srinivasreddych / aws-dataset-ingestion-metrics-collection-framework

Welcome to Dataset Ingestion Metrics Collection Framework.

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Understanding the directory structure with respect to the root of the repository:

DirectoryName	Description
accounts/	Stores the accounts landscape for the application together with supporting functions.
cdk_constructs/	This directory holds all the L3 constructs which will be leveraged in the CDK Stacks.
dataquality/	This directory holds the modules which will be leveraged to generate Metrics and Alarms.
definitions/	The metrics which needs to be scraped and alarms which needs to be generated should be declared under this directory across accounts.
glue/	Stores the dependency files for Glue jobs, including scripts, jars, etc.
lambda/	Stores the dependency files for Lambda functions.
stacks/	This directory holds the CDK Stacks, which would be instantited from app.py file.

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Understanding a sample Metric definition under definitions/account/ in detail:

metric_set = MetricSet("sample")

metric = Metric(
        metric_set: Metricset object,
        namespace: string,
        name: string,
        frequency: enum,
        statistic: string,
        dashboard: dashboard object
        metadata: Metadata object
        dimensions: Dimensions object
    )

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Properties

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metric_set

MetricSet can be instantiated with the group of metrics which belongs to a data-set. The assigned object should be provided to the key metric_set

Required: Yes

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namespace

namespace maps to the AWS CloudWatch Namespace which is either availabe by default or created by a user(custom namespace).

Required: Yes

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name

name maps to the AWS CloudWatch Metric name which is either availabe as a default or a custom metric.
Required: Yes

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frequency

frequency helps a user declare the frequency at which the declared metric would be scraped and streamed by the metric-streamer lambda.
Required: Yes

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statistic

statistic helps a user declare a valid statistic from the supporrted statistics. Required: Yes

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dashboard

dashboard helps a user create an AWS CloudWatch dashboard providing the dashboard_name and dashboard_category. Within AWS CloudWatch dashboards, there is no functionality which provides categorization/relationship between different dashboards and in order to bridge that gap, dashboard_category can be used to determine the category type and add relevant dashboards using dashboard_name under it.

dashboard_name can be used to map to a data-set (if applies)
dashboard_category can be used to map to a data-source (if applies)

Required: Yes

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metadata

metadata helps a user declare custom meta-data that could be streamed which helps from the reporting/querying perspective.

Required: Optional

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dimensions

dimensions helps a user declare the Dimesions under which AWS CloudWatch metric isn available under.

Required: Optional

---

Understanding a sample SLA definition under definitions/account/ in detail:

sla_set = SLASet()

sla = SLA(
    sla_set: sla_set object
    metric: metric object,
    threshold: int,
    comparison_operator: string,
    details: str,
    short_description: str,
    severity: str,
    central_sns_enabled: bool
)

---

Properties

---

sla_set

SLASet can be instantiated with the group of SLAs which belongs to a data-set. The assigned object should be provided to the key sla_set

Required: Yes

---

threshold

threshold maps to the AWS CloudWatch MetricAlarm's attribute Threshold, which decides the CloudWatch alarming action relative to the datapoints received.

Required: Yes

---

comparison_operator

comparison_operator maps to the AWS CloudWatch MetricAlarm's attribute ComparisonOperator, which is used when comparing the specified statistic and threshold.
Required: Yes

---

severity

severity helps a user declare the custom severity.
Required: Optional

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details

details helps a user declare what details should be published to the SIM/TT, when the threshold is breached.

Example: Location to the playbook that needs to be followed when the threshold is breached.
Required: Yes

---

short_description

short_description helps a user declare description about the breached activity, which would be published to the SIM/TT.

Required: Yes

central_sns_enabled

central_sns_enabled helps a user to control alarm events flow to the central sns topic.

Required: Optional

---

Examples

How to define a metric definition?

metric_set = MetricSet("dataset-1")
dashboard = Widget(dashboard_name='dataset-1', dashboard_category='data-project')

test_metric = Metric(
        metric_set=metric_set,
        namespace='AWS/Lambda',
        name='Invocations',
        frequency=Metric.DAY,
        statistic='Average',
        dashboard=dashboard,
        metadata=[
            Metadata(
                name='Account',
                value='Ingest'
            ),
            Metadata(
                name='Dataset',
                value='dataset-1'
            )
        ],
        dimensions=[
            Dimension(
                name='FunctionName',
                value='hello-world'
            )
        ]
    )

How to define an SLA definition?

sla_set = SLASet()

sla = SLA(
    sla_set = sla_set,
    metric= test_metric,
    threshold=1,
    comparison_operator="LESS_THAN_OR_EQUAL_TO_THRESHOLD",
    details = 'What details should i let a user when the SLA is breached?',
    short_description = 'Short description about the breaching activity',
    severity = "SEV_4",
    central_sns_enabled = True
)

Security See CONTRIBUTING for more information.

License This library is licensed under the MIT-0 License. See the LICENSE file.