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How To Implement Video Information and Editing APIs in Java

DZone

In the past 15+ years, online video traffic has experienced a dramatic boom utterly unmatched by any other form of content. It must be said that this video traffic phenomenon primarily owes itself to modernizations in the scalability of streaming infrastructure, which simply weren’t present fifteen years ago.

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Title Launch Observability at Netflix Scale

The Netflix TechBlog

Accurately Reflecting Production Behavior A key part of our solution is insights into production behavior, which necessitates our requests to the endpoint result in traffic to the real service functions that mimics the same pathways the traffic would take if it came from the usualcallers. We call this capability TimeTravel.

Traffic 180
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Optimizing Java XPath CPU and memory overhead by 98%

Dynatrace

Therefore, it was unsurprising to see a huge spike in traffic for Family Visa enrollment via Metrash. Let’s start with the spike in load: The high demand on family visa enrollments resulted in a huge traffic and CPU spike. The post Optimizing Java XPath CPU and memory overhead by 98% appeared first on Dynatrace blog.

Java 246
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RabbitMQ vs. Kafka: Key Differences

Scalegrid

This decoupling simplifies system architecture and supports scalability in distributed environments. Kafka stores and distributes data through a partitioned log system, which spans multiple brokers to provide fault tolerance and scalability. However, performance can decline under high traffic conditions. What is RabbitMQ?

Latency 147
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Kubernetes OOMKilled troubleshooting: Diagnosing out-of-memory issues automatically

Dynatrace

Each tenant gets its own e-commerce site deployed on a shared Kubernetes cluster, isolated through separate namespaces and additional traffic isolation. There was not much traffic during the weekend, but as Monday came along, Dynatrace started sending alerts about a high HTTP failure rate across almost every tenant on the backend service.

Java 246
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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

Our tactical approach was to use Netflix-specific libraries for collecting traces from Java-based streaming services until open source tracer libraries matured. We chose Open-Zipkin because it had better integrations with our Spring Boot based Java runtime environment. Storage: don’t break the bank!

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Orchestrating Data/ML Workflows at Scale With Netflix Maestro

The Netflix TechBlog

As Big data and ML became more prevalent and impactful, the scalability, reliability, and usability of the orchestrating ecosystem have increasingly become more important for our data scientists and the company. Motivation Scalability and usability are essential to enable large-scale workflows and support a wide range of use cases.

Java 211