SAP and Dell Transforming Data at the Edge, Cloud, and Core
Wed, 17 May 2023 15:05:08 -0000
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Organizations understand that to thrive in the digital economy, they must derive better insights from the data they own—and do this in a more automated, reliable way. The faster this process, the faster the time to insights.
SAP, supported by Dell Technologies and Red Hat, organized the SAP Business Technology Platform (BTP) Packathon, engaging the APJ partner community to design and develop industry solutions of high business value by leveraging BTP services that were hosted between the SAP cloud and the Dell Technologies Sydney Customer Solution Center (CSC).
SAP data intelligence and SAP HANA infrastructure were hosted from the Dell Technologies Sydney CSC, running on the Red Hat operating system and Red Hat OpenShift Cluster 4.6. These systems were integrated into SAP Data Warehouse Cloud, SAP Analytics Cloud, S/4 HANA systems, and partner environments (hosting external systems and data sources).
The following image shows a high-level overview of the BTP Packathon architecture:
This is a testimony to the role Dell plays as customer infrastructure strategy evolves: at the edge, in the cloud, or at the core.
Edge
Enterprises want to become smarter when it comes to their operations, their cloud strategy, and their approach to extracting value from an ever‑increasing volume of data.
For businesses running SAP, the key lies in adopting SAP HANA and S/4HANA applications with a cloud‑smart strategy. SAP S/4HANA and SAP Intelligent Technologies address this integrative approach by bringing transactional data together with Big Data and the Internet of Things (IoT).
That means fueling business processes with insights from data across all information sources: at the edge; in core SAP environments; from IOT, data lakes and Hadoop repositories; in the cloud.
When exploring the edge, customers will look to solve one of these objectives:
- Minimize latency and maximize availability for distributed operations
- Build an agile cloud-native application development platform
- Minimize costs of edge data management, transport, and associated network bandwidth
- Run artificial intelligence applications closer to machines or devices
Deploying artificial intelligence (AI) at the edge opens a whole new world of possibilities. Edge deployments with AI can deliver real-time, actionable insights at the point of decision while incurring lower latency and costs than by transferring data back and forth between the data center and the cloud. Limited staffing and harsh environments can make it difficult to turn the vision of the intelligent edge into a reality, however. This is where the Dell Technologies and SAP end-to-end approach comes in. To help empower you at the edge, Dell Technologies is taking a three-pronged approach:
- Designing and launching specific edge solutions that target current edge implementations and use cases
- Optimizing our portfolio for the edge, building a foundation by delivering necessary capabilities across our portfolio
- Integrating our technologies into the Dell Technologies Edge Platform, creating edge-specific technology that is purpose-built for the platform
In a recent joint podcast, Dell Technologies and SAP discussed some of the key components of the intelligent enterprise: cloud, edge, data analytics, and automation. See Dell and SAP: Powering the Intelligent Enterprise.
Cloud—Complementing RISE with SAP
Dell Technologies is now at the very center of SAP’s transformation strategy to RISE and S/4HANA. Our customers can consume SAP S/4HANA “as a device” with all the benefits of the Dell Technologies APEX model. RISE with SAP powered by APEX simplifies the path to the SAP Intelligent Enterprise with an on-premises cloud experience in either the customer’s own data center or a co-location environment.
A turnkey cloud subscription offering with Dell Technologies APEX, which is available through SAP, reduces the risk of implementation and outages and frees up resources so that customers can focus on the business outcomes that SAP S/4HANA provides.
The subscription helps customers leverage cloud economies and capabilities while keeping their SAP software landscape and data securely in their own data center or co-location—for data sovereignty concerns, for latency or application entanglement reasons, or because they simply lack access to hyperscalers.
APEX offers the ease and scale of cloud delivered as-a-service with simplicity, agility, and control for our customers. Create your own on-demand environment with infrastructure and services you customize to order. Deploy a pay-per-use consumption model or an enterprise-scale managed utility. See Introducing RISE with SAP S/4HANA Cloud, powered by APEX - Dell Technologies.
Core—Choosing the right platform
According to Gartner, by 2022 80 percent of SAP HANA deployments will continue to be on-premises. IDC and Gartner survey results and deployments show a preference for an on-premises deployment and hybrid model for SAP applications running on the SAP HANA database and edge-based applications. Organizations prefer a cloud-like experience, where they have features such as simplicity, flexibility, quick turnaround for faster innovation, and pay-for-use at their fingertips.
One of the most critical decisions a customer makes when planning an SAP S/4HANA migration is selecting the type of deployment option which best suits their business needs: on-premises; private cloud; public cloud; or hybrid cloud. As they evaluate the options, the total cost of ownership (TCO) is top of mind.
Based on business requirements and global surveys, top priorities for our customers are migrating some of their SAP landscapes to cloud while keeping their crown jewels on-premises. Also, some customers that are repatriating from public cloud to on-premises have primary reasons such as data residency and regulatory requirements, cyber security, overhead costs, and so on.
The following document presents the result of a three-year TCO comparison of an SAP HANA database and S/4HANA application server landscape that is deployed on-premises, running on Dell EMC VxRail hyperconverged infrastructure, against one that is deployed on an Amazon Web Services (AWS) cloud computing platform: The Total Cost of Ownership of On-Premises SAP on Dell EMC VxRail HCI Versus Amazon Web Services Public Cloud | Dell Technologies Info Hub
The SAP, Dell, and Red Hat BTP platform and services are available for customer and partner proof of concepts, demos, events, and industry-aligned solution developments. Contact your SAP, Dell, or Red Hat account manager for more information.
Related Blog Posts
Deploying SAP HANA at the Rugged Edge
Mon, 14 Dec 2020 18:38:19 -0000
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SAP HANA is one of those demanding workloads that has been steadfastly contained within the clean walls of the core data center. However, this time last year VxRail began to chip away at these walls and brought you SAP HANA certified configurations based on the VxRail all-flash P570F workhorse and powerful quad socket all-NVMe P580N. This year, we are once again in the giving mood and are bringing SAP HANA to the edge. Let us explain.
Dell Technologies defines the edge as “The edge exists wherever the digital world & physical world intersect. It’s where data is securely collected, generated and processed to create new value.” This is a very broad definition that extends the edge from the data center to oil rigs, to mobile response centers for natural disasters. It is a broad claim not only to provide compute and storage in such harsh locations, but also to provide enough of it that meets the strict and demanding needs of SAP HANA, all while not consuming a lot of physical space. After all -- it is the edge where space is at a premium.
Shrinking the amount of rack space needed was the easier of the two challenges, and our 1U E for Everything (or should that be E for Everywhere?) was a perfect fit. The all-flash E560F and all-NVMe E560N, both of which can be enhanced with Intel Optane Persistent Memory, can be thought of as the shorter sibling of our 2U P570F, packing a powerful punch with equivalent processor and memory configurations.
While the E Series fits the bill for space constrained environments, it still needs data center like conditions. This is not the case for the durable D560F, the tough little champion that joined the VxRail family in June of this year, and which is now the only SAP HANA certified ruggedized platform in the industry. Weighing in at a lightweight 28 lbs. and a short depth of 20 inches, this little fighter will run all day at 45°C with eight hour sprints of up to 55°C, all while enduring shock, vibration, dust, humidity, and EMI, as this little box is MIL-STD 810G and DNV-GL Maritime certified. In other words, if your holiday plans involve a trip to hot sand beaches, a ship cruise through a hurricane, or an alpine climb, and you’re bringing SAP HANA with you (we promise we won’t ask why), then the durable D560F is for you.
The best presents sometimes come in small packages. So, we won’t belabor this blog with anything more than to announce that these two little gems, the E560 and the D560, are now SAP HANA certified.
Author: David Glynn, Sr. Principal Engineer, VxRail Tech Marketing
References:
360° View: VxRail D Series: The Toughest VxRail Yet
Video: HCI Computing at the Edge
Solution brief: Taking HCI to the Edge: Rugged Efficiency for Federal Teams
Press release: Dell Technologies Brings IT Infrastructure and Cloud Capabilities to Edge Environments
SAP Certification link: Certified and Supported SAP HANA® Hardware Directory
Edge AI Integration in Retail: Revolutionizing Operational Efficiency
Mon, 12 Feb 2024 11:43:11 -0000
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Edge AI plays a significant role in the digital transformation of retail warehouses and stores, offering benefits in terms of efficiency, responsiveness, and enhanced customer experience in the following areas:
- Real-time analytics—Edge AI enables real-time analytics for monitoring and optimizing warehouse management systems (WMS). This includes tracking inventory levels, predicting demand, and identifying potential issues in the supply chain. In the store, real-time analytics can be applied to monitor customer behavior, track product popularity, and adjust pricing or promotions dynamically based on the current context using AI algorithms that analyze this data and provide personalized recommendations.
- Inventory management—Edge AI can improve inventory management by implementing real-time tracking systems. This helps in reducing stockouts, preventing overstock situations, and improving the overall supply chain efficiency. On the store shelves, edge devices equipped with AI can monitor product levels, automate reordering processes, and provide insights into shelf stocking and arrangement.
- Optimized supply chain—Edge AI assists in optimizing the supply chain by analyzing data at the source. This includes predicting delivery times, identifying inefficiencies, and dynamically adjusting logistics routes for both warehouses and stores.
- Autonomous systems—Edge AI facilitates the deployment of autonomous systems, such as autonomous robots, conveyor belts, robotic arms, automated guided vehicles (AGVs), and collaborative robotics (cobots). Autonomous systems in the store can include checkout processes, inventory monitoring, and even in-store assistance.
- Predictive maintenance—In both warehouses and stores, Edge AI can enable predictive maintenance of equipment. By analyzing data from sensors on machinery, it can predict when equipment is likely to fail, reducing downtime and maintenance costs.
- Offline capabilities—Edge AI systems can operate offline, ensuring that critical functions can continue even when there is a loss of internet connectivity. This is especially important in retail environments where uninterrupted operations are crucial.
The Operational Complexity Behind the Edge-AI Transformation
The scale and complexity of Edge-AI transformation in retail are influenced by factors such as the number of edge devices, data volume, AI model complexity, real-time processing requirements, integration challenges, security considerations, scalability, and maintenance needs.
The Scalability and Maintenance Challenge
A mid-size retail organization is composed of tens of warehouses and hundreds of stores spread across different locations. In addition to that, it needs to support dozens of external suppliers that also need to become an integral part of the supply chain system. To enable Edge-AI retail, it will need to introduce many new sensors, devices, and systems that will enable it to automate a large part of its daily operation. This will result in hundreds of thousands of devices across the stores and warehouses.
Figure 1. The Edge-AI device scale challenge
The scale of the transformation depends on the number of edge devices deployed in retail environments. These devices could include smart cameras, sensors, RFID readers, and other internet of things (IoT) devices. The ability to scale the Edge-Ai solution as the retail operation grows is an essential factor. Scalability considerations involve not only the number of devices but also the adaptability of the overall architecture to accommodate increased data volume and computational requirements.
Breaking Silos Through Cloud Native and Cloud Transformation
Each device comes with its proprietary stack, making the overall management and maintenance of such a diverse and highly fragmented environment extremely challenging. To address that, Edge-Ai transformation also includes the transformation to a more common cloud-native and cloud-based infrastructure. This level of modernization is quite massive and costly and cannot happen in one go.
Figure 2. Cloud native and cloud transformation break the device management silos challenges
This brings the need to handle the integration with existing systems (brownfield) to enable smoother transformation. This often involves integration with existing retail systems, such as point-of-sale systems, inventory management software, and customer relationship management tools.
NativeEdge and Centerity Solution to Simplify Retail Edge-AI Transformation
Dell NativeEdge serves as a generic platform for deploying and managing edge devices and applications at the edge of the network. One notable addition in the latest version of NativeEdge is the ability to deliver an end-to-end solution on top of the platform that includes PTC, Litmus, Telit, Centerity, and so on. This capability allows users to get a consistent and simple management from Bare-Metal provisioning to a fully automated full-blown solution.
Figure 3. Using NativeEdge and Centerity as part of the open edge solution stack
In this blog, we demonstrate the benefits behind the integration of NativeEdge and Centerity that simplify the retail Edge-AI transformation challenges.
Introduction to Centerity
Centerity CSM² is a purpose-built monitoring, auto-remediation, and asset management platform for enterprise retailers that provides proactive wall-to-wall observability of the in-store technology stack. The key part in the Centrity architecture is the Centerity Manager is responsible for collecting all the data from the edge devices into a common dashboard.
Figure 4. Centerity retail management and monitoring
Using NativeEdge and Centerity to Automate the Entire Retail Operation
The following are the architecture choices made to address the Edge-AI transformation challenges with Dell NativeEdge as the edge platform and Centerity as the asset management and monitoring for both the retail warehouse and store. In this case, we have two sites, one representing a warehouse where we connect to the customer’s existing environment running on VMware infrastructure, and a retail store running in a different location.
Note: The Centrify Proxy (customer site-1 in the following figure) is used to aggregate multiple remote devices through a single network connection.
Figure 5. Using NativeEdge and Centerity to fully automate and manage and retail warehouse and store
Since the store is often limited by infrastructure capacity, we will use a gateway to aggregate the data from all the devices. For this purpose, we will use a NativeEdge Endpoint as a gateway and install the Centerity monitoring agent on it. The monitoring agent will act as a proxy that on one hand connects to the individual devices in the store and, on the other hand, sends this information back to the Centerity Manager to aggregate all this information into one control plane. In this case, the warehouse runs on a private cloud based on VMware and represents a central data center. Since we have more capacity on this environment, we will collect the data directly from the device to the manager without the need for a proxy agent. The architecture is also set to enable future expansion to public clouds such as AWS and GCP.
Step 1: Use NativeEdge for zero-touch secure on-boarding of the edge infrastructure
Secure device onboarding—In this step, we will onboard three different edge compute classes (PowerEdge, OptiPlex, and Gateway) to represent a warehouse facility with diverse set of devices. NativeEdge will treat each of these devices as a separate ECE instance and, thus, provide a consistent management layer to all the devices, regardless of their compute class.
Figure 6. Zero-touch provisioning of edge infrastructure from BareMetal to cloud
Step 2: Deploy Centerity solution on top of NativeEdge infrastructure
This phase is broken down into two parts; The first is provisioning the Centerity Manager which is the main component and then provision the edge proxy on the target store and warehouse.
Step 2.1: Deploy and manage the Centerity Manager on VMware (Site 2)
To do that:
- Choose the on-prem Centerity server catalog item from the NativeEdge solution tab. Full Centerity server installation starts on VMware private cloud (external infra, not NativeEdge Endpoint).
- Use the deployment output to fetch the newly created Centerity server endpoint, credentials, and so on.
Step 2.2: Deploy and manage the Centerity Edge proxy (agent) on NativeEdge Endpoints
To install Centerity Edge proxy collector on each warehouse:
- Choose the Centerity Collector or Edge proxy catalog item.
- Select the target environment and deploy the proxy on all the selected sites. The installation happens in parallel installation on all sites.
- Fill the relevant deployment inputs and install deployment.
- Native Edge starting the fulfillment phase with all operations.
- Install and configure Centos VM per each warehouse, install edge proxy agent/ collector, and connect it to server.
- Execute day-2 operations, such as updating one of the warehouses using security update check, custom workflow.
The following blueprint automates the deployment of the Centerity agent on a NativeEdge Endpoint. It launches a virtual machine (VM) on the remote device which is configured to connect to the Centerity Manager. It also optimizes the VM to support AI workload by enabling GPU passthrough.
Figure 7. Create an AI optimized VM on the target device
NativeEdge can execute the above blueprint simultaneously on all the devices. The following figure shows the result of executing this blueprint on three devices.
Figure 8. Deploy the Edge Proxy on all the stores in one bulk
Step 3: Connect the retail and logistic devices to Centerity
In this step, we will configure and set up the devices and connect them to the Centerity monitoring service. Note that this step is done directly on the centerity management console and not through NativeEdge console.
In this case, we chose the following endpoints within the logistic center or warehouse.
- Tablet type – Dell Windows11
- Mobile terminal type – Zebra TC52
- API based devices – SES (Digital signage)
- Printer – Bixolon (Log based)
- Agentless based devices – Security camera
Figure 9. Centerity Management connected to the edge device managed by NativeEdge
Step 4: Managing and monitoring the retail warehouse and store
In this step, we will manage the retail warehouse and store through the monitoring of the devices that we connected to the system in the previous step. This will include the following set of operations:
- Device monitoring
- Inventory tracking (if applicable)
- Failures alerts
- Auto remediation (if applicable)
- Operational and business SLA dashboards
- Reports
- Generating events for proactive operational support
- Updating and keeping up the system software for compliance
- Breaking or fixing the workflow
Figure 10. Monitoring and managing retail devices
Conclusion
Dell NativeEdge provides a fully-automated secure device onboarding from Bare Metal to the cloud. As a DevEdgeOps platform, NativeEdge also provides the ability to validate and continuously manage the provisioning and configuration of those devices in a secure way. This minimizes the risk of failure and security breaches due to misconfiguration or human errorThose potential vulnerabilities can be detected earlier in the pre-deployment development process. The introduction of NativeEdge Orchestrator enables customers to have a consistent and simple management of built-in solutions across their entire fleet of new and existing devices. The separation between the device management and solution is key to enabling consistent operational management between different solution vendors as well as cloud infrastructure. In addition to that, the ability to integrate with the retail existing infrastructure (VMware in this specific example) as well as cloud-native infrastructure simultaneously ensures smoother transformation to a modern Edge-AI-enabled infrastructure.
The specific integration between NativeEdge and Centerity in this specific use case enables customers to deliver a full-blown retail management which integrates with both their legacy and new AI enabled devices. According to recent studies, this level of end-to-end monitoring and automation can reduce the maintenance overhead and potential downtime by 57 percent.
Figure 11. Moving to a fully automated and monitored retail warehouse and store brings a significant TCO saving
It is also worth noting that the open solution framework provided by NativeEdge allows partners such as Centerity to use Dell NativeEdge as a generic edge infrastructure framework, addressing fundamental aspects of device fleet management. Vendors can then focus on delivering the unique value of their solution, be it predictive maintenance or real-time monitoring, as demonstrated by the Centerity use case in this blog.