Remove Latency Remove Monitoring Remove Tuning
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RabbitMQ vs. Kafka: Key Differences

Scalegrid

RabbitMQ can be deployed in distributed environments and includes monitoring tools through a built-in dashboard and CLI. Its partitioned log architecture supports both queuing and publish-subscribe models, allowing it to handle large-scale event processing with minimal latency.

Latency 147
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Netflix’s Distributed Counter Abstraction

The Netflix TechBlog

By: Rajiv Shringi , Oleksii Tkachuk , Kartik Sathyanarayanan Introduction In our previous blog post, we introduced Netflix’s TimeSeries Abstraction , a distributed service designed to store and query large volumes of temporal event data with low millisecond latencies. Today, we’re excited to present the Distributed Counter Abstraction.

Latency 247
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Introducing Impressions at Netflix

The Netflix TechBlog

Highlighting NewReleases For new content, impression history helps us monitor initial user interactions and adjust our merchandising efforts accordingly. Automating Performance Tuning with Autoscalers Tuning the performance of our Apache Flink jobs is currently a manual process.

Tuning 165
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Title Launch Observability at Netflix Scale

The Netflix TechBlog

The Challenge of Title Launch Observability As engineers, were wired to track system metrics like error rates, latencies, and CPU utilizationbut what about metrics that matter to a titlessuccess? Option 1: Log Processing Log processing offers a straightforward solution for monitoring and analyzing title launches.

Traffic 168
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Telltale: Netflix Application Monitoring Simplified

The Netflix TechBlog

You’re half awake and wondering, “Is there really a problem or is this just an alert that needs tuning? Over the years we’ve learned from on-call engineers about the pain points of application monitoring: too many alerts, too many dashboards to scroll through, and too much configuration and maintenance. By Andrei U.,

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Best Practices for Scaling RabbitMQ

Scalegrid

Optimizing RabbitMQ performance through strategies such as keeping queues short, enabling lazy queues, and monitoring health checks is essential for maintaining system efficiency and effectively managing high traffic loads. Monitoring the cluster nodes preemptively addresses potential issues, ensuring the system operates smoothly.

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How digital experience monitoring helps deliver business observability

Dynatrace

Digital experience monitoring (DEM) allows an organization to optimize customer experiences by taking into account the context surrounding digital experience metrics. What is digital experience monitoring? Primary digital experience monitoring tools.