Remove Latency Remove Presentation Remove Speed
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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? RTT isn’t a you-thing, it’s a them-thing.

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The Three Cs: Concatenate, Compress, Cache

CSS Wizardry

Plotted on the same horizontal axis of 1.6s, the waterfalls speak for themselves: 201ms of cumulative latency; 109ms of cumulative download. 4,362ms of cumulative latency; 240ms of cumulative download. When we talk about downloading files, we—generally speaking—have two things to consider: latency and bandwidth. It gets worse.

Cache 338
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Bandwidth or Latency: When to Optimise for Which

CSS Wizardry

When it comes to network performance, there are two main limiting factors that will slow you down: bandwidth and latency. Latency is defined as…. Where bandwidth deals with capacity, latency is more about speed of transfer 2. and reduction in latency. and reduction in latency. Bandwidth is defined as….

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Time to First Byte: What It Is and Why It Matters

CSS Wizardry

The first—and often most surprising for people to learn—thing that I want to draw your attention to is that TTFB counts one whole round trip of latency. The reason is because mobile networks are, as a rule, high latency connections. Last mile latency deals with the disproportionate complexity toward the terminus of a connection.

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Edgar: Solving Mysteries Faster with Observability

The Netflix TechBlog

Edgar helps Netflix teams troubleshoot distributed systems efficiently with the help of a summarized presentation of request tracing, logs, analysis, and metadata. Telltale provides Edgar with latency benchmarks that indicate if the individual trace’s latency is abnormal for this given service. What is Edgar?

Latency 299
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Consistent caching mechanism in Titus Gateway

The Netflix TechBlog

In the time since it was first presented as an advanced Mesos framework, Titus has transparently evolved from being built on top of Mesos to Kubernetes, handling an ever-increasing volume of containers. This blog post presents how our current iteration of Titus deals with high API call volumes by scaling out horizontally.

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Why applying chaos engineering to data-intensive applications matters

Dynatrace

Stream processing systems, designed for continuous, low-latency processing, demand swift recovery mechanisms to tolerate and mitigate failures effectively. This significantly increases event latency. Spark Structured Streaming can also provide consistent fault recovery for applications where latency is not a critical requirement.