AI and ML-backed CDNs: Better Performance at an Affordable Cost

CDNs use AI and ML to improve response times to offer a seamless and disruption-free content delivery experience through the network, all at a more efficient cost to businesses.

FREMONT, CA : Technological innovation has entered into an interesting era — the twin pair of Machine Learning (ML) and Artificial Intelligence (AI) has created stimulating discussions in a business circle with their capabilities and opportunities. These two concepts tend to be coupled together. Content Delivery Networks (CDNs) are no exception here. CDNs play a very vital role in the online world today. CDNs help to offer excellent content delivery and performance. CDNs are also witnessing the effect of significant technological breakthroughs of AI, ML, and in the migration of network infrastructures to the cloud. These breakthroughs are offering the most significant opportunities for CDN service providers.

CDNs cache data across a network of data centers to offer the requested content to the user from the edge server rather than having the request travel to the origin server and then back again. As an outcome, the user experiences an enhanced server response time. With content being pushed to the edge, it becomes vital to infuse network management and optimization with intelligence. ML and AI can be leveraged to a distributed infrastructure so that network operators can proactively identify network traffic patterns and appropriately respond to communications traffic requirements to experience better content performance.

ML algorithms are trained with data from networks to develop an appropriate model for the network to make effective real-time decisions. This mitigates the chance of small incidents, like HTTP errors, IO access, or cache miss rates, from becoming full-blown problems. Open-source ML and AI also offer an opportunity for CDN service providers to develop an intelligent solution without investing heavily in technology.

To use the opportunities that AI and ML present, service providers want to build a virtual CDN infrastructure embedded with next-generation ML and AI-powered solutions. This type of solution will assist in managing an increasingly complex network effectively and dynamically, offer an intelligent management solution capable of providing better experiences to content consumers, and unlock new revenue streams for organizations. Data-based learning and predictive analytics can be harnessed to inform decisions that will grow the bottom line.

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