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Introducing the F5 Application Study Tool (AST)
In the ever-evolving world of application delivery and security, gaining actionable insights into your infrastructure and applications has become more critical than ever. The Application Study Tool (AST) is designed to help technical teams and administrators leverage the power of open-source telemetry and visualization tools to enhance their monitoring, diagnostics, and analysis workflows.
Chad_Davis
Apr 17, 2025 Place Technical Articles
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01 - Visualization of F5 BIG-IP metrics on Grafana using Prometheus and Telemetry Streaming service
This user guide is all about configuration and deployment of telemetry streaming service on F5 BIG-IP device and scraps those metrics by Prometheus which will be finally visualized by the Grafana. One can select the relevant metrics scraped by the Prometheus and visualize them on the Grafana which will be demonstrated later in the guide. Note: More detailed steps along with configuration images can be found on : https://nishalrai.com.np/2022/08/18/visualization-of-f5-big-ip-metrics-on-grafana-using-prometheus-and-telemetry-streaming-service/ This guide is heavily based on the work performed by Michael O'Leary and one can view on here. The purpose of this guide is to document a little more elaborated guide for both learning and deployment aspects and also address the possible issues that could be faced during the process of deployment. Telemetry streaming (TS) is an iControl LX extension delivered as a TMOS-independent RPM file with the ability to declaratively aggregate, normalize and forward statistics and events from the BIG-IP to a consumer application by posting a single TS JSON declaration to TS’s declarative REST API endpoint. Additional information about Telemetry streaming can be found here. Prometheus is an open-source monitoring solution that stores time series data like metrics whereas Grafana allows visualizing the data stored in Prometheus and also supports a wide range of other sources. A short briefing about the architecture diagram in case of this user-deployment case scenario, the F5 BIG-IP system is on standalone mode with a management IP of 172.20.100.173, and both Prometheus and Grafana services are running on the same host with an IP address of 192.168.180.191 where the service port for Prometheus is on default – 9090 and the service port for Grafana is 5000. The whole deployment guide is broadly divided into the following sections and one can jump to the required step if they have achieved the previous configuration successfully: Section I: Download and install Telemetry Streaming Section II: Telemetry Streaming Declaration on the F5 BIG-IP device Section III: Configuration of Prometheus Section IV: Configuration on Grafana using Prometheus as a data source Section I: Download and install Telemetry Streaming We need to first download and install the telemetry streaming package on the F5 BIG-IP device. Since the telemetry streaming package is an RPM file that can be downloaded and can install through GUI or curl command on the CLI of the F5 BIG-IP device. In this user manual guide, we will download and then upload the telemetry streaming package on the BIG-IP using the iControl/iApp LX framework. One can use the alternative way which can be found here. First, we need to download the RPM file, one can find the latest telemetry streaming RPM file on the F5 Telemetry site on GitHub and download the latest RPM file. The GitHub page to download telemetry streaming can be found here. After downloading the file, you need to access your F5 BIG-IP GUI with your admin privilege account then follow the following steps: Go To iApps module > Package Management LX > Import > Browse to the downloaded location > Select Section II: Telemetry Streaming Declaration on the F5 BIG-IP device Once the download and installation of the F5 telemetry streaming package have been completed, we need to send a Telemetry Streaming declaration to configure a Telemetry Streaming pull consumer target. Before we jump into this configuration, we need to create a new user with an administrator role on the F5 BIG-IP device and you can just continue with the default admin user on the further configuration. We can create a new user in the following steps: Go to System > Users > User List Click on Create button Input the new user’s name and password Select role as administrator then add Click on the Finished button As we’re using Prometheus on this user-guide manual so, the Telemetry Streaming consumer target will be Prometheus which is hosted on 192.168.180.191:5000 We can either use Postman or using curl command on the CLI of the F5 BIG-IP device to configure a Telemetry Streaming pull consumer target. Configuration using Postman application Just follow the following steps for the configuration of the telemetry streaming consumer target using the Postman application. Step I: Open the Postman and create a new tab Step II: Select the GET method and paste the following link https://<big-ip-management-ip-address>/mgmt/shared/telemetry/declare Step III: Browse on Auth field and fill up the credentials Use the credentials used to log into F5 BIG-IP (in this case, recently created new user) Step IV: Select on Body option Change the method into POST, then select raw sub-option and then JSON data format. Past the Telemetry Streaming declaration on the body section and then click on the send button. { "class": "Telemetry", "My_Poller": { "class": "Telemetry_System_Poller", "interval": 0 }, "My_System": { "class": "Telemetry_System", "enable": "true", "systemPoller": [ "My_Poller" ] }, "metrics": { "class": "Telemetry_Pull_Consumer", "type": "Prometheus", "systemPoller": "My_Poller" } } Step V: Verify the response as the success status Select GET HTTP method on https://<big-ip-management-ip-address>/mgmt/shared/telemetry/declare Step VI: Verify the available metrics Create a new tab on Postman: - On the URL section https://<big-ip-management-ip-address>/mgmt/shared/telemetry/pullconsumer/metrics - On the authorization section, use the same credentials used before
Nishal_Rai
Sep 09, 2022 Place Technical Forum
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02 - Visualization of F5 BIG-IP metrics on Grafana using Prometheus and Telemetry Streaming service
Configuration using CLI of F5 BIG-IP device Following steps for the configuration of telemetry streaming consumer target using CLI of F5 BIG-IP device are discussed below: Once you have accessed your F5 BIG-IP device CLI terminal then access either your default admin credentials or the new user you’ve recently created on the above section. Then execute the following commands on the terminal: On the username and password section, you either enter your default admin credentials or the new user you’ve recently created has the administrator privilege. curl -u username:password -k https://localhost/mgmt/shared/telemetry/declare Note: -k, --insecure to be made secure by using the CA certificate bundle installed by default. This makes all connections considered "insecure" fail unless -k, --insecure is used. ChangChange into tmp directory and create a file called ts-config.json and I am using vi editor for it. cd /tmp vi ts-config.json Paste the Telemetry Streaming declaration and then save the file and exit the vi editor. { "class": "Telemetry", "My_Poller": { "class": "Telemetry_System_Poller", "interval": 0 }, "My_System": { "class": "Telemetry_System", "enable": "true", "systemPoller": [ "My_Poller" ] }, "metrics": { "class": "Telemetry_Pull_Consumer", "type": "Prometheus", "systemPoller": "My_Poller" } } Then execute the following command on the terminal on the same directory /tmp and change the username and password section with your F5 BIG-IP device credentials having the administrator privilege. curl -X POST -u username:password -k https://localhost/mgmt/shared/telemetry/declare -d @ts-config.json -H “content-type:application/json” To verify the available metrics curl -u username:password -k https://localhost/mgmt/shared/telemetry/pullconsumer/metrics Section III: Configuration of Prometheus Once the telemetry streaming service has been successfully configured and the metrics are available on the path. We need to configure Prometheus in order to scrape the metrics data on the predefined path. The following are the steps to configure the Prometheus: Note: On this user-guide demonstration, both Grafana and Prometheus are installed on the same host with different service ports as mentioned earlier. CentOS 7 is used as the OS for this host machine and you may have different syntax to view the following status check. First, check the status of the Prometheus sudo systemctl status prometheus.service View the current working directory and change into /etc/prometheus pwd cd /etc/prometheus ls -al global: scrape_interval: 10s scrape_configs: - job_name: 'TelemetryStreaming' scrape_timeout: 30s scrape_interval: 30s scheme: https tls_config: insecure_skip_verify: true metrics_path: '/mgmt/shared/telemetry/pullconsumer/metrics' basic_auth: username: 'F5-BIG-IP-username' password: 'F5-BIG-IP-password' static_configs: - targets: ['BIGIP-managementIP:443'] Then restart the Prometheus service and check the status of the Prometheus service. sudo systemctl restart prometheus.service sudo systemctl status prometheus.service Note: If the configuration is correct, then the Prometheus service will be enabled otherwise, the status of the Prometheus service will be disabled. To further verify whether instances has been discovered on the Prometheus: - Go to http://prometheus-ip:service/port - Click on the Status option and select the Target option Section IV: Configuration on Grafana using Prometheus as a data source In this section, we need to connect Prometheus as a data source on Grafana Once the data source has been successfully configured on Grafna then Create a new dashboard and select Prometheus as the data source then select the relevant metrics and change the refresh interval as required. Save and apply the panel. Then, Save the dashboard and view the metrics on the Grafana dashboard. The possible issue that can arise during the configuration If you use the default TS declare from the official telemetry streaming document website then you may fail to view the available metrics on the mentioned link: https://<f5-management-ip>/mgmt/shared/telemetry/pullconsumer/metrics
Nishal_Rai
Sep 09, 2022 Place Technical Forum
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Prometheus and basic auth
Dear all I have setup telemetry streaming so that a remote prometheus server can scrape metrics. I used this advice to use a guest account for "basic auth" done on prometheus : https://devcentral.f5.com/s/articles/icontrol-rest-fine-grained-role-based-access-control-30773 Here is the prometheus scrape_configs entry : - job_name: bigip honor_timestamps: true scrape_interval: 10s scrape_timeout: 10s metrics_path: /mgmt/shared/telemetry/pullconsumer/My_Prometheus scheme: https basic_auth: username: prometheus password: <secret> tls_config: ca_file: /etc/ssl/certs/ca.crt cert_file: /etc/ssl/certs/prometheus.crt key_file: /etc/ssl/certs/prometheus.key insecure_skip_verify: false static_configs: - targets: - lb5 My problem is excessive warning messages in the logs : Dec 13 16:33:37 lb5 warning httpd[13888]: [warn] [client XXXX] AUTHCACHE Error processing cookie 7BA470C4F1E2F722E1685046756D1F1A70621E38 - Cookie user mismatch The problem is clearly identified (K11140735) but changing pam idle timeout is not a solution as promtheus scrapes every 10s which is too low for an usual webui idle timeout. I was wondering if there is a fix or other way to do it ? Using a F5 token is not a solution as prometheus does not seam to support it in its scrape_config section (https://prometheus.io/docs/prometheus/latest/configuration/configuration/#scrape_config). Thanks for your help ;-))
mgateau
Dec 13, 2020 Place Technical Forum
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the F5 Application Study Tool (AST)","conversation":{"__ref":"Conversation:conversation:340273"},"id":"message:340273","revisionNum":15,"uid":340273,"depth":0,"board":{"__ref":"Tkb:board:TechnicalArticles"},"author":{"__ref":"User:user:417402"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" In the ever-evolving world of application delivery and security, gaining actionable insights into your infrastructure and applications has become more critical than ever. The Application Study Tool (AST) is designed to help technical teams and administrators leverage the power of open-source telemetry and visualization tools to enhance their monitoring, diagnostics, and analysis workflows. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":4083},"postTime":"2025-03-18T09:30:02.944-07:00","lastPublishTime":"2025-03-18T09:30:02.944-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" For application delivery and security, the ability to quickly take concrete actions to improve infrastructure is more important than ever. F5 users should try the new Application Study Tool (AST). \n AST is designed to help technical teams and administrators use open-source telemetry and visualization tools to improve their monitoring, diagnosis, and analysis workflows. Whether you’re trying to pinpoint root causes for outages or streamline BIG-IP fleet management, the Application Study Tool provides a foundation for powerful, customizable insights. \n In this article, you will learn the basics of the Application Study Tool, AST's key features, and how it can provide value to your organization. \n \n \n What is the Application Study Tool? \n The Application Study Tool is a lightweight, modular tool designed to integrate seamlessly with your BIG-IP ecosystem. AST uses modern open-source tools to track and visualize data. These tools include OpenTelemetry, Prometheus, and Grafana. This allows users to get more information about their BIG-IP deployments without heavily investing in new infrastructure. \n Application Study Tool is a simple, easy-to-use solution that can be used for quick Day 2 operations or to start a more complete telemetry solution. It can be used to observe at the speed and depth your organization needs. \n \n Why use AST? \n BIG-IP fleets have always been important for application delivery. But traditional telemetry options often don’t give deep, customizable analysis and visualization. Here are the challenges AST aims to address: \n \n Simplified Root Cause Analysis: Quickly identify bottlenecks, track performance metrics, and debug outages across your infrastructure. \n Day 2 Operations Made Easy: Analyze application behavior, usage patterns, and other telemetry data at scale for informed troubleshooting. \n Customizable Insights: Move beyond static, rigid monitoring tools with open-source dashboards and integrations tailored to your unique requirements. \n Seamless Integration: While BIG-IQ is excellent for configuration and backup management, AST bridges the gap to provide deep analytics and visualization. \n \n The Application Study Tool leverages open-source components to help F5 users analyze, view, and improve applications. \n \n How does AST work? \n The Application Study Tool brings together popular open-source tools to unlock powerful insights: \n \n OpenTelemetry Collector: \n \n Fetches enhanced BIG-IP metrics via iControlREST API calls. \n Collects telemetry data from your fleet for detailed analysis. \n \n Prometheus: \n \n Stores collected metrics in a highly efficient time-series database. \n Enables deep querying for actionable analysis. \n \n Grafana: \n \n Pre-configured dashboards provide out-of-the-box insights. \n Offers customizable visualizations for device-level and fleet-level data. \n \n Docker: \n \n Enables rapid deployment of AST in a containerized environment. \n \n \n \n Application Study Tool Use Cases \n The Application Study Tool is designed to tackle key challenges by addressing the following use cases: \n \n Visualizing BIG-IP Telemetry Data: Gain deep insights into your BIG-IP fleet with pre-built dashboards and configurable charts. \n API Endpoint Discovery & Analysis (LADT): \n \n Detect commonly used API endpoints in your ecosystem. \n Understand whether these APIs are authenticated and how often they’re accessed. \n \n Proactively Tackling Outages: Analyze metrics and logs to pinpoint the root cause of application issues before they escalate. \n \n Additionally, AST provides a foundation to enhance your setup for production-grade monitoring with high-availability, security features (For example., Grafana OIDC integration), and more. \n \n Features of the Local API Discovery Tool (LADT) \n The Local API Discovery Tool (LADT) is an integral part of this solution, providing insights into API-level usage across applications hosted on BIG-IP. Its core functionality includes: \n \n Batch Analysis of HTTP Data: LADT processes per-HTTP request data, providing detailed insights into API usage patterns. \n API Endpoint Discovery: Automatically identify likely API endpoints on BIG-IP, categorize them by authentication type, and track usage statistics. \n Lightweight Deployment: A Docker-ready solution that requires just a Linux system, BIG-IP’s telemetry data, and network connectivity. \n \n By using LADT, you can take API endpoint monitoring and analysis to the next level, even in environments with complex BIG-IP deployments. \n \n Local API Discovery – System Overview Visualized \n \n \n \n Prerequisites for running Application Study Tool \n Before beginning your journey with AST, ensure that your environment meets the following requirements: \n \n Infrastructure: A Linux VM with at least 4vCPU, 16GB RAM, and 200GB of available storage. \n BIG-IP Devices: Access to one or more BIG-IPs to collect telemetry data. Any current version of BIG-IP is supported. \n Network Connectivity: Ensure connectivity between the BIG-IP devices and the AST deployment for telemetry data collection. \n \n \n Why Upload Metrics to F5 Data Fabric? \n The F5 Data Fabric integration improves your telemetry experience by adding AI-driven security insights and advanced proactive threat detection. By uploading metrics to the F5 Data Fabric, you can: \n \n Gain actionable intelligence about potential threats in near-real-time. \n Bolster your defensive strategies with AI-driven analysis. \n Provide seamless access to your data when collaborating with your F5 Account Team or SEs. \n \n This collaboration allows F5 to better understand your environment and provide tailored recommendations specific to your organization’s needs. \n \n Getting Started with Application Study Tool \n Deployment of AST is straightforward. As a containerized solution, you can spin up the necessary stack quickly using Docker Compose on any standard Linux VM. Once deployed, the pre-configured Grafana dashboards will give you instant insights into your BIG-IP infrastructure. \n For example, you can start visualizing metrics like: \n \n Application traffic flow \n System/resource utilization \n API request behaviors \n \n Your customization possibilities don’t stop there. With OpenTelemetry’s flexible architecture and Grafana’s customizable dashboards, AST ensures you can tailor everything to your exact needs. \n \n Conclusion \n The Application Study Tool is a game-changer for organizations using F5 BIG-IP solutions. AST unlocks a new level of insight into BIG-IP environments by integrating open-source resources. This tool sets a strong foundation for observability and monitoring. \n Download the Application Study Tool and take the first step toward building a truly observable infrastructure. \n Need help getting started? \n \n Visit the official GitHub Repository for AST for deployment instructions \n See additional resources: F5 Application Study Tool Labs F5 AST Local API \n Check out JRahm's recent livestream DevCentral Connects: Application Study Tool \n \n Have you checked out the Application Study Tool? Tell us what you think below. ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"7172","kudosSumWeight":5,"repliesCount":7,"readOnly":false,"images":{"__typename":"AssociatedImageConnection","edges":[{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDE","node":{"__ref":"AssociatedImage:{\"url\":\"https://community.f5.com/t5/s/zihoc95639/images/bS0zNDAyNzMta3VhRWJY?revision=15\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDI","node":{"__ref":"AssociatedImage:{\"url\":\"https://community.f5.com/t5/s/zihoc95639/images/bS0zNDAyNzMtR3p3WFNV?revision=15\"}"}}],"totalCount":2,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}}},"Conversation:conversation:300431":{"__typename":"Conversation","id":"conversation:300431","topic":{"__typename":"ForumTopicMessage","uid":300431},"lastPostingActivityTime":"2022-09-09T13:04:54.486-07:00","solved":false},"User:user:306253":{"__typename":"User","uid":306253,"login":"Nishal_Rai","registrationData":{"__typename":"RegistrationData","status":null},"deleted":false,"avatar":{"__typename":"UserAvatar","url":"https://community.f5.com/t5/s/zihoc95639/images/dS0zMDYyNTMtMjY3MzFpODE4N0MzOUE1RjhBMjVDRQ"},"id":"user:306253"},"ForumTopicMessage:message:300431":{"__typename":"ForumTopicMessage","subject":"01 - Visualization of F5 BIG-IP metrics on Grafana using Prometheus and Telemetry Streaming service","conversation":{"__ref":"Conversation:conversation:300431"},"id":"message:300431","revisionNum":1,"uid":300431,"depth":0,"board":{"__ref":"Forum:board:TechnicalForum"},"author":{"__ref":"User:user:306253"},"metrics":{"__typename":"MessageMetrics","views":8468},"postTime":"2022-08-27T04:37:37.474-07:00","lastPublishTime":"2022-08-27T04:37:37.474-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" This user guide is all about configuration and deployment of telemetry streaming service on F5 BIG-IP device and scraps those metrics by Prometheus which will be finally visualized by the Grafana. One can select the relevant metrics scraped by the Prometheus and visualize them on the Grafana which will be demonstrated later in the guide. Note: More detailed steps along with configuration images can be found on : https://nishalrai.com.np/2022/08/18/visualization-of-f5-big-ip-metrics-on-grafana-using-prometheus-and-telemetry-streaming-service/ This guide is heavily based on the work performed by Michael O'Leary and one can view on here. The purpose of this guide is to document a little more elaborated guide for both learning and deployment aspects and also address the possible issues that could be faced during the process of deployment. Telemetry streaming (TS) is an iControl LX extension delivered as a TMOS-independent RPM file with the ability to declaratively aggregate, normalize and forward statistics and events from the BIG-IP to a consumer application by posting a single TS JSON declaration to TS’s declarative REST API endpoint. Additional information about Telemetry streaming can be found here. Prometheus is an open-source monitoring solution that stores time series data like metrics whereas Grafana allows visualizing the data stored in Prometheus and also supports a wide range of other sources. A short briefing about the architecture diagram in case of this user-deployment case scenario, the F5 BIG-IP system is on standalone mode with a management IP of 172.20.100.173, and both Prometheus and Grafana services are running on the same host with an IP address of 192.168.180.191 where the service port for Prometheus is on default – 9090 and the service port for Grafana is 5000. The whole deployment guide is broadly divided into the following sections and one can jump to the required step if they have achieved the previous configuration successfully: Section I: Download and install Telemetry Streaming Section II: Telemetry Streaming Declaration on the F5 BIG-IP device Section III: Configuration of Prometheus Section IV: Configuration on Grafana using Prometheus as a data source Section I: Download and install Telemetry Streaming We need to first download and install the telemetry streaming package on the F5 BIG-IP device. Since the telemetry streaming package is an RPM file that can be downloaded and can install through GUI or curl command on the CLI of the F5 BIG-IP device. In this user manual guide, we will download and then upload the telemetry streaming package on the BIG-IP using the iControl/iApp LX framework. One can use the alternative way which can be found here. First, we need to download the RPM file, one can find the latest telemetry streaming RPM file on the F5 Telemetry site on GitHub and download the latest RPM file. The GitHub page to download telemetry streaming can be found here. After downloading the file, you need to access your F5 BIG-IP GUI with your admin privilege account then follow the following steps: Go To iApps module > Package Management LX > Import > Browse to the downloaded location > Select Section II: Telemetry Streaming Declaration on the F5 BIG-IP device Once the download and installation of the F5 telemetry streaming package have been completed, we need to send a Telemetry Streaming declaration to configure a Telemetry Streaming pull consumer target. Before we jump into this configuration, we need to create a new user with an administrator role on the F5 BIG-IP device and you can just continue with the default admin user on the further configuration. We can create a new user in the following steps: Go to System > Users > User List Click on Create button Input the new user’s name and password Select role as administrator then add Click on the Finished button As we’re using Prometheus on this user-guide manual so, the Telemetry Streaming consumer target will be Prometheus which is hosted on 192.168.180.191:5000 We can either use Postman or using curl command on the CLI of the F5 BIG-IP device to configure a Telemetry Streaming pull consumer target. Configuration using Postman application Just follow the following steps for the configuration of the telemetry streaming consumer target using the Postman application. Step I: Open the Postman and create a new tab Step II: Select the GET method and paste the following link https://<big-ip-management-ip-address>/mgmt/shared/telemetry/declare Step III: Browse on Auth field and fill up the credentials Use the credentials used to log into F5 BIG-IP (in this case, recently created new user) Step IV: Select on Body option Change the method into POST, then select raw sub-option and then JSON data format. Past the Telemetry Streaming declaration on the body section and then click on the send button. { \"class\": \"Telemetry\", \"My_Poller\": { \"class\": \"Telemetry_System_Poller\", \"interval\": 0 }, \"My_System\": { \"class\": \"Telemetry_System\", \"enable\": \"true\", \"systemPoller\": [ \"My_Poller\" ] }, \"metrics\": { \"class\": \"Telemetry_Pull_Consumer\", \"type\": \"Prometheus\", \"systemPoller\": \"My_Poller\" } } Step V: Verify the response as the success status Select GET HTTP method on https://<big-ip-management-ip-address>/mgmt/shared/telemetry/declare Step VI: Verify the available metrics Create a new tab on Postman: - On the URL section https://<big-ip-management-ip-address>/mgmt/shared/telemetry/pullconsumer/metrics - On the authorization section, use the same credentials used before ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"6489","kudosSumWeight":4,"repliesCount":4,"readOnly":true,"images":{"__typename":"AssociatedImageConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}}},"Conversation:conversation:300433":{"__typename":"Conversation","id":"conversation:300433","topic":{"__typename":"ForumTopicMessage","uid":300433},"lastPostingActivityTime":"2022-09-09T13:01:05.108-07:00","solved":false},"ForumTopicMessage:message:300433":{"__typename":"ForumTopicMessage","subject":"02 - Visualization of F5 BIG-IP metrics on Grafana using Prometheus and Telemetry Streaming service","conversation":{"__ref":"Conversation:conversation:300433"},"id":"message:300433","revisionNum":1,"uid":300433,"depth":0,"board":{"__ref":"Forum:board:TechnicalForum"},"author":{"__ref":"User:user:306253"},"metrics":{"__typename":"MessageMetrics","views":3801},"postTime":"2022-08-27T04:43:24.746-07:00","lastPublishTime":"2022-08-27T04:43:24.746-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Configuration using CLI of F5 BIG-IP device Following steps for the configuration of telemetry streaming consumer target using CLI of F5 BIG-IP device are discussed below: Once you have accessed your F5 BIG-IP device CLI terminal then access either your default admin credentials or the new user you’ve recently created on the above section. Then execute the following commands on the terminal: On the username and password section, you either enter your default admin credentials or the new user you’ve recently created has the administrator privilege. curl -u username:password -k https://localhost/mgmt/shared/telemetry/declare Note: -k, --insecure to be made secure by using the CA certificate bundle installed by default. This makes all connections considered \"insecure\" fail unless -k, --insecure is used. ChangChange into tmp directory and create a file called ts-config.json and I am using vi editor for it. cd /tmp vi ts-config.json Paste the Telemetry Streaming declaration and then save the file and exit the vi editor. { \"class\": \"Telemetry\", \"My_Poller\": { \"class\": \"Telemetry_System_Poller\", \"interval\": 0 }, \"My_System\": { \"class\": \"Telemetry_System\", \"enable\": \"true\", \"systemPoller\": [ \"My_Poller\" ] }, \"metrics\": { \"class\": \"Telemetry_Pull_Consumer\", \"type\": \"Prometheus\", \"systemPoller\": \"My_Poller\" } } Then execute the following command on the terminal on the same directory /tmp and change the username and password section with your F5 BIG-IP device credentials having the administrator privilege. curl -X POST -u username:password -k https://localhost/mgmt/shared/telemetry/declare -d @ts-config.json -H “content-type:application/json” To verify the available metrics curl -u username:password -k https://localhost/mgmt/shared/telemetry/pullconsumer/metrics Section III: Configuration of Prometheus Once the telemetry streaming service has been successfully configured and the metrics are available on the path. We need to configure Prometheus in order to scrape the metrics data on the predefined path. The following are the steps to configure the Prometheus: Note: On this user-guide demonstration, both Grafana and Prometheus are installed on the same host with different service ports as mentioned earlier. CentOS 7 is used as the OS for this host machine and you may have different syntax to view the following status check. First, check the status of the Prometheus sudo systemctl status prometheus.service View the current working directory and change into /etc/prometheus pwd cd /etc/prometheus ls -al global: scrape_interval: 10s scrape_configs: - job_name: 'TelemetryStreaming' scrape_timeout: 30s scrape_interval: 30s scheme: https tls_config: insecure_skip_verify: true metrics_path: '/mgmt/shared/telemetry/pullconsumer/metrics' basic_auth: username: 'F5-BIG-IP-username' password: 'F5-BIG-IP-password' static_configs: - targets: ['BIGIP-managementIP:443'] Then restart the Prometheus service and check the status of the Prometheus service. sudo systemctl restart prometheus.service sudo systemctl status prometheus.service Note: If the configuration is correct, then the Prometheus service will be enabled otherwise, the status of the Prometheus service will be disabled. To further verify whether instances has been discovered on the Prometheus: - Go to http://prometheus-ip:service/port - Click on the Status option and select the Target option Section IV: Configuration on Grafana using Prometheus as a data source In this section, we need to connect Prometheus as a data source on Grafana Once the data source has been successfully configured on Grafna then Create a new dashboard and select Prometheus as the data source then select the relevant metrics and change the refresh interval as required. Save and apply the panel. Then, Save the dashboard and view the metrics on the Grafana dashboard. The possible issue that can arise during the configuration If you use the default TS declare from the official telemetry streaming document website then you may fail to view the available metrics on the mentioned link: https://<f5-management-ip>/mgmt/shared/telemetry/pullconsumer/metrics ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"5414","kudosSumWeight":2,"repliesCount":3,"readOnly":true,"images":{"__typename":"AssociatedImageConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}}},"Conversation:conversation:240532":{"__typename":"Conversation","id":"conversation:240532","topic":{"__typename":"ForumTopicMessage","uid":240532},"lastPostingActivityTime":"2020-12-13T07:46:39.000-08:00","solved":false},"User:user:70707":{"__typename":"User","uid":70707,"login":"mgateau","registrationData":{"__typename":"RegistrationData","status":null},"deleted":false,"avatar":{"__typename":"UserAvatar","url":"https://community.f5.com/t5/s/zihoc95639/m_assets/avatars/default/avatar-12.svg?time=0"},"id":"user:70707"},"ForumTopicMessage:message:240532":{"__typename":"ForumTopicMessage","subject":"Prometheus and basic auth","conversation":{"__ref":"Conversation:conversation:240532"},"id":"message:240532","revisionNum":1,"uid":240532,"depth":0,"board":{"__ref":"Forum:board:TechnicalForum"},"author":{"__ref":"User:user:70707"},"metrics":{"__typename":"MessageMetrics","views":872},"postTime":"2020-12-13T07:46:39.000-08:00","lastPublishTime":"2020-12-13T07:46:39.000-08:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Dear all I have setup telemetry streaming so that a remote prometheus server can scrape metrics. I used this advice to use a guest account for \"basic auth\" done on prometheus : https://devcentral.f5.com/s/articles/icontrol-rest-fine-grained-role-based-access-control-30773 Here is the prometheus scrape_configs entry : - job_name: bigip honor_timestamps: true scrape_interval: 10s scrape_timeout: 10s metrics_path: /mgmt/shared/telemetry/pullconsumer/My_Prometheus scheme: https basic_auth: username: prometheus password: <secret> tls_config: ca_file: /etc/ssl/certs/ca.crt cert_file: /etc/ssl/certs/prometheus.crt key_file: /etc/ssl/certs/prometheus.key insecure_skip_verify: false static_configs: - targets: - lb5 My problem is excessive warning messages in the logs : Dec 13 16:33:37 lb5 warning httpd[13888]: [warn] [client XXXX] AUTHCACHE Error processing cookie 7BA470C4F1E2F722E1685046756D1F1A70621E38 - Cookie user mismatch The problem is clearly identified (K11140735) but changing pam idle timeout is not a solution as promtheus scrapes every 10s which is too low for an usual webui idle timeout. I was wondering if there is a fix or other way to do it ? Using a F5 token is not a solution as prometheus does not seam to support it in its scrape_config section (https://prometheus.io/docs/prometheus/latest/configuration/configuration/#scrape_config). Thanks for your help ;-)) ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"1674","kudosSumWeight":0,"repliesCount":0,"readOnly":false,"images":{"__typename":"AssociatedImageConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}}},"CachedAsset:text:en_US-components/community/Navbar-1745595729370":{"__typename":"CachedAsset","id":"text:en_US-components/community/Navbar-1745595729370","value":{"community":"Community Home","inbox":"Inbox","manageContent":"Manage Content","tos":"Terms of Service","forgotPassword":"Forgot Password","themeEditor":"Theme Editor","edit":"Edit Navigation Bar","skipContent":"Skip to content","migrated-link-9":"Groups","migrated-link-7":"Technical Articles","migrated-link-8":"DevCentral News","migrated-link-1":"Technical Forum","migrated-link-10":"Community Groups","migrated-link-2":"Water Cooler","migrated-link-11":"F5 Groups","Common-external-link":"How Do I...?","migrated-link-0":"Forums","article-series":"Article Series","migrated-link-5":"Community Articles","migrated-link-6":"Articles","security-insights":"Security Insights","migrated-link-3":"CrowdSRC","migrated-link-4":"CodeShare","migrated-link-12":"Events","migrated-link-13":"Suggestions"},"localOverride":false},"CachedAsset:text:en_US-components/community/NavbarHamburgerDropdown-1745595729370":{"__typename":"CachedAsset","id":"text:en_US-components/community/NavbarHamburgerDropdown-1745595729370","value":{"hamburgerLabel":"Side Menu"},"localOverride":false},"CachedAsset:text:en_US-components/community/BrandLogo-1745595729370":{"__typename":"CachedAsset","id":"text:en_US-components/community/BrandLogo-1745595729370","value":{"logoAlt":"Khoros","themeLogoAlt":"Brand Logo"},"localOverride":false},"CachedAsset:text:en_US-components/community/NavbarTextLinks-1745595729370":{"__typename":"CachedAsset","id":"text:en_US-components/community/NavbarTextLinks-1745595729370","value":{"more":"More"},"localOverride":false},"CachedAsset:text:en_US-components/authentication/AuthenticationLink-1745595729370":{"__typename":"CachedAsset","id":"text:en_US-components/authentication/AuthenticationLink-1745595729370","value":{"title.login":"Sign In","title.registration":"Register","title.forgotPassword":"Forgot Password","title.multiAuthLogin":"Sign In"},"localOverride":false},"CachedAsset:text:en_US-components/nodes/NodeLink-1745595729370":{"__typename":"CachedAsset","id":"text:en_US-components/nodes/NodeLink-1745595729370","value":{"place":"Place {name}"},"localOverride":false},"CachedAsset:text:en_US-components/tags/TagSubscriptionAction-1745595729370":{"__typename":"CachedAsset","id":"text:en_US-components/tags/TagSubscriptionAction-1745595729370","value":{"success.follow.title":"Following Tag","success.unfollow.title":"Unfollowed Tag","success.follow.message.followAcrossCommunity":"You will be notified when this tag is used anywhere across the community","success.unfollowtag.message":"You will no longer be notified when this tag is used anywhere in this place","success.unfollowtagAcrossCommunity.message":"You will no longer be notified when this tag is used anywhere across the community","unexpected.error.title":"Error - Action Failed","unexpected.error.message":"An unidentified problem occurred during the action you took. 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