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1
Introduction
2
Meet Harald
3
Agenda
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Relevance
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Dynamic content
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Big ball of mud
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Personalization
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Actor Systems
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Orleans Runtime
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Actor behaviour
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Actor state injection
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Actor proxy
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Network latency
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Actor model
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Catalog
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Favorites
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Positions
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Favorite
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Bloom Filter
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State Storage
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Version State
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Pattern Matching
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Etag Caching
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Reporting
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Operations
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Docker images
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Web API
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Silo hosts
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Preproduction
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Fresh State
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Dashboard
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Grains
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Single grains
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Application Insights
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Lessons Learned
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Idempotency
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deadlock
38
position grains
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logging
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direct clients
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deploy to production
42
storage
Description:
Explore actor modeling for personalization using Orleans in this conference talk. Learn why Orleans, an open-source Virtual Actor platform, was chosen to build a new personalization system for favorites and progress at tv.nrk.no and radio.nrk.no. Dive into the differences of actor modeling, examine key design decisions, and see how it was implemented using F#. Discover the importance of build pipelines and deployment strategies for Orleans applications, including Docker builds, Azure Kubernetes Service deployment, and monitoring with Application Insights. Gain insights into actor behavior, state injection, network latency, catalog management, favorites handling, position tracking, state storage, version control, pattern matching, and Etag caching. Understand the lessons learned about idempotency, deadlock prevention, logging, and deploying to production environments.

Building Personalization with Orleans and Actor Modelling

NDC Conferences
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