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Why applying chaos engineering to data-intensive applications matters

Dynatrace

Stream processing One approach to such a challenging scenario is stream processing, a computing paradigm and software architectural style for data-intensive software systems that emerged to cope with requirements for near real-time processing of massive amounts of data. This significantly increases event latency.

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

The Netflix TechBlog

Migrating Critical Traffic At Scale with No Downtime — Part 1 Shyam Gala , Javier Fernandez-Ivern , Anup Rokkam Pratap , Devang Shah Hundreds of millions of customers tune into Netflix every day, expecting an uninterrupted and immersive streaming experience.

Traffic 339
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An approach to index tuning – Part 2

SQL Performance

In my last post , I started to outline the process I go through when tuning queries – specifically when I discover that I need to add a new index, or modify an existing one. Once we have that data, we can move on to the next steps in the process. Once we have that data, we can move on to the next steps in the process.

Tuning 137
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MySQL Performance Tuning 101: Key Tips to Improve MySQL Database Performance

Percona

While there is no magic bullet for MySQL performance tuning, there are a few areas that can be focused on upfront that can dramatically improve the performance of your MySQL installation. What are the Benefits of MySQL Performance Tuning? A finely tuned database processes queries more efficiently, leading to swifter results.

Tuning 52
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An analysis of performance evolution of Linux’s core operations

The Morning Paper

An analysis of performance evolution of Linux’s core operations Ren et al., Perhaps the most interesting lesson/reminder is this: it takes a lot of effort to tune a Linux kernel. Google’s data center kernel is carefully performance tuned for their workloads. SOSP’19. to protect against Meltdown and Spectre ) ). (4)

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Dynatrace simplifies StatsD, Telegraf, and Prometheus observability with Davis AI

Dynatrace

Stay tuned for an upcoming blog series where we’ll give you a more hands-on walkthrough of how to ingest any kind of data from StatsD, Telegraf, Prometheus, scripting languages, or our integrated REST API. So you get auto-adaptive baselining for custom metrics and Davis automated root cause analysis from Day 1.

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

Dynatrace

This challenge has given rise to the discipline of observability engineering, which concentrates on the details of telemetry data to fine-tune observability use cases. This covers the infrastructure, processes, and the application stack, including tracing, profiling, and logs. Labels we don’t need. Jolly good!

Metrics 172