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How We Optimized Performance To Serve A Global Audience

Smashing Magazine

How We Optimized Performance To Serve A Global Audience How We Optimized Performance To Serve A Global Audience Liran Cohen 2023-08-03T10:00:00+00:00 2023-08-03T13:06:00+00:00 I work for Bookaway , a digital travel brand. Large preview ) We’ve known for a long time that fast page performance influences search engine rankings.

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Towards a Reliable Device Management Platform

The Netflix TechBlog

System Setup Architecture The following diagram summarizes the architecture description: Figure 1: Event-sourcing architecture of the Device Management Platform. By the following morning, alerts were received regarding high memory consumption and GC latencies, to the point where the service was unresponsive to HTTP requests.

Latency 213
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Plan Your Multi Cloud Strategy

Scalegrid

It focuses on aligning organizational needs with cloud services, balancing performance and cost, and ensuring compliance, security, and effective cost management. They can also bolster uptime and limit latency issues or potential downtimes. Pick combinations that are not just affordable but also high-performing.

Strategy 130
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Snap: a microkernel approach to host networking

The Morning Paper

I’m jumping ahead a bit here, but the component of Snap which provides the transport and communications stack is called Pony Express. Here are the bombshell paragraphs: Our datacenter applications seek ever more CPU-efficient and lower-latency communication, which Pony Express delivers. Enter Google! Emphasis mine).

Network 92
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How Park ‘N Fly eliminated silos and improved customer experience with Dynatrace cloud monitoring

Dynatrace

Organizations are rapidly adopting multicloud architectures to achieve the agility needed to drive customer success through new digital service channels. Dynatrace’s cloud monitoring capabilities support this by giving Park ‘N Fly a single source of truth into any performance changes across its technology stack in real-time.

Cloud 156
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RPCValet: NI-driven tail-aware balancing of µs-scale RPCs

The Morning Paper

Last week we learned about the [increased tail-latency sensitivity of microservices based applications with high RPC fan-outs. Seer uses estimates of queue depths to mitigate latency spikes on the order of 10-100ms, in conjunction with a cluster manager. So what we have here is a glimpse of the limits for low-latency RPCs under load.

Latency 80
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Why I hate MPI (from a performance analysis perspective)

John McCalpin

Bandwidth, performance analysis has two recurring themes: How fast should this code (or “simple” variations on this code) run on this hardware? If I am analyzing (apparent) performance shortfalls, how can I distinguish between cause and effect ? The MPI runtime library. in ways that are seldom transparent.