1. –filter parameter can get filtering properties directly from the command line:

aws ec2 describe-instances --filter Name="instance-id",Values="i-1234abcd"

2. –filter parameter will also use JSON-encoded filter file:

aws ec2 describe-instances --filters file://filters.json

The filters.json file uses the following structure:

[
  {
    "Name": "instance-type",
    "Values": ["m1.small", "m1.medium"]
  },
  {
    "Name": "availability-zone",
    "Values": ["us-west-2c"]
  }
]

There are various AWS CLI components that provide –filter parameters. For additional information check the References section.

To demonstrate the way this functionality can be used in various scenarios, there are several examples:

1. Filter by availability zone:

aws ec2 describe-instances --filter Name="availability-zone",Values="us-east-1b"

2. Filter by security group (EC2-Classic):

aws ec2 describe-instances --filter Name="group-name",Values="default"

3. Filter by security group (EC2-VPC):

aws ec2 describe-instances --filter Name="instance.group-name",Values="default"

4. Filter only spot instances

aws ec2 describe-instances --filter Name="instance-lifecycle",Values="spot"

5. Filter only running EC2 instances:

aws ec2 describe-instances --filter Name="instance-state-name",Values="running"

6. Filter only stopped EC2 instances:

aws ec2 describe-instances --filter Name="instance-state-name",Values="stopped"

7. Filter by SSH Key name

aws ec2 describe-instances --filter Name="key-name",Values="ssh-key"

8. Filter by Tag:

aws ec2 describe-instances --filter "Name=tag-key,Values=Name" "Name=tag-value,Values=string"

9. Filter by Tag with a wildcard (‘*’):

aws ec2 describe-instances --filter "Name=tag-key,Values=MyTag" "Name=tag-value,Values=abcd*efgh"

10. Filter by multiple criteria (all running instances with string ’email’ in the value of the Name tag):

aws ec2 describe-instances --filter "Name=instance-state-name,Values=running" "Name=tag-key,Values=Name" "Name=tag-value,Values=*email*"

11. Filter by multiple criteria (all running instances with empty Name tag);

aws ec2 describe-instances --filter "Name=instance-state-name,Values=running" "Name=tag-key,Values=Name" "Name=tag-value,Values=''"

Those examples are very close to production ones used in several large AWS deployments. They are used to:

• Monitor changes in instance populations;
• Monitor successful configuration of resources;
• Track deployment / rollout of new software version;
• Track stopped instances to prevent unnecessary resource usage;
• Ensure desired service distributions over availability zones and regions;
• Ensure service distribution over instances with different lifecycle;

Be sure to utilize this functionality in your monitoring infrastructure. It has been powerful source of operational insights and great source of raw data for our intelligent control planes!

If you want to talk more on this subject or just share your experience, do not hesitate to Contact Us!

References

• http://docs.aws.amazon.com/cli/latest/reference/ec2/describe-instances.html
• http://docs.aws.amazon.com/cli/latest/reference/ec2/describe-spot-instance-requests.html
• http://docs.aws.amazon.com/cli/latest/reference/ec2/describe-reserved-instances.html
• http://docs.aws.amazon.com/cli/latest/reference/ec2/describe-network-acls.html
• http://docs.aws.amazon.com/cli/latest/reference/ec2/describe-key-pairs.html
• http://docs.aws.amazon.com/cli/latest/reference/ec2/index.html

Default documentation (http://docs.aws.amazon.com/cli/latest/reference/ec2/run-instances.html) although a good start is somewhat limited. Several tips and tricks will be presented here.

The location of the JSON block device mapping specification can be quite flexible. The mappings can be supplied:

1. Using command line directly:

--block-device-mappings '[ {"DeviceName":"/dev/sdb","VirtualName":"ephemeral0"}, {"DeviceName":"/dev/sdc","VirtualName":"ephemeral1"}]'

2. Using file as a source:

--block-device-mappings file:////home/ec2-user/mapping.json

3. Using URL as a source:

--block-device-mappings http://mybucket.s3.amazonaws.com/mapping.json

Source: http://understeer.hatenablog.com/entry/2013/10/18/223618

Other common scenarios:

1. To reorder default ephemeral volumes to ensure stability of the environment:

[
  {
    "DeviceName": "/dev/sde",
    "VirtualName": "ephemeral0"
  },
  {
    "DeviceName": "/dev/sdf",
    "VirtualName": "ephemeral1"
  }
]

NOTE: Useful for additional UserData processing or deployments with hardcoded settings.

2. To allocate additional EBS Volume with specific size (100GB), to be associated with the EC2 instance:

[
  {
    "DeviceName": "/dev/sdg",
    "Ebs": {
      "VolumeSize": 100
    }
  }
]

NOTE: Useful for cases where cheaper instance types are outfitted with big volumes (Disk intensive tasks run on low-CPU/MEM instance types).

3. To allocate new volume from Snapshot ID:

[
  {
    "DeviceName": "/dev/sdh",
    "Ebs": {
      "SnapshotId": "snap-xxxxxxxx"
    }
  }
]

NOTE: Useful to pre-loading newly created instances with specific disk data and still retaining the ability to modify the local copy.

4. To omit mapping of a particular Device Name:

[
  {
    "DeviceName": "/dev/sdj",
    "NoDevice": ""
  }
]

NOTE: Useful to overwrite default AWS behavior.

5. To allocate new EBS Volume with explicit termination behavior (Keep after instance termination):

[
  {
    "DeviceName": "/dev/sdc",
    "Ebs": {
      "VolumeSize": 10,
      "DeleteOnTermination": false
    }
  }
]

NOTE: Useful to keep instance data after termination, additional cost may be significant if those volumes are not released after examination.

6. To allocate new, encrypted, EBS Volume with Reserved IOPS:

[
  {
    "DeviceName": "/dev/sdc",
    "Ebs": {
      "VolumeSize": 10,
      "VolumeType": "io1",
      "Iops": 1000,
      "Encrypted": true
    }
  }
]

NOTE: Useful to set minimum required performance levels (I/O Operations Per Second) for the specified volume.

Outlined functionality should cover wide range of potentially use cases for DevOps engineers who want to use automation to customize their infrastructure. Flexible instance volume management is a key ingredient for successful implementation of the ‘Infrastructure-as-Code’ paradigm!

References

• http://docs.aws.amazon.com/cli/latest/reference/ec2/run-instances.html
• http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/block-device-mapping-concepts.html
• http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-ec2-blockdev-mapping.html
• http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EBSVolumeTypes.html
• http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EBSEncryption.html

AWS provides proper command line interface, aws ec2 request-spot-instances exposes multiple options to the user. However, some of the common use cases are not comprehensively covered in the documentation. For example, creating Spot Instances with Userdata using the command line tools is somewhat obscure and convoluted, although common need in DevOps and Developers lives. The tricky part: It must be BASE64 encoded!

Assume the following, simple UserData script, must be deployed on numerous EC2 Spot Instances:

#!/bin/bash -ex

# Debian apt-get install function
apt_get_install()
{
        DEBIAN_FRONTEND=noninteractive apt-get -y \
        -o DPkg::Options::=--force-confdef \
        -o DPkg::Options::=--force-confold \
        install $@
}

# Mark execution start
echo "STARTING" > /root/user_data_run

# Some initial setup
set -e -x
export DEBIAN_FRONTEND=noninteractive
apt-get update && apt-get upgrade -y

# Install required packages
apt_get_install nginx

# Create test html page
mkdir /var/www
cat > /var/www/index.html << "EOF"

        
                
                

        
                
Demo Page

                Status: running
        

EOF

# Configure NginX
cat > /etc/nginx/conf.d/demo.conf << "EOF"
# Minimal NginX VirtualHost setup
server {
        listen 8080;

        root /var/www;
        index index.html index.htm;

        location / {
                try_files $uri $uri/ =404;
        }
}
EOF

# Restart NginX with the new settings
/etc/init.d/nginx restart

# Mark execution end
echo "DONE" > /root/user_data_run

Make sure base64 command is available in your system, or use equivalent, to encode the sample userdata.sh file before passing to the launch specification:

aws ec2 request-spot-instances \
    --spot-price 0.01 \
    --instance-count 2 \
    --launch-specification \
        "{ \
            \"ImageId\":\"ami-a6926dce\", \
            \"InstanceType\":\"m3.medium\", \
            \"KeyName\":\"test-key\", \
            \"SecurityGroups\": [\"test-sg\"], \
            \"UserData\":\"`base64 userdata.sh`\" \
        }"

In this example two spot instance requests will be created for m3.medim instances, using ami-a6926dce AMI, test-key SSH key, running in test-sg Security Group. BASE64-encoded contents of userdata.sh will be attached to the request so upon fulfillment the Userdata will be passed to the newly created instances and executed after boot-up.

Spot instance requests will be created in the AWS EC2 Dashboard:

Once the Spot Instance Requests (SIRs) are fulfilled, InstanceID will be associated for each SIR:

EC2 Instances dashboard will show newly created Spot Instances (notice the “Lifecycle: spot” in Instance details):

Using the proper credentials, one can verify successful execution of the userdata.sh on each instance:

:~> ssh -i ~/.ssh/test-key.pem ubuntu@ec2-54-211-6-104.compute-1.amazonaws.com "tail /var/log/cloud-init-output.log"
Setting up nginx (1.4.6-1ubuntu3) ...
Processing triggers for libc-bin (2.19-0ubuntu6) ...
+ mkdir /var/www
+ cat
+ cat
+ /etc/init.d/nginx restart
 * Restarting nginx nginx
   ...done.
+ echo DONE
Cloud-init v. 0.7.5 finished at Sat, 12 Jul 2014 18:17:09 +0000. Datasource DataSourceEc2.  Up 76.38 seconds
:~>

… and more importantly, if the configured service works as expected:

:~> curl http://ec2-54-211-6-104.compute-1.amazonaws.com:8080/

        
                
                

        
                
Demo Page

                Status: running
        

:~>

Newly created Spot Instances are serving traffic, running at 0.01 USD/hr and will happily do so until the market price for this instance type goes above the specified price!

References

• http://docs.aws.amazon.com/cli/latest/reference/ec2/request-spot-instances.html

1. t2.micro
2. t2.small
3. t2.medium

Those instance types are all “Burstable Performance Instances” which means they are suitable for unsustained loads. This is also supported by the EBS Only store, which effectively means that high-volume I/O is out of the question. The fact that those instances are all using HVM-based virtualization, however, supports quick SCALE-UP to more potent instance types, if needs arise. One notable remark here is that T2 instances are VPC-only, which is a strong indication of the will to move everything into VPCs nowadays. AWS wants you to start using VPCs from the start!

The instance resource matrix now looks like this:

As stated by AWS, the target uses for the new, T2 instance type family, includes:

• Development environments;
• Private experimentation;
• Educational use;
• Build servers / Code repositories;
• Low-traffic web applications;
• Small databases.

To evaluate the meaning of “Burstable Performance Instances“, here are CPU benchmark results on several instance instance types:

All instances use detault settings for storage, Amazon Linux AMI 2014.03.2, John The Ripper 1.8.0, measuring real crypts with many salts! The test is fairly synthetic, but answers the key question: What difference does it make to have a Burstable instance type? And the answer: If CPU load is not sustainable, it’s more than twice as fast!

Price-wise the new instance types are also better. Cost reduction of On Demand prices of more than 35% allows you to run t2.micro for less than 10 USD/m! Watch out, DigitalOcean! Obviously, Amazon wants change the already established “AWS for business, DigitalOcean for home” mantra into “AWS Everywhere”.

In conclusion, the new, T2 instance type family, closes the gap between unacceptably low performance instance type (t1.micro) and too expensive instances types (m1.small, m3.medium) which creates the sweet-spot for entry users, cloud enthusiast and home users. As someone said: “Now you have an instance type to run WordPress on!”

In a typical Python / Web-scale environment multiple components will be implemented in a de-coupled, micro-services, REST-based architecture. One of the popular frameworks for REST is Bottle. And there are multiple approaches to build services with Bottle when full-blown HTTP Server is available (Apache, NginX, etc.) or if performance matters. All of those are valid and somewhat documented. But still, there is the case (and it more common than one would think) when developer will create Bottle server to handle simple task and it will propagate into production, using ugly solution like Screen/TMUX or even nohup. Here is a way to put this under proper control.

Test Server code: test-server.py

#!/usr/bin/env python

# Description: Demo Bottle Server to demonstrate use of SupervisorD
#
# How to run:
#       test-server.py -c test-server.conf
#
# Exepects the following configuration file:
#
#       server:
#               bind_ip: 0.0.0.0
#               bind_port: 8080
#
#       configuration_variable: true
#

import argparse
import time
import yaml
import sys

from bottle import route, run, template

# GET: /
@route('/')
def index():
        static_page = """


        


        
Test Server is working!


        """
        return static_page

# Return the server->bind_ip value from the parsed configuration
def get_bind_ip(config):
        if config:
                return config['server']['bind_ip']
        else:
                return None

# Return the server->bind_port value from the parsed configuation
def get_bind_port(config):
        if config:
                return config['server']['bind_port']
        else:
                return None

# Return sample configuration variable
def get_config_data(config):
        if config:
                return config['configuration_variable']
        else:
                return None

# Main entry point for the application
def main():
        """ Main Entry Point for the appliation """

        # Parse command line arguments
        parser = argparse.ArgumentParser(description='Demo Server using Bottle')
        parser.add_argument('-c', '--config', type=str, required=True, dest='config', help='Configuration File Location')

        args = parser.parse_args()
        conf_file = args.config

        # Check config file accessibility
        try:
                conf_fd = open(conf_file, 'r')
        except IOError as e:
                if e.errno == errno.EACCES or e.errno == errno.ENOENT:
                        print("{progname}: Unable to read the configuration file ({config})!".format(progname=sys.argv[0], config=conf_file))
                        sys.exit(1)
        else:
                with conf_fd:
                        config = yaml.load(conf_fd)
                        conf_fd.close()

        # Get configuration data
        bind_ip = get_bind_ip(config)
        bind_port = get_bind_port(config)

        if bind_ip == None or bind_port == None:
                print("{progname}: Required configuration variable is unavailable!".format(progname=sys.argv[0]))
                sys.exit(1)

        config_data = get_config_data(config)

        # Run the web-server
        if config_data == True:
                run(host=bind_ip, port=bind_port)

if __name__ == '__main__':
    main()

Test server configuration file: test-server.conf

# Sample configuration file in YAML format for test-server.py

server:
    bind_ip: 0.0.0.0
    bind_port: 8080

configuration_variable: true

Manual execution of the server code will looks like this:

ubuntu@ip-10-67-161-137:~/test-server$ ./test-server.py -c test-server.conf
Bottle v0.12.0 server starting up (using WSGIRefServer())...
Listening on http://0.0.0.0:8080/
Hit Ctrl-C to quit.

94.155.194.28 - - [23/Jun/2014 12:34:39] "GET / HTTP/1.1" 200 126
^C
ubuntu@ip-10-67-161-137:~/test-server$

When the controlling terminal is lost the server will be terminated. Obviously, this is neither acceptable, nor desirable behavior.

With SupervisorD (sudo aptitude install supervisor) the service can be properly managed using simple configuration file.

Example SupervisorD configuration file: /etc/supervisor/conf.d/test-server.conf

[program:test-server]
command=/home/ubuntu/test-server/test-server.py -c /home/ubuntu/test-server/test-server.conf
user=ubuntu
redirect_stderr=true

To start the service, execute:

ubuntu@ip-10-67-161-137:~$ sudo supervisorctl start test-server
test-server: started
ubuntu@ip-10-67-161-137:~$

To verify successful service start:

ubuntu@ip-10-67-161-137:~$ ps ax
. . . 
 4353 ?        Ss     0:00 /usr/bin/python /usr/bin/supervisord -c /etc/supervisor/supervisord.conf
 4355 ?        S      0:00 python /home/ubuntu/test-server/test-server.py -c /home/ubuntu/test-server/test-server.conf
. . .
ubuntu@ip-10-67-161-137:~$

SupervisorD will redirect stdout and stderr to properly named log files:

ubuntu@ip-10-67-161-137:~$ sudo cat /var/log/supervisor/test-server-stdout---supervisor-ssaGXP.log
Bottle v0.12.0 server starting up (using WSGIRefServer())...
Listening on http://0.0.0.0:8080/
Hit Ctrl-C to quit.

94.155.194.28 - - [23/Jun/2014 13:31:19] "GET / HTTP/1.1" 200 126
ubuntu@ip-10-67-161-137:~$

Those log files can be integrated with a centralized logging architecture or processed for error / anomaly detection separately.

SupervisorD also comes with handy, command-line control utility, supervisorctl:

ubuntu@ip-10-67-161-137:~$ sudo supervisorctl status test-server
test-server                      RUNNING    pid 4355, uptime 0:11:40
ubuntu@ip-10-67-161-137:~$

With some additional effort SupervisorD can react to various types of events (http://supervisord.org/events.html) which bring it one step closer to full process monitoring & notification solution!

References

• SupervisorD Homepage: http://supervisord.org
• Bottle Web Framework: http://bottlepy.org/docs/dev/index.html

To gather some results the following script was created: https://s3-us-west-2.amazonaws.com/blog.xi-group.com/aws-ebs-allocation-times/aws-single.sh. It will create one instance of the specified type with N GB of Root EBS volume, wait for the instance to properly start and then terminate it. The time for the whole process is measured (e.g. full ‘time-to-service’).

The script was run multiple times for each instance type and EBS volume size. Results are presented in the following table:

Graphical representation:

As shown, instance start time grows linearly with the size of the EBS Root volume. Moral of the story:

NOTE: The whole procedure is reasonably time consuming if you gather multiple data points (in this case, for each instance type / volume size the script was run 3 times and the average value is shown). It will cost money, since all EC2 allocations will be charged for at least an hour. The script, provided here is ‘AS IS’ and can be used as reference. Be sure to understand it and properly modify it before running it!

Not a problem, just a challenge!

We prefer to use UserData for automatic server setup. After some attempts it became clear that partitioning disks from a shell script is not exactly trivial tasks under Linux in AWS. BSD-based operating systems come with disklabel and fdisk and those will do the job. Linux comes with fdisk by default and that tool is somewhat limited …

Luckily, fdisk reads data from stdin so quick-and-dirty solution quickly emerged!

The following UserData is used to modify the instance store of a m3.large instance, creating 8GB swap partition and re-mounting the rest as /mnt:

#!/bin/bash -ex

# Mark execution start
echo "STARTING" > /root/user_data_run

# Unmount /dev/xvdb if already mounted
umount -f /dev/xvdb

# Partition the disk (8GB for SWAP / Rest for /mnt)
(echo n; echo p; echo 1; echo 2048; echo +8G; echo t; echo 82; echo n; echo p; echo 2; echo; echo; echo w) | fdisk /dev/xvdb

# Make and enable swap
mkswap /dev/xvdb1
swapon /dev/xvdb1

# Make /mnt partition and mount it
mkfs.ext4 /dev/xvdb2
mount /dev/xvdb2 /mnt
sed -i s/xvdb/xvdb2/g /etc/fstab

# Mark execution end
echo "DONE" > /root/user_data_run

Execute it with AWS CLI (Using stock Ubuntu 14.04 HVM AMI):

aws ec2 run-instances --image-id ami-1d8c9574 --count 1 --instance-type m3.large --key-name test-key --security-groups test-sg --user-data file://userdata.sh

The result:

:~> ssh ubuntu@ec2-54-197-66-121.compute-1.amazonaws.com "df -h"
Filesystem      Size  Used Avail Use% Mounted on
/dev/xvda1      7.8G  765M  6.6G  11% /
none            4.0K     0  4.0K   0% /sys/fs/cgroup
udev            3.7G   12K  3.7G   1% /dev
tmpfs           749M  336K  748M   1% /run
none            5.0M     0  5.0M   0% /run/lock
none            3.7G     0  3.7G   0% /run/shm
none            100M     0  100M   0% /run/user
/dev/xvdb2       22G   44M   21G   1% /mnt
:~> ssh ubuntu@ec2-54-197-66-121.compute-1.amazonaws.com "free -h"
             total       used       free     shared    buffers     cached
Mem:          7.3G       276M       7.0G       352K       8.6M       177M
-/+ buffers/cache:        90M       7.2G
Swap:         8.0G         0B       8.0G
:~>

There it is, 8GB swap partition (/dev/xvdb1) and the rest (/dev/xvdb2) mounted as /mnt. Note that /etc/fstab is also updated to account for the device name change!

There is a solution. It lies in the –block-device-mappings parameter that can be passed to aws ec2 run-instances command.

According to the documentation this parameter uses JSON-encoded block device mapping to adjust different parameter of the instances that are being started. There is a simple example that shows how to attach additional volume:

--block-device-mappings "[{\"DeviceName\": \"/dev/sdh\",\"Ebs\":{\"VolumeSize\":100}}]"

This will attach additional 100GB EBS volume as /dev/sdb. The key part: “Ebs”: {“VolumeSize”: 100}

By specifying your instance’s root partition you can adjust the root partition size. Following is an example how to create Amazon Linux instance running on t1.micro with 32GB root partition:

aws ec2 run-instances --image-id ami-fb8e9292 --count 1 --instance-type t1.micro --key-name test-key --security-groups test-sg --block-device-mapping "[ { \"DeviceName\": \"/dev/sda1\", \"Ebs\": { \"VolumeSize\": 32 } } ]"

The resulting volume details show the requested size and the fact that this is indeed root partition:

Confirming, that the instance is operating on the proper volume:

:~> ssh ec2-user@ec2-50-16-57-145.compute-1.amazonaws.com "df -h"
Filesystem      Size  Used Avail Use% Mounted on
/dev/xvda1       32G  1.1G   31G   4% /
devtmpfs        282M   12K  282M   1% /dev
tmpfs           297M     0  297M   0% /dev/shm
:~>

There is enough space in the root partition now. Note: This is EBS volume, additional charges will apply!

References

• aws ec2 run-instances help

Lets start with simple example …

We have the following EC2 instances in AWS Account:

Search for the term ‘TEST-NODE’ yields the same results as searching for ‘test-node’ in the AWS Web interface.

Searching for ‘TEST-NODE':

Searching for ‘test-node':

… it behaves the same way. It is case-insensitive.

However, commend line tools will produce totally different output.

Searching for ‘TEST-NODE':

:~> aws ec2 describe-instances --filters "Name=tag:Name,Values=*TEST-NODE*" --query 'Reservations[*].Instances[*].Tags[?Key==`Name`].Value[]' --output text
TEST-NODE-1
:~>

Searching for ‘test-node':

:~> aws ec2 describe-instances --filters "Name=tag:Name,Values=*test-node*" --query 'Reservations[*].Instances[*].Tags[?Key==`Name`].Value[]' --output text
test-node-5
:~>

Python + Boto shows the same behavior (not surprisingly, AWS CLI uses Boto):

Searching for ‘TEST-NODE':

:~> python
Python 2.7.5 (default, Mar  9 2014, 22:15:05)
[GCC 4.2.1 Compatible Apple LLVM 5.0 (clang-500.0.68)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import boto
>>> import boto.ec2
>>> conn = boto.ec2.connect_to_region('us-east-1', aws_access_key_id='', aws_secret_access_key='')
>>> reservations = conn.get_all_instances(filters = {'instance-state-name' : 'running', "tag:Name": "*" + 'TEST-NODE' + "*"})
>>> for r in reservations:
...     for i in r.instances:
...             print i.tags['Name']
...
TEST-NODE-1
>>> ^D
:~>

Searching for ‘test-node':

:~> python
Python 2.7.5 (default, Mar  9 2014, 22:15:05)
[GCC 4.2.1 Compatible Apple LLVM 5.0 (clang-500.0.68)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import boto
>>> import boto.ec2
>>> conn = boto.ec2.connect_to_region('us-east-1', aws_access_key_id='', aws_secret_access_key='')
>>> reservations = conn.get_all_instances(filters = {'instance-state-name' : 'running', "tag:Name": "*" + 'test-node' + "*"})
>>> for r in reservations:
...     for i in r.instances:
...             print i.tags['Name']
...
test-node-5
>>> ^D
:~>

Moral of the story: ALWAYS VERIFY/ENFORCE THAT DATA IS PROPERLY FORMATTED!

There are multiple possible solutions to this issue. With the cost of few extra cycles one can make sure proper comparison is implemented:

:~> python
Python 2.7.5 (default, Mar  9 2014, 22:15:05)
[GCC 4.2.1 Compatible Apple LLVM 5.0 (clang-500.0.68)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import boto
>>> import boto.ec2
>>> conn = boto.ec2.connect_to_region('us-east-1', aws_access_key_id='', aws_secret_access_key='')
>>> reservations = conn.get_all_instances(filters = {'instance-state-name' : 'running'})
>>> for r in reservations:
...     for i in r.instances:
...             if 'test-node'.upper() in i.tags['Name'].upper():
...                     print i.tags['Name']
...
TEST-NODE-1
TEST-Node-2
TEST-node-3
test-node-5
>>> ^D
:~>

References

• http://docs.aws.amazon.com/cli/latest/reference/ec2/describe-instances.html