Data Center Design Requirements Data centers typically run two types of applications outward facing( e.g serving web pages to users) internal computations(e.g, MapReduce for web indexing Workloads often unpredictable: Multiple services run concurrently within a DC k Demand for new services may spike unexpected Spike of demands for new services mean success k But this is when success spells trouble(if not prepared) Failures of servers are the norm Recall that GFS, MapReduce, etc, resort to dynamic re assignment of chunkservers, jobs/tasks(worker servers )to deal with failures; data is often replicated across racks, Traffic matrix"between servers are constantly changing
Data Center Design Requirements Data centers typically run two types of applications outward facing (e.g., serving web pages to users) internal computations (e.g., MapReduce for web indexing) Workloads often unpredictable: Multiple services run concurrently within a DC Demand for new services may spike unexpected Spike of demands for new services mean success! But this is when success spells trouble (if not prepared)! Failures of servers are the norm Recall that GFS, MapReduce, etc., resort to dynamic reassignment of chunkservers, jobs/tasks (worker servers) to deal with failures; data is often replicated across racks, … “Traffic matrix” between servers are constantly changing 16
Data center costs Amortized Cost* Component Sub-Components ~45% Servers CPU, memory, disk ~25% Power infrastructure UPS, cooling, power distribution 15% Power draw Electrical utility costs ~15% Network Switches, links, transit *3 yr amortization for servers, 15 yr for infrastructure; 5% cost of money Total cost varies upwards of $1/4 B for mega data center server costs dominate network costs significant Long provisioning timescales new servers purchased quarterly at best 17
Data Center Costs Total cost varies upwards of $1/4 B for mega data center server costs dominate network costs significant Long provisioning timescales: new servers purchased quarterly at best 17 Amortized Cost* Component Sub-Components ~45% Servers CPU, memory, disk ~25% Power infrastructure UPS, cooling, power distribution ~15% Power draw Electrical utility costs ~15% Network Switches, links, transit *3 yr amortization for servers, 15 yr for infrastructure; 5% cost of money
Overall Data Center Design Goal Agility-Any service, Any Server turn the servers into a single large fungible pool Let services"breathe": dynamically expand and contract their footprint as needed We already see how this is done in terms of Google's GFS, Bigtable, MapReduce Benefits Increase service developer productivity k Lower cost Achieve high performance and reliability These are the three motivators for most data center infrastructure projects 18
Overall Data Center Design Goal Agility – Any service, Any Server Turn the servers into a single large fungible pool Let services “breathe” : dynamically expand and contract their footprint as needed We already see how this is done in terms of Google’s GFS, BigTable, MapReduce Benefits Increase service developer productivity Lower cost Achieve high performance and reliability These are the three motivators for most data center infrastructure projects! 18
Achieving Agility Workload management means for rapidly installing a service' s code on a server dynamical cluster scheduling and server assignment M E.g., MapReduce, Bigtable, 本rtua/ machines, disk images囡 Storage Management k means for a server to access persistent data distributed file systems(e.g, GFS)M Network Management Means for communicating with other servers, regardless of where they are in the data center Achieve high performance and reliability 19
Achieving Agility … Workload Management means for rapidly installing a service’s code on a server dynamical cluster scheduling and server assignment E.g., MapReduce, Bigtable, … virtual machines, disk images Storage Management means for a server to access persistent data distributed file systems (e.g., GFS) Network Management Means for communicating with other servers, regardless of where they are in the data center Achieve high performance and reliability 19
Networking Objectives 1. Uniform high capacity Capacity between servers limited only by their Nics No need to consider topology when adding servers >In other words, high capacity between two any servers no matter which racks they are located 2. Performance isolation Traffic of one service should be unaffected by others 3. Ease of management: Plug-&-Playr(layer-2 semantics Flat addressing, so any server can have any IP address Server configuration is the same as in a LAN Legacy applications depending on broadcast must work 20
Networking Objectives 1. Uniform high capacity Capacity between servers limited only by their NICs No need to consider topology when adding servers => In other words, high capacity between two any servers no matter which racks they are located ! 2. Performance isolation Traffic of one service should be unaffected by others 3. Ease of management: “Plug-&-Play” (layer-2 semantics) Flat addressing, so any server can have any IP address Server configuration is the same as in a LAN Legacy applications depending on broadcast must work 20