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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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AI-driven analysis of Spring Micrometer metrics in context, with typology at scale

Dynatrace

Spring Boot 2 uses Micrometer as its default application metrics collector and automatically registers metrics for a wide variety of technologies, like JVM, CPU Usage, Spring MVC, and WebFlux request latencies, cache utilization, data source utilization, Rabbit MQ connection factories, and more. This enables deep explorative analysis.

Metrics 220
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Benchmark (YCSB) numbers for Redis, MongoDB, Couchbase2, Yugabyte and BangDB

High Scalability

We note that for MongoDB update latency is really very low (low is better) compared to other dbs, however the read latency is on the higher side. The latency table shows that 99th percentile latency for Yugabyte is quite high compared to others (lower is better). Again Yugabyte latency is quite high. Conclusion.

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Migrating Critical Traffic At Scale with No Downtime?—?Part 1

The Netflix TechBlog

This blog post will provide a detailed analysis of replay traffic testing, a versatile technique we have applied in the preliminary validation phase for multiple migration initiatives. It provides a good read on the availability and latency ranges under different production conditions.

Traffic 349
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Native App Network Performance Analysis

DZone

Once you're done with the app development and all looks good on the simulators and internal network devices—but out there in the wild, with bandwidth restrictions, TCP congestion, cache hit/miss, the device configuration, your user may not experience what you intend to provide & not every unhappy customer leaves feedback; they just stop coming. (..)

Network 200
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Predictive CPU isolation of containers at Netflix

The Netflix TechBlog

Because microprocessors are so fast, computer architecture design has evolved towards adding various levels of caching between compute units and the main memory, in order to hide the latency of bringing the bits to the brains. This avoids thrashing caches too much for B and evens out the pressure on the L3 caches of the machine.

Cache 260
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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 253