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Foundation Model for Personalized Recommendation

The Netflix TechBlog

Furthermore, it was difficult to transfer innovations from one model to another, given that most are independently trained despite using common data sources. Yet, many are confined to a brief temporal window due to constraints in serving latency or training costs.

Tuning 165
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Dynatrace supports SnapStart for Lambda as an AWS launch partner

Dynatrace

The new Amazon capability enables customers to improve the startup latency of their functions from several seconds to as low as sub-second (up to 10 times faster) at P99 (the 99th latency percentile). This can cause latency outliers and may lead to a poor end-user experience for latency-sensitive applications.

Lambda 246
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Introducing Netflix’s Key-Value Data Abstraction Layer

The Netflix TechBlog

These include challenges with tail latency and idempotency, managing “wide” partitions with many rows, handling single large “fat” columns, and slow response pagination. It also serves as central configuration of access patterns such as consistency or latency targets.

Latency 260
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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

The RAG process begins by summarizing and converting user prompts into queries that are sent to a search platform that uses semantic similarities to find relevant data in vector databases, semantic caches, or other online data sources.

Cache 276
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Netflix Cloud Packaging in the Terabyte Era

The Netflix TechBlog

By Xiaomei Liu , Rosanna Lee , Cyril Concolato Introduction Behind the scenes of the beloved Netflix streaming service and content, there are many technology innovations in media processing. Uploading and downloading data always come with a penalty, namely latency. Packaging has always been an important step in media processing.

Cloud 242
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Introducing Netflix TimeSeries Data Abstraction Layer

The Netflix TechBlog

Rajiv Shringi Vinay Chella Kaidan Fullerton Oleksii Tkachuk Joey Lynch Introduction As Netflix continues to expand and diversify into various sectors like Video on Demand and Gaming , the ability to ingest and store vast amounts of temporal data — often reaching petabytes — with millisecond access latency has become increasingly vital.

Latency 239
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MezzFS?—?Mounting object storage in Netflix’s media processing platform

The Netflix TechBlog

We are constantly innovating on video encoding technology at Netflix, and we have a lot of content to encode. Disk Caching? — ? MezzFS can be configured to cache objects on the local disk. Regional caching? —?Netflix we only pay the transfer costs for one worker, and the rest use the cached object. Replays? —?More

Media 218