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    DCIM x AIOps: The Next Big Trend Reshaping AI Software

    by GIGABYTE
    One unmistakable trend this year is that even as the race for next-gen AI hardware continues to heat up, tech giants are also shifting their focus to AI software that can drive hardware to perform at peak capacity and complement the artificial intelligence ecosystem. Particularly, there’s a lot of excitement about DCIM (data center infrastructure management) and AIOps (AI for IT operations), and how they can offer enterprises a decisive competitive edge. In this article, we introduce the concepts of DCIM and AIOps, and what GIGABYTE can do for you.
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    Index

  • The Current Trend: DCIM and AIOps are Paramount to Advancing AI
  • GIGABYTE Pod Manager: The Next Evolution in Modern DCIM Software
  • MLSteam: Streamlining the AI Lifecycle on GIGABYTE’s End-to-end AIOps Platform

    • The Current Trend: DCIM and AIOps are Paramount to Advancing AI

    The ongoing momentum of artificial intelligence (AI) has not only led to rapid progress in AI hardware (such as GIGABYTE's AI Servers), but also in software that facilitate AI creation and applications, whether it's through resource management, streamlining workflow, or other ways of squeezing out more performance. The numbers are clear: Gartner predicts that spending on IT operations management (ITOM) software will cap US$81 billion in 2028, with a compound annual growth rate (CAGR) of 10.3%, while IDC projects in its report titled "Worldwide IT Operations Management Software Forecast, 2023–2027" that ITOM revenue will reach US$28.4 billion by 2027, also with a CAGR of 10.3%. Specifically, IDC sees "AIOps" as having the potential to support important business outcomes. McKinsey names AIOps as a "foundational AI service" that spending will focus on, while BCG says AIOps can reduce IT support costs by 20% to 30% while increasing user satisfaction and freeing up IT time.

    "DCIM" is another field that's being rejuvenated by AI software. IBM identifies DCIM as one of the tools that can help optimize and "refresh" data centers in the age of generative AI, while DCIM heavyweight Schneider Electric highlights software as the crux of overcoming modern IT challenges.

    What are DCIM and AIOps? DCIM stands for data center infrastructure management. It involves monitoring, managing, and controlling IT equipment and infrastructure to achieve maximum efficiency and minimum downtime. In the epoch of AI, as computing clusters comprising dozens, if not hundreds of servers continuously scale up and scale out to keep pace with enormous AI models, this translates to a pressing need for convenient, intuitive, and centralized control over the supercomputers to ensure efficiency and stability.

    As for AIOps, it is an extension of MLOps that sets up an optimal "environment"—consisting of standardized frameworks, pipelines, best practices, and general operations within a data center—to nurture AI products from development (AI training) to deployment (AI inference). The latest trend in AIOps is to use AI tools to automate the process of fine-tuning the environment; in other words, it is leveraging AI to more effectively create new AI.

    “The market is moving toward the integration of AI hardware and software to present a total solution,” says Dr. Eric Ming-Chiang Chen, CEO of MyelinTek Inc., GIGABYTE Technology’s investee company that specializes in AI and machine learning (ML) software.


    "The AI software we're talking about are not GenAI applications. Instead, they take the form of DCIM and AIOps platforms that can enhance hardware performance and roll out new AI products and services at an unprecedented rate," he adds.

    In keeping with this key trend, GIGABYTE is happy to introduce unique value-added software solutions for DCIM and AIOps. GIGABYTE POD Manager (GPM) is the next evolution in DCIM software that provides total control and management over the physical resource pool and service workloads. MLSteam is an AIOps platform that not only fosters an environment for developing and deploying AI—it also features smart consulting that makes sure the client’s AI vision is guided through each step of actualization, from creation to implementation, with zero pain and the utmost utility.

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    GIGABYTE Pod Manager: The Next Evolution in Modern DCIM Software

    GPM comes as part and parcel of GIGAPOD, GIGABYTE's scalable supercomputing cluster for AI. The interconnected architecture allows 32 high-performance GPU servers housing 256 cutting-edge AI accelerators to compute as a single cohesive unit; it is currently one of the most competitive solutions for AI and HPC on the market. GPM, an all-inclusive software suite designed to streamline server and data center control, functions as GIGAPOD's command nexus, capable of optimizing resource utilization, upping operational efficiency, and accommodating the computing needs of different AI and HPC workloads.

    Similar to other DCIM software, GPM has a decked-out Cluster Management toolkit that comes preloaded with NVIDIA Base Command, as well as GIGABYTE's proprietary Cluster Manager to deliver better flexibility and support. From the user's perspective, GPM serves as a single point of access to all nodes and all components, a control center for overseeing every aspect of the infrastructure, and an easy way to customize the setup for individual requirements.

    WITHOUT

    GIGABYTE POD Manager…

    • No unified management across different equipment vendors

    • No resource pool or power usage optimization

    • No remote monitoring, provisioning, auto-update

    • No thermal management control

    • No data security or protection

    WITH

    GIGABYTE POD Manager…

    • Single access point covers all nodes & components

    • Optimized resource pool utilization & power usage

    • Real-time remote monitoring, provisioning, auto-update

    • Total control over cooling systems & data security

    • BONUS! Workload Management customizes environment to adjust to user requirements

    When you fire up GPM, you are treated to a comprehensive, real-time, remote-capable overview of the cluster or data center, including the health, status, and utilization rate of hardware, as well as event management capabilities and proactive issue resolution features geared toward high availability. GPM offers administrators unified management of heterogeneous computational resources, network switches, and storage devices, culminating in complete and centralized control over the data center's physical resource pool. GPM can also automatically discover newly connected devices within the network, vastly simplifying the deployment process of various nodes in the data center. Expanded features like the GPM Infrastructure Management module can grant further control over facility power (PDUs), cooling systems, and data security.

    The addition of Workload Management on top of Cluster Management is the quintessence of why GPM stands out among DCIM software. Workload Management lets operators allocate resources and schedule tasks across multiple nodes to achieve maximum cost-effectiveness. This is especially pertinent in the era of AI because training LLMs that contain up to trillions of parameters rely heavily on parallel computing, and the demands of developing AI differ mightily from sector to sector (for example, smart medicine has very different data and regulatory requirements compared to smart traffic). GPM assists users prepare for these diverse tasks by combining mainstream solutions like NVIDIA AI Enterprise (NVAIE) with GIGABYTE's very own AIOps platform, MLSteam (more on that later!) Other applications compatible with GPM include Apache Hadoop for big data and distributed computing, Kubernetes for container orchestration, and Slurm for HPC task scheduling. GPM enables predefined and customizable operating system (OS) installation and batch-by-batch firmware update across servers. It can also engage in provisioning, which is to remotely set up a server's software environment so that tasks may be appointed to the server.

    “If GPM Cluster Management sets the stage for supercomputing by giving users control over data center infrastructure, then GPM Workload Management is there to make sure resources in the data center can give their best performance, whether the task at hand is LLM development or AI inference at scale,” says Dr. Chen.


    GIGABYTE Clusters in Action:

    MLSteam: Streamlining the AI Lifecycle on GIGABYTE's End-to-end AIOps Platform

    MLSteam, which is a part of GPM Workload Management, is GIGABYTE's AIOps platform that fosters an intelligent and expedient environment for developing and deploying AI across a wide range of user scenarios. Unlike GPM, it is installed in the OS, which is why it can be used independently of GPM. It has a critical role to play in inventing and distributing AI products and services—from when the AI is created in the lab to when it is installed on edge computing devices spanning the IT network.

    When training AI models, MLSteam can be pictured as a fully furnished workshop staffed by consultants who are standing by to offer guidance. MLSteam puts together the most popular mainstream tools for developing AI, such as NVAIE, and then supplements them with an archive of synergistic resources, such as established best practices and standardized frameworks from comparable AI applications. For example, if a bank wants to employ deep learning and natural language processing (NLP) to launch fintech services, MLSteam can turbocharge the process with a ready toolkit and a library of templates for credit scoring, contract analysis, customer service automation, and other related applications. If a hospital wishes to use computer vision for medical image analysis and disease detection, MLSteam is loaded with convolutional neural networks (CNN) suitable for the task. The complexity of setting up an environment for AI-related work, which may require dozens of steps and hundreds of open-source resources, is condensed into a smart, customizable browser-based AIOps platform that saves the users' time and money while improving AI model accuracy.

    WITHOUT

    GIGABYTE MLSteam…

    • No resources or support for developing your own AI

    • No smart assistant to offer references or guidance

    • No quick-and-easy remote distribution & deployment

    • No IP protection

    WITH

    GIGABYTE MLSteam…

    • Complete archive of toolsets, frameworks, best practices

    • Smart customizable environment to help save time & money

    • Remote distribution & deployment across AIoT network

    • Proprietary IP protection features

    MLSteam's job is not over when AI training is done. When the pretrained model is installed across the network on devices such as edge servers, embedded AIoT systems, and IPCs, MLSteam can aid in remote distribution and deployment. It can also be used to monitor operations and provide support and maintenance. IP protection is another unique highlight of the GIGABYTE software, as MLSteam hosts proprietary safety nets that can prevent the painstakingly developed AI models from falling into the wrong hands.

    “With GPM and MLSteam, we are not just addressing the major pain points of AI data centers, we are also recreating the performance, efficiency, and stability of GIGABYTE’s AI hardware on a software level,” says Dr. Chen.


    "The market has spoken, and we have the answer. I think clients who use GPM and MLSteam in conjunction with GIGABYTE's GIGAPOD and AI Servers will find that they are taking full advantage of the latest and most enthralling trend in AI software," he concludes.

    Thank you for reading our analysis of the AI software trend and why we think AIOps and DCIM will have a deep impact on your AI competitiveness. We hope this article has been helpful and informative. For further consultation on how you can incorporate GIGABYTE Pod Manager (GPM) and MLSteam in your work, we welcome you to reach out to our representatives at marketing@gigacomputing.com.

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