èªåã®ãã·ã³ãã«ã§ã·ã¹ããããã¯ãªããæ§è½åæãã®ã«ã¼ããªé¢ã ã®ãã¡ã®2人*1 Brendan Gregg@Netflix 㨠Tanel Poder@Gluent ãç´ æµãªçµ¡ã¿ããã¦ããã®ã§ã¡ã¢ã @brendangregg Could be useful: I once documented my understanding of the typical CPU counters that perf exposes all in one place: https://t.co/pqaDdbDyi1â Tanel Poder (@TanelPoder) 2017å¹´5æ10æ¥ Brendan Gregg ã¯ãã£ããã以ä¸ã®ãããªãã¨ãè¨ã£ã¦ããã CPUã®1ãµã¤ã¯ã«ã¨æ¯è¼ãã¦ã¡ã¢ãªã¢ã¯ã»ã¹ã¯é ã*2ã®ã§ãON CPU ã§ãã¡ã¢ãªI/O*3å¾ ã¡ã§ã¹ãã¼ã«ãã¦ããã¨ãå¤ãã IPC(Instr
1. Apache Kafka vs RabbitMQ: Fit For Purpose/Decision Tree Feature Kafka RabbitMQ Need a durable message store and message replay capability Y N Need ordered storage and delivery Y* N Need multiple different consumer of same data Y N Need to handle throughput of all my data well even at web scale and not a smaller set of messages Y N Need a high throughput with low latency Y N Need to decouple pro
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