Scaling Python with Ray: adventures in cloud and serverless patterns
Serverless computing enables developers to concentrate solely on their applications rather than worry about where they've been deployed. With the Ray general-purpose serverless implementation in Python, programmers and data scientists can hide servers, implement stateful applications, support d...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Beijing ; Boston ; Farnham
O'Reilly
December 2022
|
| Ausgabe: | First edition |
| Schlagworte: | |
| Zusammenfassung: | Serverless computing enables developers to concentrate solely on their applications rather than worry about where they've been deployed. With the Ray general-purpose serverless implementation in Python, programmers and data scientists can hide servers, implement stateful applications, support direct communication between tasks, and access hardware accelerators. In this book, experienced software architecture practitioners Holden Karau and Boris Lublinsky show you how to scale existing Python applications and pipelines, allowing you to stay in the Python ecosystem while reducing single points of failure and manual scheduling. "Scaling Python with Ray" is ideal for software architects and developers eager to explore successful case studies and learn more about decision and measurement effectiveness |
| Beschreibung: | xv, 249 Seiten Illustrationen 24 cm |
| ISBN: | 9781098118808 1098118804 |
Internformat
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| 245 | 1 | 0 | |a Scaling Python with Ray |b adventures in cloud and serverless patterns |c Holden Karau and Boris Lublinsky ; foreword by Robert Nishihara |
| 250 | |a First edition | ||
| 264 | 1 | |a Beijing ; Boston ; Farnham |b O'Reilly |c December 2022 | |
| 264 | 4 | |c © 2023 | |
| 300 | |a xv, 249 Seiten |b Illustrationen |c 24 cm | ||
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| 505 | 8 | |a What is Ray, and where does it fit? -- Getting started with Ray (locally) -- Remote functions -- Remote actors -- Ray design details -- Implementing streaming applications -- Implementing microservices -- Ray workflows -- Advanced data with Ray -- How Ray powers machine learning -- Using GPUs and accelerators with Ray -- Ray in the enterprise | |
| 520 | 3 | |a Serverless computing enables developers to concentrate solely on their applications rather than worry about where they've been deployed. With the Ray general-purpose serverless implementation in Python, programmers and data scientists can hide servers, implement stateful applications, support direct communication between tasks, and access hardware accelerators. In this book, experienced software architecture practitioners Holden Karau and Boris Lublinsky show you how to scale existing Python applications and pipelines, allowing you to stay in the Python ecosystem while reducing single points of failure and manual scheduling. "Scaling Python with Ray" is ideal for software architects and developers eager to explore successful case studies and learn more about decision and measurement effectiveness | |
| 653 | 0 | |a Python (Computer program language) | |
| 653 | 0 | |a Cloud computing | |
| 700 | 1 | |a Lublinsky, Boris |e Verfasser |0 (DE-588)1044806699 |4 aut | |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-034132564 | ||
Datensatz im Suchindex
| _version_ | 1804185001700360192 |
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| author | Karau, Holden Lublinsky, Boris |
| author_GND | (DE-588)1053591268 (DE-588)1044806699 |
| author_facet | Karau, Holden Lublinsky, Boris |
| author_role | aut aut |
| author_sort | Karau, Holden |
| author_variant | h k hk b l bl |
| building | Verbundindex |
| bvnumber | BV048867600 |
| contents | What is Ray, and where does it fit? -- Getting started with Ray (locally) -- Remote functions -- Remote actors -- Ray design details -- Implementing streaming applications -- Implementing microservices -- Ray workflows -- Advanced data with Ray -- How Ray powers machine learning -- Using GPUs and accelerators with Ray -- Ray in the enterprise |
| ctrlnum | (OCoLC)1376404318 (DE-599)BVBBV048867600 |
| edition | First edition |
| format | Book |
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| physical | xv, 249 Seiten Illustrationen 24 cm |
| publishDate | 2022 |
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| spelling | Karau, Holden Verfasser (DE-588)1053591268 aut Scaling Python with Ray adventures in cloud and serverless patterns Holden Karau and Boris Lublinsky ; foreword by Robert Nishihara First edition Beijing ; Boston ; Farnham O'Reilly December 2022 © 2023 xv, 249 Seiten Illustrationen 24 cm txt rdacontent n rdamedia nc rdacarrier What is Ray, and where does it fit? -- Getting started with Ray (locally) -- Remote functions -- Remote actors -- Ray design details -- Implementing streaming applications -- Implementing microservices -- Ray workflows -- Advanced data with Ray -- How Ray powers machine learning -- Using GPUs and accelerators with Ray -- Ray in the enterprise Serverless computing enables developers to concentrate solely on their applications rather than worry about where they've been deployed. With the Ray general-purpose serverless implementation in Python, programmers and data scientists can hide servers, implement stateful applications, support direct communication between tasks, and access hardware accelerators. In this book, experienced software architecture practitioners Holden Karau and Boris Lublinsky show you how to scale existing Python applications and pipelines, allowing you to stay in the Python ecosystem while reducing single points of failure and manual scheduling. "Scaling Python with Ray" is ideal for software architects and developers eager to explore successful case studies and learn more about decision and measurement effectiveness Python (Computer program language) Cloud computing Lublinsky, Boris Verfasser (DE-588)1044806699 aut |
| spellingShingle | Karau, Holden Lublinsky, Boris Scaling Python with Ray adventures in cloud and serverless patterns What is Ray, and where does it fit? -- Getting started with Ray (locally) -- Remote functions -- Remote actors -- Ray design details -- Implementing streaming applications -- Implementing microservices -- Ray workflows -- Advanced data with Ray -- How Ray powers machine learning -- Using GPUs and accelerators with Ray -- Ray in the enterprise |
| title | Scaling Python with Ray adventures in cloud and serverless patterns |
| title_auth | Scaling Python with Ray adventures in cloud and serverless patterns |
| title_exact_search | Scaling Python with Ray adventures in cloud and serverless patterns |
| title_exact_search_txtP | Scaling Python with Ray adventures in cloud and serverless patterns |
| title_full | Scaling Python with Ray adventures in cloud and serverless patterns Holden Karau and Boris Lublinsky ; foreword by Robert Nishihara |
| title_fullStr | Scaling Python with Ray adventures in cloud and serverless patterns Holden Karau and Boris Lublinsky ; foreword by Robert Nishihara |
| title_full_unstemmed | Scaling Python with Ray adventures in cloud and serverless patterns Holden Karau and Boris Lublinsky ; foreword by Robert Nishihara |
| title_short | Scaling Python with Ray |
| title_sort | scaling python with ray adventures in cloud and serverless patterns |
| title_sub | adventures in cloud and serverless patterns |
| work_keys_str_mv | AT karauholden scalingpythonwithrayadventuresincloudandserverlesspatterns AT lublinskyboris scalingpythonwithrayadventuresincloudandserverlesspatterns |