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Facebook: Infrastructure at Scale Using Emerging Hardware. Bill Jia, PhD. Manager, Performance and Capacity Engineering Oct 8 th , 2013. Agenda. of monthly active users are outside of the U.S. (as of Q2 ’ 13). 84%. Facebook Scale. Data Centers in 5 regions. Facebook Stats.
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Facebook: Infrastructure at Scale Using Emerging Hardware Bill Jia, PhD Manager, Performance and Capacity Engineering Oct 8th, 2013
of monthly active users are outside of the U.S. (as of Q2’13) 84% Facebook Scale Data Centers in 5 regions.
Facebook Stats • 1.15 billion users (6/2013) • ~700 million people use facebook daily • 350+ million photos added per day (1/2013) • 240+ billion photos • 4.5 billion likes, posts and comments per day (5/2013)
Cost and Efficiency • Infrastructure spend in 2012(from our 10-K): • “...$1.24 billion for capital expenditures related to the purchase of servers, networking equipment, storage infrastructure, and the construction of data centers.” • Efficiency work has been a top priority for several years
Search Photos UDB ADS-DB Tao Leader Msg Others Architecture Front-End Cluster Adsfew racks Web Multifeedfew racks Other smallservices Cache Back-End Cluster Service Cluster
L L L L L L Life of a “hit” Front-End Back-End Front end Back end requeststarts MC Feed agg MC Web Database Time MC Ads requestcompletes MC
Five Server Types • Advantages: • Volume pricing • Re-purposing • Easier operations - simpler repairs, drivers, DC headcount • New servers allocated in hours rather than months • Drawbacks: • 40 major services; 200 minor ones - not all fit perfectly • The needs of the service change over time.
Efficiency at FB • Data Centers • Heat management, electrical efficiency & operations • Servers • “Vanity free” design & supply chain optimization • Software • Horizontal wins like HPHP/HHVM, cache, db, web & service optimizations
Next Opportunities? • Disaggregated Rack • Better component/service fit • Extending component useful life • Developing New Components • Alternatives in CPU, RAM, Disk & Flash
Leaf Aggregator Network Switch L A Type-6 Server L A Type-6 Server . . . . => L A Type-6 Server Type-6 Server A rack of news feed servers... 80 processors 640 cores COMPUTE RAM 5.8 TB . . . STORAGE 80 TB Type-6 Server FLASH 30 TB The application lives on a rack of equipment--not a single server.
Compute • Standard Server • N processors • 8 or 16 DIMM slots • no hard drive - small flash boot partition. • big NIC - 10 Gbps or more
Ram Sled • Hardware • 128GB to 512GB • compute: FPGA, ASIC, mobile processor or desktop processor • Performance • 450k to 1 million key/value gets/sec • Cost • Excluding RAM cost: $500 to $700 or a few dollars per GB
Storage Sled (Knox) • Hardware • 15 drives • Replace SAS expander w/ small server • Performance • 3k IOPS • Cost • Excluding drives: $500 to $700 or less than $0.01 per GB
Flash Sled • Hardware • 175GB to 18TB of flash • Performance • 600k IOPS • Cost • Excluding flash cost: $500 to $700
Three Disaggregated Rack Wins • Server/Service Fit - across services • Server/Service Fit - over time • Longer useful life through smarter hardware refreshes.
Longer Useful Life • Today servers are typically kept in production for about 3 years. • With disaggregated rack: • Compute - 3 to 6 years • RAM sled - 5 years or more • Disk sled - 4 to 5 years depending on usage • Flash sled - 6 years depending on write volume
Disaggregated Rack • Strengths: • Volume pricing, serviceability, etc. • Custom Configurations • Hardware evolves with service • Smarter Technology Refreshes • Speed of Innovation • Potential issues: • Physical changes required • Interface overhead
Approximate Win Estimates Conservative assumptions show a 12% to 20% opex savings. More aggressive assumptions promise between 14% and 30% opex savings. * These are reasonable savings estimates of what may be possible across several use cases.
20 years of the same... • The servers we deploy in the datacenter are pretty much identical to a 386 computer from 20 years ago. • New Technologies: • Math coprocessor • SMP - N processors per server • Multi-core processors • GPUs - vector math • Flash memory • The exponential improvement of CPU, RAM, disk and NIC density has been incredible.
CPU Today: Server CPUs are more compute-dense versions of desktop processors. Mobile phones are driving development of lower power processors. System on a Chip (SoC) processors for this market integrate several modules into a single package to minimize energy consumption and board real-estate. Next: Smaller Server CPUs derived from mobile processors may become compelling alternatives.
RAM Today: The DDR standard RAM modules were developed for desktop servers. The DDR standard is difficult to hit on a cost/performance basis with alternative technologies. Next: Lower latency memory technology is interesting for “near RAM.” Slower memory (between RAM and Flash) could be accommodated for “far RAM.”
Storage (ZB of data; 1 ZB = 1 billion TB) Today: Photo and data storage uses 3.5” disk drives almost exclusively. Applications and file systems expect low-latency writes and reads and unlimited write cycles. By changing these assumptions optical and solid-state media may be viable. Next: Cold and big capacity storage. Lower power density and slower performance
Flash (solid state storage) Today: Flash SSD drives are commonly used in databases and applications that need low-latency high-throughput storage. SLC – Premium MLC: Expensive, performant, high enduring (10K) MLC: Less enpensive, performant, lower enduring (3K) TLC: Cheap, performant (100-300) Worm TLC: Extremely cheap (1)
Network Interfaces Today: 10 Gbps NICs are becoming standard in servers. 40Gbps are emerging and in production Next: By focusing on rack distances (3 meters) and allowing proprietary technologies, 100 Gbps could be affordable in a few years.