Gab2015 nicolas fonrose_costefficiencywithmicrosoftazure.pptx

Microsoft Azure#gwab #ViseoSpirit
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2015
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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 !
6

• Architectural decisions now
have a huge cost impact
7

This leads to …
• Cost Driven Design
• Huge opportunities for systems
which are cheaper and more
reliable!
8

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

Means scaling Up and Down
Credit : CMG Workshop / November 2013 / Adrian Cockcroft

•  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

Gab2015 nicolas fonrose_costefficiencywithmicrosoftazure.pptx

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