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UID:pretalx-pyconde-pydata-berlin-2023-SSTCTS@pretalx.com
DTSTART;TZID=CET:20230418T114000
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DESCRIPTION:Debugging is hard. Distributed debugging is hell.\n\nDask is a 
 popular library for parallel and distributed computing in Python. Dask is 
 commonly used in data science\, actual science\, data engineering\, and ma
 chine learning to distribute workloads onto clusters of many hundreds of w
 orkers with ease.\n\nHowever\, when things go wrong life can become diffic
 ult due to all of the moving parts. These parts include your code\, other 
 PyData libraries like NumPy/pandas\, the machines you’re running on\, th
 e network between them\, storage\, the cloud\, and of course issues with D
 ask itself. It can be difficult to understand what is going on\, especiall
 y when things seem slower than they should be or fail unexpectedly. Observ
 ability is the key to sanity and success.\n\nIn this talk\, we describe th
 e tools Dask offers to help you observe your distributed cluster\, analyze
  performance\, and monitor your cluster to react to unexpected changes qui
 ckly. We will dive into distributed logging\, automated metrics\, event-ba
 sed monitoring\, and root-causing problems with diagnostic tooling. Throug
 hout the talk\, we will leverage real-world use cases to show how these to
 ols help to identify and solve problems for large-scale users in the wild.
 \n  \nThis talk should be particularly insightful for Dask users\, but the
  approaches to observing distributed systems should be relevant to anyone 
 operating at scale in production.
DTSTAMP:20260611T063707Z
LOCATION:B09
SUMMARY:Observability for Distributed Computing with Dask - Hendrik Makait
URL:https://pretalx.com/pyconde-pydata-berlin-2023/talk/SSTCTS/
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