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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)

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!"#$%&'=>8'•  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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=>8'1%/#?%&0'•  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

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=>8'9&04#&/)'@AB)0'•  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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Load Balancing

=>8'9&4),G#/)'•  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

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!"#$%&'=3#0?/'U3%/V'+4%,)'•  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

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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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!"#$%&'>3%2;(#4/E'•  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

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>3%2;(#4/E'/%&/)B40'•  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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>3%2;(#4/E'")4,./0'•  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

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>3%2;(#4/E'9&4),G#/)'•  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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>3%2;(#4/E'!3#,"0'n'!24%'+/#3.&6'•  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

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!24%'+/#3.&6'•  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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!24%'+/#3.&6':%3./.)0'•  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)

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=3#0?/'1%#;'U#3#&/.&6'•  Automatically distributes incoming traffic across multiple

EC2 instances

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=1U'G)#42,)0'•  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!

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=b#"B3)a'`);.#Q.V.'%&'=>8'•  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

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=b#"B3)a'@)04*);'0)42B'•  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%

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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

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