Build a custom metrics on AWZ cloud

Create custom Cloudwatch metrics on AWZ cloud Ahmad Karawash [email protected]

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Amazon Metrics • Metrics are used to monitor various resources in Amazon Web Services like EBS volumes, EC2 instances and RDS instances.

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AWS resources covered by CloudWatch            

Amazon Ec2 EBS Volumes AutoScaling Groups Elastic load Balancers Amazon Route 53 RDS DB instances DynamoDB tables ElastiCache clusters RedShift clusters SQS queues SNS topics Storage Gateways 12/23/2015

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Example of available metrics • Memory Utilization – Memory allocated by applications and the operating system, exclusive of caches and buffers, in percentages. • Memory Used – Memory allocated by applications and the operating system, exclusive of caches and buffers, in megabytes. • Memory Available – System memory available for applications and the operating system, in megabytes. • Disk Space Utilization – Disk space usage as percentages. • Disk Space Used – Disk space usage in gigabytes. • Disk Space Available – Available disk space in gigabytes. • Swap Space Utilization – Swap space usage as a percentage. • Swap Space Used – Swap space usage in megabytes. 12/23/2015

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Cloudwatch advantage • AWS provides some additional monitoring scripts for adding custom Cloudwatch metrics.

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Use case Example • A user might have to take automated actions based on a particular parameter. This parameter can be the number of active users in a system which can be stored in an RDS instance. A script can be used to measure this value and if the number of users is zero for a particular time period, an alarm needs to be triggered and the EC2 instance needs to be terminated.

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Prerequisites • Install python • Sudo apt-get install python python dev • Sudo apt-get install python-pip

• Install boto • Sudo pip install boto

• Create RDS Database or local Database for the new custom metric, for example RoomTemperatureDatabase.

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put_metric_data • put_metric_data ( $namespace, $metric_data, $opt ): Publishes metric data points to Amazon CloudWatch. Amazon Cloudwatch associates the data points with the specified metric. If the specified metric does not exist, Amazon CloudWatch creates the metric. • If you create a metric with the PutMetricData action, allow up to fifteen minutes for the metric to appear in calls to the ListMetrics action.

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RoomTemperatureMeasure Database

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Create a Custom Metric and connect to external database Run the python code from Ubuntu console: (how to run check: https://www.youtube.com/watch?v=zKUu4in858A} 1. from boto.ec2.cloudwatch import connect_to_region 2. import MySQLdb 3. import boto.ec2.cloudwatch 4. db=MySQLdb.connect(“Public DNS","username","password","databasename") 5. cursor=db.cursor() 6. n=cursor.execute(" select value from Temperature ORDER BY id DESC LIMIT 1 ") 7. n1=cursor.fetchone()

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Create a Custom Metric and connect to external database 8. 9. 10. 11. 12. 13.

s=str(n1) table=string.maketrans( '', '', ) number=s.translate(table,"(){},L") numbers=int(number) reg='ap-west-1' conn_cw=boto.ec2.cloudwatch.connect_to_region(reg, aws_access_key_id=’your_access_key’,aws_secret_access_key=’your_secret_k ey’) 14. conn_cw.put_metric_data(namespace='my_namespace',name='my_metric',val ue=numbers,dimensions={'InstanceId':‘instance-val'}) 12/23/2015

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Create a Custom Cloudwatch Metric • After you connect successively to the database, “put-metric-data” method will add instance of a new custom metric into you cloudwatch

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How to check whether the custom metric was created

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How to check whether the custom metric was created

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Creating a CloudWatch alarm for the custom metric • Now you can monitor you own metric using Cloudwatch • For example, you can add alarm: 1. from boto.ec2.cloudwatch import connect_to_region 2. import boto.ec2.cloudwatch 3. metric=cw.list_metrics(dimensions={'InstanceId':’ia1b2c3d4’},metric_name='my_metric')[0] 4. metric.create_alarm(name='my_alarm', comparison='