Remove 2019 Remove AWS Remove Traffic Remove Tuning
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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

We took a hybrid head-based sampling approach that allows for recording 100% of traces for a specific and configurable set of requests, while continuing to randomly sample traffic per the policy set at ingestion point. Our engineering teams tuned their services for performance after factoring in increased resource utilization due to tracing.

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Delta: A Data Synchronization and Enrichment Platform

The Netflix TechBlog

No need to acquire locks on tables, which is essential to ensure that the write traffic on the database is never blocked by our service. High availability, via standby instances across AWS Availability Zones. We currently support MySQL and Postgres, including when deployed in AWS RDS and its Aurora flavor. Please stay tuned.

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The Speed of Time

Brendan Gregg

Since instances of both CentOS and Ubuntu were running in parallel, I could collect flame graphs at the same time (same time-of-day traffic mix) and compare them side by side. Aftermath I provided details to AWS and Canonical, and then moved onto the other performance issues as part of the migration.

Speed 126
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ML Platform Meetup: Infra for Contextual Bandits and Reinforcement Learning

The Netflix TechBlog

theme of the ML Platform meetup hosted at Netflix, Los Gatos on Sep 12, 2019. For example, a ranking team would ingest live user traffic and subject it to a number of ranking configurations and simulate the event outcomes using predictive models running on canary rankers.

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The Speed of Time

Brendan Gregg

Since instances of both CentOS and Ubuntu were running in parallel, I could collect flame graphs at the same time (same time-of-day traffic mix) and compare them side by side. Aftermath I provided details to AWS and Canonical, and then moved onto the other performance issues as part of the migration.

Speed 40
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ML Platform Meetup: Infra for Contextual Bandits and Reinforcement Learning

The Netflix TechBlog

theme of the ML Platform meetup hosted at Netflix, Los Gatos on Sep 12, 2019. For example, a ranking team would ingest live user traffic and subject it to a number of ranking configurations and simulate the event outcomes using predictive models running on canary rankers.

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DBLog: A Generic Change-Data-Capture Framework

The Netflix TechBlog

Nonetheless, we found a number of limitations that could not satisfy our requirements e.g. stalling the processing of log events until a dump is complete, missing ability to trigger dumps on demand, or implementations that block write traffic by using table locks. Blocking write traffic by locking tables. Writing events to any output.

Database 212