Providing the Edge for Your Edge Cloud

In this edition of Voices of the Industry, Chao Huang, Senior Application Engineer of Intel Data Center Management Solutions shares insights on how data center management solutions can give your edge cloud strategy the edge. 

Providing the Edge for Your Edge Cloud

In this edition of Voices of the Industry, Chao Huang, Senior Application Engineer of Intel Data Center Management Solutions shares insights on how data center management solutions can give your edge cloud strategy the edge. 

Chao Huang, Senior Application Engineer of Intel® Data Center Management Solutions

Typically run from hyperscale data centers, cloud computing has dramatically accelerated the digital transformation of global businesses of every size, whether via public cloud services from providers such as AWS, Google Cloud, or Microsoft Azure, or private clouds hosted by on-premises infrastructure. As one industry expert has observed, “Cloud underpins the push to digital business, which remains at the top of CIOs’ agenda.”

There’s no question that cloud computing excels in both resource-intensive data processing and artificial intelligence (AI) and machine learning workloads, which have become ever more essential to the evolution of the enterprise business model. In fact, Flexera’s most recent State of the Cloud Report found that 41 percent of enterprises now use cloud platform-as-a-service (PaaS) for AI and machine learning applications.

That said, it’s now also widely recognized that cloud computing creates issues with latency for some workloads, as data must travel all the way to the data center and back again. No matter how fast a network or 5G connection might be, large data volumes take time to transfer over long distances. As chief engineer Scotty from Star Trek would say, “Ye cannae change the laws of physics, Jim!”

For this reason, enterprises are augmenting cloud computing with edge computing for certain types of workloads, such as latency-sensitive applications. Additionally, because the cost of bandwidth for large-scale data transmission adds up, locating computing at the edge reduces these costs. Edge technology also keeps sensitive or proprietary information closer to the source and enables compliance with data localization laws, such as the EU’s General Data Protection Regulation (GDPR).

This “edge cloud” brings the accessibility of the cloud closer to where data is being created and implemented. Extending the convenience of the cloud to edge networks, an edge cloud strategy places intelligent edge nodes closer to local resources, equipment, and devices, with software to deliver services in a way that’s similar to using public cloud services. By collecting, storing, and processing data at the edge, businesses gain meaningful insights fast, and immediately can act on those insights to deliver better customer experiences.

The edge cloud is already providing the architecture for a host of innovative IoT applications across agriculture, automotive, construction, healthcare, Oil & Gas, and retail sectors. Edge cloud deployments excel at the delivery of visual experiences, including streaming services, cloud gaming, and other visual workloads. In fact, a recent Analysys Masons survey of enterprises found that 30 percent of their IT budgets will be spent on edge cloud computing resources as early as next year.

Access Intelligence, Across Every Compute Layer

Edge clouds are typically hosted by micro-data centers, and the servers in these types of edge cloud environments operate at relatively high temperatures. Compounding matters, unlike traditional data centers, micro-data centers aren’t staffed with onsite IT personnel to conduct much-needed power and thermal monitoring and management.

Server asset management is also essential when IT staff managing edge cloud environments are making decisions based on the available computation and storage capacity. Asset information includes CPU, memory, hard disk model, serial number, and other information. Enterprises very often manually maintain and manage server assets through a configuration management database (CMDB). However, asset management solutions of this kind usually offer limited scope and can’t be easily integrated with existing systems. Moreover, this method presents a number of problems, including the failure to update data in real time and the inability to track server component maintenance updates.

Data center management solutions, through an easy-to-use dashboard, enable edge cloud deployments to be managed remotely. These tools provide high-value monitoring and management capabilities addressing power and thermal issues in edge cloud environments that are challenging for IT staff. Data center management solutions provide accurate, real-time power and thermal monitoring and management for individual servers, groups of servers, racks, and other IT equipment, such as PDUs. These tools are simple to deploy and offer interoperability among diverse server models as well as a variety of products from PDU and rack suppliers.

By providing granular sub-component failure analysis and out-of-band (OOB) real-time utilization data concerning CPU, disk and memory, data center management solutions enable edge cloud data center managers to accurately assess utilization and conduct server health component monitoring. Data center management solutions will even send alerts to remote IT staff concerning power and thermal events, thereby significantly improving server uptime. What’s more, these tools offer many asset management capabilities, such as organizing systems in physical or logical groups, easily searching for systems using their asset tags or other details, and importing and exporting an edge cloud deployment’s inventory and hierarchy.

Companies must make the best use of their resources and design more successful edge cloud and IoT strategies by placing computing at the appropriate layer. Take for example endpoint devices such as smart cameras monitoring safety at a mining site, serving as the front line for edge computing, and residing as physically close as possible to the users, equipment, and operations which they serve. In turn, edge servers offer a secondary layer for edge computing, functioning as an intermediary between localized systems and centralized business resources. Finally, a primary data center or cloud operates as yet another critical layer, residing furthest away from physical endpoints, and collecting and analyzing data over the long term to help the organization understand operational or environmental patterns.

Across all these layers, when supported by a data center management solution, IT staff can make informed, real-time decisions regarding the deployment, operations, maintenance and health of their servers and systems. In this way, these powerful tools help companies to ensure maximum business productivity while optimizing the quality of end-user experience.

This article was written by Chao Huang, Senior Application Engineer of Intel Data Center Management Solutions. Learn more about the solutions offered by Intel.