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10 things I love about SpeedCurve (that I think you'll love, too)

Speed Curve

In the spirit of celebration, I thought it would be fun to round up my ten favourite things to do in SpeedCurve (that I think you'll like, too). You can also drill down and focus on things like construction. READ : How to enable weekly reports ––––– 10. what are they doing differently?

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A Faster Blog, Faster

Alex Russell

Each of these additional steps creates several hundred more files, and the fact that everything continues to take less than 10 seconds given my newbie 11ty and nunjucks skills has been great. 10 seconds feels great for a full build, but it's not ideal in a ctrl-r development loop. Writing build/feed/feed.xml from.

Cache 49
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Speed up your security investigations with DPL Architect

Dynatrace

The best thing: the whole process is performed on read when the query is executed, which means you have full flexibility and don’t need to define a structure when ingesting data. >> 200 3395 40.30.20.109 - - [28/Aug/2023:10:22:04 -0300] "GET / HTTP/1.1" The string 40.30.20.1 ip=40.30.20.1 ip=40.30.20.1

Speed 207
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40+ Best Web Development Blogs of 2018

KeyCDN

Reading and following the right web development blogs makes it much easier to get a solid education. That’s why in this post, we’ve compiled a list of the top web development blogs that will help you find your footing and acquire essential skills in modern web dev. Visit website 3. Visit website 5.

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The Return of the Frame Pointers

Brendan Gregg

2015-2020: Overhead As part of production rollout I did many performance overhead tests, which I've described publicly before: The overhead of adding frame pointers to everything (libc and Java) was usually less than 1%, with one exception of 10%. Someone recently told me that Python can hit 10% overhead with frame pointers.

Java 145
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Kubernetes And Kernel Panics

The Netflix TechBlog

This blog post shows how to connect the dots from the worst case scenario (a kernel panic) through to Kubernetes (k8s) and eventually up to us operators so that we can track how and why our k8s nodes are going away. Imagine the whole thing operating like a dmesg | netcat -u $destination 6666, but in kernel space. Why did they go away?

Hardware 228
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Observability engineering: Getting Prometheus metrics right for Kubernetes with Dynatrace and Kepler

Dynatrace

The Collector’s primary focus is to receive telemetry data from different sources and in a variety of formats, provide the ability to manipulate and transform that data, and eventually forward things as OTLP to the desired upstream service (for example, the Dynatrace backend). One of them is dropping unsupported metric types.

Metrics 178