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GCP Push Metrics\n\n[![Build Status](https://travis-ci.org/BonnierNews/gcp-push-metrics.svg?branch=master)](https://travis-ci.org/BonnierNews/gcp-push-metrics)\n\nThis package helps you aggregate and push custom metrics to Google Cloud Monitoring from Node.js applications, for instance running using Google Cloud Run.\n\nUsing this package you can collect three types of metrics: counters, gauges and summaries. The values are aggregated in memory and every 60 seconds pushed to the [Cloud Monitoring API](https://cloud.google.com/monitoring/custom-metrics/creating-metrics).\n\nIts API is heavily inspired by the excellent [prom-client](https://github.com/siimon/prom-client/) but the inner workings are very different. As it was initially written for a scenario where applications using Prometheus for metrics was being migrated to Cloud Monitoring out of necessity there will be some comparisons with prom-client throughout this document.\n\n## Installation\n\n```sh\nnpm install @bonniernews/gcp-push-metrics\n```\n\n## Usage\n\nLet's start by looking at a basic use case, creating a counter and incrementing it.\n\n```js\nimport {pushClient, cloudRunResourceProvider} from \"@bonniernews/gcp-push-metrics\";\n\nconst client = pushClient({ resourceProvider: cloudRunResourceProvider });\n\nconst counter = client.counter({ name: \"num_requests\" });\ncounter.inc();\n```\n\nIn the above example we import the package and create a client. In order to create a client we need to supply a [resource provider](#resource-providers). It's possible to create custom resource providers but here we use one supplied by the package.\n\nWe then proceed to create a counter named \"num_requests\" and increment it. Once 60 seconds has passed the client will try to push a single time series to the Cloud Monitoring API.\n\n> Note: Every time `pushClient` is invoked it will create a new instance which in turn will set up a setTimeout loop that will push metrics collected by the client. In most cases you should only create a single client within your application and expose it as a singleton.\n\n### Disabling locally\n\nWhen running applications locally, for instance in a development environment, you may want to disable pushing metrics to the Cloud Monitoring API. This can be done by passing `disabled: true` to the client:\n\n```js\nconst client = pushClient({\n  resourceProvider: cloudRunResourceProvider,\n  disabled: process.env.NODE_ENV === \"development\"\n});\n```\n\n## Counters\n\nCounters are implemented as the CUMULATIVE metric kind and the value reported will continously increase. Let's look at an example:\n\n```js\nconst counter = client.counter({ name: \"num_requests\" });\n\nsetTimeout(() => {\n    counter.inc();\n    counter.inc();\n}, 61 * 1000);\n\nsetTimeout(() => {\n    counter.inc();\n}, 121 * 1000);\n```\n\nAfter 60 seconds the client will push a time series with metric type \"custom.googleapis.com/num_request\" metric. The value will be **0**.\n\nAfter 120 seconds the client will again push a time series, this time with the value **2**.\n\nAfter 180 seconds the client will push the time series with **3** as value.\n\nAfter 240 seconds the client will again push the time series with **3** as value.\n\n## Gauges\n\nGauges are point in time metrics that can both be increased and decresed. Example:\n\n```js\nconst gauge = client.gauge({ name: \"requests_in_progress\" });\n\nsetTimeout(() => {\n    gauge.inc();\n    gauge.inc();\n}, 61 * 1000);\n\nsetTimeout(() => {\n    gauge.dec();\n}, 121 * 1000);\n```\n\nAfter 60 seconds the client will push a time series with metric type \"custom.googleapis.com/requests_in_progress\" metric. The value will be **0**.\n\nAfter 120 seconds the client will again push a time series, this time with the value **2**.\n\nAfter 180 seconds the client will push the time series with **1** as value.\n\nAfter 240 seconds the client will again push the time series with **1** as value.\n\n## Summaries\n\nSummaries aggregate and calculate percentiles from observed values. The observed values are reset between each interval (60 seconds). Contrary to counters and gauges summary metrics will only be sent if there is at least one observation during the interval. Example:\n\n```js\nconst summary = client.summary({\n    name: \"response_time\",\n    percentiles: [0.5, 0.9]\n});\n\nsetTimeout(() => {\n    summary.observe(10);\n    summary.observe(20);\n    summary.observe(30);\n}, 61 * 1000);\n```\n\nAfter 60 seconds the client will **not send any time series** as there has been no observations.\n\nAfter 120 seconds the client will push two time series. Both will have metric type \"custom.googleapis.com/response_time\" but they will differ in their labels. One will be labeled `percentile: 50` and one `percentile: 90`. The first will have **20** as value and the latter will have **30** as value.\n\nAfter 180 seconds the client will again **not send any time series** as there has been no observations in the passed interval.\n\n> Note: `prom-client` also pushes the number of observations and the sum of all observations. This library does not.\n\n### Default percentiles\n\nIf you don't specify percentiles when creating a summary it will default to `[0.5, 0.9, 0.99]`. Note that this is different from `prom-client` which defaults to `[0.01, 0.05, 0.5, 0.9, 0.95, 0.99, 0.999]`.\n\n### Timers\n\nAs summaries are commonly used to measure execution or response times the summary object provides a convenience method for observing durations:\n\n```js\nconst summary = client.summary({\n    name: \"response_time\",\n});\n\nconst end = summary.startTimer();\n\n// Do something time consuming\n\nend();\n```\n\n## Labels\n\nAll methods for changing the values of metrics (counter.inc, summary.observe etc) supports an optional labels object which can contain one or more labels and values. Let's look at an example:\n\n```js\nconst counter = client.counter({ name: \"num_requests\" });\n\nsetTimeout(() => {\n    counter.inc({ response_code: \"2xx\" });\n    counter.inc({ response_code: \"2xx\" });\n    counter.inc({ response_code: \"3xx\" });\n}, 61 * 1000);\n```\n\nAfter 60 seconds the client will push a single time series with metric type \"custom.googleapis.com/num_requests\" and **0** as value.\n\nOnce 120 seconds has passed the client will push three time series. All three will have type \"custom.googleapis.com/num_requests\" but they will differ in labels. One will not have any labels at all. Another will have `{ response_code: \"2xx\" }` as labels and **2** as value. The last one will have `{ response_code: \"3xx\" }` as labels and **1** as value.\n\n### Default labels for counters and gauges\n\nAs we saw in the above example the client will push time series for created counters without labels as well as for incremented counters with labels. In other words, by default:\n\n- Counters (and gauges) that are intended to be used only with labels are still pushed as time series without labels.\n- When labels are used in the call to `inc` the time series will only be pushed after `inc` has been called at least once.\n\nThis behavior can be changed by specifying labels when creating counters and gauges. In order to disable sending the un-labeled version of these metric types we can create them with an empty labels object, like this:\n\n```js\nconst counter = client.counter({ labels: {} });\n```\n\nWe can also specify known label combinations up front, like this:\n\n```js\nconst counter = client.counter({\n    labels: {\n        response_code: [\"2xx\", \"3xx\", \"4xx\", \"5xx\"]\n    }\n});\n```\n\nLet's look at a concrete example:\n\n```js\nconst counter = client.counter({\n    labels: {\n        response_code: [\"2xx\", \"3xx\", \"4xx\", \"5xx\"],\n        source: [\"internal\", \"cdn\"]\n    }\n});\n\nsetTimeout(() => {\n    counter.inc({ response_code: \"2xx\", source: \"internal\" });\n    counter.inc({ response_code: \"2xx\", source: \"internal\" });\n}, 61 * 1000);\n\nsetTimeout(() => {\n    counter.inc();\n    counter.inc({ response_code: \"2xx\", source: \"unknown\" });\n}, 121 * 1000);\n```\n\nAfter 60 seconds the client will push a total of **ten** time series, all with **0** as values. Each time series will be labeled with one of the combinations among the labels we specified when creating the counter, for instance `{ response_code: \"3xx\", source: \"cdn\" }`. Note that the client will not send a time series without labels.\n\nAfter 120 the client will again push **ten** time series. The one labeled with `{ response_code: \"2xx\", source: \"internal\" }` will now have **2** as value.\n\nAfter 180 seconds the client will push **twelve** time series. Ten of them will be the same as before. The other two will be for the previously unseen label combinations, meaning one with `{ response_code: \"2xx\", source: \"unknown\" }` as labels and one without labels.\n\n## Resource providers\n\nWhen pushing metrics to Cloud Monitoring one must specify a [resource type](https://cloud.google.com/monitoring/api/resources). This package handles that by allowing you to specify a \"resource provider\" when creating the client. A resource provider is a function which must return a promise which resolves to an object with two properties, `default` and `exit`. These properties must in turn contain valid resource objects. The `exit` one will be used when the client tries to push metrics when `SIGTERM` is sent to the application while the `default` one will be used for all other requests.\n\nA minimalistic resource provider may look like this:\n\n```js\nfunction globalResourceProvider() {\n  return {\n    exit: {\n      type: \"global\",\n      labels: {\n        project_id: \"myproject\",\n      },\n    },\n    default: {\n      type: \"global\",\n      labels: {\n        project_id: \"myproject\",\n      },\n    },\n  };\n}\n```\n\nNote that the above example will only work when metrics are collected from a single source (ie one pod). In more realistic scenarios the resource should contain something that identifies the unique application instance to ensure that pushed time series won't conflict with each other.\n\n### Cloud Run resource provider\n\nThe package ships with a pre-built resource provider for applications deployed on Cloud Run, `cloudRunResourceProvider`. This resource provider will use the [generic_node](https://cloud.google.com/monitoring/api/resources#tag_generic_node) resource type. It maps the labels for the resource in the following way:\n\n- `project_id` - fetched from the [container instance metadata servers](https://cloud.google.com/run/docs/reference/container-contract#metadata-server) `/computeMetadata/v1/project/project-id` endpoint.\n- `location` - fetched and parsed from the [container instance metadata servers](https://cloud.google.com/run/docs/reference/container-contract#metadata-server) `/computeMetadata/v1/instance/region` endpoint.\n- `namespace` - fetched from the `K_SERVICE` environment variable.\n- `node_id` - fetched from the [container instance metadata servers](https://cloud.google.com/run/docs/reference/container-contract#metadata-server) `/computeMetadata/v1/instance/id` endpoint. In the `exit` resource `-exit` is appended to the `node-id`.\n\n## Maximum 200 time series\n\nThe Cloud Monitoring API currently supports a maximum of 200 time series in a single API call. This means that currently this package will only work with 200 or less time series. In the future we may implement functionality to split a greater number of time series into multiple requests.\n\n## Development/packaging\n\nAs the package is built using ES6 modules we also need to ship a CommonJS dist. This is done in the form of `index.cjs` which is generated using `npm run dist`. This command should always be run prior to `npm publish`.\n\n## Credit\n\nThe functionality for calculating percentiles was copied and modified from [node-stats-lite](https://github.com/brycebaril/node-stats-lite).\n","readmeFilename":"README.md"}