Skew is a package for identifying and enumerating cloud resources.
The name is a homonym for SKU (Stock Keeping Unit). Skew allows you to
define different SKU schemes which are a particular encoding of a
SKU. Skew then allows you to use this scheme pattern and regular expressions
based on the scheme pattern to identify and enumerate a resource or set
of resources.
At the moment, the the only available scheme is the ARN scheme.
The ARN scheme uses the basic structure of
Amazon Resource Names (ARNs) to assign a unique identifier to every AWS
resource.
An example ARN pattern would be:
arn:aws:ec2:us-west-2:123456789012:instance/i-12345678
This pattern identifies a specific EC2 instance running in the us-west-2
region under the account ID 123456789012. The account ID is the 12-digit
unique identifier for a specific AWS account as described
here.
To allow skew to find your account number, you need to create a skew
YAML config file. By default, skew will look for your config file in
~/.skew but you can use the SKEW_CONFIG environment variable to tell skew
where to find your config file if you choose to put it somewhere else. The
basic format of the skew config file is:
---
accounts:
"123456789012":
profile: dev
"234567890123":
profile: prodWithin the accounts section, you create keys named after your 12-digit
account ID (as a string). Within that, you must have an entry called profile
that lists the profile name this account maps to within your AWS credential
file.
The main purpose of skew is to identify resources or sets of resources across services, regions, and accounts and to quickly and easily return the data associated with those resources. For example, if you wanted to return the data associated with the example ARN above:
from skew import scan
arn = scan('arn:aws:ec2:us-west-2:123456789012:instance/i-12345678')
for resource in arn:
print(resource.data)The call to scan returns an ARN object which implements the
iterator pattern
and returns a Resource object for each AWS resource that matches the
ARN pattern provided. The Resource object contains all of the data
associated with the AWS resource in dictionary under the data attribute.
Any of the elements of the ARN can be replaced with a regular expression.
The simplest regular expression is * which means all available choices.
So, for example:
arn = scan('arn:aws:ec2:us-east-1:*:instance/*')would return an iterator for all EC2 instances in the us-east-1 region
found in all accounts defined in the config file.
To find all DynamoDB tables in all US regions for the account ID 234567890123 you would use:
arn = scan('arn:aws:dynamodb:us-.*:234567890123:table/*')In addition to making the metadata about a particular AWS resource available
to you, skew also tries to make it easy to access the available CloudWatch
metrics for a given resource.
For example, assume that you had did a scan on the original ARN above
and had the resource associated with that instance available as the variable
instance. You could do the following:
>>> instance.metric_names
['CPUUtilization',
'NetworkOut',
'StatusCheckFailed',
'StatusCheckFailed_System',
'NetworkIn',
'DiskWriteOps',
'DiskReadBytes',
'DiskReadOps',
'StatusCheckFailed_Instance',
'DiskWriteBytes']
>>>The metric_names attribute returns the list of available CloudWatch metrics
for this resource. The retrieve the metric data for one of these:
>>> instance.get_metric_data('CPUUtilization')
[{'Average': 0.134, 'Timestamp': '2014-09-29T14:04:00Z', 'Unit': 'Percent'},
{'Average': 0.066, 'Timestamp': '2014-09-29T13:54:00Z', 'Unit': 'Percent'},
{'Average': 0.066, 'Timestamp': '2014-09-29T14:09:00Z', 'Unit': 'Percent'},
{'Average': 0.134, 'Timestamp': '2014-09-29T13:34:00Z', 'Unit': 'Percent'},
{'Average': 0.066, 'Timestamp': '2014-09-29T14:19:00Z', 'Unit': 'Percent'},
{'Average': 0.068, 'Timestamp': '2014-09-29T13:44:00Z', 'Unit': 'Percent'},
{'Average': 0.134, 'Timestamp': '2014-09-29T14:14:00Z', 'Unit': 'Percent'},
{'Average': 0.066, 'Timestamp': '2014-09-29T13:29:00Z', 'Unit': 'Percent'},
{'Average': 0.132, 'Timestamp': '2014-09-29T13:59:00Z', 'Unit': 'Percent'},
{'Average': 0.134, 'Timestamp': '2014-09-29T13:49:00Z', 'Unit': 'Percent'},
{'Average': 0.134, 'Timestamp': '2014-09-29T13:39:00Z', 'Unit': 'Percent'}]
>>>You can also customize the data returned rather than using the default settings:
>>> instance.get_metric_data('CPUUtilization', hours=8, statistics=['Average', 'Minimum', 'Maximum'])
[{'Average': 0.132,
'Maximum': 0.33,
'Minimum': 0.0,
'Timestamp': '2014-09-29T10:54:00Z',
'Unit': 'Percent'},
{'Average': 0.134,
'Maximum': 0.34,
'Minimum': 0.0,
'Timestamp': '2014-09-29T14:04:00Z',
'Unit': 'Percent'},
...,
{'Average': 0.066,
'Maximum': 0.33,
'Minimum': 0.0,
'Timestamp': '2014-09-29T08:34:00Z',
'Unit': 'Percent'},
{'Average': 0.134,
'Maximum': 0.34,
'Minimum': 0.0,
'Timestamp': '2014-09-29T08:04:00Z',
'Unit': 'Percent'}]
>>>Each resource that is retrieved is a Python dictionary. Some of these (e.g.
an EC2 Instance) can be quite large and complex. Skew allows you to filter
the data returned by applying a jmespath query to
the resulting data. If you aren't familiar with jmespath, check it out.
Its a very powerful query language for JSON data and has full support in
Python as well as a number of other languages such as Ruby, PHP, and
Javascript. It is also the query language used in the
AWSCLI so if you are familiar with the
--query option there, you can use the same thing with skew.
To specify a query to be applied to results of a scan, simply append
the query to the end of the ARN, separated by a | (pipe) character.
For example:
arn:aws:ec2:us-west-2:123456789012:instance/i-12345678|InstanceType
Would retrieve the data for this particular EC2 instance and would then
filter the returned data through the (very) simple jmespath query to which
retrieves the value of the attribute InstanceType within the data. The
filtered data is available as the filtered_data attribute of the
Resource object. The full, unfiltered data is still available as the
data attribute.
Skew is single-threaded by default, like most Python libraries. In order to speed up the enumeration of matching resources, you can use multiple threads:
import skew
class Worker(Thread):
def __init__(self, arn):
Thread.__init__(self)
self.arn = arn
self.name = arn
def run(self):
for i in skew.scan(self.arn):
# now do something with the stuff
arn = skew.ARN()
for service in arn.service.choices():
uri = 'arn:aws:' + service + ':*:*:*/*'
worker = Worker(uri);
worker.start()(thanks to @alFReD-NSH for the snippet)