2Confidential ©2008-15 New Relic, Inc. All rights reserved.  

The Decline of the Server

▪Containerization▪Docker▪Amazon ECS

▪Zero config infrastructure-less compute▪AWS Lambda

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Lessons learned from Docker

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Docker is the app’s lightweight VM

Long lived

Short lived

VM

AmazonEC2

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6

Well, that was surprising

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49ACCOUNTS USING DOCKER

IN LAST 24 HOURS

9,974CONTAINERS REPORTING IN

IN LAST 24 HOURS

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7

Apparent usage

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Long lived

Short lived

AmazonEC2

VM

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8

Along came New Relic Synthetics…

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▪Test external availability and performance▪User authored selenium scripts run in our data

center▪Each run in its own container for security

isolation▪Most run for under a minute

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9

Disposable compute container

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Long lived

Short lived

VM

AmazonEC2

AWSLambd

a

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What the heck’s going on?

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Long lived

Short lived

? ? ?

VM

AmazonEC2

AWSLambd

a

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We’re Data Nerds!

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Docker container age, count vs. hours

100

10K

1M

3.7 M

83 days

333 days

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Docker container age, count vs. hours

100

10K

1M

3.7 M

VM’ish

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Docker container age, count vs. hours

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100

10K

1M

3.7 M

EC2’ish

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Docker container age, count vs. hours

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100

10K

1M

3.7 M

Lambda’ish

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Container age, by hour under 24 hours

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3,741,00046% under one hour

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Container age, by minute under an hour

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950,00011% under one minute

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Container age, by minute under an hour

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27% under 5 minutes (versus a VM?)

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A surprising result

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Long lived

Short lived

VMVM

AmazonEC2

AWSLambd

a

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June versus now: 5x data, same shape

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The evolution of computation as a serviceShort startup time (orders mag.) allows very short lived computing

Containers only exist, and only for as long, as they provide value.

Full stop.

Containers are created

Do their work

Go away

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Elements of monitoring computation as a service

▪A mere list of instances doesn’t scale, nor help

▪De-provisioned containers still contribute to knowledge

▪Raw metrics just table stakes

▪Context matters to identify computational intent

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Monitoring servers

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Monitoring computation

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Low friction install

New Relic AWS EC2 Beta addresses

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Managing the dynamic

nature of AWS

Managing the scale of AWS

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Increased visibility

Application Monitoring

Server Monitoring

EC2 AWS Metadata

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SaaS to SaaS monitoring, under one minute

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Dynamic management

Provides AWS status

Maintains accurate EC2 list

Detects blind spots

Shows instance state

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Context via tags and metadata as labels

AWS metadata

AWS custom

tags

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EC2 instance name

AWS metadata

Custom label

Customer example

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New Relic by instance typeSelected

labelInstance

countHealth status

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New Relic by availability zone

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New Relic by instance type in us-east-1

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Confidential ©2008-15 New Relic, Inc. All rights reserved.  

Future requirements for monitoring toolsThe obvious ones

Should handle scale

Should handle dynamic lifecycle

of resources

The less obvious ones

It’s a big data problem

Ops needs ways of quickly pivoting and

drilling in

Deeper understanding requires analytics (raw metrics not

enough) ©2008-15 New Relic, Inc. All rights reserved.  

We all love…

… and yet

Common AWS scenarios

No large infrastructure build out

Quickly provision

Scale out to meet demand

Am I under-provisioned?

Am I over-provisioned?

How well am I responding to demand?

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Prototype examples of Analytics

Application and Server metrics

Enriched with context from AWS

As New Relic Insights events

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Detecting under-provisioned

Hmm, that’s bad

The smoking gun Aha!

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Detecting over-provisionedHmm, that’s too

good

Aha!That’s a waste

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Evaluating availability elasticity

Through scale outBut never

de-provisioned

Response time settles back

Increased load

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The Ultimate AWS control panel

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RESOURCES CUSTOMER EXPERIENCE COST

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