Masterclass Webinar - Amazon EC2

Masterclass Elastic Compute Cloud Ryan Shuttleworth – Technical Evangelist @ryanAWS

Masterclass A technical deep dive beyond the basics Help educate you on how to get the best from AWS technologies Show you how things work and how to get things done Broaden your knowledge in ~45 mins

Amazon EC2 On-demand compute to run application workloads Easy come easy go – disposable resource We provide the infrastructure, you decide what you run

Complete control Elastic capacity

Flexible

What is EC2? Reliable

Secure Inexpensive

Elastic capacity Customer 1

Customer 2

…

Customer n

Hypervisor

Securely segregated Shared environment

Virtual Interfaces Customer 1 Security Groups

…

Customer 2 Security Groups

Firewall Physical Interfaces

Customer n Security Groups

Elastic capacity Customer 1

Customer 2

…

Customer n

Hypervisor

Securely segregated Shared environment

Virtual Interfaces Customer 1 Security Groups

…

Customer 2 Security Groups

Firewall Physical Interfaces

Customer n Security Groups

AMI

Amazon Machine Image

Instance

AMI

Amazon Machine Image

Running or Stopped machine

EC2

Instance

AMI

Amazon Machine Image

Running or Stopped machine

VPC

EC2

Instance

AMI

VPC

AZ Amazon Machine Image

Running or Stopped machine

Region

Instance

AMI

EC2

EC2

VPC

VPC

AZ Amazon Machine Image

Availability Zone

Running or Stopped machine

Region

Instance

AMI EBS

EC2

EC2

VPC

VPC

EBS

EBS

EBS

AZ Amazon Machine Image

EBS

EBS

Availability Zone

Running or Stopped machine

Region

Instance

AMI EBS

EC2

EC2

VPC

VPC

EBS

EBS

EBS

AZ Amazon Machine Image

Running or Stopped machine

EBS

EBS

Availability Zone EBS Snapshots

S3 Buckets S3

Region

Instance

Unit of control

Instance

Unit of scale

Unit of resilience

Unit of control

Your stack

Instance

Unit of scale

Unit of resilience

Scale out

Instance

Unit of control

Instance

Unit of scale Instance

Unit of resilience Instance

Instance

Unit of control

Instance

Unit of scale Instance

Unit of resilience Instance

Instance

Unit of control

Instance

Unit of scale Instance

Unit of resilience Instance

Instance

Unit of control

Instance

Unit of scale

Unit of resilience Instance

Instance

Unit of control

Instance

Unit of scale Instance

Unit of resilience Instance

Instance types Choose the right unit for your workload

High I/O 4XL 60.5 GB 35 EC2 Compute Units 16 virtual cores 2*1024 GB SSD-based local instance storage

256

Hi-Mem 4XL 68.4 GB 26 EC2 Compute Units 8 virtual cores

128

Memory (GB)

Hi-Mem XL 17.1 GB 6.5 EC2 Compute Units 2 virtual cores

32

Extra Large 15 GB 8 EC2 Compute Units 4 virtual cores

16

2

M3 XL 15 GB 13 EC2 Compute Units 4 virtual cores EBS storage only

Medium 3.7 GB, 2 EC2 Compute Units 1 virtual core Large 7.5 GB 4 EC2 Compute Units 2 virtual cores

4 Small 1.7 GB, 1 EC2 Compute Unit 1 virtual core

Hi-Mem Cluster Compute 8XL 244 GB 88 EC2 Compute Units 16 virtual cores 240 GB SSD

10 GB Inter-Instance Network

Hi-Mem 2XL 34.2 GB 13 EC2 Compute Units 4 virtual cores

64

8

High Storage 8XL 117 GB 35 EC2 Compute Units, 24 * 2 TB ephemeral drives 10 GB Ethernet

M3 2XL 30 GB 26 EC2 Compute Units 8 virtual cores EBS storage only

Cluster Compute 8XL 60.5 GB 88 EC2 Compute Units

Cluster Compute 4XL 23 GB 33.5 EC2 Compute Units

Cluster GPU 4XL 22 GB 33.5 EC2 Compute Units, 2 x NVIDIA Tesla “Fermi” M2050 GPUs

High-CPU XL 7 GB 20 EC2 Compute Units 8 virtual cores

High-CPU Med 1.7 GB 5 EC2 Compute Units 2 virtual cores Micro 613 MB Up to 2 ECUs (for short bursts)

1 1

2

4

8 16 32 EC2 Compute Units

64

128

256

Start small Easy to up-size

AMIs

Amazon maintained

Community maintained

Your machine images

Set of Linux and Windows images

Images published by other AWS users

AMIs you have created from EC2 instances

Kept up to date by Amazon in each region

Managed and maintained by Marketplace partners

Can be kept private or shared with other accounts

http://aws.amazon.com/amazon-linux-ami/

AMIs

Linux

Enterprise Linux

Windows

Small instance from $0.060 per hour

Small instance from $0.120 per hour

Small instance from $0.115 per hour

Small instance from $0.090 per hour

Instance types

On-demand instances Unix/Linux instances start at $0.02/hour Pay as you go for compute power Low cost and flexibility Pay only for what you use, no up-front commitments or long-term contracts Use Cases: Applications with short term, spiky, or unpredictable workloads; Application development or testing

Instance types

On-demand instances

Reserved instances

Unix/Linux instances start at $0.02/hour

1- or 3-year terms

Pay as you go for compute power

Pay low up-front fee, receive significant hourly discount

Low cost and flexibility

Low Cost / Predictability

Pay only for what you use, no up-front commitments or long-term contracts

Helps ensure compute capacity is available when needed

Use Cases: Applications with short term, spiky, or unpredictable workloads; Application development or testing

Use Cases: Applications with steady state or predictable usage Applications that require reserved capacity, including disaster recovery

Instance types

Heavy utilization RI > 80% utilization Lower costs up to 58%

On-demand instances

Reserved instances

Unix/Linux instances start at $0.02/hour

1- or 3-year terms

Pay as you go for compute power

Pay low up-front fee, receive significant hourly discount

Low cost and flexibility

Low Cost / Predictability

Pay only for what you use, no up-front commitments or long-term contracts

Helps ensure compute capacity is available when needed

Use Cases: Applications with short term, spiky, or unpredictable workloads; Application development or testing

Use Cases: Applications with steady state or predictable usage Applications that require reserved capacity, including disaster recovery

Use Cases: Databases, Large Scale HPC, Always-on infrastructure, Baseline

Instance types

Heavy utilization RI > 80% utilization Lower costs up to 58%

On-demand instances

Reserved instances

Unix/Linux instances start at $0.02/hour

1- or 3-year terms

Pay as you go for compute power

Pay low up-front fee, receive significant hourly discount

Low cost and flexibility

Low Cost / Predictability

Pay only for what you use, no up-front commitments or long-term contracts

Helps ensure compute capacity is available when needed

Use Cases: Applications with short term, spiky, or unpredictable workloads; Application development or testing

Use Cases: Applications with steady state or predictable usage Applications that require reserved capacity, including disaster recovery

Use Cases: Databases, Large Scale HPC, Always-on infrastructure, Baseline

Medium utilization RI 41-79% utilization Lower costs up to 49% Use Cases: Web applications, many heavy processing tasks, running much of the time

Instance types

Heavy utilization RI > 80% utilization Lower costs up to 58%

On-demand instances

Reserved instances

Unix/Linux instances start at $0.02/hour

1- or 3-year terms

Pay as you go for compute power

Pay low up-front fee, receive significant hourly discount

Low cost and flexibility

Low Cost / Predictability

Pay only for what you use, no up-front commitments or long-term contracts

Helps ensure compute capacity is available when needed

Use Cases: Applications with short term, spiky, or unpredictable workloads; Application development or testing

Use Cases: Databases, Large Scale HPC, Always-on infrastructure, Baseline

Medium utilization RI 41-79% utilization Lower costs up to 49% Use Cases: Web applications, many heavy processing tasks, running much of the time

Use Cases:

Light utilization RI Applications with steady state or predictable usage Applications that require reserved capacity, including disaster recovery

15-40% utilization Lower costs up to 34% Use Cases: Disaster Recovery, Weekly / Monthly reporting, Elastic Map Reduce

Instance types

On-demand instances

Reserved instances

Spot instances

Unix/Linux instances start at $0.02/hour

1- or 3-year terms

Bid on unused EC2 capacity

Pay as you go for compute power

Pay low up-front fee, receive significant hourly discount

Spot Price based on supply/demand, determined automatically

Low cost and flexibility

Low Cost / Predictability

Cost / Large Scale, dynamic workload handling

Pay only for what you use, no up-front commitments or long-term contracts

Helps ensure compute capacity is available when needed

Use Cases: Applications with short term, spiky, or unpredictable workloads; Application development or testing

Use Cases: Use Cases:

Applications with flexible start and end times

Applications with steady state or predictable usage

Applications only feasible at very low compute prices

Applications that require reserved capacity, including disaster recovery

Launch an instance Commands, keypairs & security groups

Region Instance size AMI Key pair Security group

key pairs secure access

Public Key Inserted by Amazon into each EC2 instance that you launch

EC2 Instance Comms secured with private key

Private Key Downloaded and stored by you

Keypairs & Secrets

Keypairs

Used to authenticate when accessing and instance

Credentials Access key and secret key used to authenticate against APIs

x.509

Used to authenticate against some APIs

security groups instance firewalling

Port 80 (HTTP)

Port 22 (SSH)

Security Group

instance

Name Description Protocol Port range IP Address, range, or another security group

PS C:> New-EC2Instances -ImageId ami-269dbb63 -KeyName mykey -SecurityGroupId sg-9cf9e5d9 -InstanceType t1.micro

$>

ec2-run-instances ami-54cf5c3d --instance-count 2 --group webservers --key mykey --instance-type m1.small

>>> import boto.ec2 >>> conn = boto.ec2.connect_to_region("us-east-1") >>> conn.run_instances( 'ami-54cf5c3d', key_name='mykey', instance_type='m1.small', security_groups=['webservers'])

Wait a minute I want to use those tools too…

IAM Roles and EC2 tools 1. Start an EC2 Linux instance 2. Assign an IAM role at launch time:

3. Sets up all the tools you need & manages API access credentials

{ "Statement": [ { "Effect": "Allow", "NotAction": "iam:*", "Resource": "*" } ]

1. Up and running with CLI tools in a couple of minutes – just SSH on and use 2. Terminate/stop instance when you are done

}

Now you have tools Try this…

$>

ec2-run-instances ami-54cf5c3d --instance-count 1

$>

What about all this?

ec2-run-instances ami-54cf5c3d --instance-count 1 --group webservers --key mykey --instance-type m1.small

$>

Defaults

ec2-run-instances ami-54cf5c3d --instance-count 1 --group Default --key NONE --instance-type default(m1.small)

$>

ec2-run-instances ami-54cf5c3d --instance-count 1 --group Default --key NONE --instance-type default(m1.small)

Instances don’t need keypairs But how do you configure it if you can’t log onto it?

Bootstrapping

Bake an AMI Start an instance Configure the instance Create an AMI from your instance Start new ones from the AMI

Bootstrapping

Bake an AMI

vs

Configure dynamically

Start an instance

Launch an instance

Configure the instance

Use metadata service and cloud-init to perform actions on instance when it launches

Create an AMI from your instance Start new ones from the AMI

Bootstrapping

Bake an AMI Build your base images and setup custom initialisation scripts Maintain your ‘golden’ base

+

Configure dynamically Use bootstrapping to pass custom information in and perform post launch tasks like pulling code from SVN

Bootstrapping

Bake an AMI

Time consuming configuration (startup time) Static configurations (less change management)

Configure dynamically

Bootstrapping

Bake an AMI

Configure dynamically

Continuous deployment (latest code) Environment specific (devtest-prod)

Goal is bring an instance up in a useful state The balance will vary depending upon your application

Instance request

User data

Instance request

User data

Meta-data service

Instance request

User data

Meta-data service

Instance

Shell script in user-data will be executed on launch: #!/bin/sh yum -y install httpd php mysql php-mysql chkconfig httpd on /etc/init.d/httpd start

Amazon Windows EC2Config Service executes userdata on launch: dir > c:\test.log any command that you can run

AWS Powershell Tools (use IAM roles as before…) Read-S3Object -BucketName myS3Bucket -Key myFolder/myFile.zip -File c:\destinationFile.zip 63

Automation Less fingers, less mistakes

Security

Availability

Instances locked down by default

Drive higher availability with selfhealing

Why do this? Flexible

Efficiency

Shell, Powershell, CloudFormation, Chef, Puppet, OpsWorks

Audit and manage your estate with less time & effort

Scale Manage large scale deployments and drive autoscaling

Some does and don’ts

Do Use IAM roles Go keyless if you can Strike a balance between AMI and dynamic bootstrapping

Some does and don’ts

Do

Don’t

Use IAM roles

Put your API access keys into code (and then publish to GIT) or bake into AMIs (and share)

Go keyless if you can Strike a balance between AMI and dynamic bootstrapping



Block storage Understanding instance storage vs EBS

Instance Storage Local ‘on host’ disk volumes

Data dependent upon instance lifecycle

Instance Storage

VS

Elastic Block Storage

Local ‘on host’ disk volumes

Network attached optimised block storage

Data dependent upon instance lifecycle

Data independent of instance lifecycle

Instance A

Instance Storage

Instance D Instance B

Local ‘on host’ disk volumes

Instance E

Instance C

Data dependent upon instance lifecycle

Instance F

Instance Store

eph0

Host 1

eph1

eph2

Instance Store

eph3

eph0

Host 2

eph1

eph2

eph3

Instance Storage Local ‘on host’ disk volumes

Data dependent upon instance lifecycle

If an instance reboots (intentionally or unintentionally), data in the instance store persists Data on instance store volumes is lost under the following circumstances: • Failure of an underlying drive • Stopping an Amazon EBS-backed instance • Terminating an instance

Options Differing types of instance storage

Options Differing types of instance storage

One or more ephemeral (temporary) drives (instance storage)

One or more EBS (persistent) drives

EBS snapshots (backup images)

Network attached optimised block storage

Workspace Network

EBS snapshot

Hypervisor

EC2

Elastic Block Storage

EBS

S3

Data independent of instance lifecycle

Boot cycle

Elastic Block Storage Network attached optimised block storage EBS snapshot

Hypervisor

EC2

EBS

S3

Data independent of instance lifecycle

Boot cycle

Elastic Block Storage

Workspace

Network attached optimised block storage EBS snapshot

Hypervisor

EC2

EBS

S3

Data independent of instance lifecycle

Boot cycle

Elastic Block Storage

Workspace

Network attached optimised block storage Data independent of instance lifecycle

EBS snapshot

Hypervisor

EC2

EBS

S3

Boot cycle

Elastic Block Storage

Workspace

Network attached optimised block storage Data independent of instance lifecycle

Network

Hypervisor

EC2

EBS

S3

EBS Persistence

EBS volume is off-instance storage You pay for the volume usage as long as the data persists 1. By default, EBS volumes that are attached to a running instance automatically detach from the instance with their data intact when that instance is terminated 2. By default, EBS volumes that are created and attached to an instance at launch are deleted when that instance is terminated. You can modify this behavior by changing the value of the flag DeleteOnTermination to false when you launch the instance.

Elastic Load Balancer Spreading the load and fronting EC2

A regional service Load balance across availability zones

Elastic Load Balancer

Instance

Instance

Availability Zone

Instance

Instance

Availability Zone

Region

Instance

Instance

Availability Zone

Elastic Load Balancing

Spread

Offload

Health check

Go small and wide

SSL processing on ELB

Balance resources across AZs

Remove load from EC2 instances

Choose the right healthcheck point Check whole layers

1. Persistent HTTP connections – enable them and ELB to Server will be optimized 2. Never address underlying IP – always DNS name • There’s a set behind an ELB and real clients spread across them • They will change as the ELB scales to keep ahead of demand 3. If you span ELB across AZs have an instance in all Azs 4. De-register instances from an ELB before terminating

AutoScaling Automate EC2 commissioning and decommisioning

Launch Configuration

Auto-Scaling Group

Auto-Scaling Policy

Describes what Auto Scaling will create when adding Instances

Auto Scaling managed grouping of EC2 instances

Parameters for performing an Auto Scaling action

Automatic health check to maintain pool size

Scale Up/Down and by how much

AMI Instance Type Security Group Instance Key Pair Only one active launch configuration at a time Auto Scaling will terminate instances with old launch configuration first rolling update

Automatically scale the number of instances by policy – Min, Max, Desired Automatic Integration with ELB

Automatic distribution & balancing across AZs

ChangeInCapacity (+/- #) ExactCapacity (#) ChangeInPercent (+/- %) Cool Down (seconds) Policy can be triggered by CloudWatch events

Create a launch configuration: as-create-launch-config --image-id ami-54cf5c3d --instance-type m1.small --key mykey --group webservers --launch-config 101-launch-config

Create a launch configuration: as-create-launch-config --image-id ami-54cf5c3d --instance-type m1.small --key mykey --group webservers --launch-config 101-launch-config

The usual suspects

Create an auto scaling group: as-create-auto-scaling-group 101-as-group --availability-zones us-east-1a us-east-1b us-east-1c --launch-configuration 101-launch-config --load-balancers myELB --max-size 5 --min-size 1

Create an auto scaling group: as-create-auto-scaling-group 101-as-group --availability-zones us-east-1a us-east-1b us-east-1c --launch-configuration 101-launch-config --load-balancers myELB --max-size 5 What’s going to launch --min-size 1

Create an auto scaling group: as-create-auto-scaling-group 101-as-group --availability-zones us-east-1a us-east-1b us-east-1c --launch-configuration 101-launch-config --load-balancers myELB --max-size 5 --min-size 1 Integrate with an ELB?

Create an auto-scaling policy (scale up): as-put-scaling-policy 101ScaleUpPolicy --auto-scaling-group 101-as-group --adjustment=1 --type ChangeInCapacity --cooldown 300

Create an auto-scaling policy (scale up): as-put-scaling-policy 101ScaleUpPolicy --auto-scaling-group 101-as-group --adjustment=1 --type ChangeInCapacity --cooldown 300

Period before another action will take place (Damper)

Create an auto-scaling policy (scale down): as-put-scaling-policy 101ScaleDownPolicy --auto-scaling-group 101-as-group "--adjustment=-1" --type ChangeInCapacity --cooldown 300

CloudWatch Know what is going on

Cloud Watch Alarm:

Takes action:

CPU >= 50% for 5 mins

Scale up policy

CPU < 30% for 10 mins

Scale down policy

Cloud Watch Alarm:

CPU >= 50% for 5 mins

Takes action:

Scale up policy

Cloud Watch Alarm:

Takes action:

CPU >= 50% for 5 mins

CPU < 30% for 10 mins

Deliver message to Q

SNS Topic

Post to endpoint

Send Email

Cloud Watch Alarm:

Takes action:

CPU >= 50% for 5 mins SNS Topic

Comprehensive Billing, technical, aggregate & custom metrics

SNS Integration

Alarms Set custom alarms and thresholds

Push alarms to SNS topics

CloudWatch HTTP Poke HTTP endpoints for custom alarm actions

Email integration Custom Metrics Write your own metrics in via SDKs

Send alarm notifications to emails

Other topics to look at:

Other topics…

Resource tagging

Route 53

Rolling deployments

Tag resources like EC2 and have it appear on billing reports

Front EC2 and ELBs with Route 53 for control over DNS

Use Route 53 and ELBs to do rolling deployments, A/B testing

Other topics…

Beanstalk

OpsWorks

CloudFormation

Manage an entire autoscaling stack for popular containers such as ruby, python etc

Manage stacks as layers and implement Chef recipes to automate EC2 configuration

Template everything from configuration of CloudWatch alarms, SNS topics, EC2 instances

Summary

Stop doing these: Provisioning and fixing servers Treating compute as physical things Thinking of compute as a finite commitment

Elasticity Security Build systems secure by default

Stateless autoscaling applications

Automation Create instances when you need them, drop them when not

and start doing these Replace not fix Build from scratch, don’t fix something

Be cost aware Unconstrained Say goodbye to traditional capacity planning

Tag resources, play with instance types

Watch a demo here: http://youtu.be/kMExnVKhmYc

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