Performance Tuning Go Applications on GCP (Cloud Next '19)

Ғылым және технология

I want to optimize the performance of my cloud components, to save money and above all to improve responsiveness. Nobody enjoys slow software. My strategy is to consider the whole picture, to measure, and to focus on the bottlenecks. I will tell the story of a cool app - written in Go using App Engine and GKE - which has latency problems. Let's explore how to diagnose them with the tooling: benchmarks, pprof, CPU trace, flame graphs, OpenCensus, heatmaps, and StackDriver waterfalls. Once I am able to visualize the latencies, it becomes much easier to incrementally make my app faster.
Building an App with Go → bit.ly/2TYaz6C
Watch more:
Next '19 Application Development Sessions here → bit.ly/Next19AppDev
Next ‘19 All Sessions playlist → bit.ly/Next19AllSessions
Subscribe to the GCP Channel → bit.ly/GCloudPlatform
Speaker(s): Valentin Deleplace
Session ID: DEV309
product: Cloud - General; fullname: Valentin Deleplace; event: Google Cloud Next 2019;

Пікірлер: 4

  • @GexoFlex
    @GexoFlex3 жыл бұрын

    Thank you for this talk - a lot of useful topics covered (not only related to Go, but also to the profiling in general).

  • @googlecloudtech

    @googlecloudtech

    3 жыл бұрын

    Glad it was helpful!

  • @keithlummus8173
    @keithlummus81733 жыл бұрын

    Very good class

  • @valentindeleplace7860
    @valentindeleplace78605 жыл бұрын

    8:07 Stackdriver Logging 9:02 Stackdriver Trace (waterfall) 12:02 Export logs to BigQuery 15:13 Batching 17:53 sync.WaitGroup 26:57 Stackdriver Profiler 30:15 Benchmarks 32:04 Trace 36:05 Pprof 41:11 Flame graph 42:33 Pprof graph vs. Flame graph? 44:31 Concurrency 45:35 Checklist: Unnecessary processing, Network requests, Disk I/O, Contention, Memory allocation, Heap vs Stack, Regexp, Function inlining

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