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GDE Monitoring distributed systems with Google Big Query and R Dale Humby CTO, Nomanini Google Developer Expert for Cloud Platform

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micro-transactions in emerging markets

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GDE

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GDE

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GDE

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GDE

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GDE

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GDE Continuous Delivery

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GDE

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JSON GDE Event counters { "counts": { "ERROR": 7, "WARNING": 1475, "DEBUG": 362754, "[E].EventsManager.423": 2, "[E].GPSManager.259": 1, "[E].SlaveCommsDispatcher.158": 4 }, "firmwareVersion": "4264-548923b591c6", "startTime": "2014-09-22 00:00:01.152", "endTime": "2014-09-23 00:00:06.574" }

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JSON GDE Event counters { "counts": { "SignalStrength.Percent.20-40": 18, "SignalStrength.Percent.40-60": 12, "SignalStrength.Percent.60-80": 15, "SignalStrength.Percent.80-100": 1, ... "GPRS.TimeToConnect.Seconds.0-20": 2 }, ... Histogram and timing

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GDE Upload and stream to Big Query

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GDE Diagnostics saved in Big Query

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JSON GDE Event counters { "counts": { "ERROR": 7, "WARNING": 1475, "DEBUG": 362754, "[E].EventsManager.423": 2, "[E].GPSManager.259": 1, "[E].SlaveCommsDispatcher.158": 4 }, "firmwareVersion": "4264-548923b591c6", "startTime": "2014-09-22 00:00:01.152", "endTime": "2014-09-23 00:00:06.574" }

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SQL GDE Create View SELECT JSON_EXTRACT_SCALAR(event_data, '$.firmwareVersion') AS firmware_version, device_id, SUM(INTEGER(JSON_EXTRACT_SCALAR(event_data, '$.counts.ERROR'))) AS errors, SUM(INTEGER(JSON_EXTRACT_SCALAR(event_data, '$.counts.DEBUG'))) AS debugs, 1e6 * SUM(INTEGER(JSON_EXTRACT_SCALAR(event_data,'$.counts.ERROR'))) / SUM(INTEGER(JSON_EXTRACT_SCALAR(event_data, '$.counts.DEBUG'))) AS error_rate FROM [nomanini.event_log] WHERE event = 'Counters' GROUP BY firmware_version, device_id ORDER BY firmware_version DESC, device_id DESC;

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GDE SELECT * FROM [nomanini.firmware_error_rates] LIMIT 10; Query View

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GDE Stats with R

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GDE Good Beta release

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GDE Log transform data to make more ‘Normal’

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GDE Broken Beta release

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R GDE Broken Beta release > t.test(log10(error_rate.beta), log10(error_rate.stable), paired=TRUE) Paired t-test data: log10(error_rate.beta) and log10(error_rate.stable) t = 2.8624, df = 28, p-value = 0.007872 alternative hypothesis: true difference in means is not equal to 0 95 percent confidence interval: 0.1131325 0.6825117 sample estimates: mean of the differences 0.3978221 Geometric mean of the differences (base 10): 2.499321

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R GDE Broken Beta release > wilcox.test(error_rate.beta, error_rate.stable, paired=TRUE, conf.int=TRUE) Wilcoxon signed rank test data: error_rate.beta and error_rate.stable V = 318, p-value = 0.02906 alternative hypothesis: true location shift is not equal to 0 95 percent confidence interval: 7.075123 14546.761849 sample estimates: (pseudo)median 183.0312

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GDE Broken Beta release

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JSON GDE Event counters on broken Beta { "counts": { "ERROR": 1937, "WARNING": 1427, "DEBUG": 26319, "[E].SlaveUpdateManager.442": 1912, "[E].HTTPSManager.319": 3, "[E].DOTAManager.511": 1, ... }, "masterVersion": "3976-aff309f9d073", "startTime": "2014-07-09 09:33:57.923", "endTime": "2014-07-09 15:02:37.032" }

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GDE Fixed Beta release

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GDE The Future

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GDE

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GDE Thank You [email protected] google.com/+DaleHumby @dalehumby http://goo.gl/Cwai02

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Experts Developer cloud.google.com $500 promo code: gde-in