AI Data Center Market Research

• Technology organizations believe data center network automation can drive operational efficiency, security risk reduction and improve compliance and digital agility 

• Nearly 77% of technology professionals see room for improvement in their data center network automation strategies 

• 45% of organizations expect their data center network automation investments to earn an ROI within two years • Organizations have multiple data center network automation tools ◦ More than 48% use two tools and 34% use three 

• Organizations are using a mix of commercial and homegrown data center network automation tools ◦ Nearly 93% are developing their own software ◦ 98% are using commercial solutions 

• Nearly 93% of organizations are engaged with intent-based networking solutions 

• 72% of organizations require their tools to orchestrate network automation across multiple, geographically dispersed data centers 

• Nearly 78% of organizations require their data center network automation tools to be extensible to the public cloud 

• Nearly 89% of organizations believe it is at least somewhat important for a data center network automation tool to have integrated monitoring and troubleshooting capabilities 

• Nearly 48% of organizations have automation tools that require at least some manual data gathering before implementing a change ◦ 51% of these organizations say manual data gathering has a negative impact on the effectiveness of their automation 

The report delves into the significant role of AIOps (Artificial Intelligence for IT Operations) and Intent-Based Networking (IBN) in the future of data center network automation. Below is a detailed summary of the findings related to both technologies:

Definition and Relevance:

• AIOps refers to applying artificial intelligence (AI), machine learning (ML), and big data solutions to IT operations. It is used to enable predictive analytics, anomaly detection, and intelligent automation.
• The report emphasizes that AIOps is seen as crucial in helping organizations manage increasingly complex network environments. AIOps-driven solutions improve operational efficiency by automating mundane tasks and analyzing massive datasets to detect anomalies and predict failures before they occur.

Adoption Trends:

• 66.6% of organizations surveyed require AIOps capabilities in their data center network automation tools. Another 28.3% believe it would be helpful, showing broad interest and confidence in its benefits.
• Best-in-class organizations are more likely to implement AIOps solutions. These high-performing enterprises recognize the value AIOps offers, especially in terms of enhancing visibility, improving decision-making, and delivering better business outcomes.
• Interest in AIOps increases with the number of data centers a company operates. Cloud providers demonstrate more enthusiasm for AIOps than traditional enterprises, likely due to the scale and complexity of their infrastructure.
• Americans show higher interest in AIOps than Europeans, indicating regional variation in adopting AI-driven technologies.

Benefits of AIOps:

• The key benefits of AIOps-driven network automation include:
  • Anomaly detection: Automatically identifying irregularities in network behavior and taking corrective action before they lead to larger issues.
  • Predictive analysis: Using machine learning algorithms to predict network failures or issues based on historical data.
  • Intelligent automation: Automating more sophisticated tasks, such as network optimization, by analyzing operational data in real-time.
• Over 90% of organizations believe that AIOps-driven network management will lead to better business outcomes, such as reduced downtime, enhanced performance, and more efficient operations.

Definition and Purpose:

• Intent-Based Networking refers to a type of network automation technology that abstracts the complexity of network management. Administrators define their business intent (such as performance, security policies, or service availability), and the IBN tool automatically translates that intent into network configurations and implements the necessary changes.
• IBN is designed to simplify the network management process by enabling network administrators to work at a higher, business-centric level. It integrates with automated systems that ensure the network’s state aligns with the administrator's expressed intent.

Adoption Trends:

• 78% of organizations are either already using or plan to adopt intent-based networking technologies. This indicates strong market engagement with IBN as part of network automation strategies.
  • 20.7% of organizations stated that most of their data center network automation is already based on IBN technologies.
  • Another 57.2% use IBN for some aspects of their automation.
  • 19% plan to adopt IBN in the future, showing continued interest in its benefits.
  • Only 3% of organizations reported having no plans for IBN, suggesting a broad consensus that IBN will be an essential technology in the future of network automation.
• Best-in-class organizations are more likely to leverage IBN extensively. These organizations understand the value of abstracting network complexity to enable faster and more precise responses to business needs.
• Cloud providers show lower engagement with IBN compared to communications service providers and enterprises. This may be due to differences in network architecture complexity or existing automation toolsets.

Benefits of Intent-Based Networking:

• Simplification of Network Operations: IBN allows administrators to focus on business goals instead of the technical intricacies of network configuration. By inputting high-level policies and objectives, IBN systems handle the details of how these are implemented across the network.
• Improved Agility and Accuracy: IBN enables faster changes and optimizations by dynamically adjusting the network to meet the desired business outcomes without requiring human intervention at each step.
• Alignment of Network State with Business Intent: IBN tools maintain an ongoing comparison between the current network state and the desired state (as expressed by business intent), ensuring that discrepancies are automatically identified and resolved.
• Increased Automation: The ability of IBN tools to self-correct and automate change management reduces the need for manual configuration changes, speeding up response times and reducing the risk of human error.

• The report suggests that AIOps and IBN can work together to provide a powerful approach to network automation. While IBN focuses on automating network changes based on business intent, AIOps can enhance IBN systems by providing intelligent insights, predicting issues, and optimizing performance in real-time.
• AIOps improves the decision-making process within an IBN framework by using AI to predict the outcomes of specific network changes and prevent potential issues before they arise. This makes the automation process more resilient and proactive.
• Best-in-class organizations are more likely to have both AIOps and IBN technologies integrated into their network automation strategies, allowing them to realize greater efficiency and performance improvements.

Both AIOps and Intent-Based Networking are recognized as critical technologies in the future of data center network automation. AIOps provides the intelligence and predictive capabilities needed to manage increasingly complex networks, while IBN simplifies the operational side by aligning network configurations with business needs. Together, these technologies can automate many of the tasks that traditionally required manual intervention, improving network agility, performance, and security. Best-in-class organizations are leading the way in adopting both AIOps and IBN, recognizing that these technologies are essential for achieving operational excellence in modern data centers.

The report titled "The Future of Data Center Network Automation" provides a comprehensive overview of the current and future trends in data center network automation, drawing on quantitative and qualitative research by EMA. Below is a detailed summary of the key findings:

• Enterprises and service providers are increasingly investing in data center network automation to meet modern demands such as scalability, security, agility, and operational efficiency.
• Data center network automation is seen as crucial for improving compliance, reducing security risks, and enhancing digital agility.

• While most organizations recognize the importance of automation, 77% see room for improvement in their strategies, indicating challenges in reaching their automation goals.
• A significant portion of automation strategies (62%) are viewed as only "somewhat good," with only 23% considering their approach "very good."

• Almost half (45%) of organizations expect to see ROI from automation investments within two years. This highlights the confidence in automation's ability to deliver financial benefits within a short period.
• Best-in-class organizations tend to achieve faster returns, with many expecting ROI in just one year.

• Most organizations use multiple tools for automation, with 48% using two tools and 34% using three. Multi-tool strategies are common, though this can create challenges like tool fragmentation.
• Nearly 98% of organizations use commercial automation tools, and 93% are developing their own software internally, often to meet specific security and compliance needs.

• The top benefits sought from automation include:
  • Operational efficiency (41%)
  • Reduced security risk (36%)
  • Improved compliance (34%)
  • Increased agility in responding to changes (31%)
• Automation is also seen as a means to reduce operational expenses and accelerate incident response.

• Data center automation increasingly needs to extend to public cloud environments. Nearly 78% of organizations require their automation tools to support hybrid, multi-cloud infrastructures.
• Integration with DevOps tools is becoming more critical, with 97% of organizations with DevOps teams integrating network automation into their DevOps processes.

• Artificial Intelligence for IT Operations (AIOps) is gaining traction, with 67% of organizations requiring AIOps capabilities in their automation solutions.
• Intent-based networking (IBN), which allows administrators to define business intent and automate changes based on that intent, is also highly engaged, with 78% of organizations using or planning to adopt IBN.

• Manual data collection is still prevalent in 48% of organizations, which negatively impacts automation effectiveness in many cases.
• There is a growing trend towards creating automated central repositories (52% adoption) for network data, which improves automation efficiency.

• Key features for automation tools include device lifecycle management, security policy management, change analysis, and configuration compliance. These features help ensure that network changes are handled efficiently and securely.
• Monitoring and troubleshooting are essential features, with 89% of organizations emphasizing the importance of integrated assurance capabilities in their automation solutions.

• Data center network automation budgets are growing, with 86% of organizations planning to increase their spending over the next two years. Larger organizations and those in North America expect more significant budget increases than their European counterparts.

• EMA identifies several best practices for successful automation, including:
  • Leadership should enforce policies that encourage the use of automation tools.
  • Consider reducing the number of automation tools to streamline operations.
  • Invest in tools that offer stability and resilience.
  • Opt for solutions that support hybrid cloud environments and integrate well with existing network and DevOps systems.

Data center network automation is evolving rapidly, with organizations adopting multi-tool strategies, increasing investments, and integrating with cloud and DevOps infrastructures. Despite the potential for efficiency gains, many organizations face challenges in realizing the full potential of automation, often due to tool fragmentation, manual data collection, and insufficient integration. Organizations that focus on improving automation strategies and embracing cutting-edge technologies like AIOps and intent-based networking are more likely to achieve success.