LocalData

Clustering adds fault tolerance scale out does not necessarily add ft

I think that most scale out systems are "clustered" in one sense of the word. The distinction lies in scale out's ability to expand capacity in a balanced way without introducing bottlenecks.

cluster = quorum and more active/passive. Scale out provides all nodes to perform a function.

clustering often refers to a dual node system, though not always, in a sense, most traditional scale up storage architecture are actually 2 clustered controllers

Clustering is way to achieve scale-out.

begs the question "how do clusters scale out" :-)

historically clustering was about resiliency and removing single points of failure. Let's go back to Novell Cluster Services for instance. Scale-out is focused at very different thigns.

clustering usually means tightly coupled. all the resources are pooled together. scale-out many times just means dividing up the work

@csharney Clustering doesn't necessarily add fault tolerance. It's a big place.

Clustering may not add performance or capacity

some companies have sought to merge those though - aka NetApp with scaling out dual controller clusters for their Data Fabric. I'd argue that's not scale-out per se.

I don't view clustering as a way to increase horsepower just resiliency. Scale out is all about adding linear available resources.

@johna_white true that clusters require quorum, but most scale out systems do as well

It seems like some of us are using the word "clustering" to mean "High Availability Pairs." That's pretty old school, isn't it?

@johna_white definitely agree. clustering helps survive, not increase capacity

Clustering is a tech that can potentially be used for scaling out but it depends on the architecture. For example a master/slave architecture cannot scale out in the same way as a shared-nothing architecture.

@dinisco sure, a new age quorum typically exists across all nodes now... not just one place.

Clustering focus = keep my services online. Scale-out = grow forever.

Often, clustering can be used for scale-out, but also clustering might restrict scale-out to achieve redundancy. So, the terms are somewhat orthogonal.

@fdmts I think of a cluster as a logical collection of resources performing the same task...versus a set of discreet resources allocated to different things

@fdmts I'll agree that's how I think of it. In some cases cluster capabilities could be a subset of scale-out capabilities.

Didn't Isilon invent "scale out" ? :-)

pretty sure that was Al Gore

remember the vax cluster in the early 80's...that's old school

Yup. And they spent a decade explaining what the hell it meant too.

I know I always said scale-out to describe Isilon when at an EMC partner. People seemed to get it and loved the theory.

One example is Oracle RAC. High-availability without much scale.

@dvellante DecNet was a great net protocol stack killed SNA but then TCP took over #OpenWins

Isilon scales but also hits the wall at 144 nodes, so not limitless.

@andriven and @fdmts, agree with both, think one fundamental difference between cluster and scale out is that clusters can have passive resources, scale out generally has all active resources

@dvellante VMS (DEC's) OS is what microsoft copied with Windows NT (WNT) one letter after VMS

Spinnaker :-)

@andriven Something about terms like Kleenex and Post-it.

@dinisco Good distinction - in scale-out often all resources can be used and during failure scenarios the total resources available diminishes rather than inherent performance decrease.

love that story...Dave Cutler

the ability to scale performance linearly, and predict costs in the same manner

Non-disruptive addition of additional nodes through the same management interface and the ability for the same data to grow without moving it to the new hardware

It usually describes a system where you add resources (I/O, CPU, Storage capacity) in a balanced way, which helps to stave off bottlenecks.

linear scalability of performance as add more resources without performance, administrative, or capacity bottlenecks

Opposite of scale-up. It means linear horizontal growth in performance, capacity without logical limits.

we used to scale-up (grow until you reached max allowed configuration), the challenge of our day is distributed architectures, which leverage scale-out deployments. smaller components that are highly scalable.

the ability to increase capacity and performance by adding resources horizontally in the form of nodes

I think of it as the same term as horizontal scaling in the web world...adding units of scale seamlessly as the workload increases

in some ways it's more easily defined to people in "negative terms". That is, are you used to a dual controller system? Are you used to having to purchase more CPU/RAM capacity in a storage array upfront so can add disk later?

scale out = anything that can incrementally grow and in turn shrink. Things like infrastructure, apps, and my waist line are all things that can scale out

The term applies in multiple areas - hadoop clusters, general storage applications, hyperconverged (Nutanix, etc.), even backup and recovery more recently.

@andriven agree, when explaining it, it almost always starts with an explanation of a head and sled architecture and then a comparison

@fdmts That said, there is no such thing as a system without limits. When we say "no limits," it just means we don't know them yet.

These days, scale-out also implies the ability to add capacity and performance non-disruptively.

Also applies to cloud resources in that most cloud providers have written code to make all their internal resources scale-out. Customers don't see that but assume it's the case.

It means never having to do a forklift upgrade ever again!

cloud is horizontally scalable therefore #devops software scaling out means APIs drive all the action in cloud

when talking "cloud" and diving in to the elasticity and flexibility characteristics, often there's some scale-out technologies under the covers to enable that

also #TruePrivateCloud for on prem is key to software models that operationally work across enterprises and clouds

Purchase only what you need at this time and grow with your data / performance needs

Anymore it seems like if we are talking scale out as opposed to up due to a change in application demand. Micro-services do not require big fat servers anymore

Good news is that we all seem consistent with the industry terms. Scale-out is horizontal scaling. Scale-up is vertical scaling.

applications that require data might want scale out and scale up operations

@dinisco +100 on cost - customers need predicable budget as grow. Scale-out technically isn't always paired with a similarly linear pricing model.

@patrickrogersca isn't that assuming that you stick with a solution forever? Migration and API compatibility as they relate to scale-out environments.

Scale-out = removing technical barriers to growing your environment. Spend more money faster. ;)

Cloud is not really horizontally scalable. It lacks a global namespace without logical limits.

@steve_pao great point on scale up for apps bc data is application centric but horizontal scale is how data moves

@johna_white the "shrinking" part is very interesting - it's often assumed but not always the case. Sometimes it's technically possible but not sufficiently tested/QA-ed for real world use.

@steve_pao great point on scale up for apps bc data is application centric but horizontal scale is how data moves