AST Configuration Assistance
All, I had AST configured on a RHEL platform and the 3000 port as web available. Something changed in our environment and I had to wipe away the docker configuration and I am starting from scratch on the same RHEL instance. Docker is working as "sudo docker run hello-world" states "This message shows that your installation appears to be working correctly." I deleted the old application-study-tool and added the folder from the tarball to my home directory. I copied and edited the below : cp .env-example .env cp .env.device-secrets-example .env.device-secrets vi ./config/ast_defaults.yaml vi ./config/bigip_receivers.yaml That all took like before the first installation. When I run this " docker run --rm -it -w /app -v ${PWD}:/app --entrypoint /app/src/bin/init_entrypoint.sh python:3.12.6-slim-bookworm --generate-config "...I get the error : "docker: Error response from daemon: failed to create task for container: failed to create shim task: OCI runtime create failed: runc create failed: unable to start container process: error during container init: exec: "/app/src/bin/init_entrypoint.sh": stat /app/src/bin/init_entrypoint.sh: no such file or directory: unknown" That is where I am stuck. Python version is python3.11 Wanted to reach out here first before I potentially tried it on another RHEL box - clean install. Any help or direction would be appreciated.
In Using the AST tool am I pointing it to TENANTS or to the F5OS(hardware) I have?
So I have an AST tool installation however I pointed the logins to each tenant I'm running... I was just wondering if I also should point a login to the hardware(F5OS level) as well or is AST strictly a TENANT monitoring tool.. Thanks
Does F5 AST natively support collecting and visualizing VS analytics metrics from AVR?
Hi everyone, I’d like to confirm whether F5 AST natively supports collecting and visualizing Virtual Server (VS) analytics metrics generated by the AVR module (for example, transactions per second, latency, throughput, etc.). If it doesn’t currently support AVR-based metrics out of the box, how complex would it be to add those metrics manually — for instance, by extending the telemetry configuration or customizing the data model in AST? Has anyone already tried integrating AVR data into AST dashboards? Thanks in advance!AST and Telemetry Streaming
Hi! I am quite please with the Application Study Tool, but there is one thing that I keep wondering about. The OpenTelemetry component (otel-collector) currently pulls data from the F5 using the iControl REST API, however: there is also Telemetry Streaming available. Is it possible to use Telemetry Streaming for getting the data into Prometheus?
Can I deploy the application study tool on Kubernetes?(AST)
Hi, everyone. I followed the AST guide to ensure that AST works on Docker. But, I want to deploy this on Kubernetes, is there a how-to or guide for that? If you have any suggestions on availability, or any alternative links or instructions I can refer to, I would really appreciate it. Thank you for your help.
Inquiry About the "ast-api-discovery" Repository
Hello everyone, I've been exploring the AST tool (application-study-tool) and noticed there’s a related repository at ast-api-discovery that caught my attention. Unfortunately, when I try accessing it, I receive a 404 error. I was really looking forward to diving into that tool as well. Could anyone let me know if the repository has been moved or if there are any updates on its availability? Any guidance or alternative links would be greatly appreciated. Thanks in advance for your help!Displaying Application Study Tool (AST) Dashboards in Your Own Grafana Instance
The Application Study Tool (AST) has its own Prometheus and Grafana instances. These instances run as containers and are designed to coexist with other Prometheus and Grafana instances in your environment, even on the same host. However, during demos and discussions with customers, many have expressed the desire to use their existing Grafana instance to display AST dashboards. Although it may not be obvious to new Grafana users, this process is straightforward. This blog will walk you through launching a second generic Grafana container instance, connecting it to the AST instance of Prometheus (the data source), importing a dashboard from the AST instance of Grafana, and displaying it in the new Grafana instance. If you already have a non-AST instance of Grafana running in your environment, the steps to launch a second Grafana container are optional. However, you may want to run it in order to test the import functionality and make your own customizations before importing it again into your “production” Grafana instance. Here is an example of a dashboard folder in a non-AST Grafana instance after importing three dashboards from AST: Launch a Second (Generic) Grafana Container If you already have a Grafana instance, you may skip this step. However, if you don’t, or you would like to use a “sandbox” for testing customizations before importing the dashboard into your “production“ Grafana instance, you can use the following steps to launch a new Grafana container. The following assumptions are made for the steps that follow: You are using Docker as your container runtime. (If you are using Podman, simply substitute “podman” for “docker” in each of the following commands. Other container runtimes may also work for this exercise, but I have not tested them.) You have sufficient privileges to run containers. If you don’t, you may need to run these commands with “sudo”. If that fails due to permissions errors, you will need to request the necessary privileges from your Linux administrator. We want to run Grafana version 11.5.2. Any recent version should work. However, this is the latest version as of the writing of this blog. The IP address of the host where you are running these containers is 192.168.0.15. Yours will likely be different. Use your own host’s IP when you run “curl” inside the grafana2 container. In my testing, I used MacOS. This will also work on any current Linux distribution and should work on Windows. First, launch the Grafana container. I set this new instance of Grafana to listen on port 3002 (the default for Grafana is 3000) to avoid conflicts with the AST instance, if they are running on the same host. $ docker run -d --name=grafana2 -p 3002:3000 grafana/grafana:11.5.2 Next, exec into the container to ensure it can connect to the AST instance of Prometheus. You can instead check connectivity from the Grafana UI, but the below method is a good way to troubleshoot any connectivity errors you may encounter. $ docker exec -it grafana2 bash You are now running a Bash shell inside the new Grafana container. Run a curl command to confirm the new Grafana container can reach the Prometheus application, which listens on port 9090, by default. (The IP address, 192.168.0.15, is used as an example. Use your own host's IP address here.) 5d3e8256af3d:/usr/share/grafana$ curl 192.168.0.15:9090 <a href="/graph">Found</a>. Now, it is time to test the new Grafana instance. Open a web browser and navigate to the host where this new Grafana container is running, at port 3002. If you are running on your local machine, it will be http://localhost:3002/. The default credentials are admin/admin. When first logging in, Grafana will prompt you to change the password. You may choose to change it now or click “skip” to leave it as is. Now you can export one of the dashboards from AST and import it into this instance. Export a Dashboard from AST Now that you have launched a second instance of Grafana (or you are running your own non-AST instance), it is time to import a dashboard from AST. You can import just one dashboard of your choosing (i.e., BigIP - Device Device >> Virtual Servers), or several (or even all) dashboards from AST. For this example, we will only import one dashboard, BigIP - Device Device >> Virtual Servers. If you wish to import other dashboards, the steps are the same. Navigate to the dashboard you would like to import into your Grafana instance. For the example used here, navigate to Dashboards >> BigIP – Device >> Device Virtual Servers. Click the blue "Share" button near the upper-right corner. In the pop-up box, click the Export tab. Click the blue "Save to file" button to download the JSON file representing the dashboard. Two notes: If you wish to use your own non-AST instance of Prometheus, you will need to move the slider for “Export for sharing externally” (available in the Share pop-up box, under the Export tab) to the right to enable it. This will allow you to select your own Prometheus instance as the data source when importing the dashboard into the alternate Grafana instance. The default JSON for these dashboards is also available in “dashboards” folder of the repo: https://github.com/f5devcentral/application-study-tool/tree/main/services/grafana/provisioning/dashboards. This version has the “Export for sharing externally” option enabled, so you will need to select the desired Prometheus data source – either your own or the AST instance – when importing the dashboard into the alternate Grafana instance. Import the Dashboard into the New (or Existing) Grafana Instance If you have just launched a new, generic Grafana container using the instructions in the above section, Launch a Second (Generic) Grafana Container, you can now launch the UI from a web browser by navigating to http://localhost:3002/ (assuming you are running on your local machine). The default login credentials are admin/admin. If this is just a temporary test instance, you may click “skip” when prompted to “Update your password”. (For a production instance or any instance that will be used more than just briefly, we recommend changing this to a stronger password.) If you are using an existing Grafana instance, navigate to it and log in. Connect the New Grafana Instance to the AST Prometheus Instance From this non-AST Grafana instance, verify the Prometheus data source is reachable from Grafana, and then connect to it by following these steps: In the menu bar on the left, click Connections >> Data sources. If this is a new instance of Grafana, the “Add data source” button will appear in the middle of the screen. If this is an existing instance with pre-existing data sources, the button will be in the upper-right corner of the screen and will say “Add new data source”. Click on it. Select Prometheus from the list of data sources. You may have to scroll down or enter “prometheus” in the search bar. Fill in a name (for example, “ast-prometheus”), and the URL to connect to the Prometheus instance. In my case, it was my host's private IP address, 192.168.0.15, and the port Prometheus is listening on (9090 by default): http://192.168.0.15:9090. Set the “Interval behaviour >> Scrape interval” to be the same as the value used for the collection_interval setting in your AST configuration. If you did not explicitly change it when configuring AST, it will be the default value of 60s. Click the blue "Save & test" button and ensure you get the message, “Successfully queried the Prometheus API” at the bottom of the screen. Import the Dashboard into the New Grafana Instance Click on “Dashboards” in the menu on the left. Click the blue “New” button in the upper-right and, from the drop-down, select "Import". Click on "Upload dashboard JSON file" and upload the JSON file you previously exported from the original AST dashboard. Give it a name (under Name). Under the Prometheus drop-down, select your Prometheus data source. (In the example above, it is called "ast-prometheus". If you accept the default name, it will just be “prometheus”.) Click Import. Voilà! You are now taken to the newly imported Grafana dashboard. Conclusion The Application Study Tool offers excellent observability for F5 BIG-IP systems and the traffic they handle. If you have your own Grafana instance with your own set of dashboards, there is no need to manage two separate instances. You can combine the two so you have all your dashboards in one place. The flexibility of Grafana also allows it to be highly customizable, so you can modify any of the out-of-the-box dashboards AST provides and even create your own. If you have gotten value from customizing some of the default AST dashboards, feel free to post what you did below, as many of our readers will find this valuable.
