Title: Revolutionizing Enterprise Infrastructure: The Impact of Multicloud and Network as a Service (NaaS)
Claudio Saes serves as a partner and telecom practice leader at Bell Labs Consulting, a renowned division of Nokia Bell Labs. Companies in sectors like oil, gas, utilities, and mining have heavily invested in digital transformation, leading to unprecedented efficiency and productivity. This transformation is driven by integrating sensors, video analytics, and automated guided vehicles, among other technologies.
Significantly, these advancements rely on an increasing amount of artificial intelligence (AI), which requires robust cloud resources and high performance. However, this performance comes at a cost – financially, as well as in terms of infrastructure complexity.
In the past, enterprises often relied on a single cloud service provider (CSP), routing through the internet, which could introduce latency and security concerns. Today, modern medium and large enterprises have adopted a hybrid multicloud strategy, with workloads dispersed across multiple CSPs and on-premises infrastructure.
The Allure of Hybrid Multicloud Strategies
I've witnessed enterprises adopting hybrid multicloud strategies for compelling reasons. Firstly, hybrid multicloud architectures enable unparalleled flexibility, distributing workloads across different CSPs and on-premises infrastructure while scaling resources based on demand.
Secondly, multicloud strategies promote cost optimization. By selecting the most suitable platforms for each application and negotiating between multiple providers, enterprises can take advantage of better prices and utilize on-premises infrastructure for stable workloads while leveraging public clouds for resource-intensive applications.
Consider the example of a smart city. AI analyzes historical and real-time data to identify traffic patterns, predict congestion, and dynamically adjust traffic light timings to optimize flow. These applications demand AI models that are frequently updated with nearly daily training, needing substantial cloud resources. Every location, from city data centers to cloud servers across the country, requires interconnectivity to process data effectively.
Data Centers in the Multicloud Era
Acknowledging the opportunity, data center companies have started interconnecting enterprise servers directly with CSP servers. This improves application latency, reliability, and performance while offering an additional security layer for enterprise data. However, traditional data center companies often provide connectivity only between their data centers.
With modern enterprises connected to multiple CSPs and data centers, managing inter-data center links can become burdensome. As AI traffic moves from end users to data centers hosting AI models, diverse traffic flows arise across multiple inter-data center connections.
To address this challenge, additional transport network capacity is required across telecommunications providers, hyperscalers, and enterprise network backbones. This trend is reshaping how data centers, cloud providers, and telcos operate, supporting new levels of connectivity.
Network as a Service (NaaS) for Data Center Interconnection
To tackle these challenges, Bell Labs Conducting conducted a rigorous analysis of AI's impact on devices, cloud, and networks. They discovered that network traffic generated by AI will significantly increase, driven by both consumer and enterprise applications.
While consumer AI traffic is projected to be more substantial, enterprise AI traffic is predicted to grow at a faster rate, roughly 57% CAGR. Telecom companies are well-positioned to address this challenge, serving as intermediaries connecting enterprises, making them an ideal candidate for offering needed services. However, interconnecting every enterprise with data centers can be costly, especially in environments where multiple data centers and CSPs are involved.
Network as a Service (NaaS) helps overcome this challenge. Imagine if your enterprise could consume connectivity and bandwidth as needed, interconnecting dozens of data centers across your region or globally, with a pay-per-use model.
Key Factors for Industry Leaders
Before adopting NaaS for data center interconnection, businesses should assess several factors to ensure alignment with their operational needs and digital transformation goals. First, evaluate your current network infrastructure and determine how NaaS can integrate with existing systems. Ensure compatibility with current applications, databases, and security protocols for steady performance and minimal disruptions during the transition.
Organizations should consider their specific connectivity requirements, such as bandwidth, latency, and security, to ensure that the NaaS solution can effectively meet these demands. To decide if NaaS aligns with your operational needs, analyze your digital transformation objectives, the required flexibility and scalability of network resources, and potential cost predictability and operational efficiency. Engage with potential NaaS providers to understand your service offerings, support mechanisms, and customization capabilities.
When evaluating providers, establish clear criteria that reflect your unique operational needs, analyze vendor reliability, SLAs, tailored solution capabilities, and security measures, as well as their ability to provide resources for training and implementation.
Claudio Saes, as the telecom practice leader at Bell Labs Consulting, can provide valuable insights into implementing Network as a Service (NaaS) for data center interconnection, due to the increasing demand for robust cloud resources and high performance driven by artificial intelligence (AI). Companies adopting hybrid multicloud strategies often face challenges in managing inter-data center links, making NaaS a potential solution to deliver pay-per-use connectivity and bandwidth.
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