Akamai Bets on Edge Computing to Take on AWS, Azure and Google Cloud
Akamai Technologies, a prominent global content delivery network (CDN) provider, aspires to make a mark in the cloud computing space, placing significant emphasis on edge computing infrastructure as a strategic move. The company aims to integrate cloud computing capabilities throughout its extensive edge network via generalised edge compute or Gecko (as Akamai calls it), solidifying its position as a cloud leader. Even though the market is heavily dominated by hyperscalers, Akamai feels its focus on bringing compute closer to the customers will help them gain significant market share. “This combination of cloud and edge, combined with our extensive expertise in distributed networking for delivering our services, provides a substantial advantage. This becomes crucial as industries encounter rising demands for enhanced price performance, reduced latency, and heightened security in applications and data spanning a broader spectrum of computing,” Jay Jenkins, chief technology officer, cloud computing at Akamai Technologies, told AIM in an exclusive interaction. Reduced latency in fact is a pivotal factor for numerous workloads. Jenkins emphasised the potential significance, stating, “Imagine the shift from 40 milliseconds to single-digit milliseconds for latency—this could be transformative for many customers.” A Decentralised Approach in a Centralised Market Traditionally, cloud computing predominantly occurs in centralised architectures within cloud environments. Hyperscalers serve customers from data centres located centrally but Akamai is approaching cloud in a very different way. “If you take a look at current architectures, they generally treat cloud and edge very separately. Cloud, of course, is where you have all of the compute and storage and edge is really just sort of for content delivery. Maybe they have ‘Functions as a Service’ at the edge, but what we are really trying to do is have a virtual machine at the edge as a start and then start to roll out additional services from there,” Jenkins added. Interestingly, Akamai’s journey into cloud computing began three years ago and to enable this, Akamai is leveraging its already existing CDN infrastructure and has made strategic acquisitions in the last few years. It acquired infrastructure-as-a-service (IaaS) platform provider Linode for about USD 900 million in 2022. Moreover, the company is also entering strategic partnerships with telcos, IT solutions, and local cloud service providers across the globe. In the last 25 years, Akamai has established 4100 points of presence globally and is converting them into edge facilities. As ambitious as it may sound, Akamai aims to establish 10 new edge locations by the end of the month, 100 by the end of this year and scale even further in the coming years. “Converting one of our existing points of presence into a computing facility is easy because we’ve been doing distributed computing for so long for our services,” Jenkins said. Betting on Multi-cloud Approach Jenkins acknowledges that migrating workload from an existing cloud service provider or hyperscaler to Akamai’s network could be challenging for many customers. Hence, to begin with, they are relying on the multi-cloud approach. “At Akamai, we advocate for a multi-cloud approach, allowing customers to leverage the best services irrespective of the cloud platform. Envision a scenario where core infrastructure necessitates centralised services, yet specific containers and services demanding quicker response times can seamlessly transition to the edge,” Jenkins said. He also acknowledged that other players in the industry will shift their focus to the edge, but Akamai holds a unique advantage due to the time-intensive nature of constructing a distributed infrastructure. Additionally, Akamai’s global presence, with 8 times more points of presence compared to competitors in the pureplay CDN space, further solidifies its advantage. Moreover, hyperscalers like AWS, Microsoft or Google Cloud will take even more time because they’re very focused on centralised infrastructure and are very dependent on efficiency at scale in a single location. “If they adopt a similar strategy to Akamai’s, it could take longer for them to establish similar infrastructure,” Jenkins said. Nonetheless, we have seen AWS, the global leader in the cloud computing space, expand its local zones. However, Akamai’s approach is unique as they don’t treat cloud and edge networks differently. Jenkins also mentioned that Akamai had secured a major client, a prominent social media giant (potentially ByteDance). This client uses Akamai’s infrastructure to deliver and capture video at the edge. Akamai is positive about landing more customers as they transition towards the second phase of Gecko, which is set to commence later this year. The company aims to incorporate containers into the framework and moving to Gecko’s third phase, Akamai intends to introduce automated workload orchestration. Opportunities in AI Edge Inferencing With the surge of generative AI, companies worldwide and across diverse industries are exploring the utilisation of large language models (LLMs) to their advantage. The demand for training compute, inferencing, and deploying these models has increased significantly. Jatkins believes that distributed computing has also been reinvigorated by AI and there are huge opportunities for things like AI edge inferencing. “There are different sides to this AI story. While the training side has received substantial attention in recent years, the upcoming focus will shift significantly to the operational side. Emphasis will be on efficient operations, optimising inferencing closer to customers, and deploying strategies to drive tangible value,” he added. The surge in demand for NVIDIA’s GPUs in the past year primarily resulted from the necessity for LLMs. However, for inferencing, particularly with smaller models, Jatkins suggests that a CPU architecture is generally adequate. Nonetheless, Akamai is exploring a spectrum of specialised processors beyond GPUs, actively engaging with its customers to gauge demand. Serving Underserved Locations For Akamai to emerge as a global leader in the cloud computing space, it is also targeting customers strategically, located in areas where other cloud service providers or hyperscalers are not present. This month alone, Akamai will be established in regions such as Bogotá, Colombia; Denver, Colorado; Houston, Texas; Hamburg, Germany; and Marseille, France, which are without a concentrated hyperscaler presence. Moreover, they will expand to 65 more locations by the end of this year. “We’re going to bring full stack computing to hundreds of previously underserved locations and allow customers to move workloads closer to where the users are.” En route: India Jenkins adds that India is an important market for Akamai and will launch edge locations in the country soon. Last year, Jaipur-based Znet Technologies became the first official distributor of Akamai cloud computing services in India. Akamai already has two data centres in India, in Chennai and Mumbai. Moreover, it has points of presence in other cities such as Pune, Hyderabad, Delhi and many smaller cities such as Agra, Agartala, Guwahati, Bhopal, Bhubaneswar and Ahmedabad, among others. Many companies in these regions continue to maintain their data on-premise. Jenkins contends that there’s no necessity to relocate the data to a data centre thousands of miles away; instead, substantial benefits can be derived from utilising local solutions. “Positioned on an optimised network, the same one used for content delivery and security, we aim to extend full-stack computing to numerous underserved locations. This empowers customers to place workloads closer to their end-users strategically,” Jenkins concluded.
Akamai aims to establish 10 new edge locations by the end of this month and 100 by the end of this year
Akamai will establish 25 new edge locations by the end of this month, 100 by the end of 2024 and scale to over thousands in the coming years.
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["AI", "ML", "generative AI", "Aim", "RAG", "cloud computing", "AWS", "edge computing", "distributed computing", "R"]
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