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The Three Cs: Concatenate, Compress, Cache

CSS Wizardry

Given that 66% of all websites (and 77% of all requests ) are running HTTP/2, I will not discuss concatenation strategies for HTTP/1.1 In one test, I concatenated it all into one big file, and the other had the library split into 12 files. Read the complete test methodology. in this article. If you are still running HTTP/1.1,

Cache 291
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Interpreting A/B test results: false negatives and power

The Netflix TechBlog

Martin Tingley with Wenjing Zheng , Simon Ejdemyr , Stephanie Lane , and Colin McFarland This is the fourth post in a multi-part series on how Netflix uses A/B tests to inform decisions and continuously innovate on our products. Have a look at Part 1 (Decision Making at Netflix), Part 2 (What is an A/B Test?), Need to catch up?

Testing 202
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Migrating Critical Traffic At Scale with No Downtime?—?Part 2

The Netflix TechBlog

Our previous blog post presented replay traffic testing — a crucial instrument in our toolkit that allows us to implement these transformations with precision and reliability. Compared to replay testing, canaries allow us to extend the validation scope beyond the service level.

Traffic 279
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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

For production models, this provides observability of service-level agreement (SLA) performance metrics, such as token consumption, latency, availability, response time, and error count. For model explainability, they can implement custom regression tests, providing indicators of model reputation and behavior over time.

Cache 209
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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Key Takeaways Critical performance indicators such as latency, CPU usage, memory utilization, hit rate, and number of connected clients/slaves/evictions must be monitored to maintain Redis’s high throughput and low latency capabilities. It can achieve impressive performance, handling up to 50 million operations per second.

Metrics 130
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Consistent caching mechanism in Titus Gateway

The Netflix TechBlog

In that scenario, the system would need to deal with the data propagation latency directly, for example, by use of timeouts or client-originated update tracking mechanisms. We started seeing increased response latencies and leader servers running at dangerously high utilization.

Cache 224
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What is a Distributed Storage System

Scalegrid

Data replication strategies like full, incremental, and log-based replication are crucial for improving data availability and fault tolerance in distributed systems, while synchronous and asynchronous methods impact data consistency and system costs. By implementing data replication strategies, distributed storage systems achieve greater.

Storage 130