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Distributed Computing with Python

You're reading from  Distributed Computing with Python

Product type Book
Published in Apr 2016
Publisher
ISBN-13 9781785889691
Pages 170 pages
Edition 1st Edition
Languages
Toc

Table of Contents (15) Chapters close

Distributed Computing with Python
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
1. An Introduction to Parallel and Distributed Computing 2. Asynchronous Programming 3. Parallelism in Python 4. Distributed Applications – with Celery 5. Python in the Cloud 6. Python on an HPC Cluster 7. Testing and Debugging Distributed Applications 8. The Road Ahead Index

Debugging and monitoring


Logging, monitoring, profiling, and debugging distributed systems, as discussed in Chapter 7, Testing and Debugging Distributed Applications, even today is not an easy task, especially when using languages other than C, C++, and Fortran. There is not much more to say here other than the fact that there is an important vacuum to be filled.

Most medium-to-large teams end up developing their own custom solutions based on log aggregators such as Sentry (https://getsentry.com) and monitoring solutions such as Ganglia (http://ganglia.sourceforge.net).

What would be nice to have are the equivalent of I/O monitoring tools such as Darshan (http://www.mcs.anl.gov/research/projects/darshan/) and distributed profilers such as Allinea MAP (http://www.allinea.com/products/map) for Python distributed applications.

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