Performance concepts - Scaling

Scalability indicates the ease in with which a system or component can be modified, added, or removed, to accommodate changing load. A system whose performance improves after adding hardware, proportionally to the capacity added, is said to be a scalable system.    

In general there are two ways of increasing the scalability of a system: vertical scaling and horizontal scaling. 

Vertical scaling (also known as scaling up) means adding resources to a single node in a system, typically involving the addition of CPUs or memory to a single computer (“To make the system faster, just add more memory”). The problem with vertical scaling is that there is always a limit to the amount of scalability of a system. There is only so much memory that a system board can support. And the effect of adding more resources to a single system can quickly get very expensive.

An alternative to vertical scaling is horizontal scaling. Horizontal scaling (also known as scaling out) means adding more nodes to a system, such as adding a new web server in a pool of web servers or more disks in a disk array. These days low cost "commodity" systems can be combined to perform tasks that could in the past only be handled by supercomputers.

In general larger numbers of computers means increased management complexity, as well as a more complex programming model and issues such as throughput and latency between nodes. But while horizontal scaling is more complex to implement than vertical scaling, but it pays off in the long term, as the scalability is much higher.


This entry was posted on Tuesday 03 May 2011

Earlier articles

My Book

DevOps for infrastructure

Infrastructure as a Service (IaaS)

(Hyper) Converged Infrastructure

Object storage

Software Defined Networking (SDN) and Network Function Virtualization (NFV)

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What's the point of using Docker containers?

Identity and Access Management

Using user profiles to determine infrastructure load

Public wireless networks

Supercomputer architecture

Desktop virtualization

Stakeholder management

x86 platform architecture

Midrange systems architecture

Mainframe Architecture

Software Defined Data Center - SDDC

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What are concurrent users?

Performance and availability monitoring in levels

UX/UI has no business rules

Technical debt: a time related issue

Solution shaping workshops

Architecture life cycle

Project managers and architects

Using ArchiMate for describing infrastructures

Kruchten’s 4+1 views for solution architecture

The SEI stack of solution architecture frameworks

TOGAF and infrastructure architecture

The Zachman framework

An introduction to architecture frameworks

How to handle a Distributed Denial of Service (DDoS) attack

Architecture Principles

Views and viewpoints explained

Stakeholders and their concerns

Skills of a solution architect architect

Solution architects versus enterprise architects

Definition of IT Architecture

What is Big Data?

How to make your IT "Greener"

What is Cloud computing and IaaS?

Purchasing of IT infrastructure technologies and services

IDS/IPS systems

IP Protocol (IPv4) classes and subnets

Infrastructure Architecture - Course materials

Introduction to Bring Your Own Device (BYOD)

IT Infrastructure Architecture model

Fire prevention in the datacenter

Where to build your datacenter

Availability - Fall-back, hot site, warm site

Reliabilty of infrastructure components

Human factors in availability of systems

Business Continuity Management (BCM) and Disaster Recovery Plan (DRP)

Performance - Design for use

Performance concepts - Load balancing

Performance concepts - Scaling

Performance concept - Caching

Perceived performance

Ethical hacking

The first computers

Open group ITAC /Open CA Certification

Sjaak Laan


Recommended links

Ruth Malan
Gaudi site
Byelex
XR Magazine
Esther Barthel's site on virtualization


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The postings on this site are my opinions and do not necessarily represent CGI’s strategies, views or opinions.

 

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