Whitepaper Resource-Pooled Server Trends Data Center Software Division Tencent Explores Datacenter Resource-Pooling Using Intel® Rack Scale Architecture (Intel® RSA) Traditional rack servers do not meet today’s datacenter needs. Tencent worked with Intel on a proof-of-concept involving Intel® RSA technology. Tencent, a leading provider of • Datacenters globally consume Internet Services in China, recently over 100 GWh per year, a figure collaborated with Intel on a proof- industry analysts expect to of-concept to demonstrate that exceed 130 GWh by 2016.3 resource-pooling—even in the early • As measured by the power stages of development—could usage effectiveness (PUE) index bring better experience to users, defined by The Green Grid, reduce power consumption, and CRAC (computer room air yield measurable total cost of own- conditioning) units alone can ership (TCO) savings. consume as much as half of a This paper addresses the reasons datacenter’s power needs.4 for developing a resource-pooled “As a leading provider of Internet Over the last decade, Tencent has server technology standard; been involved in several efforts to Services in China, Tencent has a keen explains some of the challenges we interest in Intel® RSA technology. How improve datacenter design, face; offers insights on trends in the including a partnership with other resource-pooling can help us reduce development of this technology; datacenter total cost of ownership while Internet business leaders to create and presents some of the findings a rack-design specification, called simultaneously improving our from the Tencent proof-of-concept. customers’ user experience is a key Project Scorpio. Tencent focuses on question for our business.” Datacenter growth—in storage, maximizing datacenter perfor- power consumption, traffic, and mance and increasing resource uti- Herry Wang processing needs—is driving inno- lization; reducing hardware Principal Engineer and Architect vations in constructing more cost- acquisition, operations, and mainte- Tencent Holdings Limited efficient facilities. These efficien- nance costs; reducing datacenter cies are direly needed as datacen- TCO; and ultimately delivering a ters burst at the seams: better user experience to cus- tomers. • Ninety percent of the world’s data has been created in the last five years, and we add more than 2.5 quintillion bytes to the total every day.1 • Worldwide mobile data traffic— projected to grow at a compound annual rate of 57% for the next four years—is expected to reach a throughput of 24.3 exabytes per month by the year 2019.2 Tencent Explores Datacenter Resource-Pooling Using Intel® Rack Scale Architecture (Intel® RSA) The shortcomings of rack servers hardware configurations. As a every two to three years, while result, server specialization has storage capacity has been doubling The rapid expansion of datacenters become the norm. Tencent’s data- at a rate of about five years. Mis- worldwide has been fueled by the center, for example, houses hun- aligned technology advances such explosive growth in social media dreds of thousands of rack servers, as these produce gaps in server and the commoditization of rela- more than 90% of which have been optimization. An all-in-one server, tively inexpensive rack servers. custom-provisioned for specific with equally provisioned resources, Ironically, that very same prolifera- workloads and purposes. will see one area of its resources tion of rack servers has also intro- become outdated more frequently duced new concerns. For example, This expansion of server types has than another area. This misalign- many servers are not optimally con- partially mitigated the inflexible ment of technologies makes it diffi- provisioning of traditional cookie- figured for their purposes, which cult to upgrade to more efficient can result in waste and inefficiency. cutter servers, but it has also led to processors, memory, and storage broader server diversity in the data- without unnecessarily discarding The “one size fits all” server config- center, which introduces new chal- still-useful resources. uration does not work in today’s lenges to server resource datacenter. In resource-intensive management, day-to-day mainte- Compounding this problem is the environments, a traditional rack nance, and overall datacenter oper- fact that businesses seldom replace server suffers from low operation ations. Each new custom server servers as often as they’d like—or efficiency and low deployment den- type introduces an additional layer as often as they should. The sity. Some negative side-effects of complexity to datacenter man- majority of organizations have old, include the following: agement and maintenance. less efficient servers. • In compute-dense applications, Moreover, past efforts to compen- Homogeneously provisioned unused memory slots, HDD sate for different application needs servers could ameliorate these (hard disk drive) slots, and and inflexible provisioning have run unavoidable mismatches in tech- expansion slots negatively into unsynchronized server compo- nology advancements by isolating affect computing density. nent lifecycles, which have also the technology to specific resource • In memory-dense applications, raised the TCO. For example, CPU pools. unused expansion slots and performance has been doubling HDD slots waste server “real estate” that could be used for more memory. Figure 1 Diversity of datacenter workloads. Most organizations customize servers according to workload needs. Plotting these workloads on a graph separating CPU/memory and input/output • In storage-dense applications, capacity shows the disparity of server provisioning required to optimize servers for specific workloads. CPUs and memory might be overprovisioned. As Figure 1 shows, the modern compute environment features a Enterprise applications variety of workloads, each with dif- High-performance computing ferent compute, storage, and I/O needs. With I/O intensity on the Graphics rendering horizontal axis and CPU and memory intensity on the vertical axis, it is difficult, perhaps impos- Edge routing sible, for a traditional server—with Cloud RAN its balanced configuration of com- puting, memory, and storage E-commerce Content delivery and gaming resources—to support the wide variety of applications encountered Small cell in a modern datacenter. Storage dedupe For years, Tencent and many other Low-end networking cloud service providers (CSPs) CPU and memory intensive worldwide have been customizing servers to perform specific types of Dedicated hosting Cold storage tasks from different workloads, pro- visioning the servers with different I/O intensive 2 Tencent Explores Datacenter Resource-Pooling Using Intel® Rack Scale Architecture (Intel® RSA) To address these old and new chal- In other words, virtualization and multinode (m-to-n) resource alloca- lenges, we must devise a solution cloud services go part of the way, tion. Cloud services remain virtual- that allows us to intelligently provi- but they are no substitute for ized at the software level, but sion servers and manage the newly resource pooling. resource-pooled servers provide configured datacenter more effi- further virtualization capability at The first example in Figure 2 shows ciently. the hardware level. a 1-to-1 single-server environment, with various apps running on a These last two approaches are not Virtualization is not enough single operating system on one contradictory, but complementary. As with many large Internet service physical server. To increase With resource-pooled servers, we providers, Tencent’s datacenter capacity, you add more servers, but can continue to run virtualization currently features sophisticated vir- it is already obvious that this leads and cloud server software on logical tualization and cloud services, pro- to underutilization. servers and create virtual machines viding end-users with a better for end-users. This shrinks the In the 1-to-n virtualized server resource allocation hole left by experience and minimizing IT model (center), a single physical cloud services, improves the utiliza- expenses. With such an efficient server can divide its physical environment, why would an IT tion of hardware resources, and resources and allocate portions to ultimately reduces TCO. Compared department seek to pool its servers’ multiple virtual machines. This does resources? to the generic virtualization of a reduce idle resources, but it does single server into multiple nodes, Virtualization is a good midpoint not entirely eliminate inefficiencies, multiserver-to-multinode virtual- as different workloads require spe- phase in datacenter server optimi- ization provides even better utiliza- zation. With a firm footing in data- cially configured servers that virtu- tion of a pool of servers’ resources. centers today, virtualization and alization alone is not equipped to cloud implementations have handle. The biggest challenges in resource- pooling are interconnectivity/ improved resource utilization for Pooled resource technology (right) datacenter servers; however, CPUs latency, provisioning, and manage- allows a datacenter to allocate ment software. and memory in such environments resources with even greater effi- are still often underutilized, due to ciency by providing multiserver-to- the granularity of server resources. Figure 2 Virtualization overdrive. In a one-to-one environment, every physical server is a unique node. Adding users or nodes means adding servers. A virtualized server environment allows