# Setting up Nuclio with AKS, Application Insights, and Grafana #### In This Document - [Application Insights overview](#application-insights-overview) - [Create a new Application Insights account and obtain the instrumentation key](#create-a-new-application-insights-account-and-obtain-the-instrumentation-key) - [Set up Nuclio on Microsoft's Azure Container Service (AKS)](#set-up-nuclio-on-microsofts-azure-container-service-aks) - [Send metrics telemetry to Azure Application Insights](#send-metrics-telemetry-to-azure-application-insights) - [Configure Nuclio Logger to send logs to Application Insights](#configure-nuclio-logger-to-send-logs-to-application-insights) - [Visualize your Application Insights using Grafana](#visualize-your-application-insights-using-grafana) ## Application Insights overview [Microsoft Azure Application Insights](https://azure.microsoft.com/en-us/services/application-insights/) is an extensible Application Performance Management (APM) service for web developers on multiple platforms. Use it to monitor your live web application. It will automatically detect performance anomalies. It includes powerful analytics tools to help you diagnose issues and to understand what users actually do with your app. It's designed to help you continuously improve performance and usability. It works for apps on a wide variety of platforms including .NET, Node.js and J2EE, hosted on-premises or in the cloud. For more information about Application Insights, see Microsoft's [product overview](https://docs.microsoft.com/en-us/azure/application-insights/app-insights-overview). ## Create a new Application Insights account and obtain the instrumentation key See the [Application Insights documentation](https://docs.microsoft.com/en-us/azure/application-insights/app-insights-create-new-resource) for information on how to set up a new Application Insights account, and obtain your instrumentation key, as you'll use it later in the guide. ## Set up Nuclio on Microsoft's Azure Container Service (AKS) For detailed information on setting up in Nuclio with Microsoft's [Azure Container Service (AKS)](https://azure.microsoft.com/services/container-service/), see [Getting Started with Nuclio on Azure Container Service (AKS)](getting-started-aks.md). ## Send metrics telemetry to Azure Application Insights Nuclio abstracts the metrics sink. You inject into the `platform config` which metric implementation to use, and the Nuclio internal communicates with the abstract layer of the metrics sink, agnostic to the implementation. ### Configuring the platform In Kubernetes, a platform configuration is stored as a ConfigMap named `platform-config` in the namespace of the function. You'll create a ConfigMap in the Nuclio namespace from a local file called `platform.yaml`. Create a new file on your computer called `platform.yaml`. The system expects this specific name. Place the following yaml code in this file: ```yaml metrics: sinks: myAppInsights: kind: appinsights attributes: interval: 2s instrumentationKey: maxBatchSize: 1024 maxBatchInterval: 5s system: - myAppInsights functions: - myAppInsights ``` The configuration makes use of the instrumentation key you obtained earlier in this guide. Navigate to the location of your `platform.yaml` file and run the following `kubectl` command: ```sh kubectl create configmap platform-config --namespace nuclio --from-file platform.yaml ``` At this stage, all metrics will be sent to application insights custom metrics table. To read more about platform configuration [click here](../../tasks/configuring-a-platform.md) ## Configure Nuclio Logger to send logs to Application Insights The logger sink is configured in a similar way to the metrics sink. Edit your `platform.yaml` file from the previous step,and append to it the following code: ```yaml logger: sinks: stdout: kind: stdout myAppInsightsLogger: kind: appinsights attributes: instrumentationKey: maxBatchSize: 1024 maxBatchInterval: 5s system: - level: debug sink: stdout - level: info sink: myAppInsightsLogger functions: - level: info sink: myAppInsightsLogger ``` The configuration makes use of the instrumentation key you obtained earlier in this guide. Navigate to the location of your `platform.yaml` file and run the following `kubectl` command: ```sh kubectl create configmap platform-config --namespace nuclio --from-file platform.yaml ``` At this stage, all logs will be sent to application insights traces table. For example, to use the logger in your function, you can simply add the following: ```go context.Logger.InfoWith("Some message", "arg1", 1, "arg2", 2) ``` To read more about platform configuration [click here](../../tasks/configuring-a-platform.md) ## Visualize your Application Insights using Grafana [Grafana](https://grafana.com/) is the leading tool for querying and visualizing time series and metrics. To use Grafana, you first need to install it in your cluster. You'll do this by using `helm`, the package manager for Kubernetes, and the [Grafana chart](https://hub.kubeapps.com/charts/stable/grafana). If you are unfamiliar with `helm`, read more about it [here](https://helm.sh/docs/). To allow Grafana to display data from Application Insights, the [Azure Monitor plugin](https://grafana.com/plugins/grafana-azure-monitor-datasource), developed by Grafana, is required. To add the plugin, create a new file named `values.yaml`. Copy the following values to this file, and edit relevant values, such as `persistence`, `adminUser`, `adminPassword`, and `plugins`. ```yaml replicas: 1 image: repository: grafana/grafana tag: 5.0.4 pullPolicy: IfNotPresent downloadDashboardsImage: repository: appropriate/curl tag: latest pullPolicy: IfNotPresent service: type: ClusterIP port: 80 annotations: {} ingress: enabled: false annotations: {} # kubernetes.io/ingress.class: nginx # kubernetes.io/tls-acme: "true" path: / hosts: - chart-example.local tls: [] resources: {} nodeSelector: {} tolerations: [] affinity: {} persistence: enabled: true storageClassName: default accessModes: - ReadWriteOnce size: 10Gi adminUser: admin adminPassword: strongpassword env: {} plugins: "grafana-azure-monitor-datasource" dashboardProviders: {} dashboards: {} grafana.ini: paths: data: /var/lib/grafana/data logs: /var/log/grafana plugins: /var/lib/grafana/plugins analytics: check_for_updates: true log: mode: console grafana_net: url: https://grafana.net ``` To install Grafana, run the following command: ``` helm install stable/grafana --values values.yaml ``` When the pod is up and running, you can access the web console. To do that, first find the name of the Grafana: ``` kubectl get pods ``` Then run the following port-forward command to browse the web console: ``` kubectl --namespace default port-forward 3000 ``` Now, browse to http://127.0.0.1:3000/ and log in using the admin username and password you provided in the `values.yaml` file. Verify that `Azure Monitor` exists in the plugins page. Configure a data source using the [plugin support page](https://github.com/grafana/azure-monitor-datasource?tab=readme-ov-file#configure-the-data-source. You can import a [sample Grafana JSON file](https://raw.githubusercontent.com/nuclio/nuclio/development/docs/assets/grafana-sample-dashboard.json) from the Grafana dashboard: from the menu (plus icon - `+`) select **Create > Import** and upload the sample JSON file. ![Grafana Dashboard](../../assets/images/grafana-dashboard.jpg) ### Further metric analysis using Application Insights Go to your Application Insights account. You'll be able to query your tables for information. The query language uses Kusto. Following are a few samples to quickly start querying: ```sql customMetrics | where name == "EventsHandleSuccessTotal" and timestamp > now(-1d) | extend trigger = tostring(customDimensions.TriggerID) | summarize sum(value) by trigger | render piechart ``` ```sql customMetrics | where name == "FunctionDuration" and timestamp > now(-1d) | extend workerIndex = tostring(customDimensions.WorkerIndex) | project timestamp, value ,valueCount, workerIndex ```