{ "info": { "author": "Amazon Web Services", "author_email": "", "bugtrack_url": null, "classifiers": [], "description": "## Amazon CloudWatch Construct Library\n\n---\n\n\n![Stability: Stable](https://img.shields.io/badge/stability-Stable-success.svg?style=for-the-badge)\n\n---\n\n\nMetric objects represent a metric that is emitted by AWS services or your own\napplication, such as `CPUUsage`, `FailureCount` or `Bandwidth`.\n\nMetric objects can be constructed directly or are exposed by resources as\nattributes. Resources that expose metrics will have functions that look\nlike `metricXxx()` which will return a Metric object, initialized with defaults\nthat make sense.\n\nFor example, `lambda.Function` objects have the `fn.metricErrors()` method, which\nrepresents the amount of errors reported by that Lambda function:\n\n```python\n# Example may have issues. See https://github.com/aws/jsii/issues/826\nerrors = fn.metric_errors()\n```\n\n### Aggregation\n\nTo graph or alarm on metrics you must aggregate them first, using a function\nlike `Average` or a percentile function like `P99`. By default, most Metric objects\nreturned by CDK libraries will be configured as `Average` over `300 seconds` (5 minutes).\nThe exception is if the metric represents a count of discrete events, such as\nfailures. In that case, the Metric object will be configured as `Sum` over `300 seconds`, i.e. it represents the number of times that event occurred over the\ntime period.\n\nIf you want to change the default aggregation of the Metric object (for example,\nthe function or the period), you can do so by passing additional parameters\nto the metric function call:\n\n```python\n# Example may have issues. See https://github.com/aws/jsii/issues/826\nminute_error_rate = fn.metric_errors(\n statistic=\"avg\",\n period=Duration.minutes(1),\n label=\"Lambda failure rate\"\n)\n```\n\nThis function also allows changing the metric label or color (which will be\nuseful when embedding them in graphs, see below).\n\n> Rates versus Sums\n>\n> The reason for using `Sum` to count discrete events is that *some* events are\n> emitted as either `0` or `1` (for example `Errors` for a Lambda) and some are\n> only emitted as `1` (for example `NumberOfMessagesPublished` for an SNS\n> topic).\n>\n> In case `0`-metrics are emitted, it makes sense to take the `Average` of this\n> metric: the result will be the fraction of errors over all executions.\n>\n> If `0`-metrics are not emitted, the `Average` will always be equal to `1`,\n> and not be very useful.\n>\n> In order to simplify the mental model of `Metric` objects, we default to\n> aggregating using `Sum`, which will be the same for both metrics types. If you\n> happen to know the Metric you want to alarm on makes sense as a rate\n> (`Average`) you can always choose to change the statistic.\n\n## Alarms\n\nAlarms can be created on metrics in one of two ways. Either create an `Alarm`\nobject, passing the `Metric` object to set the alarm on:\n\n```python\n# Example may have issues. See https://github.com/aws/jsii/issues/826\nAlarm(self, \"Alarm\",\n metric=fn.metric_errors(),\n threshold=100,\n evaluation_periods=2\n)\n```\n\nAlternatively, you can call `metric.createAlarm()`:\n\n```python\n# Example may have issues. See https://github.com/aws/jsii/issues/826\nfn.metric_errors().create_alarm(self, \"Alarm\",\n threshold=100,\n evaluation_periods=2\n)\n```\n\nThe most important properties to set while creating an Alarms are:\n\n* `threshold`: the value to compare the metric against.\n* `comparisonOperator`: the comparison operation to use, defaults to `metric >= threshold`.\n* `evaluationPeriods`: how many consecutive periods the metric has to be\n breaching the the threshold for the alarm to trigger.\n\n## Dashboards\n\nDashboards are set of Widgets stored server-side which can be accessed quickly\nfrom the AWS console. Available widgets are graphs of a metric over time, the\ncurrent value of a metric, or a static piece of Markdown which explains what the\ngraphs mean.\n\nThe following widgets are available:\n\n* `GraphWidget` -- shows any number of metrics on both the left and right\n vertical axes.\n* `AlarmWidget` -- shows the graph and alarm line for a single alarm.\n* `SingleValueWidget` -- shows the current value of a set of metrics.\n* `TextWidget` -- shows some static Markdown.\n\n### Graph widget\n\nA graph widget can display any number of metrics on either the `left` or\n`right` vertical axis:\n\n```python\n# Example may have issues. See https://github.com/aws/jsii/issues/826\ndashboard.add_widgets(GraphWidget(\n title=\"Executions vs error rate\",\n\n left=[execution_count_metric],\n\n right=[error_count_metric.with(\n statistic=\"average\",\n label=\"Error rate\",\n color=\"00FF00\"\n )]\n))\n```\n\n### Alarm widget\n\nAn alarm widget shows the graph and the alarm line of a single alarm:\n\n```python\n# Example may have issues. See https://github.com/aws/jsii/issues/826\ndashboard.add_widgets(AlarmWidget(\n title=\"Errors\",\n alarm=error_alarm\n))\n```\n\n### Single value widget\n\nA single-value widget shows the latest value of a set of metrics (as opposed\nto a graph of the value over time):\n\n```python\n# Example may have issues. See https://github.com/aws/jsii/issues/826\ndashboard.add_widgets(SingleValueWidget(\n metrics=[visitor_count, purchase_count]\n))\n```\n\n### Text widget\n\nA text widget shows an arbitrary piece of MarkDown. Use this to add explanations\nto your dashboard:\n\n```python\n# Example may have issues. See https://github.com/aws/jsii/issues/826\ndashboard.add_widgets(TextWidget(\n markdown=\"# Key Performance Indicators\"\n))\n```\n\n### Dashboard Layout\n\nThe widgets on a dashboard are visually laid out in a grid that is 24 columns\nwide. Normally you specify X and Y coordinates for the widgets on a Dashboard,\nbut because this is inconvenient to do manually, the library contains a simple\nlayout system to help you lay out your dashboards the way you want them to.\n\nWidgets have a `width` and `height` property, and they will be automatically\nlaid out either horizontally or vertically stacked to fill out the available\nspace.\n\nWidgets are added to a Dashboard by calling `add(widget1, widget2, ...)`.\nWidgets given in the same call will be laid out horizontally. Widgets given\nin different calls will be laid out vertically. 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