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14 matches found for 'operating system'

OS 101

Kernel A kernel is the core software application of the operating system. It is generally not intended to be interacted with from a user-level perspective. Some responsibilities it can handle: Hardware management e.

Virtual Memory

... remove it completely would be quite extreme, and the user probably wouldn't want that. Instead, operating systems will put the memory contents of idle applications into the swap file, so that it could free up that space in physical memory.

Seattle Conference on Scalability: YouTube Scalability

... with Apache at first. Lasted about 3 months. High load, high context switching (whenever the operating system stops a thread from running in the CPU and puts another thread to run in its place).

AWS Lambda and other Maven projects

... and focus on the application logic instead of worrying about fine details of servers such as the operating system, the hardware specs, and lifecycle of servers (i.e. what to do when one crashes or shuts down?) Implementation Implementation of AWS Lambda can be done in many ways; as of this writing, one can write a AWS Lambda application with Python, Node.

2PC - Two Phase Commit and Why it Sucks

Background Two Phase Commit (abbreviated 2PC) is a protocol used to achieve atomic writes in distributed systems. It was a novel concept in the 1970's and had good intentions, but in practice the implementations are not too great.

Distributed scaling with Relational Databases

Background A lot of articles will talk about how to scale databases. Typically, they will talk about the purpose and the general idea of sharding and replication, but often times these topics are explained separately and not so much in conjunction.

Web Development 101

HTTP vs. HTTPS HTTP stands for Hypertext Transfer Protocol. It typically runs on TCP port 80. It is a protocol for sending data through browsers in the form of webpages and such. One major flaw with HTTP is that it is vulnerable to man in the middle attacks.

Algorithm Handbook

Introduction Welcome to the algorithm handbook wiki! In this wiki you will find a mini-cheat sheet overview of data structures, and examples of their usages in modern languages. Algorithm problems can be found here.

Data stores in Software Architectures

Use Cases There are many ways to store your data. In this article we'll walk through some examples of data storage in common system designs. Reminder: There is no single best storage choice and they may vary heavily depending on things such as access patterns and scale.

Local Secondary Index vs. Global Secondary Index

Secondary Index A secondary index is used in databases to help speed up queries when we want to grab data from popular columns or if we want to do some type of key range lookup efficiently. Secondary indices are used in relational databases (e.

What is DDD? What is CQRS?

Domain Driven Design DDD is an approach to developing software systems that is large and complex, and has ever-changing business rules. DDD captures the sweet spot between the business knowledge and the code.

Big Data Processing: Batching vs. Streaming

Intro In data processing, we often have to work with large amounts of data. The way in which this data is gathered comes in a few variants: batching, where we aggregate a collection of data (e.g., by hourly time), streaming for data that needs to be processed in real-time, and a unified variant which simply does not distinguish the technical difference between batching and streaming, allowing you to programmatically use the same API for both.

Ether and Ethereum is not the same thing

Ether vs. Ethereum Ethereum is... A network built on blockchain technology It's focus is to have decentralized apps (DAPPS) Based on Smart Contracts: A self-executing contract where given an input, a certain is output is guaranteed.

NoSQL - the Radical Databases

NoSQL NoSQL is a category of databases that aren't relational. For example, MySQL would be a relational database, where as MongoDB would be a NoSQL database. Back then, relational databases were the tried-and-true, prevalent and reliable data stores.