Docker image update

README.md

@@ -3,9 +3,13 @@
 ## Overview
 
 > Prior to installation, please see the [AST Docsite](https://f5devcentral.github.io/application-study-tool/) for detailed
-configuration, troubleshooting (REST changes) info, etc.
+configuration, troubleshooting (REST changes, HIGH CPU on control plane) info, etc.
 
 > See the [F5 Application Study Tool Labs](https://clouddocs.f5.com/training/community/ast/html/) for an educational guided lab experience.
+> 
+> For enabling HTTPS within Grafana, see the [Make Grafana Listen on HTTPS guide](https://community.f5.com/kb/technicalarticles/application-study-tool-make-grafana-listen-on-https/341728) for guidance.
+>
+> To review ideas on integrating your secrets with a vault, see the [Integrating your secrets with Hashi vault](https://community.f5.com/kb/TechnicalArticles/f5-app-study-tool-with-passwords-stored-in-vault/341155) for further information.
 
 The F5 Application Study Tool is intended to provide enhanced insights into (classic) BIG-IP products, leveraging best in class
 open source telemetry tools. The full installation includes:

docker-compose.yaml

@@ -29,7 +29,7 @@ services:
 
   otel-collector:
     # ghcr.io/f5devcentral/application-study-tool/otel_custom_collector:v0.9.5
-    image: ghcr.io/f5devcentral/application-study-tool/otel_custom_collector:v0.9.5
+    image: ghcr.io/f5devcentral/application-study-tool/otel_custom_collector@sha256:bcb5faa7489849c0ea36ec645a77b50203dbe7378af1bc6e9ebc923430cce634
     restart: unless-stopped
     volumes:
       - ./services/otel_collector:/etc/otel-collector-config

pages/troubleshooting/troubleshooting.md

@@ -11,6 +11,21 @@ permalink: /troubleshooting
 1. TOC
 {:toc}
 
+## Extremely high CPU usage >80%
+In the receivers file, please modify the concurrent worker count. The default count is 2, please set to 1 within the configuration file using the concurrent_workers attribute. This is only necessary if you have an extremely large amount of virtual servers (monolithic approach) 1000+ virtual servers. It's recommended to separate or split the workload with another instance of BIG-IP to reduce blast radius for changes.
+Example:
+```
+receivers:
+  bigip:
+    collection_interval: 30s
+    endpoint: https://localhost:443
+    username: otelu
+    password: ${env:BIGIP_PASSWORD}
+    tls:
+      insecure_skip_verify: true
+    concurrent_workers: 1
+```
+
 ## Increase REST memory and timeouts to improve Big-IP REST experience
 Per [AS3 Best Practices guide](https://clouddocs.f5.com/products/extensions/f5-appsvcs-extension/latest/userguide/best-practices.html#increase-timeout-values-if-the-rest-api-is-timing-out)