KeyCDN

SEPTEMBER 20, 2018

Let’s take a look at some of the best error monitoring tools and strategies for 2018. Not all back-end errors affect the user experience, but keeping track of them can prove helpful when tuning your app. It also keeps track of JavaScript errors, browser metadata, console logs, stack traces, network requests and much more.

Strategy 67

Strategy Monitoring Website Google 67

Dynatrace

OCTOBER 24, 2019

Sometimes, you need to check the availability of internal resources that aren’t accessible from outside your network. A private Synthetic location is a location in your private network infrastructure where you install a Synthetic-enabled ActiveGate. Of course, you can still configure private locations per environment.

Hardware 20

Hardware Tuning Monitoring Network 20

Abhishek Tiwari

JULY 12, 2018

A data pipeline is a software which runs on hardware. The software is error-prone and hardware failures are inevitable. If tuned for performance, there is a good change reliability is compromised - and vice versa. A data pipeline can process data in a different order than they were received.

Latency 63

Latency Analytics Scalability Engineering 63

SQL Server According to Bob

JANUARY 11, 2020

Example 1: ​​ Hardware failure (CPU board) Battery backup on the caching controller maintained the data. Important Always consult with your hardware manufacturer for proper stable media strategies. For specific information on I/O tuning and balancing, you will find more details in the following document.

Servers 40

Servers Cache Media Hardware 40

High Scalability

NOVEMBER 25, 2019

To add elasticity, reliability and durability, these data centers are connected to Google Cloud platform using high speed, secure Google Interconnect network. What is your storage strategy? What is your object and content caching strategy? Document store. Video Transcoding. Architecture should be malleable.

Architecture 52

Architecture Cache Azure Storage 52

O'Reilly

NOVEMBER 28, 2023

Even with cloud-based foundation models like GPT-4, which eliminate the need to develop your own model or provide your own infrastructure, fine-tuning a model for any particular use case is still a major undertaking. That pricing won’t be sustainable, particularly as hardware shortages drive up the cost of building infrastructure.

Open Source 108

Open Source Artificial Intelligence Google Infrastructure 108

O'Reilly

SEPTEMBER 19, 2023

Doubly so as hardware improved, eating away at the lower end of Hadoop-worthy work. And that brings our story to the present day: Stage 3: Neural networks High-end video games required high-end video cards. Google goes a step further in offering compute instances with its specialized TPU hardware.

Hardware 99

Hardware Storage Big Data Blockchain 99

SQL Server According to Bob

JANUARY 11, 2020

url=/library/en-us/fileio/fs/sparse_files.asp ) ​​ on the ​​ Microsoft Developer Network ​​ (MSDN). Restore backups on secondary systems ​​ frequently ​​ to make sure that your complete backup strategy is functioning correctly.

Servers 40

Servers Cache Database Media 40

O'Reilly

OCTOBER 11, 2022

As a trend, it’s not performing well on Google; it shows little long-term growth, if any, and gets nowhere near as many searches as terms like “Observability” and “Generative Adversarial Networks.” Our current set of AI algorithms are good enough, as is our hardware; the hard problems are all about data. Is retraining needed?

Games 116

Games Healthcare Processing Retail 116