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Optimising for High Latency Environments

CSS Wizardry

This gives fascinating insights into the network topography of our visitors, and how much we might be impacted by high latency regions. Round-trip-time (RTT) is basically a measure of latency—how long did it take to get from one endpoint to another and back again? What is RTT? Where Does CrUX’s RTT Data Come From?

Latency 215
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Dynatrace Managed turnkey Premium High Availability for globally distributed data centers (Early Adopter)

Dynatrace

Dynatrace Managed is intrinsically highly available as it stores three copies of all events, user sessions, and metrics across its cluster nodes. The network latency between cluster nodes should be around 10 ms or less. Turnkey high availability across globally distributed data centers. Dynatrace news.

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Investigation of a Workbench UI Latency Issue

The Netflix TechBlog

Using this approach, we observed latencies ranging from 1 to 10 seconds, averaging 7.4 To efficiently utilize our compute resources, Titus employs a CPU oversubscription feature , meaning the combined virtual CPUs allocated to containers exceed the number of available physical CPUs on a Titus agent. We then exported the .har

Latency 217
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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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MySQL on Azure Performance Benchmark – ScaleGrid vs. Azure Database

Scalegrid

While Microsoft offers their own Azure Database product, there are other alternatives available that may be able to help you improve your MySQL performance. In this blog post, we compare Azure Database for MySQL vs. ScaleGrid MySQL on Azure so you can see which provider offers the best throughput and latency performance.

Azure 299
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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
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Seeing through hardware counters: a journey to threefold performance increase

The Netflix TechBlog

At Netflix, we periodically reevaluate our workloads to optimize utilization of available capacity. 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. let’s call it GS2?—?to

Hardware 363