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Consistent caching mechanism in Titus Gateway

The Netflix TechBlog

We introduce a caching mechanism in the API gateway layer, allowing us to offload processing from singleton leader elected controllers without giving up strict data consistency and guarantees clients observe. After the jobs are created, it monitors their execution progress. The cache is kept in sync with the current leader process.

Cache 224
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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

You will need to know which monitoring metrics for Redis to watch and a tool to monitor these critical server metrics to ensure its health. This blog post lists the important database metrics to monitor. Effective monitoring of key performance indicators plays a crucial role in maintaining this optimal speed of operation.

Metrics 130
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Redis® Monitoring Strategies for 2024

Scalegrid

In today’s data-driven world, the ability to effectively monitor and manage data is of paramount importance. With its widespread use in modern application architectures, understanding the ins and outs of Redis® monitoring is essential for any tech professional. Redis®, a powerful in-memory data store, is no exception.

Strategy 130
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Seeing through hardware counters: a journey to threefold performance increase

The Netflix TechBlog

A quick canary test was free of errors and showed lower latency, which is expected given that our standard canary setup routes an equal amount of traffic to both the baseline running on 4xl and the canary on 12xl. What’s worse, average latency degraded by more than 50%, with both CPU and latency patterns becoming more “choppy.”

Hardware 363
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Observability vs. monitoring: What’s the difference?

Dynatrace

This trend is prompting advances in both observability and monitoring. But exactly what are the differences between observability vs. monitoring? Monitoring and observability provide a two-pronged approach. To get a better understanding of observability vs monitoring, we’ll explore the differences between the two.

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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. Observing AI models Running AI models at scale can be resource-intensive.

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Best practices and key metrics for improving mobile app performance

Dynatrace

As a result, organizations need to monitor mobile app performance metrics that are meaningful and actionable by gaining adequate observability of mobile app performance. Closely monitoring mobile app performance will help ensure customer interactions via mobile apps are meeting the expectations of the customers. Proactive monitoring.