cloud economics for java at java2days

All Change!

https://www.flickr.com/photos/teegardin/

why the economics of Cloud will make you think differently about Java

Steve Poole – IBM Making Java Real Since Version 0.9

DevOps Practitioner (whatever that means!)

@spoole167

This talk is about how this sort of measurement:

GB/hrIs already changing your life & the direction of the Java ecosystem

The ‘Cloud’ has a lot to answer for

Outline• Part 1 – The economics of Cloud provisioning• Part 2 - How Java measures up• Part 3 – The API economy and Java• Part 4 – wrap up

Part 1 – The economics of Cloud provisioning

Why ‘Cloud’ ?Your business wants needs to get ideas into production faster, cheaper and with less risk

A big challenge is its traditional infrastructure

A local, hand-crafted, static environment which requires in-house specialist

support, doesn’t scale well and requires long term investment and commitment

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What ‘Cloud’ promises

a virtual, dynamic environment which maximizes use, is infinitely scalable, always available and needs minimal upfront investment or commitment

Take your code – host it on someone else's machine and pay only for the

resource you use for the time you use it

AND be able to do that very quickly and repeatedly in parallel

How quickly do you need to get good code into production?

• Would you believe < 1hr?

• Case Study: A fashion retailer can show measureable increase in sales if a item similar to that seen in the media can be placed on their on-line store landing page within 1 hr of it appearing in public.

• Each product placement is different so they need a fast, agile, approach that does not jeopardize their on-line stores availability and quality.

• We know how to do this..

Cloud computing is real. Major vendors are providing substantial capacity and it’s growing all the time

Businesses see the opportunities

Improved value for money, decreased time-to-market, shorter time to value“I can now get my ideas into production in hours,days or weeks. I can get immediate feedback AND then I can improve the idea and repeat”

70% of IT Leaders are pursuing a hybrid

cloud strategy

http://www.fodey.com/generators/newspaper/snippet.asp

Hybrid Cloud is coming to a data centre near you

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The ability to have ‘cloud burst’ capacity is changing the way software is being designed, developed and supported

It’s a new development world

We’re moving to a more industrial scale

v1 v2 v3

time

computecapacity

V1

We’re moving to a more industrial scale

v1 v2 v3

time

computecapacity

V1 V1.1

V1.2

V1.3

V1.4

V1.5 V1

.6 V1.7

v1 v2

time

computecapacity

We’re moving to a more industrial scale

v3

• Why buy one computer for a year when you can hire 365 computers for a day..

(Or a hour or a minute or a millisecond)

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“Compute on demand” – it’s what we always wanted

Cloud EconomicsWe really are getting closer all the time to

‘Compute on Tap’

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But with taps come meters…

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Cloud Economics

Cloud computing: compute == money

Money changes everything

With a measureable and direct relationship between $£€¥ and CPU/RAM, disk etc the financial success or failure of a project is even easier to see

And that means…

Even more focus on value for money.

American Society of Civil Engineers

Someone will be looking at your leaky app

Interlude

You run a tram company• How do you most profitably get people from A

to B?

A B

If there are more passengers waiting than the tram can hold you will lose business(no one waits a hour for the next tram)

1 tram an hour?

If there are few or no passengers waiting you lose money

1 tram an hour?

Less likely to lose customers. More likely to have empty seats

1 tram every 10 minutes?

Bigger trams in the rush hours?

Better: but you’ve got to predict demand accurately or you could be worse off than before (more idle or empty trams)

Lots of really small trams?

Helps with maximizing usage but don’t go too far. You need to maintain and support each tram

There is no simple answeryou need to be able to react to demand

More passengers = more trams or larger tramsFew passengers = less trams or smaller tramsNo passengers = no trams?

The economics are simple• react to demand as quickly as you can

– Rush hour vs slack times– The faster a service starts the less likely you are to lose customers

• Have the smallest unit of supply you can afford– Don’t buy really big carriages– Single purpose services are more flexible to scale than large monoliths– Don’t buy really small carriages– Too small and your infrastructure and support costs escalate

• deliver the unit supply as cheaply as you can– Don’t buy expensive trams if cheaper ones can do the same job– Smaller memory footprint for the same response time wins

Part 2 - How Java measures up

Compute == moneyEasier than ever

beforea business can

buy a CPU

Just for how long they need it.

No long term capital

investment.

Just as much as they need

$ == GB/hr-Xmx: $100

Unnecessary baggage(you have loads)

Java applications have to get lighter.

Java 9 modularity will help but you have to consider footprint across the board.

Choose your dependencies wisely

Your choice of OS & distribution is important.

The aim is ‘carry on only’

Your application isn’t going on a long trip

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Startup timesHow long do you want to wait?How long do you have to wait?

Do you need to preemptively start instances ‘just in case’ due to start up time?

To bad – that costs

BTW – think about this:

Everything that happens at startup – happens every time, all the time.

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Java & fast startup time – It’s known for it!Application developers can reduce service startup time by deferring optional costs to when its needed.

Maybe even create services with different behaviors rather than one with optional behavior

But it’s not enough

The JVM needs to revisit all the places where startup time was traded for throughput and turn them around.

what about

“ Everything that happens at startup – happens every time, all the time”

ConsequencesFor container based services start up effort happens multiple times during development and production

And it’s always the same result.AND you will pay $ for it every time

We don’t have a good way to capture all this effort or formalise starting a JVM from a precanned image. (Shared classes doesn’t hack it)

Other languages have better / faster startup!

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https://www.flickr.com/photos/isherwoodchris/

• Q: How much RAM does

your application use?

• A: Too much

Runtime costs Most cloud providers will charge you for your RAM usage over time: $GB/hr. (Sometimes the charge is $0)

Increasing –Xmx directly effects cost. Something businesses can understand

Net effect – you’ll be tuning your application to fit into specific RAM sizes. Smaller than you use today.

You need to measure where the storage goes. You’ll be picking some components based onmemory usage

increasing the amount of memory for 1 service increases the bill by the number of concurrent instances

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SimplyJava applications are going to be running in a remote, constrained and metered environment

There will be precise limits on how much disk, CPU, RAM, Bandwidth an application can use and for how long

Whether your application is large or small, granular or monolithic. Someone will be paying for each unit used

That person will want to get the most out of that investment

Your application is going on a dietThe JVM needs to change

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Part 3 – The API economyAnd what that means for Java

The API economyIf your company has data it will eventually be shared and monetized

Really.

Cloud APIs are one of the fastest growing areas in our industry.

Sharing data and services though APIs is enabling new opportunities and solutions Everyone is getting into the game.

What makes a good cloud api ?roughly in selection order.

Availability 100% of course with performance SLAs

elievability – Are those published 100% metrics true?ost – how much and what’s the unit of measure? iagnosability – can users debug problems without you?xcitement – is there a vibrant community using the API?unctionality – what else can the API do?

BCDEF

Where you code runs day-to-day and moment-to-moment will be driven by

economics, legal requirements and how much risk your business wants to take.Your code has to scale better, be more efficient, resilient, secure and work in

constrained environmentsYou will have to design, code, deliver, support and debug code in new ways

It’s going to be scary

How scary?

design, coding, deployment , startup, execution, scalingdebugging, security, resilience …

Almost everything about your

application is effected

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Resilient applicationsDesign for short term failure: something fails all the time. Expect data and service outages regularly

Fail and recover: don’t diagnose problems in running systems. Kill it and move on

Every IO operation you perform may fail – do as few as possible

Every IO operation may stall – costing you GB/hrs and resources– timeout everything quickly

Every piece of data you receive may be badly formed – check everything

Retry, compensation, backout strategies– these are your new friends

“Everything in the cloud fails all the time” : Werner Vogels

DebuggingRemote support for your family? Fancy having to do that for your own apps?

You have to assume:

You will never be able to log into a remote server.

You will never be able to attach a remote debugger to a failing app Ever.

All problems must be resolved by local reproduction or logs and dumps

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DebuggingIt gets more challenging.

Failures during deployment or initial startup can be difficult or impossible to diagnose.

If your service instance didn’t start there is little chance of logs being kept!

Learn to love logs, dumps and traces.

Remote log stores and tools are going to be your best friend

BTW: they’ll cost too

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Debugging• Q: Why can’t you just keep the

failed instance around?

• A: You can – if you accept the $$$ consequences…

Hard metrics and limits keeping a failed app around or having apps

on standby can be costly in multiple ways

Runtime costs and taking up vital resource

allocation

Part 4 – wrap-up

It’s all changeHow you design, code, deploy, debug, support etc will be effected by the metrics and limits imposed on you.

Financial metrics and limits always change behavior. It also creates opportunity

You will have to learn new techniques and tools

The JVM and Java applications have to get leaner and meaner

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Multiple languages on the JVM.What’s the benefit of running them on the JVM vs having a native service?

They can take more memory, and take longer to execute.

Cloud applications are increasingly heterogeneous.

Anyway they share data not objects

Nashorn JavaScript engine delivered in JDK8

Utilizes new JVM level features for performance

Avatar.js provides Node.js support on Nashorn

Results of “Octane” JavaScript benchmark using Java 8 pre-u20

Node.js is 4.8x fasterAvatar.js is >10x larger

Feb 12th, 2015: Avatar is “put on hold”

https://blogs.oracle.com/theaquarium/entry/project_avatar_update

More thoughts• Do we need a JVM anymore? If your container has code that will

ONLY run on one OS/arch do we need hardware abstraction like class files and bytecode?

• Modularity etc coming in Java 9 helps reduce footprint and some startup time.

• We need more AOT to convert Java into executable code once only

• Individual service lifetimes are short so dynamic recompilation is not useful unless the generated code is shared. How do we share compiled code cheaper than it costs to generate the code?

• Remember – you’ll be paying for all the ‘wasted’ CPU / RAM etc.

Summary1. Your business will need to adapt to ‘cloud’2. Your developers will need to adapt to ‘cloud’3. Your application will need to adapt to ‘cloud’4. Your competitors are already adapting

We don’t know all the answers (or even the questions) yet.We do know the next and largest ever pain point for Java is ‘cloud’Big changes are needed to keep Java successful and competitive

Your world is changing dramatically and all because of …

GB/hr

Thank you