A cluster is a large unit of deployment, involving hundreds of server cabinets with top of rack (TOR) switches aggregated on a set of large, high-radix cluster switches. Our previous data center networks were built using clusters. Our goal is to make deploying and operating our networks easier and faster over time, despite the scale and exponential growth. At the same time, we are always striving to keep our networking infrastructure simple enough that small, highly efficient teams of engineers can manage it. The ability to move fast and support rapid growth is at the core of our infrastructure design philosophy. We are constantly optimizing internal application efficiency, but nonetheless the rate of our machine-to-machine traffic growth remains exponential, and the volume has been doubling at an interval of less than a year. They rely on extensive real-time “cooperation” with each other to deliver a fast and seamless experience on the front end, customized for each person using our apps and our site. Our back-end service tiers and applications are distributed and logically interconnected. What happens inside the Facebook data centers – “machine to machine” traffic – is several orders of magnitude larger than what goes out to the Internet. However, this type of traffic is only the tip of the iceberg. The amount of traffic from Facebook to Internet – we call it “machine to user” traffic – is large and ever increasing, as more people connect and as we create new products and services. Moving fast, network infrastructure needs to constantly scale and evolve, rapidly adapting to our application needs. In this post, we will focus on the latest developments in our data center networking and unveil the next-generation architecture that we have successfully deployed in our new Altoona facility: data center fabric. On the back end, we have many advanced sub-systems and infrastructures in place that make such a real-time experience possible, and our scalable, high-performance network is one of them.įacebook’s production network by itself is a large distributed system with specialized tiers and technologies for different tasks: edge, backbone, and data centers. The more than 1.35 billion people who use Facebook on an ongoing basis rely on a seamless, “always on” site performance.
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