CS 91: Cloud Systems & Datacenter Networks

Transcription

1 CS 91: Cloud Systems & Datacenter Networks The Datacenter Environment Kevin Webb Swarthmore College September 3, 2014

2 Announcements Sign up for piazza If you didn t just add the course, you should have two files in your home dir: CS91- AWS: Amazon credenpals CS91- GS: gradesource secret number

3 Agenda Why datacenters now? Current trends What are the guiding principles? Characterize the environment IntroducPon to next topics (virtualizapon, MR)

4 Datacenters MulPple Walmarts in size $500,000,000 to build 10, ,000 servers miles of cabling Why does it make sense to build these monsters?

5 Trends in CompuPng 1. What trends in technology have led to the feasibility of (and need for) datacenters? 2. How have economic trends and factors (e.g., pricing) influenced things?

6 Technology Trends? Fast consumer Internet connecpons PlenPful mobile devices, expect interacpve media Large data sets to process, relentless demand Moore s law isn t bailing us out anymore Cloud abstracpon: infinite resources out there Somebody has to build a system to provide it

7 Economic Trends? Good hardware is cheap (commodity) If you can sapsfy tech demands, you make $$ Pueng lots of hardware in DC yields economy of scale

8 Design Principle: Scale Out Scale out rather than scale up Design system to be distributed from the start Scale system such that it improves as more resources are added Why? ImplicaPons? Even if CPUs never get faster, more work gets done Can (ohen) incrementally improve by buying cheap HW

9 Environment hip:// facebooks- lulea- data- center/

10 Server Hardware COTS : commodity off the shelf Could buy (most of) it from Newegg/Amazon SPll expensive, high- end hardware Lots of RAM, many cores Not usually specialized enterprise grade

11 Network ConnecPvity Top of rack switch connects servers to tree Performance implicapons?

12 Network ConnecPvity Top of rack switch connects servers to tree BisecPon Bandwidth Performance implicapons?

13 Sohware Reliable, scalable distributed systems (This is one of the main topics we ll be reading about, I can t summarize it in one slide!)

14 Google Search Request This is an illusion. Reality is much more complex! Response

15 Google Search Web Index G+ Profile Load Balancer Request Front- End Ads Whole process: less than 1/10 th of a second.

16 Non- CompuPng Resources Huge benefits from economy of scale People to manage infrastructure Air condiponing systems Backup generators ( s gallons diesel) Building maintenance Capital Expenditure (CAPEX) vs. OperaPonal Expenditure (OPEX)

17 Clouds: Public vs. Private Datacenters are the cloud infrastructure Might be public: Anyone can pay to rent Pme Amazon AWS, Windows Azure, etc. Might be private: Large pool of resources for company- only use Google, Microsoh, Facebook, etc.

18 Challenges What makes this environment difficult? Scale naming and finding resources exploipng locality management Reliability MulP- tenancy Parallelizability Side note: DC vs. Supercomputer SupercompuPng ohen spll scales up, when possible. ImplicaPons of supercomputer failures usually less dire.

19 (Machine) VirtualizaPon Recall virtual memory: Make each process think it owns enpre memory Virtual machines take this idea a step further: Make OS think it owns enpre machine Run mulpple OSes on one machine

20 VirtualizaPon Benefits MulP- tenancy: Account for resources, divide them among users Keep users isolated from one another Reliability: Decouple machine state from physical machine Move execupon elsewhere, if necessary Management: Users get their own OS, with (mostly) full control

21 Upcoming Papers VM/370: Historical look at virtualizapon Xen: virtualizapon mechanisms, making it easier for OSes running inside VM Eucalyptus: A cloud plasorm for provisioning virtual machine resources on demand But first MapReduce (for lab)

22 MapReduce (Google, 2004) Extremely influenpal paper / system Elegant solupon for parallel processing Scales out really well as machines added Used extensively all over the place

23 Reading Academic CS Papers Resource on course web page: How to Read an Engineering Research Paper Mark the paper as you read along Step 0: Get the context for the paper When was the paper published? Who are the authors (first & last)? Where do they work, how might that influence it?

24 Reading Academic CS Papers What is the mopvapon / major problem? What is the hypothesis / proposed solupon? How is the solupon evaluated? What is your analysis of the problem / solupon? What are the major contribupons? What are the next steps (or missing)? Also: mark clarificapons or cool stuff

25 (Time permieng) Reading Discussion