Gab2015 nicolas fonrose_costefficiencywithmicrosoftazure.pptx

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•  Welcome to your new job •  Cloud cost efficiency defined •  Avoiding waste •  Architecting for cost efficiency •  Choosing Azure services •  Deployment strategy •  Measuring cost efficiency

Presentation


WELCOME TO YOUR NEW JOB !

Now, you also need to care about cost


The Cloud introduces a revolution …

• Everything you do now has a direct impact on costs !

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• Architectural decisions now have a huge cost impact

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This leads to …

• Cost Driven Design • Huge opportunities for systems which are cheaper and more reliable!

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CLOUD COST EFFICIENCY DEFINED

What is it and why would you care ?


Cost efficiency …

Why would anyone care ??


Cost efficiency, why would you care ?

When you scale, every cost optimization pays *10000

–  Selling many robots, –  many connected cars, –  having many players on your game …


And because when it’s cheap, you can do even crazier things !

–  GMail pre-opening/rendering all your email attachments

Cost efficiency, why would you care ?


Definition


Definition

•  Very different from pure performance. •  We’re not looking for the fastest Web stack here.


Definition

How to express that part ??


Definition

How to measure that part ?


A DEEPER LOOK AT THE COMPONENTS OF THE « EQUATION »


Measuring perf

•  Perf. – Fairly easy –  Concepts well defined

•  Throughput (Req/s, DataVolume/s, …), Latency, Consistency of response times, …


Measuring perf

•  Perf. – Fairly easy –  Tons of tools and litterature

•  Tools to replay, to load-test, to graph results …


Classification of requests by response time

Average response time for each « competitors »


Measuring costs

•  Cost – Fairly easy –  Once you know how to precisely measure it



Mesuring Quality of service

•  QoS – Much harder –  How you, as a user of the system, perceive its usage


Mesuring Quality of service –  Cloud solutions bring new opportunities to lower costs –  But sometimes at the expense of QoS !

•  Which is why is very important to consider the costEff and not just the cost


QoS - Examples

•  Perfect(costEff) –  A system that is ‘on’ only when a user request comes in

•  Nearly infinite cost efficiency (by moving the cost toward 0)


COST OPTIMIZATION MATURITY LEVELS From the obvious to the most advanced techniques


Cloud cost maturity level

Initial

Monitored

Allocated

Business valued

1 Cost are not estimated or monitored and are are to predict

1 Costs are monitored at a global level, or per account

1 Costs are monitored by amount of business transactions

1 Costs are monitored and allocated to business units, products, …


AVOIDING WASTE

The first obvious step (not so easy !)


•  Don’t let things running if you don’t use them –  Easier said than done ! How do you know what is used

and what is not ? –  –  Examples of pure waste

•  Don’t keep 'stopped' Azure Applications in any other tier than the 'F1 Free tier' (automation helps here)

Pure Waste


•  Ensure you use what has been pre-purchased at the optimal price –  Avoid using rogue Subscriptions that would be at on-

demand (instead of within Enterprise Agreement) prices

Less obvious waste


ARCHITECTING FOR COST EFFICIENCY The most decisive factor impacting costs


Follow the (sun / users)

•  Autoscale

•  Reducing cost by Right-sizing in real-time


Follow the users

Credit : CMG Workshop / November 2013 / Adrian Cockcroft


Follow the users



Means scaling Up and Down



•  Avoid expensive resources


Exemple of expensive resources

•  Caviar in cloud = outgoing traffic –  Can you implement efficient client-side caching ? –  Can you move part of the trafic to a CDN (hopefully

less expensive) ?


Pricing keeps changing

•  What is expensive varies a lot •  Over the various providers •  Over time for each provider


Don’t burn too much CPU

•  Reduce resources consumption

•  Obvious, but many people don’t really pay attention …


How can you act on that ? –  Thread swapping is a major SYSTEM CPU cycles

burner !

•  Real customer story about this


New concerns

•  Speed of boot –  Wasn’t a concern up to now

•  Now, slow booting speed is a major pain in some Cloud environments (Jersey + Google AppEngine for instance)

•  And the Azure Cloud …


CONCRETE EXEMPLES

Exemple of how to reduce spending without reducing QoS


Ex1 – Web site with external depend.

•  Web site making many calls to slow payment APIs



•  Move to non-blocking I/O –  Runtime cost divided by 8 !

•  For the exact same service, same QoS, same SLA •  4 Xlarge instances become 2 small instances •  Tomcat/Java => NodeJS (would be the same with

RxJava/…)



•  The perfect « ad » for NodeJS –  This is not always the case, as we will see in the

following examples

–  Actually perfect Ad for any Reactive framework (NodeJS based or not)


Ex2 – Unfreq. used service

•  Web site with unfrequently called micro-service

•  Only called once each time a new user creates an account


Ex2 – Unfreq. used service –  Perfect candidate for onDemand short duration

instances + –  Non-blocking I/Os

•  Would bring the cost close to 0


Ex2 – Need ultra fast resp.

•  BUT … – 



•  BUT … –  Users won’t wait for an instance to boot (value would

decrease)



•  So we keep an instance idle •  A CSP with very very fast booting instances could

solve it though ! –  => cf AWS Lambda (should appear in Azure shortly)


Ex3 – Web ticketing

•  Another ideal case for non blocking I/O

– 



•  Looks like another ideal case for non blocking I/O –  Cut the number of instances from 54 to 9



•  Looks like another ideal case for non blocking I/O –  BUT why not cut it to 0 ?



•  Actually another ideal case for Object Storage –  Amazon S3, Azure Blob Storage, Google GCS, …

•  Just need one instance (non-blocking) to generate self-signed URLs


DEPLOYMENT STRATEGY

The more flexible and the more automated your deployments are, the more opportunities there are for cost optimization


What’s the link between « Deployment automation » and

« Cloud cost Efficiency » ???


•  You need to be able to shut things DOWN and turn them ON very regularly –  It shouldn’t take long to switch power ON/OFF –  You can’t spend several minutes every morning and

night switching things on and off. With the potentiel errors that would come with it

Deployment automation benefits


•  You need to be able to test several variants of your systems –  Test with different instance types –  Test various configurations



•  You need to be able to test several variants of your systems regularly –  Things change fast in the Cloud world



•  Continuous cost improvement –  Continuous deployment (Infra + App) –  Load generation –  Cost measurement –  Comparison with previous runs

=> Feedback for architects and developers



MEASURING COST EFFICIENCY

How-to and tools


Repeatability

•  Thanks to scripting, things are precisely repeatable –  And we can assign a testId to every test execution


Measuring tests costs

•  Measuring small cost increments (few mins)

•  Tags (Need to change tag values on each run) •  Need to change instances (1h / 10min) •  Need to use taggable servicesTag *all* services


Measuring tests costs

•  Cost-allocate every test execution –  Tag all the resources created

•  Propagate tags to elements which are not tagged by default

•  If some elements are not taggeable, run them on specific subscriptions (cost are per subscriptions)

tag[TestId]=bfd3e690-ce14-11e3-9c1a-0800200c9a66


Measuring tests costs (continued)

•  With some Cloud providers, you can retrieve specific debug cost information –  Detailed cost items provided by the Cloud provider –  For instance, Google AppEngine log lines contain cost

information •  Very precise because isolated per requests but no

global overview


Collect the cost data (after test execution)

•  Scan through detailed cost logs –  Detailed Billing Files provided by Azure (equivalent to

the information provided by AWS or Google Cloud) –  Cost data coming after a delay (4 to 24h)


Collect the business value data (after exec)

•  Scan through application logs and performance logs –  Application logs to determine the value produced –  Performance logs for the QoS computation


Compute your cost-efficiency level

•  « Cost of test run » + « Generated business throughput » => « Cost by business metrics » –  Exemple : 3.47€ HT per 100 « vehicule configuration

simulation »


Cost by business metrics analysis

•  Iterate, improve –  Continuously


Implementing this with the Azure Cloud


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Gab2015 nicolas fonrose_costefficiencywithmicrosoftazure.pptx