diff --git a/config/_default/menus/main.en.yaml b/config/_default/menus/main.en.yaml index 663402a58e4ea..05ca2f2a1cdc8 100644 --- a/config/_default/menus/main.en.yaml +++ b/config/_default/menus/main.en.yaml @@ -3363,22 +3363,18 @@ menu: parent: serverless identifier: serverless_gcr weight: 7 - - name: Containers (Sidecar) + - name: Containers url: serverless/google_cloud_run/containers parent: serverless_gcr weight: 701 - - name: Containers (In-Process) - url: serverless/google_cloud_run/containers_in_process - parent: serverless_gcr - weight: 702 - name: Functions url: serverless/google_cloud_run/functions parent: serverless_gcr - weight: 703 + weight: 702 - name: Functions (1st generation) url: serverless/google_cloud_run/functions_1st_gen parent: serverless_gcr - weight: 704 + weight: 703 - name: Glossary url: serverless/glossary parent: serverless diff --git a/content/en/serverless/google_cloud_run/containers.md b/content/en/serverless/google_cloud_run/containers.md index 43969b0486b22..a1146e10ce832 100644 --- a/content/en/serverless/google_cloud_run/containers.md +++ b/content/en/serverless/google_cloud_run/containers.md @@ -1,877 +1,42 @@ --- -title: Instrumenting Google Cloud Run Containers +title: Choosing an Instrumentation Method for Google Cloud Run Containers further_reading: -- link: 'https://www.datadoghq.com/blog/instrument-cloud-run-with-datadog-sidecar/' - tag: 'Blog' - text: 'Instrument Google Cloud Run applications with the new Datadog Agent sidecar' -- link: 'https://www.datadoghq.com/blog/collect-traces-logs-from-cloud-run-with-datadog/' - tag: 'Blog' - text: 'Collect traces, logs, and custom metrics from Cloud Run services' - + - link: "/integrations/google-cloud-run/" + tag: "Documentation" + text: "Google Cloud Run Integration" + - link: 'https://www.datadoghq.com/blog/collect-traces-logs-from-cloud-run-with-datadog/' + tag: 'Blog' + text: 'Collect traces, logs, and custom metrics from Cloud Run services' + - link: "/serverless/google_cloud_run/containers_in_process/" + tag: 'Documentation' + text: 'Instrument your container with the in-process approach' + - link: "/serverless/google_cloud_run/containers_sidecar/" + tag: 'Documentation' + text: 'Instrument your container with the sidecar approach' --- -## Overview - -Google Cloud Run is a fully managed serverless platform for deploying and scaling container-based applications. - -This page provides instructions for instrumenting your Google Cloud Run containers with the Datadog Agent, which enables tracing, custom metrics, and direct log collection. The Datadog Agent runs in a sidecar container. - -
To instrument your Google Cloud Run applications with an in-process approach, see Instrument Google Cloud Run In-Process.
- -
-Have you set up your Google Cloud integration? Datadog recommends setting up the integration, which collects metrics and logs from Google Cloud services, before proceeding on to instrumentation. Remember to add the cloud asset viewer role to your service account and enable the Cloud Asset Inventory API in Google Cloud. -
- -## Setup - -### Application - -{{< tabs >}} -{{% tab "Node.js" %}} -#### Tracing - -In your main application, add the `dd-trace-js` library. See [Tracing Node.js applications][1] for instructions. - -Set `ENV NODE_OPTIONS="--require dd-trace/init"`. This specifies that the `dd-trace/init` module is required when the Node.js process starts. - -#### Profiling -The profiler is shipped within the `dd-trace-js` library. If you are already using APM to collect traces for your application, you can skip installing the library and go directly to enabling the profiler. See [Enabling the Node.js Profiler][5]. - -#### Metrics -The `dd-trace-js` library also collects custom metrics. See the [code examples][2]. - -#### Logs -The Datadog sidecar collects logs through a shared volume. To forward logs from your main container to the sidecar, configure your application to write all logs to a location such as `shared-volume/logs/*.log` using the steps below. During the [container step](#containers), add the environment variable `DD_SERVERLESS_LOG_PATH` and a shared volume mount to both the main and sidecar container. If you decide to deploy using YAML or Terraform, the environment variables, health check, and volume mount are already added. - -To set up logging in your application, see [Node.js Log Collection][3]. To set up trace log correlation, see [Correlating Node.js Logs and Traces][4]. - -[1]: /tracing/trace_collection/automatic_instrumentation/dd_libraries/nodejs/#getting-started -[2]: /metrics/custom_metrics/dogstatsd_metrics_submission/#code-examples -[3]: /logs/log_collection/nodejs/?tab=winston30 -[4]: /tracing/other_telemetry/connect_logs_and_traces/nodejs -[5]: https://docs.datadoghq.com/profiler/enabling/nodejs?tab=environmentvariables - -{{% /tab %}} -{{% tab "Python" %}} -#### Tracing - -In your main application, add the `dd-trace-py` library. See [Tracing Python Applications][1] for instructions. You can also use [Tutorial - Enabling Tracing for a Python Application and Datadog Agent in Containers][5]. - -#### Profiling -The profiler is shipped within the `dd-trace-py` library. If you are already using APM to collect traces for your application, you can skip installing the library and go directly to enabling the profiler. See [Enabling the Python Profiler][7]. - -#### Metrics -The `dd-trace-py` library also collects custom metrics. See the [code examples][2]. - -#### Logs -The Datadog sidecar collects logs through a shared volume. To forward logs from your main container to the sidecar, configure your application to write all logs to a location such as `shared-volume/logs/*.log` using the steps below. During the [container step](#containers), add the environment variable `DD_SERVERLESS_LOG_PATH` and a shared volume mount to both the main and sidecar container. If you decide to deploy using YAML or Terraform, the environment variables, health check, and volume mount are already added. - -To set up logging in your application, see [Python Log Collection][3]. [Python Logging Best Practices][6] can also be helpful. To set up trace log correlation, see [Correlating Python Logs and Traces][4]. - -[1]: /tracing/trace_collection/automatic_instrumentation/dd_libraries/python -[2]: /metrics/custom_metrics/dogstatsd_metrics_submission/#code-examples -[3]: /logs/log_collection/python -[4]: /tracing/other_telemetry/connect_logs_and_traces/python -[5]: /tracing/guide/tutorial-enable-python-containers/ -[6]: https://www.datadoghq.com/blog/python-logging-best-practices/ -[7]: https://docs.datadoghq.com/profiler/enabling/python - -{{% /tab %}} -{{% tab "Java" %}} -#### Tracing - -In your main application, add the `dd-trace-java` library. Follow the instructions in [Tracing Java Applications][1] or use the following example Dockerfile to add and start the `dd-trace-java` library with automatic instrumentation: - -```dockerfile -FROM eclipse-temurin:17-jre-jammy -WORKDIR /app -COPY target/cloudrun-java-1.jar cloudrun-java-1.jar - - -# Add the Datadog tracer -ADD 'https://dtdg.co/latest-java-tracer' dd-java-agent.jar - - -EXPOSE 8080 - - -# Start the Datadog tracer with the javaagent argument -ENTRYPOINT [ "java", "-javaagent:dd-java-agent.jar", "-jar", "cloudrun-java-1.jar" ] -``` -#### Profiling -The profiler is shipped within the `dd-trace-java` library. If you are already using APM to collect traces for your application, you can skip installing the library and go directly to enabling the profiler. See [Enabling the Java Profiler][5]. - -#### Metrics -To collect custom metrics, [install the Java DogStatsD client][2]. - -#### Logs -The Datadog sidecar collects logs through a shared volume. To forward logs from your main container to the sidecar, configure your application to write all logs to a location such as `shared-volume/logs/*.log` using the steps below. During the [container step](#containers), add the environment variable `DD_SERVERLESS_LOG_PATH` and a shared volume mount to both the main and sidecar container. If you decide to deploy using YAML or Terraform, the environment variables, health check, and volume mount are already added. - -To set up logging in your application, see [Java Log Collection][3]. To set up trace log correlation, see [Correlating Java Logs and Traces][4]. - -[1]: /tracing/trace_collection/automatic_instrumentation/dd_libraries/java/#getting-started -[2]: /developers/dogstatsd/?tab=hostagent&code-lang=java#install-the-dogstatsd-client -[3]: /logs/log_collection/java/?tab=winston30 -[4]: /tracing/other_telemetry/connect_logs_and_traces/java -[5]: https://docs.datadoghq.com/profiler/enabling/java?tab=datadogprofiler - -{{% /tab %}} -{{% tab "Go" %}} -#### Tracing - -In your main application, add the `dd-trace-go` library. See [Tracing Go Applications][1] for instructions. - -#### Profiling -The profiler is shipped within the `dd-trace-go` library. If you are already using APM to collect traces for your application, you can skip installing the library and go directly to enabling the profiler. See [Enabling the Go Profiler][5]. - -#### Metrics -The `dd-trace-go` library also collects custom metrics. See the [code examples][2]. - -#### Logs -The Datadog sidecar collects logs through a shared volume. To forward logs from your main container to the sidecar, configure your application to write all logs to a location such as `shared-volume/logs/*.log` using the steps below. During the [container step](#containers), add the environment variable `DD_SERVERLESS_LOG_PATH` and a shared volume mount to both the main and sidecar container. If you decide to deploy using YAML or Terraform, the environment variables, health check, and volume mount are already added. - -To set up logging in your application, see [Go Log Collection][3]. To set up trace log correlation, see [Correlating Go Logs and Traces][4]. - -[1]: /tracing/trace_collection/automatic_instrumentation/dd_libraries/go/ -[2]: /metrics/custom_metrics/dogstatsd_metrics_submission/#code-examples -[3]: /logs/log_collection/go -[4]: /tracing/other_telemetry/connect_logs_and_traces/go -[5]: https://docs.datadoghq.com/profiler/enabling/go - -{{% /tab %}} -{{% tab ".NET" %}} -#### Tracing - -In your main application, add the `dd-trace-dotnet` library. See [Tracing .NET Applications][1] for instructions. - -Example Dockerfile: - -```dockerfile -FROM mcr.microsoft.com/dotnet/aspnet:8.0-jammy -WORKDIR /app -COPY ./bin/Release/net8.0/publish /app - -ADD https://github.com/DataDog/dd-trace-dotnet/releases/download/v2.56.0/datadog-dotnet-apm_2.56.0_amd64.deb /opt/datadog/datadog-dotnet-apm_2.56.0_amd64.deb -RUN dpkg -i /opt/datadog/datadog-dotnet-apm_2.56.0_amd64.deb -RUN mkdir -p /shared-volume/logs/ - -ENV CORECLR_ENABLE_PROFILING=1 -ENV CORECLR_PROFILER={846F5F1C-F9AE-4B07-969E-05C26BC060D8} -ENV CORECLR_PROFILER_PATH=/opt/datadog/Datadog.Trace.ClrProfiler.Native.so -ENV DD_DOTNET_TRACER_HOME=/opt/datadog/ - -ENV DD_TRACE_DEBUG=true - -ENTRYPOINT ["dotnet", "dotnet.dll"] -``` -#### Profiling -The profiler is shipped within the `dd-trace-dotnet` library. If you are already using APM to collect traces for your application, you can skip installing the library and go directly to enabling the profiler. See [Enabling the .NET Profiler][5]. -The above Dockerfile example also has the environment variables that enable the profiler. - -#### Metrics -The `dd-trace-dotnet` library also collects custom metrics. See the [code examples][2]. - -#### Logs -The Datadog sidecar collects logs through a shared volume. To forward logs from your main container to the sidecar, configure your application to write all logs to a location such as `shared-volume/logs/*.log` using the steps below. During the [container step](#containers), add the environment variable `DD_SERVERLESS_LOG_PATH` and a shared volume mount to both the main and sidecar container. If you decide to deploy using YAML or Terraform, the environment variables, health check, and volume mount are already added. - -To set up logging in your application, see [C# Log Collection][3]. To set up trace log correlation, see [Correlating .NET Logs and Traces][4]. - -[1]: /tracing/trace_collection/automatic_instrumentation/dd_libraries/dotnet-core/?tab=linux#enable-the-tracer-for-your-service -[2]: https://www.datadoghq.com/blog/statsd-for-net-dogstatsd/ -[3]: /log_collection/csharp/?tab=serilog -[4]: /tracing/other_telemetry/connect_logs_and_traces/dotnet/?tab=serilog -[5]: https://docs.datadoghq.com/profiler/enabling/dotnet?tab=nuget - -{{% /tab %}} -{{% tab "PHP" %}} -In your main application, add the `dd-trace-php` library. See [Tracing PHP Applications][1] for instructions. - -#### Metrics -The `dd-trace-php` library also collects custom metrics. See the [code examples][2]. - -#### Logs -The Datadog sidecar collects logs through a shared volume. To forward logs from your main container to the sidecar, configure your application to write all logs to a location such as `shared-volume/logs/*.log` using the steps below. During the [container step](#containers), add the environment variable `DD_SERVERLESS_LOG_PATH` and a shared volume mount to both the main and sidecar container. If you decide to deploy using YAML or Terraform, the environment variables, health check, and volume mount are already added. - -To set up logging in your application, see [PHP Log Collection][3]. To set up trace log correlation, see [Correlating PHP Logs and Traces][4]. - -[1]: /tracing/trace_collection/automatic_instrumentation/dd_libraries/php/ -[2]: /metrics/custom_metrics/dogstatsd_metrics_submission/#code-examples -[3]: /logs/log_collection/php -[4]: /tracing/other_telemetry/connect_logs_and_traces/php -{{% /tab %}} -{{< /tabs >}} - -### Containers -{{< tabs >}} -{{% tab "GCR UI" %}} - -#### Sidecar container - -1. In Cloud Run, select **Edit & Deploy New Revision**. -1. At the bottom of the page, select **Add Container**. -1. For **Container image URL**, select `gcr.io/datadoghq/serverless-init:latest`. -1. Go to **Volume Mounts** and set up a volume mount for logs. Ensure that the mount path matches your application's write location. For example: - {{< img src="serverless/gcr/volume_mount.png" width="80%" alt="Volume Mounts tab. Under Mounted volumes, Volume Mount 1. For Name 1, 'shared-logs (In-Memory)' is selected. For Mount path 1, '/shared-volume' is selected.">}} -1. Go to **Settings** and add a startup check. - - **Select health check type**: Startup check - - **Select probe type**: TCP - - **Port**: Enter a port number. Make note of this, as it is used in the next step. -1. Go to **Variables & Secrets** and add the following environment variables as name-value pairs: - - `DD_SERVICE`: A name for your service. For example, `gcr-sidecar-test`. - - `DD_ENV`: A name for your environment. For example, `dev`. - - `DD_SERVERLESS_LOG_PATH`: Your log path. For example, `/shared-volume/logs/*.log`. - - `DD_API_KEY`: Your [Datadog API key][1]. - - `DD_HEALTH_PORT`: The port you selected for the startup check in the previous step. - - For a list of all environment variables, including additional tags, see [Environment variables](#environment-variables). - -#### Main container - -1. Go to **Volume Mounts** and add the same shared volume as you did for the sidecar container. - **Note**: Save your changes by selecting **Done**. Do not deploy changes until the final step. -1. Go to **Variables & Secrets** and add the same `DD_SERVICE` environment variable that you set for the sidecar container. -1. Go to **Settings**. In the **Container start up order** drop-down menu, select your sidecar. -1. Deploy your main application. - -#### Add a service label in Google Cloud - -In your Cloud Run service's info panel, add a label with the following key and value: - -| Key | Value | -|-----------|-------------------------------------------------------------| -| `service` | The name of your service. Matches the value provided as the `DD_SERVICE` environment variable. | - -See [Configure labels for services][2] in the Cloud Run documentation for instructions. - -[1]: https://app.datadoghq.com/organization-settings/api-keys -[2]: https://cloud.google.com/run/docs/configuring/services/labels - -{{% /tab %}} -{{% tab "YAML deploy" %}} -To deploy your Cloud Run service with YAML service specification, use the following example configuration file. - -1. Create a YAML file that contains the following: - - ```yaml - apiVersion: serving.knative.dev/v1 - kind: Service - metadata: - name: '' - labels: - cloud.googleapis.com/location: '' - service: '' - spec: - template: - metadata: - labels: - service: '' - annotations: - autoscaling.knative.dev/maxScale: '100' # The maximum number of instances that can be created for this service. https://cloud.google.com/run/docs/reference/rest/v1/RevisionTemplate - run.googleapis.com/container-dependencies: '{"run-sidecar-1":["serverless-init-1"]}' # Configure container start order for sidecar deployments https://cloud.google.com/run/docs/configuring/services/containers#container-ordering - run.googleapis.com/startup-cpu-boost: 'true' # The startup CPU boost feature for revisions provides additional CPU during instance startup time and for 10 seconds after the instance has started. https://cloud.google.com/run/docs/configuring/services/cpu#startup-boost - spec: - containers: - - env: - - name: DD_SERVICE - value: '' - image: '' - name: run-sidecar-1 - ports: - - containerPort: 8080 - name: http1 - resources: - limits: - cpu: 1000m - memory: 512Mi - startupProbe: - failureThreshold: 1 - periodSeconds: 240 - tcpSocket: - port: 8080 - timeoutSeconds: 240 - volumeMounts: - - mountPath: /shared-volume - name: shared-volume - - env: - - name: DD_SERVERLESS_LOG_PATH - value: shared-volume/logs/*.log - - name: DD_SITE - value: '' - - name: DD_ENV - value: serverless - - name: DD_API_KEY - value: '' - - name: DD_SERVICE - value: '' - - name: DD_VERSION - value: '' - - name: DD_LOG_LEVEL - value: debug - - name: DD_LOGS_INJECTION - value: 'true' - - name: DD_HEALTH_PORT - value: '12345' - image: gcr.io/datadoghq/serverless-init:latest - name: serverless-init-1 - resources: - limits: - cpu: 1000m - memory: 512Mi # Can be updated to a higher memory if needed - startupProbe: - failureThreshold: 3 - periodSeconds: 10 - tcpSocket: - port: 12345 - timeoutSeconds: 1 - volumeMounts: - - mountPath: /shared-volume - name: shared-volume - volumes: - - emptyDir: - medium: Memory - sizeLimit: 512Mi - name: shared-volume - traffic: # make this revision and all future ones serve 100% of the traffic as soon as possible, overriding any established traffic split - - latestRevision: true - percent: 100 - ``` - In this example, the environment variables, startup health check, and volume mount are already added. If you don't want to enable logs, remove the shared volume. Ensure the container port for the main container is the same as the one exposed in your Dockerfile/service. -1. Supply placeholder values: - - ``: A name for your service. For example, `gcr-sidecar-test`. See [Unified Service Tagging][2]. - - ``: The region you are deploying your service in. For example, `us-central`. - - ``: Your [Datadog site][3], {{< region-param key="dd_site" code="true" >}}. - - ``: Your [Datadog API key][1]. - - ``: The version number of your deployment. See [Unified Service Tagging][2]. - - ``: The image of the code you are deploying to Cloud Run. For example, `us-docker.pkg.dev/cloudrun/container/hello`. - -1. Run: - ```bash - gcloud run services replace .yaml - ``` - -[1]: https://app.datadoghq.com/organization-settings/api-keys -[2]: /getting_started/tagging/unified_service_tagging/ -[3]: /getting_started/site/ - -{{% /tab %}} -{{% tab "Terraform deploy" %}} -To deploy your Cloud Run service with Terraform, use the following example configuration file. In this example, the environment variables, startup health check, and volume mount are already added. If you don't want to enable logs, remove the shared volume. Ensure the container port for the main container is the same as the one exposed in your Dockerfile/service. If you do not want to allow public access, remove the IAM policy section. - -```terraform -provider "google" { - project = "" - region = "" # example: us-central1 -} - -resource "google_cloud_run_service" "terraform_with_sidecar" { - name = "" - location = "" - - template { - metadata { - annotations = { - # Correctly formatted container-dependencies annotation - "run.googleapis.com/container-dependencies" = jsonencode({main-app = ["sidecar-container"]}) - } - labels = { - service = "" - } - } - spec { - # Define shared volume - volumes { - name = "shared-volume" - empty_dir { - medium = "Memory" - } - } +To instrument your Google Cloud Run containers with Datadog, choose one of two options: - # Main application container - containers { - name = "main-app" - image = "" +{{% google-cloud-run-container-options %}} - # Expose a port for the main container - ports { - container_port = 8080 - } - # Mount the shared volume - volume_mounts { - name = "shared-volume" - mount_path = "/shared-volume" - } +- [**In-process**][1]: Wraps your application container with the Datadog Agent. Choose this option for a simpler setup, lower cost overhead, and direct log piping. +- [**Sidecar**][2]: Deploys the Datadog Agent in a separate container alongside your app container. Choose this option if you have multiple containers in a single service, if you prefer strict isolation of the Datadog Agent, or if you have performance-sensitive workloads. - # Startup Probe for TCP Health Check - startup_probe { - tcp_socket { - port = 8080 - } - initial_delay_seconds = 0 # Delay before the probe starts - period_seconds = 10 # Time between probes - failure_threshold = 3 # Number of failures before marking as unhealthy - timeout_seconds = 1 # Number of failures before marking as unhealthy - } +## Comparison: in-process versus sidecar instrumentation - # Environment variables for the main container - env { - name = "DD_SERVICE" - value = "" - } +| Aspect | In-process | Sidecar | +|-------------------------------|----------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------| +| Deployment | One container (your app, wrapped with the Datadog Agent) | Two containers ( your app, Datadog Agent) | +| Image changes | Increases app image size. | No change to app image. | +| Cost overhead | Less than sidecar (no extra container). | Extra vCPU/memory. Overallocating the sidecar wastes cost; underallocating leads to premature scaling. | +| Logging | Direct stdout/stderr access. | Shared volume + log library routing to a log file. Uncaught errors require extra handling, since they are not automatically handled by your logging library. | +| Failure isolation | In rare cases, Datadog Agent bugs can affect your app. | Datadog Agent faults are isolated. | +| Observing multiple containers | Not supported | Supported | - # Resource limits for the main container - resources { - limits = { - memory = "512Mi" - cpu = "1" - } - } - } - - # Sidecar container - containers { - name = "sidecar-container" - image = "gcr.io/datadoghq/serverless-init:latest" - - # Mount the shared volume - volume_mounts { - name = "shared-volume" - mount_path = "/shared-volume" - } - - # Startup Probe for TCP Health Check - startup_probe { - tcp_socket { - port = 12345 - } - initial_delay_seconds = 0 # Delay before the probe starts - period_seconds = 10 # Time between probes - failure_threshold = 3 # Number of failures before marking as unhealthy - timeout_seconds = 1 - } - - # Environment variables for the sidecar container - env { - name = "DD_SITE" - value = "" - } - env { - name = "DD_SERVERLESS_LOG_PATH" - value = "shared-volume/logs/*.log" - } - env { - name = "DD_ENV" - value = "serverless" - } - env { - name = "DD_API_KEY" - value = "" - } - env { - name = "DD_SERVICE" - value = "" - } - env { - name = "DD_VERSION" - value = "" - } - env { - name = "DD_LOG_LEVEL" - value = "debug" - } - env { - name = "DD_LOGS_INJECTION" - value = "true" - } - env { - name = "DD_HEALTH_PORT" - value = "12345" - } - - # Resource limits for the sidecar - resources { - limits = { - memory = "512Mi" - cpu = "1" - } - } - } - } - } - - # Define traffic splitting - traffic { - percent = 100 - latest_revision = true - } -} - -# IAM Member to allow public access (optional, adjust as needed) -resource "google_cloud_run_service_iam_member" "invoker" { - service = google_cloud_run_service.terraform_with_sidecar.name - location = google_cloud_run_service.terraform_with_sidecar.location - role = "roles/run.invoker" - member = "allUsers" -} -``` - -Supply placeholder values: -- ``: Your Google Cloud project ID. -- ``: The region you are deploying your service in. For example, `us-central1`. -- ``: A name for your service. For example, `gcr-sidecar-test`. See [Unified Service Tagging][2]. -- ``: The image of the code you are deploying to Cloud Run. -- ``: Your [Datadog site][3], {{< region-param key="dd_site" code="true" >}}. -- ``: Your [Datadog API key][1]. -- ``: The version number of your deployment. See [Unified Service Tagging][2]. - -[1]: https://app.datadoghq.com/organization-settings/api-keys -[2]: /getting_started/tagging/unified_service_tagging/ -[3]: /getting_started/site/ -{{% /tab %}} -{{< /tabs >}} - -## Environment variables - -| Variable | Description | -| -------- | ----------- | -|`DD_API_KEY`| [Datadog API key][4] - **Required**| -| `DD_SITE` | [Datadog site][5] - **Required** | -| `DD_LOGS_INJECTION`| When true, enrich all logs with trace data for supported loggers in [Java][6], [Node][7], [.NET][8], and [PHP][9]. See additional docs for [Python][10], [Go][11], and [Ruby][12]. | -| `DD_SERVICE` | See [Unified Service Tagging][13]. | -| `DD_VERSION` | See [Unified Service Tagging][13]. | -| `DD_ENV` | See [Unified Service Tagging][13]. | -| `DD_SOURCE` | See [Unified Service Tagging][13]. | -| `DD_TAGS` | See [Unified Service Tagging][13]. | - -Do not use the `DD_LOGS_ENABLED` environment variable. This variable is only used for [in-process container instrumentation][14]. - -## Example application - -The following example contains a single app with tracing, metrics, and logs set up. - -{{< tabs >}} -{{% tab "Node.js" %}} - -```js -const tracer = require('dd-trace').init({ - logInjection: true, -}); -const express = require("express"); -const app = express(); -const { createLogger, format, transports } = require('winston'); - -const logger = createLogger({ - level: 'info', - exitOnError: false, - format: format.json(), - transports: [new transports.File({ filename: `/shared-volume/logs/app.log`}), - ], -}); - -app.get("/", (_, res) => { - logger.info("Welcome!"); - res.sendStatus(200); -}); - -app.get("/hello", (_, res) => { - logger.info("Hello!"); - metricPrefix = "nodejs-cloudrun"; - // Send three unique metrics, just so we're testing more than one single metric - metricsToSend = ["sample_metric_1", "sample_metric_2", "sample_metric_3"]; - metricsToSend.forEach((metric) => { - for (let i = 0; i < 20; i++) { - tracer.dogstatsd.distribution(`${metricPrefix}.${metric}`, 1); - } - }); - res.status(200).json({ msg: "Sending metrics to Datadog" }); -}); - -const port = process.env.PORT || 8080; -app.listen(port); -``` - -{{% /tab %}} -{{% tab "Python" %}} - -### app.py - -```python -import ddtrace -from flask import Flask, render_template, request -import logging -from datadog import initialize, statsd - -ddtrace.patch(logging=True) -app = Flask(__name__) -options = { - 'statsd_host':'127.0.0.1', - 'statsd_port':8125 -} -FORMAT = ('%(asctime)s %(levelname)s [%(name)s] [%(filename)s:%(lineno)d] ' - '[dd.service=%(dd.service)s dd.env=%(dd.env)s dd.version=%(dd.version)s dd.trace_id=%(dd.trace_id)s dd.span_id=%(dd.span_id)s] ' - '- %(message)s') -logging.basicConfig(level=logging.DEBUG, filename='app.log', format=FORMAT) -logger = logging.getLogger(__name__) -logger.level = logging.INFO - -ddlogs = [] - -@ddtrace.tracer.wrap(service="dd_gcp_log_forwader") -@app.route('/', methods=["GET"]) -def index(): - log = request.args.get("log") - if log != None: - with tracer.trace('sending_logs') as span: - statsd.increment('dd.gcp.logs.sent') - span.set_tag('logs', 'nina') - logger.info(log) - ddlogs.append(log) - return render_template("home.html", logs=ddlogs) - -if __name__ == '__main__': - tracer.configure(port=8126) - initialize(**options) - app.run(debug=True) -``` - -### Home.html -```html - - - - - - - Datadog Test - - -

Welcome to Datadog!πŸ’œ

-
- - -
-

Logs Sent to Datadog:

-
    - {% for log in logs%} - {% if log %} -
  • {{ log }}
    • - {% endif %} - {% endfor %} -
- - -``` -{{% /tab %}} -{{% tab "Java" %}} - -```java -package com.example.springboot; - -import org.springframework.web.bind.annotation.GetMapping; -import org.springframework.web.bind.annotation.RestController; - -import com.timgroup.statsd.NonBlockingStatsDClientBuilder; -import com.timgroup.statsd.StatsDClient; - -import org.apache.commons.logging.Log; -import org.apache.commons.logging.LogFactory; - -@RestController -public class HelloController { - Private static final StatsDClient Statsd = new NonBlockingStatsDClientBuilder().hostname("localhost").build(); - private static final Log logger = LogFactory.getLog(HelloController.class); - @GetMapping("/") - public String index() { - Statsd.incrementCounter("page.views"); - logger.info("Hello Cloud Run!"); - return "πŸ’œ Hello Cloud Run! πŸ’œ"; - } -} -``` - -{{% /tab %}} -{{% tab "Go" %}} -```go -package main - - -import ( - "fmt" - "log" - "net/http" - "os" - "path/filepath" - - - "github.com/DataDog/datadog-go/v5/statsd" - "github.com/DataDog/dd-trace-go/v2/ddtrace" - "github.com/DataDog/dd-trace-go/v2/ddtrace/tracer" -) - - -const logDir = "/shared-volume/logs" - -var logFile *os.File -var logCounter int -var dogstatsdClient *statsd.Client - -func handler(w http.ResponseWriter, r *http.Request) { - log.Println("Yay!! Main container works") - span := tracer.StartSpan("maincontainer", tracer.ResourceName("/handler")) - defer span.Finish() - logCounter++ - writeLogsToFile(fmt.Sprintf("received request %d", logCounter), span.Context()) - dogstatsdClient.Incr("request.count", []string{"test-tag"}, 1) -} - -func writeLogsToFile(log_msg string, context ddtrace.SpanContext) { - span := tracer.StartSpan( - "writeLogToFile", - tracer.ResourceName("/writeLogsToFile"), - tracer.ChildOf(context)) - defer span.Finish() - _, err := logFile.WriteString(log_msg + "\n") - if err != nil { - log.Println("Error writing to log file:", err) - } -} - -func main() { - log.Print("Main container started...") - - err := os.MkdirAll(logDir, 0755) - if err != nil { - panic(err) - } - logFilePath := filepath.Join(logDir, "maincontainer.log") - log.Println("Saving logs in ", logFilePath) - logFileLocal, err := os.OpenFile(logFilePath, os.O_WRONLY|os.O_APPEND|os.O_CREATE, 0644) - if err != nil { - panic(err) - } - defer logFileLocal.Close() - - logFile = logFileLocal - - dogstatsdClient, err = statsd.New("localhost:8125") - if err != nil { - panic(err) - } - defer dogstatsdClient.Close() - - tracer.Start() - defer tracer.Stop() - - http.HandleFunc("/", handler) - log.Fatal(http.ListenAndServe(":8080", nil)) -} -``` -{{% /tab %}} -{{% tab ".NET" %}} -```csharp -using Microsoft.AspNetCore.Mvc; -using Microsoft.AspNetCore.Mvc.RazorPages; -using Serilog; -using Serilog.Formatting.Json; -using Serilog.Formatting.Compact; -using Serilog.Sinks.File; -using StatsdClient; - - -namespace dotnet.Pages; - - -public class IndexModel : PageModel -{ - private readonly static DogStatsdService _dsd; - static IndexModel() - { - var dogstatsdConfig = new StatsdConfig - { - StatsdServerName = "127.0.0.1", - StatsdPort = 8125, - }; - - - _dsd = new DogStatsdService(); - _dsd.Configure(dogstatsdConfig); - - - Log.Logger = new LoggerConfiguration() - .WriteTo.File(new RenderedCompactJsonFormatter(), "/shared-volume/logs/app.log") - .CreateLogger(); - } - public void OnGet() - { - _dsd.Increment("page.views"); - Log.Information("Hello Cloud Run!"); - } -} -``` -{{% /tab %}} -{{% tab "PHP" %}} - -```php - '127.0.0.1', - 'port' => 8125, - ) - ); - - -$log = new logger('datadog'); -$formatter = new JsonFormatter(); - - -$stream = new StreamHandler('/shared-volume/logs/app.log', Logger::DEBUG); -$stream->setFormatter($formatter); - - -$log->pushHandler($stream); - - -$log->info("Hello Datadog!"); -echo 'πŸ’œ Hello Datadog! πŸ’œ'; - - -$log->info("sending a metric"); -$statsd->increment('page.views', 1, array('environment'=>'dev')); - - -?> -``` - -{{% /tab %}} -{{< /tabs >}} ## Further reading {{< partial name="whats-next/whats-next.html" >}} - -[1]: /integrations/google_cloud_platform/#log-collection -[2]: https://app.datadoghq.com/organization-settings/api-keys -[3]: https://hub.docker.com/r/datadog/serverless-init -[4]: /account_management/api-app-keys/#api-keys -[5]: /getting_started/site/ -[6]: /tracing/other_telemetry/connect_logs_and_traces/java/?tab=log4j2 -[7]: /tracing/other_telemetry/connect_logs_and_traces/nodejs -[8]: /tracing/other_telemetry/connect_logs_and_traces/dotnet?tab=serilog -[9]: /tracing/other_telemetry/connect_logs_and_traces/php -[10]: /tracing/other_telemetry/connect_logs_and_traces/python -[11]: /tracing/other_telemetry/connect_logs_and_traces/go -[12]: /tracing/other_telemetry/connect_logs_and_traces/ruby -[13]: /getting_started/tagging/unified_service_tagging/ -[14]: /serverless/google_cloud/google_cloud_run_in_process -[15]: https://cloud.google.com/run/docs/configuring/services/labels +[1]: /serverless/google_cloud_run/containers_in_process +[2]: /serverless/google_cloud_run/containers_sidecar \ No newline at end of file diff --git a/content/en/serverless/google_cloud_run/containers_in_process.md b/content/en/serverless/google_cloud_run/containers_in_process.md index 5ac6ad776b0bb..270f3a75960f9 100644 --- a/content/en/serverless/google_cloud_run/containers_in_process.md +++ b/content/en/serverless/google_cloud_run/containers_in_process.md @@ -1,5 +1,5 @@ --- -title: Instrumenting Google Cloud Run In-Process +title: Instrumenting Google Cloud Run Containers In-Process further_reading: - link: 'https://www.datadoghq.com/blog/collect-traces-logs-from-cloud-run-with-datadog/' @@ -10,7 +10,7 @@ further_reading: ## Overview -Google Cloud Run is a fully managed serverless platform for deploying and scaling container-based applications. +Google Cloud Run is a fully managed serverless platform for deploying and scaling container-based applications. This page provides instructions for instrumenting your Google Cloud Run containers with the Datadog Agent, which enables tracing, custom metrics, and direct log collection. @@ -26,10 +26,6 @@ Make sure you have a [Datadog API key][7] and are using a programming language [ ## Instrument your application -You can instrument your application in one of two ways: [Dockerfile](#dockerfile) or [buildpack](#buildpack). - -### Dockerfile - Datadog publishes new releases of the `serverless-init` container image to Google’s gcr.io, AWS’s ECR, and on Docker Hub: | dockerhub.io | gcr.io | public.ecr.aws | @@ -88,6 +84,8 @@ To get full instrumentation, ensure you are calling `datadog-init` as the first ### Buildpack +
Buildpack instrumentation is deprecated.
+ [`Pack Buildpacks`][3] provide a convenient way to package your container without using a Dockerfile. First, manually install your tracer: diff --git a/content/en/serverless/google_cloud_run/containers_sidecar.md b/content/en/serverless/google_cloud_run/containers_sidecar.md new file mode 100644 index 0000000000000..7f2f83b69e595 --- /dev/null +++ b/content/en/serverless/google_cloud_run/containers_sidecar.md @@ -0,0 +1,877 @@ +--- +title: Instrumenting Google Cloud Run Containers with Sidecar +further_reading: +- link: 'https://www.datadoghq.com/blog/instrument-cloud-run-with-datadog-sidecar/' + tag: 'Blog' + text: 'Instrument Google Cloud Run applications with the new Datadog Agent sidecar' +- link: 'https://www.datadoghq.com/blog/collect-traces-logs-from-cloud-run-with-datadog/' + tag: 'Blog' + text: 'Collect traces, logs, and custom metrics from Cloud Run services' + +--- + +## Overview + +Google Cloud Run is a fully managed serverless platform for deploying and scaling container-based applications. + +This page provides instructions for instrumenting your Google Cloud Run containers with the Datadog Agent, which enables tracing, custom metrics, and direct log collection. The Datadog Agent runs in a sidecar container. + +
To instrument your Google Cloud Run applications with an in-process approach, see Instrument Google Cloud Run In-Process.
+ +
+Have you set up your Google Cloud integration? Datadog recommends setting up the integration, which collects metrics and logs from Google Cloud services, before proceeding on to instrumentation. Remember to add the cloud asset viewer role to your service account and enable the Cloud Asset Inventory API in Google Cloud. +
+ +## Setup + +### Application + +{{< tabs >}} +{{% tab "Node.js" %}} +#### Tracing + +In your main application, add the `dd-trace-js` library. See [Tracing Node.js applications][1] for instructions. + +Set `ENV NODE_OPTIONS="--require dd-trace/init"`. This specifies that the `dd-trace/init` module is required when the Node.js process starts. + +#### Profiling +The profiler is shipped within the `dd-trace-js` library. If you are already using APM to collect traces for your application, you can skip installing the library and go directly to enabling the profiler. See [Enabling the Node.js Profiler][5]. + +#### Metrics +The `dd-trace-js` library also collects custom metrics. See the [code examples][2]. + +#### Logs +The Datadog sidecar collects logs through a shared volume. To forward logs from your main container to the sidecar, configure your application to write all logs to a location such as `shared-volume/logs/*.log` using the steps below. During the [container step](#containers), add the environment variable `DD_SERVERLESS_LOG_PATH` and a shared volume mount to both the main and sidecar container. If you decide to deploy using YAML or Terraform, the environment variables, health check, and volume mount are already added. + +To set up logging in your application, see [Node.js Log Collection][3]. To set up trace log correlation, see [Correlating Node.js Logs and Traces][4]. + +[1]: /tracing/trace_collection/automatic_instrumentation/dd_libraries/nodejs/#getting-started +[2]: /metrics/custom_metrics/dogstatsd_metrics_submission/#code-examples +[3]: /logs/log_collection/nodejs/?tab=winston30 +[4]: /tracing/other_telemetry/connect_logs_and_traces/nodejs +[5]: https://docs.datadoghq.com/profiler/enabling/nodejs?tab=environmentvariables + +{{% /tab %}} +{{% tab "Python" %}} +#### Tracing + +In your main application, add the `dd-trace-py` library. See [Tracing Python Applications][1] for instructions. You can also use [Tutorial - Enabling Tracing for a Python Application and Datadog Agent in Containers][5]. + +#### Profiling +The profiler is shipped within the `dd-trace-py` library. If you are already using APM to collect traces for your application, you can skip installing the library and go directly to enabling the profiler. See [Enabling the Python Profiler][7]. + +#### Metrics +The `dd-trace-py` library also collects custom metrics. See the [code examples][2]. + +#### Logs +The Datadog sidecar collects logs through a shared volume. To forward logs from your main container to the sidecar, configure your application to write all logs to a location such as `shared-volume/logs/*.log` using the steps below. During the [container step](#containers), add the environment variable `DD_SERVERLESS_LOG_PATH` and a shared volume mount to both the main and sidecar container. If you decide to deploy using YAML or Terraform, the environment variables, health check, and volume mount are already added. + +To set up logging in your application, see [Python Log Collection][3]. [Python Logging Best Practices][6] can also be helpful. To set up trace log correlation, see [Correlating Python Logs and Traces][4]. + +[1]: /tracing/trace_collection/automatic_instrumentation/dd_libraries/python +[2]: /metrics/custom_metrics/dogstatsd_metrics_submission/#code-examples +[3]: /logs/log_collection/python +[4]: /tracing/other_telemetry/connect_logs_and_traces/python +[5]: /tracing/guide/tutorial-enable-python-containers/ +[6]: https://www.datadoghq.com/blog/python-logging-best-practices/ +[7]: https://docs.datadoghq.com/profiler/enabling/python + +{{% /tab %}} +{{% tab "Java" %}} +#### Tracing + +In your main application, add the `dd-trace-java` library. Follow the instructions in [Tracing Java Applications][1] or use the following example Dockerfile to add and start the `dd-trace-java` library with automatic instrumentation: + +```dockerfile +FROM eclipse-temurin:17-jre-jammy +WORKDIR /app +COPY target/cloudrun-java-1.jar cloudrun-java-1.jar + + +# Add the Datadog tracer +ADD 'https://dtdg.co/latest-java-tracer' dd-java-agent.jar + + +EXPOSE 8080 + + +# Start the Datadog tracer with the javaagent argument +ENTRYPOINT [ "java", "-javaagent:dd-java-agent.jar", "-jar", "cloudrun-java-1.jar" ] +``` +#### Profiling +The profiler is shipped within the `dd-trace-java` library. If you are already using APM to collect traces for your application, you can skip installing the library and go directly to enabling the profiler. See [Enabling the Java Profiler][5]. + +#### Metrics +To collect custom metrics, [install the Java DogStatsD client][2]. + +#### Logs +The Datadog sidecar collects logs through a shared volume. To forward logs from your main container to the sidecar, configure your application to write all logs to a location such as `shared-volume/logs/*.log` using the steps below. During the [container step](#containers), add the environment variable `DD_SERVERLESS_LOG_PATH` and a shared volume mount to both the main and sidecar container. If you decide to deploy using YAML or Terraform, the environment variables, health check, and volume mount are already added. + +To set up logging in your application, see [Java Log Collection][3]. To set up trace log correlation, see [Correlating Java Logs and Traces][4]. + +[1]: /tracing/trace_collection/automatic_instrumentation/dd_libraries/java/#getting-started +[2]: /developers/dogstatsd/?tab=hostagent&code-lang=java#install-the-dogstatsd-client +[3]: /logs/log_collection/java/?tab=winston30 +[4]: /tracing/other_telemetry/connect_logs_and_traces/java +[5]: https://docs.datadoghq.com/profiler/enabling/java?tab=datadogprofiler + +{{% /tab %}} +{{% tab "Go" %}} +#### Tracing + +In your main application, add the `dd-trace-go` library. See [Tracing Go Applications][1] for instructions. + +#### Profiling +The profiler is shipped within the `dd-trace-go` library. If you are already using APM to collect traces for your application, you can skip installing the library and go directly to enabling the profiler. See [Enabling the Go Profiler][5]. + +#### Metrics +The `dd-trace-go` library also collects custom metrics. See the [code examples][2]. + +#### Logs +The Datadog sidecar collects logs through a shared volume. To forward logs from your main container to the sidecar, configure your application to write all logs to a location such as `shared-volume/logs/*.log` using the steps below. During the [container step](#containers), add the environment variable `DD_SERVERLESS_LOG_PATH` and a shared volume mount to both the main and sidecar container. If you decide to deploy using YAML or Terraform, the environment variables, health check, and volume mount are already added. + +To set up logging in your application, see [Go Log Collection][3]. To set up trace log correlation, see [Correlating Go Logs and Traces][4]. + +[1]: /tracing/trace_collection/automatic_instrumentation/dd_libraries/go/ +[2]: /metrics/custom_metrics/dogstatsd_metrics_submission/#code-examples +[3]: /logs/log_collection/go +[4]: /tracing/other_telemetry/connect_logs_and_traces/go +[5]: https://docs.datadoghq.com/profiler/enabling/go + +{{% /tab %}} +{{% tab ".NET" %}} +#### Tracing + +In your main application, add the `dd-trace-dotnet` library. See [Tracing .NET Applications][1] for instructions. + +Example Dockerfile: + +```dockerfile +FROM mcr.microsoft.com/dotnet/aspnet:8.0-jammy +WORKDIR /app +COPY ./bin/Release/net8.0/publish /app + +ADD https://github.com/DataDog/dd-trace-dotnet/releases/download/v2.56.0/datadog-dotnet-apm_2.56.0_amd64.deb /opt/datadog/datadog-dotnet-apm_2.56.0_amd64.deb +RUN dpkg -i /opt/datadog/datadog-dotnet-apm_2.56.0_amd64.deb +RUN mkdir -p /shared-volume/logs/ + +ENV CORECLR_ENABLE_PROFILING=1 +ENV CORECLR_PROFILER={846F5F1C-F9AE-4B07-969E-05C26BC060D8} +ENV CORECLR_PROFILER_PATH=/opt/datadog/Datadog.Trace.ClrProfiler.Native.so +ENV DD_DOTNET_TRACER_HOME=/opt/datadog/ + +ENV DD_TRACE_DEBUG=true + +ENTRYPOINT ["dotnet", "dotnet.dll"] +``` +#### Profiling +The profiler is shipped within the `dd-trace-dotnet` library. If you are already using APM to collect traces for your application, you can skip installing the library and go directly to enabling the profiler. See [Enabling the .NET Profiler][5]. +The above Dockerfile example also has the environment variables that enable the profiler. + +#### Metrics +The `dd-trace-dotnet` library also collects custom metrics. See the [code examples][2]. + +#### Logs +The Datadog sidecar collects logs through a shared volume. To forward logs from your main container to the sidecar, configure your application to write all logs to a location such as `shared-volume/logs/*.log` using the steps below. During the [container step](#containers), add the environment variable `DD_SERVERLESS_LOG_PATH` and a shared volume mount to both the main and sidecar container. If you decide to deploy using YAML or Terraform, the environment variables, health check, and volume mount are already added. + +To set up logging in your application, see [C# Log Collection][3]. To set up trace log correlation, see [Correlating .NET Logs and Traces][4]. + +[1]: /tracing/trace_collection/automatic_instrumentation/dd_libraries/dotnet-core/?tab=linux#enable-the-tracer-for-your-service +[2]: https://www.datadoghq.com/blog/statsd-for-net-dogstatsd/ +[3]: /log_collection/csharp/?tab=serilog +[4]: /tracing/other_telemetry/connect_logs_and_traces/dotnet/?tab=serilog +[5]: https://docs.datadoghq.com/profiler/enabling/dotnet?tab=nuget + +{{% /tab %}} +{{% tab "PHP" %}} +In your main application, add the `dd-trace-php` library. See [Tracing PHP Applications][1] for instructions. + +#### Metrics +The `dd-trace-php` library also collects custom metrics. See the [code examples][2]. + +#### Logs +The Datadog sidecar collects logs through a shared volume. To forward logs from your main container to the sidecar, configure your application to write all logs to a location such as `shared-volume/logs/*.log` using the steps below. During the [container step](#containers), add the environment variable `DD_SERVERLESS_LOG_PATH` and a shared volume mount to both the main and sidecar container. If you decide to deploy using YAML or Terraform, the environment variables, health check, and volume mount are already added. + +To set up logging in your application, see [PHP Log Collection][3]. To set up trace log correlation, see [Correlating PHP Logs and Traces][4]. + +[1]: /tracing/trace_collection/automatic_instrumentation/dd_libraries/php/ +[2]: /metrics/custom_metrics/dogstatsd_metrics_submission/#code-examples +[3]: /logs/log_collection/php +[4]: /tracing/other_telemetry/connect_logs_and_traces/php +{{% /tab %}} +{{< /tabs >}} + +### Containers +{{< tabs >}} +{{% tab "GCR UI" %}} + +#### Sidecar container + +1. In Cloud Run, select **Edit & Deploy New Revision**. +1. At the bottom of the page, select **Add Container**. +1. For **Container image URL**, select `gcr.io/datadoghq/serverless-init:latest`. +1. Go to **Volume Mounts** and set up a volume mount for logs. Ensure that the mount path matches your application's write location. For example: + {{< img src="serverless/gcr/volume_mount.png" width="80%" alt="Volume Mounts tab. Under Mounted volumes, Volume Mount 1. For Name 1, 'shared-logs (In-Memory)' is selected. For Mount path 1, '/shared-volume' is selected.">}} +1. Go to **Settings** and add a startup check. + - **Select health check type**: Startup check + - **Select probe type**: TCP + - **Port**: Enter a port number. Make note of this, as it is used in the next step. +1. Go to **Variables & Secrets** and add the following environment variables as name-value pairs: + - `DD_SERVICE`: A name for your service. For example, `gcr-sidecar-test`. + - `DD_ENV`: A name for your environment. For example, `dev`. + - `DD_SERVERLESS_LOG_PATH`: Your log path. For example, `/shared-volume/logs/*.log`. + - `DD_API_KEY`: Your [Datadog API key][1]. + - `DD_HEALTH_PORT`: The port you selected for the startup check in the previous step. + + For a list of all environment variables, including additional tags, see [Environment variables](#environment-variables). + +#### Main container + +1. Go to **Volume Mounts** and add the same shared volume as you did for the sidecar container. + **Note**: Save your changes by selecting **Done**. Do not deploy changes until the final step. +1. Go to **Variables & Secrets** and add the same `DD_SERVICE` environment variable that you set for the sidecar container. +1. Go to **Settings**. In the **Container start up order** drop-down menu, select your sidecar. +1. Deploy your main application. + +#### Add a service label in Google Cloud + +In your Cloud Run service's info panel, add a label with the following key and value: + +| Key | Value | +|-----------|-------------------------------------------------------------| +| `service` | The name of your service. Matches the value provided as the `DD_SERVICE` environment variable. | + +See [Configure labels for services][2] in the Cloud Run documentation for instructions. + +[1]: https://app.datadoghq.com/organization-settings/api-keys +[2]: https://cloud.google.com/run/docs/configuring/services/labels + +{{% /tab %}} +{{% tab "YAML deploy" %}} +To deploy your Cloud Run service with YAML service specification, use the following example configuration file. + +1. Create a YAML file that contains the following: + + ```yaml + apiVersion: serving.knative.dev/v1 + kind: Service + metadata: + name: '' + labels: + cloud.googleapis.com/location: '' + service: '' + spec: + template: + metadata: + labels: + service: '' + annotations: + autoscaling.knative.dev/maxScale: '100' # The maximum number of instances that can be created for this service. https://cloud.google.com/run/docs/reference/rest/v1/RevisionTemplate + run.googleapis.com/container-dependencies: '{"run-sidecar-1":["serverless-init-1"]}' # Configure container start order for sidecar deployments https://cloud.google.com/run/docs/configuring/services/containers#container-ordering + run.googleapis.com/startup-cpu-boost: 'true' # The startup CPU boost feature for revisions provides additional CPU during instance startup time and for 10 seconds after the instance has started. https://cloud.google.com/run/docs/configuring/services/cpu#startup-boost + spec: + containers: + - env: + - name: DD_SERVICE + value: '' + image: '' + name: run-sidecar-1 + ports: + - containerPort: 8080 + name: http1 + resources: + limits: + cpu: 1000m + memory: 512Mi + startupProbe: + failureThreshold: 1 + periodSeconds: 240 + tcpSocket: + port: 8080 + timeoutSeconds: 240 + volumeMounts: + - mountPath: /shared-volume + name: shared-volume + - env: + - name: DD_SERVERLESS_LOG_PATH + value: shared-volume/logs/*.log + - name: DD_SITE + value: '' + - name: DD_ENV + value: serverless + - name: DD_API_KEY + value: '' + - name: DD_SERVICE + value: '' + - name: DD_VERSION + value: '' + - name: DD_LOG_LEVEL + value: debug + - name: DD_LOGS_INJECTION + value: 'true' + - name: DD_HEALTH_PORT + value: '12345' + image: gcr.io/datadoghq/serverless-init:latest + name: serverless-init-1 + resources: + limits: + cpu: 1000m + memory: 512Mi # Can be updated to a higher memory if needed + startupProbe: + failureThreshold: 3 + periodSeconds: 10 + tcpSocket: + port: 12345 + timeoutSeconds: 1 + volumeMounts: + - mountPath: /shared-volume + name: shared-volume + volumes: + - emptyDir: + medium: Memory + sizeLimit: 512Mi + name: shared-volume + traffic: # make this revision and all future ones serve 100% of the traffic as soon as possible, overriding any established traffic split + - latestRevision: true + percent: 100 + ``` + In this example, the environment variables, startup health check, and volume mount are already added. If you don't want to enable logs, remove the shared volume. Ensure the container port for the main container is the same as the one exposed in your Dockerfile/service. +1. Supply placeholder values: + - ``: A name for your service. For example, `gcr-sidecar-test`. See [Unified Service Tagging][2]. + - ``: The region you are deploying your service in. For example, `us-central`. + - ``: Your [Datadog site][3], {{< region-param key="dd_site" code="true" >}}. + - ``: Your [Datadog API key][1]. + - ``: The version number of your deployment. See [Unified Service Tagging][2]. + - ``: The image of the code you are deploying to Cloud Run. For example, `us-docker.pkg.dev/cloudrun/container/hello`. + +1. Run: + ```bash + gcloud run services replace .yaml + ``` + +[1]: https://app.datadoghq.com/organization-settings/api-keys +[2]: /getting_started/tagging/unified_service_tagging/ +[3]: /getting_started/site/ + +{{% /tab %}} +{{% tab "Terraform deploy" %}} +To deploy your Cloud Run service with Terraform, use the following example configuration file. In this example, the environment variables, startup health check, and volume mount are already added. If you don't want to enable logs, remove the shared volume. Ensure the container port for the main container is the same as the one exposed in your Dockerfile/service. If you do not want to allow public access, remove the IAM policy section. + +```terraform +provider "google" { + project = "" + region = "" # example: us-central1 +} + +resource "google_cloud_run_service" "terraform_with_sidecar" { + name = "" + location = "" + + template { + metadata { + annotations = { + # Correctly formatted container-dependencies annotation + "run.googleapis.com/container-dependencies" = jsonencode({main-app = ["sidecar-container"]}) + } + labels = { + service = "" + } + } + spec { + # Define shared volume + volumes { + name = "shared-volume" + empty_dir { + medium = "Memory" + } + } + + # Main application container + containers { + name = "main-app" + image = "" + + # Expose a port for the main container + ports { + container_port = 8080 + } + # Mount the shared volume + volume_mounts { + name = "shared-volume" + mount_path = "/shared-volume" + } + + # Startup Probe for TCP Health Check + startup_probe { + tcp_socket { + port = 8080 + } + initial_delay_seconds = 0 # Delay before the probe starts + period_seconds = 10 # Time between probes + failure_threshold = 3 # Number of failures before marking as unhealthy + timeout_seconds = 1 # Number of failures before marking as unhealthy + } + + # Environment variables for the main container + env { + name = "DD_SERVICE" + value = "" + } + + # Resource limits for the main container + resources { + limits = { + memory = "512Mi" + cpu = "1" + } + } + } + + # Sidecar container + containers { + name = "sidecar-container" + image = "gcr.io/datadoghq/serverless-init:latest" + + # Mount the shared volume + volume_mounts { + name = "shared-volume" + mount_path = "/shared-volume" + } + + # Startup Probe for TCP Health Check + startup_probe { + tcp_socket { + port = 12345 + } + initial_delay_seconds = 0 # Delay before the probe starts + period_seconds = 10 # Time between probes + failure_threshold = 3 # Number of failures before marking as unhealthy + timeout_seconds = 1 + } + + # Environment variables for the sidecar container + env { + name = "DD_SITE" + value = "" + } + env { + name = "DD_SERVERLESS_LOG_PATH" + value = "shared-volume/logs/*.log" + } + env { + name = "DD_ENV" + value = "serverless" + } + env { + name = "DD_API_KEY" + value = "" + } + env { + name = "DD_SERVICE" + value = "" + } + env { + name = "DD_VERSION" + value = "" + } + env { + name = "DD_LOG_LEVEL" + value = "debug" + } + env { + name = "DD_LOGS_INJECTION" + value = "true" + } + env { + name = "DD_HEALTH_PORT" + value = "12345" + } + + # Resource limits for the sidecar + resources { + limits = { + memory = "512Mi" + cpu = "1" + } + } + } + } + } + + # Define traffic splitting + traffic { + percent = 100 + latest_revision = true + } +} + +# IAM Member to allow public access (optional, adjust as needed) +resource "google_cloud_run_service_iam_member" "invoker" { + service = google_cloud_run_service.terraform_with_sidecar.name + location = google_cloud_run_service.terraform_with_sidecar.location + role = "roles/run.invoker" + member = "allUsers" +} +``` + +Supply placeholder values: +- ``: Your Google Cloud project ID. +- ``: The region you are deploying your service in. For example, `us-central1`. +- ``: A name for your service. For example, `gcr-sidecar-test`. See [Unified Service Tagging][2]. +- ``: The image of the code you are deploying to Cloud Run. +- ``: Your [Datadog site][3], {{< region-param key="dd_site" code="true" >}}. +- ``: Your [Datadog API key][1]. +- ``: The version number of your deployment. See [Unified Service Tagging][2]. + +[1]: https://app.datadoghq.com/organization-settings/api-keys +[2]: /getting_started/tagging/unified_service_tagging/ +[3]: /getting_started/site/ +{{% /tab %}} +{{< /tabs >}} + +## Environment variables + +| Variable | Description | +| -------- | ----------- | +|`DD_API_KEY`| [Datadog API key][4] - **Required**| +| `DD_SITE` | [Datadog site][5] - **Required** | +| `DD_LOGS_INJECTION`| When true, enrich all logs with trace data for supported loggers in [Java][6], [Node][7], [.NET][8], and [PHP][9]. See additional docs for [Python][10], [Go][11], and [Ruby][12]. | +| `DD_SERVICE` | See [Unified Service Tagging][13]. | +| `DD_VERSION` | See [Unified Service Tagging][13]. | +| `DD_ENV` | See [Unified Service Tagging][13]. | +| `DD_SOURCE` | See [Unified Service Tagging][13]. | +| `DD_TAGS` | See [Unified Service Tagging][13]. | + +Do not use the `DD_LOGS_ENABLED` environment variable. This variable is only used for [in-process container instrumentation][14]. + +## Example application + +The following example contains a single app with tracing, metrics, and logs set up. + +{{< tabs >}} +{{% tab "Node.js" %}} + +```js +const tracer = require('dd-trace').init({ + logInjection: true, +}); +const express = require("express"); +const app = express(); +const { createLogger, format, transports } = require('winston'); + +const logger = createLogger({ + level: 'info', + exitOnError: false, + format: format.json(), + transports: [new transports.File({ filename: `/shared-volume/logs/app.log`}), + ], +}); + +app.get("/", (_, res) => { + logger.info("Welcome!"); + res.sendStatus(200); +}); + +app.get("/hello", (_, res) => { + logger.info("Hello!"); + metricPrefix = "nodejs-cloudrun"; + // Send three unique metrics, just so we're testing more than one single metric + metricsToSend = ["sample_metric_1", "sample_metric_2", "sample_metric_3"]; + metricsToSend.forEach((metric) => { + for (let i = 0; i < 20; i++) { + tracer.dogstatsd.distribution(`${metricPrefix}.${metric}`, 1); + } + }); + res.status(200).json({ msg: "Sending metrics to Datadog" }); +}); + +const port = process.env.PORT || 8080; +app.listen(port); +``` + +{{% /tab %}} +{{% tab "Python" %}} + +### app.py + +```python +import ddtrace +from flask import Flask, render_template, request +import logging +from datadog import initialize, statsd + +ddtrace.patch(logging=True) +app = Flask(__name__) +options = { + 'statsd_host':'127.0.0.1', + 'statsd_port':8125 +} +FORMAT = ('%(asctime)s %(levelname)s [%(name)s] [%(filename)s:%(lineno)d] ' + '[dd.service=%(dd.service)s dd.env=%(dd.env)s dd.version=%(dd.version)s dd.trace_id=%(dd.trace_id)s dd.span_id=%(dd.span_id)s] ' + '- %(message)s') +logging.basicConfig(level=logging.DEBUG, filename='app.log', format=FORMAT) +logger = logging.getLogger(__name__) +logger.level = logging.INFO + +ddlogs = [] + +@ddtrace.tracer.wrap(service="dd_gcp_log_forwader") +@app.route('/', methods=["GET"]) +def index(): + log = request.args.get("log") + if log != None: + with tracer.trace('sending_logs') as span: + statsd.increment('dd.gcp.logs.sent') + span.set_tag('logs', 'nina') + logger.info(log) + ddlogs.append(log) + return render_template("home.html", logs=ddlogs) + +if __name__ == '__main__': + tracer.configure(port=8126) + initialize(**options) + app.run(debug=True) +``` + +### Home.html +```html + + + + + + + Datadog Test + + +

Welcome to Datadog!πŸ’œ

+
+ + +
+

Logs Sent to Datadog:

+
    + {% for log in logs%} + {% if log %} +
  • {{ log }}
    • + {% endif %} + {% endfor %} +
+ + +``` +{{% /tab %}} +{{% tab "Java" %}} + +```java +package com.example.springboot; + +import org.springframework.web.bind.annotation.GetMapping; +import org.springframework.web.bind.annotation.RestController; + +import com.timgroup.statsd.NonBlockingStatsDClientBuilder; +import com.timgroup.statsd.StatsDClient; + +import org.apache.commons.logging.Log; +import org.apache.commons.logging.LogFactory; + +@RestController +public class HelloController { + Private static final StatsDClient Statsd = new NonBlockingStatsDClientBuilder().hostname("localhost").build(); + private static final Log logger = LogFactory.getLog(HelloController.class); + @GetMapping("/") + public String index() { + Statsd.incrementCounter("page.views"); + logger.info("Hello Cloud Run!"); + return "πŸ’œ Hello Cloud Run! πŸ’œ"; + } +} +``` + +{{% /tab %}} +{{% tab "Go" %}} +```go +package main + + +import ( + "fmt" + "log" + "net/http" + "os" + "path/filepath" + + + "github.com/DataDog/datadog-go/v5/statsd" + "github.com/DataDog/dd-trace-go/v2/ddtrace" + "github.com/DataDog/dd-trace-go/v2/ddtrace/tracer" +) + + +const logDir = "/shared-volume/logs" + +var logFile *os.File +var logCounter int +var dogstatsdClient *statsd.Client + +func handler(w http.ResponseWriter, r *http.Request) { + log.Println("Yay!! Main container works") + span := tracer.StartSpan("maincontainer", tracer.ResourceName("/handler")) + defer span.Finish() + logCounter++ + writeLogsToFile(fmt.Sprintf("received request %d", logCounter), span.Context()) + dogstatsdClient.Incr("request.count", []string{"test-tag"}, 1) +} + +func writeLogsToFile(log_msg string, context ddtrace.SpanContext) { + span := tracer.StartSpan( + "writeLogToFile", + tracer.ResourceName("/writeLogsToFile"), + tracer.ChildOf(context)) + defer span.Finish() + _, err := logFile.WriteString(log_msg + "\n") + if err != nil { + log.Println("Error writing to log file:", err) + } +} + +func main() { + log.Print("Main container started...") + + err := os.MkdirAll(logDir, 0755) + if err != nil { + panic(err) + } + logFilePath := filepath.Join(logDir, "maincontainer.log") + log.Println("Saving logs in ", logFilePath) + logFileLocal, err := os.OpenFile(logFilePath, os.O_WRONLY|os.O_APPEND|os.O_CREATE, 0644) + if err != nil { + panic(err) + } + defer logFileLocal.Close() + + logFile = logFileLocal + + dogstatsdClient, err = statsd.New("localhost:8125") + if err != nil { + panic(err) + } + defer dogstatsdClient.Close() + + tracer.Start() + defer tracer.Stop() + + http.HandleFunc("/", handler) + log.Fatal(http.ListenAndServe(":8080", nil)) +} +``` +{{% /tab %}} +{{% tab ".NET" %}} +```csharp +using Microsoft.AspNetCore.Mvc; +using Microsoft.AspNetCore.Mvc.RazorPages; +using Serilog; +using Serilog.Formatting.Json; +using Serilog.Formatting.Compact; +using Serilog.Sinks.File; +using StatsdClient; + + +namespace dotnet.Pages; + + +public class IndexModel : PageModel +{ + private readonly static DogStatsdService _dsd; + static IndexModel() + { + var dogstatsdConfig = new StatsdConfig + { + StatsdServerName = "127.0.0.1", + StatsdPort = 8125, + }; + + + _dsd = new DogStatsdService(); + _dsd.Configure(dogstatsdConfig); + + + Log.Logger = new LoggerConfiguration() + .WriteTo.File(new RenderedCompactJsonFormatter(), "/shared-volume/logs/app.log") + .CreateLogger(); + } + public void OnGet() + { + _dsd.Increment("page.views"); + Log.Information("Hello Cloud Run!"); + } +} +``` +{{% /tab %}} +{{% tab "PHP" %}} + +```php + '127.0.0.1', + 'port' => 8125, + ) + ); + + +$log = new logger('datadog'); +$formatter = new JsonFormatter(); + + +$stream = new StreamHandler('/shared-volume/logs/app.log', Logger::DEBUG); +$stream->setFormatter($formatter); + + +$log->pushHandler($stream); + + +$log->info("Hello Datadog!"); +echo 'πŸ’œ Hello Datadog! πŸ’œ'; + + +$log->info("sending a metric"); +$statsd->increment('page.views', 1, array('environment'=>'dev')); + + +?> +``` + +{{% /tab %}} +{{< /tabs >}} + +## Further reading + +{{< partial name="whats-next/whats-next.html" >}} + + +[1]: /integrations/google_cloud_platform/#log-collection +[2]: https://app.datadoghq.com/organization-settings/api-keys +[3]: https://hub.docker.com/r/datadog/serverless-init +[4]: /account_management/api-app-keys/#api-keys +[5]: /getting_started/site/ +[6]: /tracing/other_telemetry/connect_logs_and_traces/java/?tab=log4j2 +[7]: /tracing/other_telemetry/connect_logs_and_traces/nodejs +[8]: /tracing/other_telemetry/connect_logs_and_traces/dotnet?tab=serilog +[9]: /tracing/other_telemetry/connect_logs_and_traces/php +[10]: /tracing/other_telemetry/connect_logs_and_traces/python +[11]: /tracing/other_telemetry/connect_logs_and_traces/go +[12]: /tracing/other_telemetry/connect_logs_and_traces/ruby +[13]: /getting_started/tagging/unified_service_tagging/ +[14]: /serverless/google_cloud/google_cloud_run_in_process +[15]: https://cloud.google.com/run/docs/configuring/services/labels diff --git a/layouts/shortcodes/google-cloud-run-container-options.html b/layouts/shortcodes/google-cloud-run-container-options.html new file mode 100644 index 0000000000000..e78d49c229ed2 --- /dev/null +++ b/layouts/shortcodes/google-cloud-run-container-options.html @@ -0,0 +1,21 @@ +
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