Google Axion Updates

Author: Pranay Bakre

content/learning-paths/cross-platform/gitlab/1-gitlab-runner.md

@@ -16,9 +16,7 @@ A GitLab Runner works with GitLab CI/CD to run jobs in a pipeline. It acts as an
 3. Multi-architecture support: GitLab runners support multiple architectures including - `x86/amd64` and `arm64`
 
 ## What is Google Axion?
-Axion is Google’s first Arm-based server processor, built using the Armv9 Neoverse V2 CPU. The VM instances are part of the `C4A` family of compute instances. To learn more about Google Axion refer to this [blog](https://cloud.google.com/blog/products/compute/introducing-googles-new-arm-based-cpu).
-
-Note: These `C4A` VM instances are in public preview and needs a signup to be enabled in your Google Cloud account/project.
+Axion is Google’s first Arm-based server processor, built using the Armv9 Neoverse V2 CPU. The VM instances are part of the `C4A` family of compute instances. To learn more about Google Axion refer to this [page](cloud.google.com/products/axion).
 
 ## Install GitLab runner on a Google Axion VM
 

content/learning-paths/servers-and-cloud-computing/csp/google.md

@@ -11,7 +11,7 @@ layout: "learningpathall"
 
 As with most cloud service providers, Google Cloud offers a pay-as-you-use [pricing policy](https://cloud.google.com/pricing), including a number of [free](https://cloud.google.com/free/docs/free-cloud-features) services.
 
-This section is to help you get started with [Google Cloud Compute Engine](https://cloud.google.com/compute) compute services, using Arm-based [Tau T2A](https://cloud.google.com/tau-vm) Virtual Machines. This is a general-purpose compute platform, essentially your own personal computer in the cloud.
+This section is to help you get started with [Google Cloud Compute Engine](https://cloud.google.com/compute) compute services, using Arm-based Virtual Machines. Google Cloud offers two generations of Arm-based VMs, `C4A` is the latest generation based on [Google Axion](cloud.google.com/products/axion), Google’s first Arm-based server processor, built using the Armv9 Neoverse V2 CPU. The previous generation VMs are based on Ampere Altra processor and part of [Tau T2A](https://cloud.google.com/tau-vm) family of Virtual Machines. 
 
 Detailed instructions are available in the Google Cloud [documentation](https://cloud.google.com/compute/docs/instances). 
 
@@ -23,7 +23,7 @@ If using an organization's account, you will likely need to consult with your in
 
 ## Browse for an appropriate instance
 
-Google Cloud offers a wide range of instance types, covering all performance (and pricing) points. For an overview of the Tau T2A instance types, see the [General-purpose machine family](https://cloud.google.com/compute/docs/general-purpose-machines#t2a_machines) overview. 
+Google Cloud offers a wide range of instance types, covering all performance (and pricing) points. For an overview of the `C4A` instance types, see this [page](cloud.google.com/products/axion). Similarly, to know more about the `T2A` instance types, see the [General-purpose machine family](https://cloud.google.com/compute/docs/general-purpose-machines#t2a_machines) overview. 
 
 Also note which [regions](https://cloud.google.com/compute/docs/regions-zones#available) these servers are available in.
 
@@ -49,15 +49,15 @@ Select an appropriate `region` and `zone` that support Arm-based servers.
 
 ![google3 #center](https://github.com/ArmDeveloperEcosystem/arm-learning-paths/assets/71631645/f2a19cd0-7565-44d3-9e6f-b27bccad3e86 "Select an appropriate region and zone")
 
-To view the latest information on which available regions and zones support Arm-based servers, see the [Compute Engine documentation](https://cloud.google.com/compute/docs/regions-zones#available). To filter for Arm-based machines, click on `Select a machine type`, then select `T2A` from the pull-down menu.
+To view the latest information on which available regions and zones support Arm-based servers, see the [Compute Engine documentation](https://cloud.google.com/compute/docs/regions-zones#available). To filter for Arm-based machines, click on `Select a machine type`, then select `T2A` or `C4A` from the pull-down menu.
 
 ![google4 #center](https://github.com/ArmDeveloperEcosystem/arm-learning-paths/assets/71631645/5b1683dc-724f-4c60-aea6-dc945c7bf6bc "Check which regions and zones support Arm-based machines")
 
 ### Machine configuration
 
-Select `T2A` from the `Series` pull-down menu. Then select an appropriate `Machine type` configuration for your needs.
+Select `C4A` from the `Series` pull-down menu. Then select an appropriate `Machine type` configuration for your needs.
 
-![google5 #center](images/gcp_instance.png "Select an appropriate T2A machine type")
+![google5 #center](images/gcp_instance_new.png "Select an appropriate C4A machine type")
 
 ### Boot disk configuration
 

content/learning-paths/servers-and-cloud-computing/gcp/jump_server.md

@@ -69,7 +69,7 @@ resource "google_project_iam_member" "project" {
 resource "google_compute_instance" "bastion_host" {
   project      = var.project
   name         = "bastion-vm"
-  machine_type = "t2a-standard-1"
+  machine_type = "c4a-standard-1"
   zone         = var.zone
   tags         = ["public"]
   boot_disk {
@@ -91,7 +91,7 @@ resource "google_compute_instance" "bastion_host" {
 resource "google_compute_instance" "private" {
   project                   = var.project
   name                      = "bastion-private"
-  machine_type              = "t2a-standard-1"
+  machine_type              = "c4a-standard-1"
   zone                      = var.zone
   allow_stopping_for_update = true
   tags                      = ["private"]

content/learning-paths/servers-and-cloud-computing/gcp/terraform.md

@@ -39,7 +39,7 @@ provider "google" {
 
 resource "google_compute_instance" "vm_instance" {
   name         = "instance-arm"
-  machine_type = "t2a-standard-1"
+  machine_type = "c4a-standard-1"
 
   boot_disk {
     initialize_params {

content/learning-paths/servers-and-cloud-computing/gke-multi-arch/_index.md

@@ -1,12 +1,12 @@
 ---
-title: Learn how to migrate an x86 application to multi-architecture with Arm on Google Kubernetes Engine (GKE)
+title: Learn how to migrate an x86 application to multi-architecture with Arm-based on Google Axion Processor on GKE
 
 minutes_to_complete: 30
 
 who_is_this_for: This is an advanced topic for software developers who are looking to migrate their existing x86 containerized applications to Arm
 
 learning_objectives: 
-    - Add Arm-based nodes to an existing x86-based GKE cluster
+    - Add Arm-based nodes (Google Axion) to an existing x86-based GKE cluster
     - Rebuild an x86-based application to make it multi-arch and run on Arm
     - Learn how to add taints and tolerations to GKE clusters to schedule application pods on architecture specific nodes
     - Run a multi-arch application across multiple architectures on a single GKE cluster

content/learning-paths/servers-and-cloud-computing/gke-multi-arch/how-to-1.md

@@ -8,7 +8,7 @@ layout: learningpathall
 
 ## Migrate an existing x86-based application to run on Arm-based nodes in a single GKE cluster 
 
-Google Kubernetes Engine (GKE) supports hybrid clusters with x86 and Arm based nodes. The Arm-based nodes can be deployed on the `Tau T2A` family of virtual machines. The `Tau T2A` virtual machines are powered by Ampere Altra Arm-based processors.
+Google Kubernetes Engine (GKE) supports hybrid clusters with x86 and Arm based nodes. The Arm-based nodes can be deployed on the `C4A` family of virtual machines. The `C4A` VMs are based on [Google Axion](cloud.google.com/products/axion), Google’s first Arm-based server processor, built using the Armv9 Neoverse V2 CPU.
 
 ## Before you begin
 
@@ -102,13 +102,13 @@ Hello from NODE:gke-multi-arch-cluster-default-pool-45537239-q83v, POD:x86-hello
 
 ## Add Arm-based nodes to your GKE cluster
 
-Use the following command to add an Arm-based node pool with VM type `t2a-standard-2` to your GKE cluster:
+Use the following command to add an Arm-based node pool with VM type `c4a-standard-2` to your GKE cluster:
 
 ```console
 gcloud container node-pools create arm-pool \
     --cluster $CLUSTER_NAME \
     --zone $ZONE \
-    --machine-type=t2a-standard-2 \
+    --machine-type=c4a-standard-2 \
     --num-nodes=3
 ```
 After the Arm-nodes are successfully added to the cluster, run the following command to check if both types of nodes show up in the cluster:

content/learning-paths/servers-and-cloud-computing/java-on-axion/1-create-instance.md

@@ -8,11 +8,7 @@ layout: learningpathall
 
 ## Create an Axion instance
 
-Axion is Google’s first Arm-based server processor, built using the Armv9 Neoverse V2 CPU. Created specifically for the data center, Axion delivers industry-leading performance and energy efficiency.
-
-{{% notice Note %}}
-The Axion instance type (C4A) is currently in public preview. A GA (General Availability) release will happen in the coming months.
-{{% /notice %}}
+Axion is Google’s first Arm-based server processor, built using the Armv9 Neoverse V2 CPU. Created specifically for the data center, Axion delivers industry-leading performance and energy efficiency. To learn more about Google Axion, refer to this [page](cloud.google.com/products/axion)
 
 There are several ways to create an Arm-based Google Axion VM: the Google Cloud console, the gcloud CLI tool, or using your choice of IaC (Infrastructure as Code).
 

content/learning-paths/servers-and-cloud-computing/java-on-axion/2-deploy-java.md

@@ -90,7 +90,7 @@ java -jar target/*.jar
 Once the application is running, you can open the web app in a web browser by visiting
 
 ```bash
-http://[EXTERNAL IP]:8080
+http://<EXTERNAL_IP>:8080
 ```
 
-Where `[EXTERNAL IP]` is the value you obtained in the [last section](/learning-paths/servers-and-cloud-computing/java-on-axion/1-create-instance/#obtain-the-ip-of-your-instance).
+Where `<EXTERNAL_IP>` is the value you obtained in the [last section](/learning-paths/servers-and-cloud-computing/java-on-axion/1-create-instance/#obtain-the-ip-of-your-instance).

content/learning-paths/servers-and-cloud-computing/java-on-axion/select_axion_instance.png

@@ -14,7 +14,7 @@ The underlying storage technology and the file system format can impact performa
 
 Aside from the storage technology, the file system format used with `MySQL` can impact performance. The `xfs` file system is a good starting point. The `ext4` file system is another good alternative. Last, it is recommended to use storage drives that are dedicated to the database (i.e. not shared with the OS or other applications).
 
-When running in the cloud, the disk scheduling algorithm is typically set to `noop` or a similar "dumb" algorithm. This is typically optimal for `MySQL` in the cloud, so no adjustment is needed. However, if running `MySQL` on an on-prem server, it's a good idea to double check what the disk scheduling algorithm is, and possibly change it. According to the [Optimizing InnoDB Disk I/O documentation]https://dev.mysql.com/doc/refman/en/optimizing-innodb-diskio.html), `noop` or `deadline` might be better options. It's worth testing this with on-prem systems.
+When running in the cloud, the disk scheduling algorithm is typically set to `noop` or a similar "dumb" algorithm. This is typically optimal for `MySQL` in the cloud, so no adjustment is needed. However, if running `MySQL` on an on-prem server, it's a good idea to double check what the disk scheduling algorithm is, and possibly change it. According to the [Optimizing InnoDB Disk I/O documentation](https://dev.mysql.com/doc/refman/en/optimizing-innodb-diskio.html), `noop` or `deadline` might be better options. It's worth testing this with on-prem systems.
 
 ##  MySQL storage engines