330 processors (2 x 28 cores, at 2.0 GHz)

Memory

16 x 32 GB (512 GB)

16 x 32-GB DDR4 (512 GB)

Boot

M.2 with 2 x 960-GB SSDs

M.2 with 2 x 960-GB SSDs

Storage

24 x 2.4-TB 10K rpm SFF SAS HDDs (or 24 x 16-TB Enterprise Value SATA SSDs) and 2x 3.8-TB NVMe

16 x 16-TB LFF HDD and 2 x 3.8-TB NVMe

Virtual interface card (VIC)

4 x 25G mLOM Cisco UCS VIC 1467

4 x 25-G mLOM Cisco UCS VIC 1467

Storage controller

Cisco 12-Gbps SAS modular RAID controller with 8-GB flash-based write cache (FBWC) or Cisco 12-Gbps modular SAS host bus adapter (HBA)

Cisco 12-Gbps SAS modular RAID controller with 8-GB FBWC or Cisco 12-Gbps modular SAS host bus adapter (HBA)

Network connectivity

Cisco UCS 6454 Fabric Interconnect

Cisco UCS 6454 Fabric Interconnect

GPU (optional)

NVIDIA GPU A10 or NVIDIA GPU A100

NVIDIA GPU A10 or NVIDIA GPU A100

Private Cloud reference architecture

Table 2 lists the CDIP private cloud configuration for master and worker nodes.

Table 2.        Cisco Data Intelligence Platform with CDP Private Cloud Experiences configuration

 

High core option

Servers

Cisco UCS X-Series with X210C Blades (up to 8 per chassis)

CPU

2 x 3rd-Gen Intel Xeon Scalable Processors 6338 processors (2 x 32 cores, at 2.0 GHz)

Memory

16 x 64-GB (1TB)

Boot

M.2 with 2 x 960-GB SSD

Storage

6 x 3.8-TB NVMe (Portworx [2 drives], local storage [4 drives])

VIC

4 x 25 Gigabit Ethernet with Cisco UCS VIC 14425 mLOM

Storage controller

Cisco 12-Gbps SAS modular RAID controller with 4-GB FBWC or Cisco 12-Gbps modular SAS HBA

Network connectivity

Cisco UCS 6454 Fabric Interconnect

 

Reference Architecture for Management Nodes

Figure 8.            

Reference Architecture for Management Nodes

Future proofing advanced analytics deployment with CDIP

As enterprises are embarking on the journey of digital transformation, an integrated extensible infrastructure implementation purpose-built to keep pace with constant challenges of technological advancement for each workload can reduce bottlenecks, improve performance, decrease bandwidth constraints, and minimize business disruption.

Cisco UCS C-Series Rack-Mount Servers

Cisco UCS C-Series Rack-Mount Servers keep pace with Intel Xeon processor innovation by offering the latest processors with increased processor frequency and improved security and availability features. With the increased performance provided by the Intel Xeon Scalable Family Processors, Cisco UCS C-Series servers offer an improved price-to-performance ratio. They also extend Cisco UCS innovations to an industry-standard rack-mount form factor, including a standards-based unified network fabric, Cisco VN-Link virtualization support, and Cisco Extended Memory Technology.

It is designed to operate both in standalone environments, and as part of a Cisco UCS managed configuration, these servers enable organizations to deploy systems incrementally—using as many or as few servers as needed—on a schedule that best meets the organization’s timing and budget. Cisco UCS C-Series servers offer investment protection through the capability to deploy them either as standalone servers or as part of Cisco UCS. One compelling reason that many organizations prefer rack-mount servers is the wide range of I/O options available in the form of PCIe adapters. Cisco UCS C-Series servers support a broad range of I/O options, including interfaces supported by Cisco and adapters from third parties.

Cisco UCS C240 M6 Rack-Mount Server

The Cisco UCS C240 M6 Rack-Mount Server is well suited for a wide range of storage and I/O-intensive applications such as big data analytics, databases, collaboration, virtualization, consolidation, and high-performance computing in its two-socket, 2RU form factor.

The Cisco UCS C240 M6 Server extends the capabilities of the Cisco UCS rack server portfolio with 3rd-Gen Intel Xeon Scalable Processors supporting more than 43 percent more cores per socket and 33 percent more memory when compared with the previous generation.

You can deploy the Cisco UCS C-Series rack servers as standalone servers or as part of the Cisco Unified Computing System managed by Cisco Intersight, or Intersight Managed Mode to take advantage of Cis-co standards-based unified computing innovations that can help reduce your total cost of ownership (TCO) and increase your business agility.

These improvements deliver significant performance and efficiency gains that will improve your application performance. The Cisco UCS C240 M6 Rack Server delivers outstanding levels of expandability and performance.

Cisco UCS C240 M6S

Figure 9.            

Cisco UCS C240 M6S

The Cisco UCS C220 M6 Rack Server is the most versatile general-purpose infrastructure and application server in the industry. This high-density, 1RU, 2-socket rack server delivers industry-leading performance and efficiency for a wide range of workloads, including virtualization, collaboration, and bare-metal applications. You can deploy the Cisco UCS C-Series Rack Servers as standalone servers or as part of the Cisco Unified Computing System managed by Cisco Intersight, Cisco UCS Manager, or Intersight Managed Mode to take advantage of Cisco standards-based unified computing innovations that can help reduce your total cost of ownership (TCO) and increase your business agility.

The Cisco UCS C220 M6 Rack Server extends the capabilities of the Cisco UCS rack server portfolio. The Cisco UCS C220 M6 Rack Server delivers outstanding levels of expandability and performance.

Cisco UCS C220 M6S

Figure 10.         

Cisco UCS C220 M6S

Cisco UCS X-Series Modular System

The Cisco UCS X-Series with Cisco Intersight is a modular system managed from the cloud. It is designed to meet the needs of modern applications and improve operational efficiency, agility, and scale through an adaptable, future-ready, modular design.

Designed to be managed exclusively from the cloud:

      Simplify with cloud-operated infrastructure

      Simplify with an adaptable system designed for modern applications

      Simplify with a system engineered for the future

Support a broader range of workloads

A single server type supporting a broader range of workloads means fewer different products to support, reduced training costs, and increased flexibility. The system supports workloads including the following:

      Virtualized workloads

      Private cloud

      Enterprise applications

      Database management systems

      Infrastructure applications

      Cloud-native applications

      In-memory databases

      Big data clusters

      GPU-accelerated AI/ML workloads

Cisco UCS X9508 Chassis

Figure 11.         

Cisco UCS X9508 Chassis

The Cisco UCS X9508 chassis is ready to house technology for today with an approach that embraces the future. Just slide into the chassis what you need today. Embrace the future without needing a forklift.

The seven-rack-unit (7RU) chassis has eight flexible slots. These can house a combination of compute nodes and a pool of future I/O resources that may include GPU accelerators, disk storage, and nonvolatile memory.

At the top rear of the chassis are two intelligent fabric modules that connect the chassis to upstream Cisco UCS 6400 Series Fabric Interconnects. At the bottom are slots ready to house future I/O modules that can flexibly connect the compute modules with I/O devices. We call this connectivity Cisco UCS X-Fabric technology because “X” is a variable that can evolve with new technology developments.

Six 2800W power supply units (PSUs) provide 54V power to the chassis with N, N+1, and N+N redundancy. A higher voltage allows efficient power delivery with less copper and reduced power loss. Efficient, 100-mm, dual counter-rotating fans deliver industry-leading airflow and power efficiency. Optimized thermal algorithms enable different cooling modes to best support your environment. Cooling is modular so that future enhancements can potentially handle open- or closed-loop liquid cooling to support even higher-power processors.

Modular networking components

Network connectivity is provided by a pair of Cisco UCS 9108 Intelligent Fabric Modules (IFMs). Similar to the fabric extenders used in the Cisco UCS 5108 Blade Server Chassis, these modules carry all network traffic to a pair of Cisco UCS 6400 Series Fabric Interconnects. Having a single point of network connectivity and control in a system provides deterministic latency. This, in turn, frees you to place workloads without regard to whether the compute nodes are in the same chassis:

      Server ports: Up to 200 Gbps of unified fabric connectivity per compute node with two IFMs.

      Uplink ports: 8 x 25-Gbps SFP28 ports. The unified fabric carries management, production, and Fiber Channel over Ethernet (FCoE) traffic to the fabric interconnects. There, management traffic connects to the Cisco Intersight cloud operations platform, FCoE traffic is passed to native fiber channel interfaces through universal ports on the fabric interconnects, and production Ethernet traffic is passed upstream to the data center network.

Management consolidation

The IFM connects to the Cisco Integrated Management Controller on each compute node, enabling Intersight access to configuration and monitoring capabilities. It also connects to the chassis, power supply, and fan speed and temperature sensors, enabling both zone-based cooling and policy-based power management.

The Cisco UCS X9508 Modular System Chassis supports a wide range of workloads and is equipped to accommodate future I/O technologies as they emerge

Figure 12.         

The Cisco UCS X9508 Modular System Chassis supports a wide range of workloads and is equipped to accommodate future I/O technologies as they emerge

Conclusion

Evolving workloads need a highly flexible platform to cater to various requirements, whether data intensive (data lake) or compute intensive (AI/ML/DL) or just storage dense (object store).

To bring in seamless operation of the application at this scale, one needs:

      An Infrastructure automation with centralized management,

      Deep telemetry, simplified and granular trouble-shooting capabilities, and

      Multi-tenancy allowing application workloads, including containers and micro-services, with the right level of security and SLA for each workload.

Cisco UCS with Intersight and Cisco ACI can enable this next-generation, cloud-scale architecture, deployed and managed with ease.

For more information

For additional information, see the following resources:

      To find out more about Cisco UCS big data solutions, see www.cisco.com/go/bigdata

      To find out more about Cisco UCS big data validated designs, see www.cisco.com/c/en/us/solutions/design-zone/data-center-design-guides/data-center-big-data.html

      To find out more about Cisco Data Intelligence Platform, see www.cisco.com/c/dam/en/us/products/servers-unified-computing/ucs-c-series-rack-servers/solution-overview-c22-742432.pdf

      To find out more about Cisco UCS AI/ML solutions, see www.cisco.com/c/en/us/solutions/data-center/artificial-intelligence-machine-learning/index.html

 

 

 

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