![]() ![]() Take you to skim a web page before you click on a link - or 1.2 billion instructions It can run 24 billion instructions in the ten seconds it might Instructions per second (and this does not even count multi-core Waking up periodically to check some state.Ĭonsider a 2.4 GHz processor. Since most of these programs are waiting for user input, a network message, or sleeping and The time, all these processes collectively are using less than 3% of the CPU. ![]() Spreadsheet, several shell windows, Photoshop, iTunes, and various This includes a few browser windows, a word processor, As I write this on my Mac, I have 44 processes running Most interactive processes, in fact, spend the vast bulk of their existenceĭoing nothing but waiting on data. Even though it readsĪnd writes data, it spends most of its time processing that data. A video transcoder isĪn example of a process with long CPU bursts. Interactive burstsĬompute-intensive processes, conversely, spend more time running instructions and Interactive processes spend more time waiting for I/O andĮxample of an interactive process with short CPU bursts. The period of computation between I/O requests is called the CPU burst. After that, it executes more instructions and then, again, (computing) and then makes some I/O request, for example, to read or write data to a file or to If you look at any process, you’ll notice that it spends some time executing instructions Ja Relic va y ub 5.The finest eloquence is that which gets things done the worst is that which delays them. I/O performance - (virtualized to dedicated).RUM Beacons Real User Asynchronously Browsers Billions of metrics from Servlets Capture and across the globe enqueue (in-memory) aggregate and forward Timeslices to our Collectors Over 1 Billion user sessions measured for performance in first Currently at EC2 month. Beacon Architecture Response Time 0.15ms.Doubled our total inbound HTTP requests in a MONTH.Monitoring >1 Billion page views per week.Browser reports data to our ‘Beacon’ servers.Using Episodes to measure browser load time of every page view.9 Collector /Īggregator / DB’s Sustained 100K insertion rate per second S Customer’s environment HTTP 24 Core Intel Nehalem 48 GB RAM SAS attached RAID 5 No Virtualization (either cloud or datacenter) 2 Web App Servers 12 Core Intel Nehalem 48 GB RAM Interface Data Collectors Data Store & REST API MySQL Servlets on Jetty Sharded by accounts Rails 2.3 Page caching and other easy solutions don’t work for us. ![]()
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