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Università degli studi di Roma “Tor Vergata”

Facoltà di Ingegneria

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E.Casalicchio, L.Silvestri "Architectures for autonomic service management in cloud-based systems," Computers and Communications (ISCC), 2011 IEEE Symposium on, pp.161-166, June 28 2011-July 1 2011, Kerkyra (Corfù), Greece

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•

 

Compute

–  Amazon Elastic Compute Cloud (EC2)

–  Amazon Elastic MapReduce –  Auto Scaling

–  Elastic Load Balancing

•

 

Storage

–  Simple Storage Service (S3) –  Elastic Block Store (EBS)

•

 

Database

–  Amazon SimpleDB

–  Amazon Relational Database Service (RDS)

–  Amazon DynamoDB

•

 

Messaging

–  Simple Queue Service (SQS) –  Simple Notification Service

(SNS)

•

 

Networking & Content Delivery

–  Amazon Route 53

–  Amazon Virtual Private Cloud (VPC)

–  Amazon CloudFront

•

 

Deployment & Management

–  Amazon CloudWatch –  AWS Elastic Beanstalk –  AWS Identity and Access

Management (IAM)

5

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•  Provides resizable compute capacity in the

cloud

•  Allows to increase/decrease capacity (start/

stop instances) within minutes

•  Pay-per-use on hourly basis

•  From one to thousands of server instances can

be launched simultaneously

•  Guarantees complete control over instances

–  root SSH access, GUI, command line tools, APIs

•  offers advanced services

–  Elastic Block Store –  Elastic Load Balancer –  CloudWatch + AutoScaling –  Elastic IP

–  Amazon Elastic Beanstalk

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•

 

Regions

–  geographically dispersed

–  consist of

one or more

availability zones

–  Current regions:US East (Northern Virginia), US West

(Oregon),US West (Northern California), EU (Ireland), Asia

Pacific (Singapore), Asia Pacific (Singapore), Asia Pacific

(Tokyo), South America (Sao Paulo)

–  Special Region AWS GovCloud

•

 

Availability Zones

–  distinct locations in the same region engineered to be insulated

from failures in other availability zones

–  used to protect applications from failure of a single location

•

 

Load Balancing

–  allowed only between different Availability Zones in the same

Region

–  not supported between different Regions

7

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•

 

On-Demand Instances

–  billing per-hour with no long-term commitments

•

 

Reserved Instances

–  one-time payment to reserve an instance for 1 or 3 years –  significant discount on hourly usage charge

•

 

Spot Instances

–  enable users to bid for unused EC2 capacity

–  Spot Price fluctuates periodically depending on supply of/demand for Spot Instance capacity

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•  AWS Management Console

•  Command Line Tools

•  Java-based command-line client

•  AWS SDKS (available for Java, PHP and .NET) •  Third Party Libraries

•  Query and SOAP APIs

13

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•  Offers persistent storage for EC2 instances

•  Provides off-instance storage that persist independently from the

life of an instance

•  EBS volumes from 1GB to 1 TB

•  EBS volumes can be used ad instance’s boot partitions or attached

to running instances as standard block devices

•  A volume can only be attached to one instance at a time, but many

volumes can be attached to a single instance

•  EBS volumes can be attached only to instances in the same

Availability Zone

•  EBS volumes automatically replicated within the same Availability

Zone to avoid data loss

•  EBS provides the ability to create point-in-time snapshots of

volumes that can be stored using S3

21

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•  Elastic IP

–  addresses are not associated with a particular instance but with

a user account

–  the user control an elastic IP address address until he explicitly

release it

–  allow to mask instance or Availability Zone failures by quickly

remapping the Elastic IP address to another instance/load

balancer

•  Virtual Private Cloud

–  enables enterprises to connect their existing infrastructure to a

set of isolated AWS compute resources via a Virtual Private

Network (VPN) connection

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•  Provides monitoring for AWS cloud resources and applications

•  CloudWatch is Metric repository

•  AWS services put metrics in the repository •  users retrieve statistics based on those metrics

23

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•  Metric

–  a time ordered set of data points

–  PutMetricData API allows users to create custom metrics

•  Statistics

–  metric data aggregations over specified periods of time

–  available statistics: Minimum, Maximum, Sum, Average, SampleCount –  can be retrieved by GetMetricStatistics API

•  Period

–  length of time associated with a specific CloudWatch statistic

–  expressed in seconds, range from 60 (one minute) to 1209600 (two weeks)

•  Alarm

–  watches a single metric over a specified time period

–  performs one or more actions based on the value of the metric relative to a given threshold over a number of time periods

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•  EC2 metrics

–  CPUUTilization!

–  DiskReadOps/DiskWriteOps!

–  DiskReadBytes/DiskWriteBytes!

–  NetworkIn/NetworkOut!

•  Elastic Load Balancing Metrics

–  Latency!

–  RequestCount!

–  HealthyHostCount/UnHealthyHostCount!

–  Count of HTTP Response Codes (2xx, 3xx, 4xx, 5xx)generated

by Load Balancer or back-end instances

25

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•  Command Line Tools

•  Libraries

–  (JAVA, PHP, Python, Ruby, Android, iOS, Wndows and .NET)

•  Query API

–  HTTP/HTTPS GET or POST requests

•  AWS Management Console

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•  An alarm watches a single metric over a time period and performs one or more actions based on the value of the metric relative to a given

threshold over a number of time periods

•  Possible states: OK, ALARM, INSUFFICIENT_DATA! •  When an alarm changes its state an action is invoked

–  notification through Amazon SNS –  Auto Scaling policy

Example

Threshold = 3

minimum breach = 3 periods

27

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•  Auto Scaling allows to scale EC2 capacity up or down

automatically according to user defined conditions

•  Enabled by Amazon CloudWatch

–  uses CloudWatch alarms

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•  Auto Scaling policies defines action to take when an alarm state

changes

•  For every monitored event 2 policies should be defined

–  a

scale-up

policy

–  a

scale-down

policy

•  A policy can be created using PutScalingPolicy API with the

following parameters:

–

 

AdjustmentType: possible values are ChangeInCapacity,

ExactCapacity, PercentChangeInCapacity!

–

 

Cooldown: amount of time after a scaling activity completes

before any further trigger-related scaling activities can start

–

 

PolicyName!

–

 

ScalingAdjustment: the number of instances by which to

scale (positive or negative)

29

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•  Automatically distributes incoming traffic across multiple

EC2 instances

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•  Detects unhealthy instances within a poll and automatically reroute

traffic to healthy instances

•  Can be enabled across multiple Availability Zones within a Region

–  NOT between Availability Zones in different Regions!

•  Uses a Least Loaded balancing policy

•  Supports sticky sessions

–  load balancer generatedHTTP cookies (browser based session lifetime)

–  application-generated HTTP cookies (application-specific session lifetimes)

•  Supports HTTPS

•  Enables the client to define an application healthcheck for the

instances through the following parameters

–  Threshold, Interval, Target, Timeout, UnhealthyThreshold!

•  Provides APIs to add/remove instances

–  RegisterInstancesWithLoadBalancer! –  DeregisterInstancesWithLoadBalancer!

31

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•  To test the AWS Auto Scaling capabilities we deployed Mediawiki

on Amazon EC2

–  MediaWiki is a free software open source wiki package written in PHP

•  We populated the DB with a dump from Wikipedia

•  We replicated traffic from a real Wikipedia workload trace properly

reduced

35

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•  1-10 Amazon EC2 m1.small instances

–  32 bit Linux VMs with 1 EC2 Compute Unit and 1.7 GB memory –  Each VM replicates the front-end of the MediaWiki web application –  Apache 2.2.16 is used as application server

•  1 Amazon EC2 m1.large instance

–  64 bit Linux VM with 4 EC2 Compute Units (2 cores) and 7.5 GB memory

–  MySQL 5.1.52 is used to implement the back-end tier

–  The system is dimensioned to guarantee that the centralized DB never represents the system bottleneck

•  1 Amazon Elastic Load Balancer

•  1 EC2 m1.small instance as workload generator

•  All components run in the same Availability Zone

–  the effects of network latency are reduced at the minimum

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•  Utilization-based, one alarm (UT-1AL)

–  add 1 instance if average CPU utilization > 62% –  remove 1 instance if average CPU utilization < 50% •  Utilization-based, two alarms (UT-2AL)

–  add 2 istances if utilization > 70%, 1 if utilization>62% –  remove 1 instance if utilization < 50%, 2 if utilization < 25% •  Latency-based, one alarm (LAT-1AL)

–  add 1 instance if latency (average response time seen by the ELB) is > 0.2 seconds

–  remove 1 instance if average CPU utilization < 50% •  Latency based, two alarms (LAT-2AL)

–  add 2 istances if latency > 0.5 sec, 1 if latency > 0.2 sec –  remove 1 instances if utilization < 50%,2 if utilization < 25%

37

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•  ELB bugs

–  problems with start/stop instances, better use launch/terminate –  if an instance crashes it remains forever in “unhealthy” status –  unhealthy instances are not automatically replaced

•  CloudWatch problems

–  metric variation over a time interval is missing

–  request count considers only the requests processed by the load balancer (system throughput behind the ELB)

–  a metric to know the number ofrequest arrived at the load balancer is missing

•  General Problems

–  no real-time billing

–  performance level of a single VM is quite variable –  load balancing policy cannot be customized