Terraform: SAP HANA scale-up high-availability cluster configuration guide

This guide shows you how to automate the deployment of SAP HANA in a Red Hat Enterprise Linux (RHEL) or SUSE Linux Enterprise Server (SLES) high-availability (HA) cluster that uses an internal passthrough Network Load Balancer to manage the virtual IP (VIP) address.

The guide uses Terraform to deploy two Compute Engine virtual machines (VMs), two SAP HANA scale-up systems, a virtual IP address (VIP) with an internal passthrough Network Load Balancer implementation, and an OS-based HA cluster, all according to the best practices from Google Cloud, SAP, and the OS vendor.

One of the SAP HANA systems functions as the primary, active system and the other functions as a secondary, standby system. You deploy both SAP HANA systems within the same region, ideally in different zones.

Overview of a high-availability Linux cluster for a single-node SAP HANA scaleup system

The deployed cluster includes the following functions and features:

  • The Pacemaker high-availability cluster resource manager.
  • A Google Cloud fencing mechanism.
  • A virtual IP (VIP) that uses a level 4 TCP internal load balancer implementation, including:
    • A reservation of the IP address that you select for the VIP.
    • Two Compute Engine instance groups.
    • A TCP internal load balancer.
    • A Compute Engine health check.
  • In RHEL HA clusters:
    • The Red Hat high-availability pattern.
    • The Red Hat resource agent and fencing packages.
  • In SLES HA clusters:
    • The SUSE high-availability pattern.
    • The SUSE SAPHanaSR resource agent package.
  • Synchronous system replication.
  • Memory preload.
  • Automatic restart of the failed instance as the new secondary instance.

If you need a scale-out system with standby hosts for SAP HANA automatic host failover, then you must instead see Terraform: SAP HANA scale-out system with host auto-failover deployment guide.

To deploy an SAP HANA system without a Linux high-availability cluster or standby hosts, use the Terraform: SAP HANA Deployment Guide.

This guide is intended for advanced SAP HANA users who are familiar with Linux high-availability configurations for SAP HANA.

Prerequisites

Before you create the SAP HANA high availability cluster, make sure that the following prerequisites are met:

Creating a network

For security purposes, create a new network. You can control who has access by adding firewall rules or by using another access control method.

If your project has a default VPC network, don't use it. Instead, create your own VPC network so that the only firewall rules in effect are those that you create explicitly.

During deployment, VM instances typically require access to the internet to download Google Cloud's Agent for SAP. If you are using one of the SAP-certified Linux images that are available from Google Cloud, the VM instance also requires access to the internet in order to register the license and to access OS vendor repositories. A configuration with a NAT gateway and with VM network tags supports this access, even if the target VMs do not have external IPs.

To create a VPC network for your project, complete the following steps:

  1. Create a custom mode network. For more information, see Creating a custom mode network.

  2. Create a subnetwork, and specify the region and IP range. For more information, see Adding subnets.

Setting up a NAT gateway

If you need to create one or more VMs without public IP addresses, you need to use network address translation (NAT) to enable the VMs to access the internet. Use Cloud NAT, a Google Cloud distributed, software-defined managed service that lets VMs send outbound packets to the internet and receive any corresponding established inbound response packets. Alternatively, you can set up a separate VM as a NAT gateway.

To create a Cloud NAT instance for your project, see Using Cloud NAT.

After you configure Cloud NAT for your project, your VM instances can securely access the internet without a public IP address.

Adding firewall rules

By default, an implied firewall rule blocks incoming connections from outside your Virtual Private Cloud (VPC) network. To allow incoming connections, set up a firewall rule for your VM. After an incoming connection is established with a VM, traffic is permitted in both directions over that connection.

HA clusters for SAP HANA require at least two firewall rules, one that allows the Compute Engine health check to check the health of the cluster nodes and another that allows the cluster nodes to communicate with each other.

If you are not using a shared VPC network, you need to create the firewall rule for the communication between the nodes, but not for the health checks. The Terraform configuration file creates the firewall rule for the health checks, which you can modify after deployment is complete, if needed.

If you are using a shared VPC network, a network administrator needs to create both firewall rules in the host project.

You can also create a firewall rule to allow external access to specified ports, or to restrict access between VMs on the same network. If the default VPC network type is used, some additional default rules also apply, such as the default-allow-internal rule, which allows connectivity between VMs on the same network on all ports.

Depending on the IT policy that is applicable to your environment, you might need to isolate or otherwise restrict connectivity to your database host, which you can do by creating firewall rules.

Depending on your scenario, you can create firewall rules to allow access for:

  • The default SAP ports that are listed in TCP/IP of All SAP Products.
  • Connections from your computer or your corporate network environment to your Compute Engine VM instance. If you are unsure of what IP address to use, talk to your company's network administrator.
  • SSH connections to your VM instance, including SSH-in-browser.
  • Connection to your VM by using a third-party tool in Linux. Create a rule to allow access for the tool through your firewall.

To create the firewall rules for your project, see Creating firewall rules.

Creating a high-availability Linux cluster with SAP HANA installed

The following instructions use the Terraform configuration file to create a RHEL or SLES cluster with two SAP HANA systems, a primary single-host SAP HANA system on one VM instance and a standby SAP HANA system on another VM instance in the same Compute Engine region. The SAP HANA systems use synchronous system replication and the standby system preloads the replicated data.

You define configuration options for the SAP HANA high-availability cluster in a Terraform configuration file.

  1. Confirm that your current quotas for resources such as persistent disks and CPUs are sufficient for the SAP HANA systems you are about to install. If your quotas are insufficient, then you deployment fails.

    For the SAP HANA quota requirements, see Pricing and quota considerations for SAP HANA.

    Go to Quotas

  2. Open the Cloud Shell.

    Open Cloud Shell

  3. Download the sap_hana_ha.tf configuration file for the SAP HANA high-availability cluster to your working directory:

    $ wget https://storage.googleapis.com/cloudsapdeploy/terraform/latest/terraform/sap_hana_ha/terraform/sap_hana_ha.tf
  4. Open the sap_hana_ha.tf file in the Cloud Shell code editor.

    To open the Cloud Shell code editor, click the pencil icon in the upper right corner of the Cloud Shell terminal window.

  5. In the sap_hana_ha.tf file, update the argument values by replacing the contents inside the double quotation marks with the values for your installation. The arguments are described in the following table.

    Argument Data type Description
    source String

    Specifies the location and version of the Terraform module to use during deployment.

    The sap_hana_ha.tf configuration file includes two instances of the source argument: one that is active and one that is included as a comment. The source argument that is active by default specifies latest as the module version. The second instance of the source argument, which by default is deactivated by a leading # character, specifies a timestamp that identifies a module version.

    If you need all of your deployments to use the same module version, then remove the leading # character from the source argument that specifies the version timestamp and add it to the source argument that specifies latest.

    project_id String Specify the ID of your Google Cloud project in which you are deploying this system. For example, my-project-x.
    machine_type String Specify the type of Compute Engine virtual machine (VM) on which you need to run your SAP system. If you need a custom VM type, then specify a predefined VM type with a number of vCPUs that is closest to the number you need while still being larger. After deployment is complete, modify the number of vCPUs and the amount of memory.

    For example, n1-highmem-32.

    network String Specify the name of the network in which you need to create the load balancer that manages the VIP.

    If you are using a shared VPC network, you must add the ID of the host project as a parent directory of the network name. For example, HOST_PROJECT_ID/NETWORK_NAME.

    subnetwork String Specify the name of the subnetwork that you created in a previous step. If you are deploying to a shared VPC, then specify this value as SHARED_VPC_PROJECT_ID/SUBNETWORK. For example, myproject/network1.
    linux_image String Specify the name of the Linux operating system image on which you want to deploy your SAP system. For example, rhel-9-2-sap-ha or sles-15-sp5-sap. For the list of available operating system images, see the Images page in the Google Cloud console.
    linux_image_project String Specify the Google Cloud project that contains the image that you have specified for the argument linux_image. This project might be your own project or a Google Cloud image project. For a Compute Engine image, specify either rhel-sap-cloud or suse-sap-cloud. To find the image project for your operating system, see Operating system details.
    primary_instance_name String Specify a name of the VM instance for the primary SAP HANA system. The name can contain lowercase letters, numbers, or hyphens.
    primary_zone String Specify a zone in which the primary SAP HANA system is deployed. The primary and secondary zones must be in the same region. For example, us-east1-c.
    secondary_instance_name String Specify a name of the VM instance for the secondary SAP HANA system. The name can contain lowercase letters, numbers, or hyphens.
    secondary_zone String Specify a zone in which the secondary SAP HANA system is deployed. The primary and secondary zones must be in the same region. For example, us-east1-b.
    sap_hana_deployment_bucket String To automatically install SAP HANA on the deployed VMs, specify the path of the Cloud Storage bucket that contains the SAP HANA installation files. Do not include gs:// in the path; include only the bucket name and the names of any folders. For example, my-bucket-name/my-folder.

    The Cloud Storage bucket must exist in the Google Cloud project that you specify for the project_id argument.

    sap_hana_sid String To automatically install SAP HANA on the deployed VMs, specify the SAP HANA system ID. The ID must consist of three alpha-numeric characters and begin with a letter. All letters must be in uppercase. For example, ED1.
    sap_hana_instance_number Integer Optional. Specify the instance number, 0 to 99, of the SAP HANA system. The default is 0.
    sap_hana_sidadm_password String To automatically install SAP HANA on the deployed VMs, specify a temporary SIDadm password for the installation scripts to use during deployment. The password must contain at least 8 characters and include at least one uppercase letter, one lowercase letter, and a number.

    Instead of specifying password as plain text, we recommend that you use a secret. For more information, see Password management.

    sap_hana_sidadm_password_secret String Optional. If you are using Secret Manager to store the SIDadm password, then specify the Name of the secret that corresponds to this password.

    In Secret Manager, make sure that the Secret value, which is the password, contains at least 8 characters and includes at least one uppercase letter, one lowercase letter, and a number.

    For more information, see Password management.

    sap_hana_system_password String To automatically install SAP HANA on the deployed VMs, specify a temporary database superuser password for the installation scripts to use during deployment. The password must contain at least 8 characters and include at least one uppercase letter, one lowercase letter, and a number.

    Instead of specifying password as plain text, we recommend that you use a secret. For more information, see Password management.

    sap_hana_system_password_secret String Optional. If you are using Secret Manager to store the database superuser password, then specify the Name of the secret that corresponds to this password.

    In Secret Manager, make sure that the Secret value, which is the password, contains at least 8 characters and includes at least one uppercase letter, one lowercase letter, and a number.

    For more information, see Password management.

    sap_hana_double_volume_size Boolean Optional. To double the HANA volume size, specify true. This argument is useful when you want to deploy multiple SAP HANA instances or a disaster-recovery SAP HANA instance on the same VM. By default, the volume size is automatically calculated to be the minimum size required for the size of your VM, while still meeting the SAP certification and support requirements. The default value is false.
    sap_hana_backup_size Integer Optional. Specify size of the /hanabackup volume in GB. If you don't specify this argument or set it to 0, then the installation script provisions Compute Engine instance with a HANA backup volume of two times the total memory.
    sap_hana_sidadm_uid Integer Optional. Specify a value to override the default value of the SID_LCadm user ID. The default value is 900. You can change this to a different value for consistency within your SAP landscape.
    sap_hana_sapsys_gid Integer Optional. Overrides the default group ID for sapsys. The default value is 79.
    sap_vip String Specify the IP address that you are going to use for your VIP. The IP address must be within the range of IP addresses that are assigned to your subnetwork. The Terraform configuration file reserves this IP address for you.
    primary_instance_group_name String Optional. Specify the name of the unmanaged instance group for the primary node. The default name is ig-PRIMARY_INSTANCE_NAME.
    secondary_instance_group_name String Optional. Specify the name of the unmanaged instance group for the secondary node. The default name is ig-SECONDARY_INSTANCE_NAME.
    loadbalancer_name String Optional. Specify the name of the internal passthrough Network Load Balancer. The default name is lb-SAP_HANA_SID-ilb.
    network_tags String Optional. Specify one or more comma-separated network tags that you want to associate with your VM instances for firewall or routing purposes.

    A network tag for the ILB components is automatically added to VM's Network tags.

    nic_type String Optional. Specify the network interface to use with the VM instance. You can specify the value GVNIC or VIRTIO_NET. To use a Google Virtual NIC (gVNIC), you need to specify an OS image that supports gVNIC as the value for the linux_image argument. For the OS image list, see Operating system details.

    If you do not specify a value for this argument, then the network interface is automatically selected based on the machine type that you specify for the machine_type argument.

    This argument is available in sap_hana module version 202302060649 or later.
    disk_type String Optional. Specify the default type of persistent disk or Hyperdisk that you want to deploy for all the SAP volumes in your deployment. The default value is pd-ssd. The following are valid values for this argument: pd-ssd, pd-balanced, hyperdisk-extreme, hyperdisk-balanced, and pd-extreme.

    Note that when you specify the value hyperdisk-extreme or hyperdisk-balanced, the /usr/sap directory is mounted on a separate balanced persistent disk (pd-balanced). This is because /usr/sap directory doesn't require as high a performance as the /hana/data or /hana/log directory. In SAP HANA scale-up deployments, a separate balanced persistent disk is also deployed for the /hana/shared directory.

    You can override this default disk type and the associated default disk size and default IOPS using some advanced arguments. For more information, navigate to your working directory, then run the terraform init command, and then see the /.terraform/modules/sap_hana_ha/variables.tf file. Before you use these arguments in production, make sure to test them in a test environment.

    use_single_shared_data_log_disk Boolean Optional. The default value is false, which directs Terraform to deploy a separate persistent disk or Hyperdisk for each of the following SAP volumes: /hana/data, /hana/log, /hana/shared, and /usr/sap. To mount these SAP volumes on the same persistent disk or Hyperdisk, specify true.
    include_backup_disk Boolean Optional. This argument is applicable to SAP HANA scale-up deployments. The default value is true, which directs Terraform to deploy a standard HDD persistent disk to host the /hanabackup directory. The size of this disk is determined by the sap_hana_backup_size argument.

    If you set the value for include_backup_disk as false, then no disk is deployed for the /hanabackup directory.

    backup_disk_type String Optional. For scale-up deployments, specify the type of persistent disk or Hyperdisk that you want to deploy for the /hanabackup volume. By default, a Balanced Persistent Disk (pd-balanced) is deployed. The following are the valid values for this argument: pd-ssd, pd-balanced, pd-standard, hyperdisk-extreme, hyperdisk-balanced, and pd-extreme.

    This argument is available in sap_hana_ha module version 202307061058 or later.

    enable_fast_restart Boolean Optional. This argument determines whether or not the SAP HANA Fast Restart option is enabled for your deployment. The default value is true. Google Cloud strongly recommends enabling the SAP HANA Fast Restart option.

    This argument is available in sap_hana_ha module version 202309280828 or later.

    public_ip Boolean Optional. Determines whether or not a public IP address is added to your VM instance. The default value is true.
    service_account String Optional. Specify the email address of a user-managed service account to be used by the host VMs and by the programs that run on the host VMs. For example, svc-acct-name@project-id.iam.gserviceaccount.com.

    If you specify this argument without a value, or omit it, then the installation script uses the Compute Engine default service account. For more information, see Identity and access management for SAP programs on Google Cloud.

    sap_deployment_debug Boolean Optional. Only when Cloud Customer Care asks you to enable debugging for your deployment, specify true, which makes the deployment generate verbose deployment logs. The default value is false.
    primary_reservation_name String Optional. To use a specific Compute Engine VM reservation for provisioning the VM instance that hosts your HA cluster's primary SAP HANA instance, specify the name of the reservation. By default, the installation script selects any available Compute Engine reservation based on the following conditions.

    For a reservation to be usable, regardless of whether you specify a name or the installation script selects it automatically, the reservation must be set with the following:

    • The specificReservationRequired option is set to true or, in the Google Cloud console, the Select specific reservation option is selected.
    • Some Compute Engine machine types support CPU platforms that are not covered by the SAP certification of the machine type. If the target reservation is for any of the following machine types, then the reservation must specify the minimum CPU platforms as indicated:
      • n1-highmem-32: Intel Broadwell
      • n1-highmem-64: Intel Broadwell
      • n1-highmem-96: Intel Skylake
      • m1-megamem-96: Intel Skylake
    • The minimum CPU platforms for all of the other machine types that are certified by SAP for use on Google Cloud conform to the SAP minimum CPU requirement.
    secondary_reservation_name String Optional. To use a specific Compute Engine VM reservation for provisioning the VM instance that hosts your HA cluster's secondary SAP HANA instance, specify the name of the reservation. By default, the installation script selects any available Compute Engine reservation based on the following conditions.

    For a reservation to be usable, regardless of whether you specify a name or the installation script selects it automatically, the reservation must be set with the following:

    • The specificReservationRequired option is set to true or, in the Google Cloud console, the Select specific reservation option is selected.
    • Some Compute Engine machine types support CPU platforms that are not covered by the SAP certification of the machine type. If the target reservation is for any of the following machine types, then the reservation must specify the minimum CPU platforms as indicated:
      • n1-highmem-32: Intel Broadwell
      • n1-highmem-64: Intel Broadwell
      • n1-highmem-96: Intel Skylake
      • m1-megamem-96: Intel Skylake
    • The minimum CPU platforms for all of the other machine types that are certified by SAP for use on Google Cloud conform to the SAP minimum CPU requirement.
    primary_static_ip String Optional. Specify a valid static IP address for the primary VM instance in your high-availability cluster. If you don't specify one, then an IP address is automatically generated for your VM instance. For example, 128.10.10.10.

    This argument is available in sap_hana_ha module version 202306120959 or later.

    secondary_static_ip String Optional. Specify a valid static IP address for the secondary VM instance in your high-availability cluster. If you don't specify one, then an IP address is automatically generated for your VM instance. For example, 128.11.11.11.

    This argument is available in sap_hana_ha module version 202306120959 or later.

    The following examples show completed configuration file that defines a high-availability cluster for SAP HANA. The cluster uses an internal passthrough Network Load Balancer to manage the VIP.

    Terraform deploys the Google Cloud resources that are defined in the configuration file and then scripts take over to configure the operating system, install SAP HANA, configure replication, and configure the Linux HA cluster.

    Click RHEL or SLES to see the example that is specific to your operating system. For clarity, comments in the configuration file are omitted in the examples.

    RHEL

        # ...
        module "sap_hana_ha" {
        source = "https://storage.googleapis.com/cloudsapdeploy/terraform/latest/terraform/sap_hana_ha/sap_hana_ha_module.zip"
        #
        # By default, this source file uses the latest release of the terraform module
        # for SAP on Google Cloud.  To fix your deployments to a specific release
        # of the module, comment out the source argument above and uncomment the source argument below.
        #
        # source = "https://storage.googleapis.com/cloudsapdeploy/terraform/YYYYMMDDHHMM/terraform/sap_hana_ha/sap_hana_ha_module.zip"
        #
        # ...
        #
        project_id = "example-project-123456"
        machine_type = "n2-highmem-32"
        network = "example-network"
        subnetwork = "example-subnet-us-central1"
        linux_image = "rhel-8-4-sap-ha"
        linux_image_project = "rhel-sap-cloud"
    
        primary_instance_name = "example-ha-vm1"
        primary_zone = "us-central1-a"
    
        secondary_instance_name = "example-ha-vm2"
        secondary_zone = "us-central1-c"
        # ...
        sap_hana_deployment_bucket = "my-hana-bucket"
        sap_hana_sid = "HA1"
        sap_hana_instance_number = 00
        sap_hana_sidadm_password = "TempPa55word"
        sap_hana_system_password = "TempPa55word"
        # ...
        sap_vip = 10.0.0.100
        primary_instance_group_name = ig-example-ha-vm1
        secondary_instance_group_name = ig-example-ha-vm2
        loadbalancer_name = lb-ha1
        # ...
        network_tags = hana-ha-ntwk-tag
        service_account = "sap-deploy-example@example-project-123456.iam.gserviceaccount.com"
        primary_static_ip = "10.0.0.1"
        secondary_static_ip = "10.0.0.2"
        enable_fast_restart = true
        # ...
        }

    SLES

        # ...
        module "sap_hana_ha" {
        source = "https://storage.googleapis.com/cloudsapdeploy/terraform/latest/terraform/sap_hana_ha/sap_hana_ha_module.zip"
        #
        # By default, this source file uses the latest release of the terraform module
        # for SAP on Google Cloud.  To fix your deployments to a specific release
        # of the module, comment out the source argument above and uncomment the source argument below.
        #
        # source = "https://storage.googleapis.com/cloudsapdeploy/terraform/YYYYMMDDHHMM/terraform/sap_hana_ha/sap_hana_ha_module.zip"
        #
        # ...
        #
        project_id = "example-project-123456"
        machine_type = "n2-highmem-32"
        network = "example-network"
        subnetwork = "example-subnet-us-central1"
        linux_image = "sles-15-sp3-sap"
        linux_image_project = "suse-sap-cloud"
    
        primary_instance_name = "example-ha-vm1"
        primary_zone = "us-central1-a"
    
        secondary_instance_name = "example-ha-vm2"
        secondary_zone = "us-central1-c"
        # ...
        sap_hana_deployment_bucket = "my-hana-bucket"
        sap_hana_sid = "HA1"
        sap_hana_instance_number = 00
        sap_hana_sidadm_password = "TempPa55word"
        sap_hana_system_password = "TempPa55word"
        # ...
        sap_vip = 10.0.0.100
        primary_instance_group_name = ig-example-ha-vm1
        secondary_instance_group_name = ig-example-ha-vm2
        loadbalancer_name = lb-ha1
        # ...
        network_tags = hana-ha-ntwk-tag
        service_account = "sap-deploy-example@example-project-123456.iam.gserviceaccount.com"
        primary_static_ip = "10.0.0.1"
        secondary_static_ip = "10.0.0.2"
        enable_fast_restart = true
        # ...
        }
  6. Initialize your current working directory and download the Terraform provider plugin and module files for Google Cloud:

    terraform init

    The terraform init command prepares your working directory for other Terraform commands.

    To force a refresh of the provider plugin and configuration files in your working directory, specify the --upgrade flag. If the --upgrade flag is omitted and you don't make any changes in your working directory, Terraform uses the locally cached copies, even if latest is specified in the source URL.

    terraform init --upgrade 
  7. Optionally, create the Terraform execution plan:

    terraform plan

    The terraform plan command shows the changes required by your current configuration. If you skip this step, the terraform apply command automatically creates a new plan and prompts you to approve it.

  8. Apply the execution plan:

    terraform apply

    When you are prompted to approve the actions, enter yes.

    The terraform apply command sets up the Google Cloud infrastructure and then hands control over to a script that configures the HA cluster and installs SAP HANA according to the arguments defined in the terraform configuration file.

    While Terraform has control, status messages are written to the Cloud Shell. After the scripts are invoked, status messages are written to Logging and are viewable in the Google Cloud console, as described in Check the logs.

Verifying the deployment of your HANA HA system

Verifying an SAP HANA HA cluster involves several different procedures:

  • Checking Logging
  • Checking the configuration of the VM and the SAP HANA installation
  • Checking the cluster configuration
  • Checking the load balancer and the health of the instance groups
  • Checking the SAP HANA system using SAP HANA Studio
  • Performing a failover test

Check the logs

  1. In the Google Cloud console, open Cloud Logging to monitor installation progress and check for errors.

    Go to Cloud Logging

  2. Filter the logs:

    Logs Explorer

    1. In the Logs Explorer page, go to the Query pane.

    2. From the Resource drop-down menu, select Global, and then click Add.

      If you don't see the Global option, then in the query editor, enter the following query:

      resource.type="global"
      "Deployment"
      
    3. Click Run query.

    Legacy Logs Viewer

    • In the Legacy Logs Viewer page, from the basic selector menu, select Global as your logging resource.
  3. Analyze the filtered logs:

    • If "--- Finished" is displayed, then the deployment processing is complete and you can proceed to the next step.
    • If you see a quota error:

      1. On the IAM & Admin Quotas page, increase any of your quotas that do not meet the SAP HANA requirements that are listed in the SAP HANA planning guide.

      2. Open Cloud Shell.

        Go to Cloud Shell

      3. Go to your working directory and delete the deployment to clean up the VMs and persistent disks from the failed installation:

        terraform destroy

        When you are prompted to approve the action, enter yes.

      4. Rerun your deployment.

Check the configuration of the VM and the SAP HANA installation

  1. After the SAP HANA system deploys without errors, connect to each VM by using SSH. From the Compute Engine VM instances page, you can click the SSH button for each VM instance, or you can use your preferred SSH method.

    SSH button on Compute Engine VM instances page.

  2. Change to the root user.

    sudo su -
  3. At the command prompt, enter df -h. Ensure that you see output that includes the /hana directories, such as /hana/data.

    RHEL

    [root@example-ha-vm1 ~]# df -h
    Filesystem                        Size  Used Avail Use% Mounted on
    devtmpfs                          126G     0  126G   0% /dev
    tmpfs                             126G   54M  126G   1% /dev/shm
    tmpfs                             126G   25M  126G   1% /run
    tmpfs                             126G     0  126G   0% /sys/fs/cgroup
    /dev/sda2                          30G  5.4G   25G  18% /
    /dev/sda1                         200M  6.9M  193M   4% /boot/efi
    /dev/mapper/vg_hana-shared        251G   52G  200G  21% /hana/shared
    /dev/mapper/vg_hana-sap            32G  477M   32G   2% /usr/sap
    /dev/mapper/vg_hana-data          426G  9.8G  417G   3% /hana/data
    /dev/mapper/vg_hana-log           125G  7.0G  118G   6% /hana/log
    /dev/mapper/vg_hanabackup-backup  512G  9.3G  503G   2% /hanabackup
    tmpfs                              26G     0   26G   0% /run/user/900
    tmpfs                              26G     0   26G   0% /run/user/899
    tmpfs                              26G     0   26G   0% /run/user/1003

    SLES

    example-ha-vm1:~ # df -h
    Filesystem                        Size  Used Avail Use% Mounted on
    devtmpfs                          126G  8.0K  126G   1% /dev
    tmpfs                             189G   54M  189G   1% /dev/shm
    tmpfs                             126G   34M  126G   1% /run
    tmpfs                             126G     0  126G   0% /sys/fs/cgroup
    /dev/sda3                          30G  5.4G   25G  18% /
    /dev/sda2                          20M  2.9M   18M  15% /boot/efi
    /dev/mapper/vg_hana-shared        251G   50G  202G  20% /hana/shared
    /dev/mapper/vg_hana-sap            32G  281M   32G   1% /usr/sap
    /dev/mapper/vg_hana-data          426G  8.0G  418G   2% /hana/data
    /dev/mapper/vg_hana-log           125G  4.3G  121G   4% /hana/log
    /dev/mapper/vg_hanabackup-backup  512G  6.4G  506G   2% /hanabackup
    tmpfs                              26G     0   26G   0% /run/user/473
    tmpfs                              26G     0   26G   0% /run/user/900
    tmpfs                              26G     0   26G   0% /run/user/0
    tmpfs                              26G     0   26G   0% /run/user/1003
  4. Check the status of the new cluster by entering the status command that is specific to your operating system:

    RHEL

    pcs status

    SLES

    crm status

    You should see results similar to the following the example, in which both VM instances are started and example-ha-vm1 is the active primary instance:

    RHEL

    [root@example-ha-vm1 ~]# pcs status
    Cluster name: hacluster
    Cluster Summary:
      * Stack: corosync
      * Current DC: example-ha-vm1 (version 2.0.3-5.el8_2.4-4b1f869f0f) - partition with quorum
      * Last updated: Wed Jul  7 23:05:11 2021
      * Last change:  Wed Jul  7 23:04:43 2021 by root via crm_attribute on example-ha-vm2
      * 2 nodes configured
      * 8 resource instances configured
    
    Node List:
      * Online: [ example-ha-vm1 example-ha-vm2 ]
    
    Full List of Resources:
      * STONITH-example-ha-vm1      (stonith:fence_gce):    Started example-ha-vm2
      * STONITH-example-ha-vm2      (stonith:fence_gce):    Started example-ha-vm1
      * Resource Group: g-primary:
        * rsc_healthcheck_HA1       (service:haproxy):      Started example-ha-vm2
        * rsc_vip_HA1_00    (ocf::heartbeat:IPaddr2):       Started example-ha-vm2
      * Clone Set: SAPHanaTopology_HA1_00-clone [SAPHanaTopology_HA1_00]:
        * Started: [ example-ha-vm1 example-ha-vm2 ]
      * Clone Set: SAPHana_HA1_00-clone [SAPHana_HA1_00] (promotable):
        * Masters: [ example-ha-vm2 ]
        * Slaves: [ example-ha-vm1 ]
    
    Failed Resource Actions:
      * rsc_healthcheck_HA1_start_0 on example-ha-vm1 'error' (1): call=29, status='complete', exitreason='', last-rc-change='2021-07-07 21:07:35Z', queued=0ms, exec=2097ms
      * SAPHana_HA1_00_monitor_61000 on example-ha-vm1 'not running' (7): call=44, status='complete', exitreason='', last-rc-change='2021-07-07 21:09:49Z', queued=0ms, exec=0ms
    
    Daemon Status:
      corosync: active/enabled
      pacemaker: active/enabled
      pcsd: active/enabled

    SLES

    example-ha-vm1:~ # crm status
    Cluster Summary:
      * Stack: corosync
      * Current DC: example-ha-vm1 (version 2.0.4+20200616.2deceaa3a-3.9.1-2.0.4+20200616.2deceaa3a) - partition with quorum
      * Last updated: Wed Jul  7 22:57:59 2021
      * Last change:  Wed Jul  7 22:57:03 2021 by root via crm_attribute on example-ha-vm1
      * 2 nodes configured
      * 8 resource instances configured
    
    Node List:
      * Online: [ example-ha-vm1 example-ha-vm2 ]
    
    Full List of Resources:
      * STONITH-example-ha-vm1      (stonith:external/gcpstonith):   Started example-ha-vm2
      * STONITH-example-ha-vm2      (stonith:external/gcpstonith):   Started example-ha-vm1
      * Resource Group: g-primary:
        * rsc_vip_int-primary       (ocf::heartbeat:IPaddr2):        Started example-ha-vm1
        * rsc_vip_hc-primary        (ocf::heartbeat:anything):       Started example-ha-vm1
      * Clone Set: cln_SAPHanaTopology_HA1_HDB00 [rsc_SAPHanaTopology_HA1_HDB00]:
        * Started: [ example-ha-vm1 example-ha-vm2 ]
      * Clone Set: msl_SAPHana_HA1_HDB00 [rsc_SAPHana_HA1_HDB00] (promotable):
        * Masters: [ example-ha-vm1 ]
        * Slaves: [ example-ha-vm2 ]
  5. Change to the SAP admin user by replacing SID_LC in the following command with the sap_hana_sid value that you specified in the sap_hana_ha.tf file. The SID_LC value must be in lowercase.

    su - SID_LCadm
    
  6. Ensure that the SAP HANA services, such as hdbnameserver, hdbindexserver, and others, are running on the instance by entering the following command:

    HDB info
    
  7. If you are using RHEL for SAP 9.0 or later, then make sure that the packages chkconfig and compat-openssl11 are installed on your VM instance.

    For more information from SAP, see SAP Note 3108316 - Red Hat Enterprise Linux 9.x: Installation and Configuration .

Check your cluster configuration

Check the parameter settings of your cluster. Check both the settings that are displayed by your cluster software and the parameter settings in the cluster configuration file. Compare your settings to the settings in the examples below, which were created by the automation scripts that are used in this guide.

Click on the tab for your operating system.

RHEL

  1. Display your cluster resource configurations:

    pcs config show

    The following example shows the resource configurations that are created by the automation scripts on RHEL 8.1 and later.

    If you are running RHEL 7.7 or earlier, the resource definition Clone: SAPHana_HA1_00-clone does not include Meta Attrs: promotable=true.

     Cluster Name: hacluster
     Corosync Nodes:
      example-rha-vm1 example-rha-vm2
     Pacemaker Nodes:
      example-rha-vm1 example-rha-vm2
    
     Resources:
      Group: g-primary
       Resource: rsc_healthcheck_HA1 (class=service type=haproxy)
        Operations: monitor interval=10s timeout=20s (rsc_healthcheck_HA1-monitor-interval-10s)
                    start interval=0s timeout=100 (rsc_healthcheck_HA1-start-interval-0s)
                    stop interval=0s timeout=100 (rsc_healthcheck_HA1-stop-interval-0s)
       Resource: rsc_vip_HA1_00 (class=ocf provider=heartbeat type=IPaddr2)
        Attributes: cidr_netmask=32 ip=10.128.15.100 nic=eth0
        Operations: monitor interval=3600s timeout=60s (rsc_vip_HA1_00-monitor-interval-3600s)
                    start interval=0s timeout=20s (rsc_vip_HA1_00-start-interval-0s)
                    stop interval=0s timeout=20s (rsc_vip_HA1_00-stop-interval-0s)
      Clone: SAPHanaTopology_HA1_00-clone
       Meta Attrs: clone-max=2 clone-node-max=1 interleave=true
       Resource: SAPHanaTopology_HA1_00 (class=ocf provider=heartbeat type=SAPHanaTopology)
        Attributes: InstanceNumber=00 SID=HA1
        Operations: methods interval=0s timeout=5 (SAPHanaTopology_HA1_00-methods-interval-0s)
                    monitor interval=10 timeout=600 (SAPHanaTopology_HA1_00-monitor-interval-10)
                    reload interval=0s timeout=5 (SAPHanaTopology_HA1_00-reload-interval-0s)
                    start interval=0s timeout=600 (SAPHanaTopology_HA1_00-start-interval-0s)
                    stop interval=0s timeout=300 (SAPHanaTopology_HA1_00-stop-interval-0s)
      Clone: SAPHana_HA1_00-clone
       Meta Attrs: promotable=true
       Resource: SAPHana_HA1_00 (class=ocf provider=heartbeat type=SAPHana)
        Attributes: AUTOMATED_REGISTER=true DUPLICATE_PRIMARY_TIMEOUT=7200 InstanceNumber=00 PREFER_SITE_TAKEOVER=true SID=HA1
        Meta Attrs: clone-max=2 clone-node-max=1 interleave=true notify=true
        Operations: demote interval=0s timeout=3600 (SAPHana_HA1_00-demote-interval-0s)
                    methods interval=0s timeout=5 (SAPHana_HA1_00-methods-interval-0s)
                    monitor interval=61 role=Slave timeout=700 (SAPHana_HA1_00-monitor-interval-61)
                    monitor interval=59 role=Master timeout=700 (SAPHana_HA1_00-monitor-interval-59)
                    promote interval=0s timeout=3600 (SAPHana_HA1_00-promote-interval-0s)
                    reload interval=0s timeout=5 (SAPHana_HA1_00-reload-interval-0s)
                    start interval=0s timeout=3600 (SAPHana_HA1_00-start-interval-0s)
                    stop interval=0s timeout=3600 (SAPHana_HA1_00-stop-interval-0s)
    
     Stonith Devices:
      Resource: STONITH-example-rha-vm1 (class=stonith type=fence_gce)
       Attributes: pcmk_delay_max=30 pcmk_monitor_retries=4 pcmk_reboot_timeout=300 port=example-rha-vm1 project=sap-certification-env zone=us-central1-a
       Operations: monitor interval=300s timeout=120s (STONITH-example-rha-vm1-monitor-interval-300s)
                   start interval=0 timeout=60s (STONITH-example-rha-vm1-start-interval-0)
      Resource: STONITH-example-rha-vm2 (class=stonith type=fence_gce)
       Attributes: pcmk_monitor_retries=4 pcmk_reboot_timeout=300 port=example-rha-vm2 project=sap-certification-env zone=us-central1-c
       Operations: monitor interval=300s timeout=120s (STONITH-example-rha-vm2-monitor-interval-300s)
                   start interval=0 timeout=60s (STONITH-example-rha-vm2-start-interval-0)
     Fencing Levels:
    
     Location Constraints:
       Resource: STONITH-example-rha-vm1
         Disabled on: example-rha-vm1 (score:-INFINITY) (id:location-STONITH-example-rha-vm1-example-rha-vm1--INFINITY)
       Resource: STONITH-example-rha-vm2
         Disabled on: example-rha-vm2 (score:-INFINITY) (id:location-STONITH-example-rha-vm2-example-rha-vm2--INFINITY)
     Ordering Constraints:
       start SAPHanaTopology_HA1_00-clone then start SAPHana_HA1_00-clone (kind:Mandatory) (non-symmetrical) (id:order-SAPHanaTopology_HA1_00-clone-SAPHana_HA1_00-clone-mandatory)
     Colocation Constraints:
       g-primary with SAPHana_HA1_00-clone (score:4000) (rsc-role:Started) (with-rsc-role:Master) (id:colocation-g-primary-SAPHana_HA1_00-clone-4000)
     Ticket Constraints:
    
     Alerts:
      No alerts defined
    
     Resources Defaults:
      migration-threshold=5000
      resource-stickiness=1000
     Operations Defaults:
      timeout=600s
    
     Cluster Properties:
      cluster-infrastructure: corosync
      cluster-name: hacluster
      dc-version: 2.0.2-3.el8_1.2-744a30d655
      have-watchdog: false
      stonith-enabled: true
      stonith-timeout: 300s
    
     Quorum:
       Options:
    
  2. Display your cluster configuration file, corosync.conf:

    cat /etc/corosync/corosync.conf

    The following example shows the parameters that the automation scripts set for RHEL 8.1 and later.

    If you are using RHEL 7.7 or earlier, the value of transport: is udpu instead of knet:

     totem {
         version: 2
         cluster_name: hacluster
         transport: knet
         join: 60
         max_messages: 20
         token: 20000
         token_retransmits_before_loss_const: 10
         crypto_cipher: aes256
         crypto_hash: sha256
     }
    
     nodelist {
         node {
             ring0_addr: example-rha-vm1
             name: example-rha-vm1
             nodeid: 1
         }
    
         node {
             ring0_addr: example-rha-vm2
             name: example-rha-vm2
             nodeid: 2
         }
     }
    
     quorum {
         provider: corosync_votequorum
         two_node: 1
     }
    
     logging {
         to_logfile: yes
         logfile: /var/log/cluster/corosync.log
         to_syslog: yes
         timestamp: on
     }
    

SLES

  1. Display your cluster resource configurations:

    crm config show

    The automation scripts that are used by this guide create the resource configurations that are shown in the following example:

     node 1: example-ha-vm1 \
             attributes hana_ha1_op_mode=logreplay lpa_ha1_lpt=1635380335 hana_ha1_srmode=syncmem hana_ha1_vhost=example-ha-vm1 hana_ha1_remoteHost=example-ha-vm2 hana_ha1_site=example-ha-vm1
     node 2: example-ha-vm2 \
             attributes lpa_ha1_lpt=30 hana_ha1_op_mode=logreplay hana_ha1_vhost=example-ha-vm2 hana_ha1_site=example-ha-vm2 hana_ha1_srmode=syncmem hana_ha1_remoteHost=example-ha-vm1
     primitive STONITH-example-ha-vm1 stonith:external/gcpstonith \
             op monitor interval=300s timeout=120s \
             op start interval=0 timeout=60s \
             params instance_name=example-ha-vm1 gcloud_path="/usr/bin/gcloud" logging=yes pcmk_reboot_timeout=300 pcmk_monitor_retries=4 pcmk_delay_max=30
     primitive STONITH-example-ha-vm2 stonith:external/gcpstonith \
             op monitor interval=300s timeout=120s \
             op start interval=0 timeout=60s \
             params instance_name=example-ha-vm2 gcloud_path="/usr/bin/gcloud" logging=yes pcmk_reboot_timeout=300 pcmk_monitor_retries=4
     primitive rsc_SAPHanaTopology_HA1_HDB00 ocf:suse:SAPHanaTopology \
             operations $id=rsc_sap2_HA1_HDB00-operations \
             op monitor interval=10 timeout=600 \
             op start interval=0 timeout=600 \
             op stop interval=0 timeout=300 \
             params SID=HA1 InstanceNumber=00
     primitive rsc_SAPHana_HA1_HDB00 ocf:suse:SAPHana \
             operations $id=rsc_sap_HA1_HDB00-operations \
             op start interval=0 timeout=3600 \
             op stop interval=0 timeout=3600 \
             op promote interval=0 timeout=3600 \
             op demote interval=0 timeout=3600 \
             op monitor interval=60 role=Master timeout=700 \
             op monitor interval=61 role=Slave timeout=700 \
             params SID=HA1 InstanceNumber=00 PREFER_SITE_TAKEOVER=true DUPLICATE_PRIMARY_TIMEOUT=7200 AUTOMATED_REGISTER=true
     primitive rsc_vip_hc-primary anything \
             params binfile="/usr/bin/socat" cmdline_options="-U TCP-LISTEN:60000,backlog=10,fork,reuseaddr /dev/null" \
             op monitor timeout=20s interval=10s \
             op_params depth=0
     primitive rsc_vip_int-primary IPaddr2 \
             params ip=10.128.15.101 cidr_netmask=32 nic=eth0 \
             op monitor interval=3600s timeout=60s
     group g-primary rsc_vip_int-primary rsc_vip_hc-primary
     ms msl_SAPHana_HA1_HDB00 rsc_SAPHana_HA1_HDB00 \
             meta notify=true clone-max=2 clone-node-max=1 target-role=Started interleave=true
     clone cln_SAPHanaTopology_HA1_HDB00 rsc_SAPHanaTopology_HA1_HDB00 \
             meta clone-node-max=1 target-role=Started interleave=true
     location LOC_STONITH_example-ha-vm1 STONITH-example-ha-vm1 -inf: example-ha-vm1
     location LOC_STONITH_example-ha-vm2 STONITH-example-ha-vm2 -inf: example-ha-vm2
     colocation col_saphana_ip_HA1_HDB00 4000: g-primary:Started msl_SAPHana_HA1_HDB00:Master
     order ord_SAPHana_HA1_HDB00 Optional: cln_SAPHanaTopology_HA1_HDB00 msl_SAPHana_HA1_HDB00
     property cib-bootstrap-options: \
             have-watchdog=false \
             dc-version="1.1.24+20210811.f5abda0ee-3.18.1-1.1.24+20210811.f5abda0ee" \
             cluster-infrastructure=corosync \
             cluster-name=hacluster \
             maintenance-mode=false \
             stonith-timeout=300s \
             stonith-enabled=true
     rsc_defaults rsc-options: \
             resource-stickiness=1000 \
             migration-threshold=5000
     op_defaults op-options: \
             timeout=600
    
  2. Display your cluster configuration file, corosync.conf:

    cat /etc/corosync/corosync.conf

    The automation scripts that are used by this guide specify parameters settings in the corosync.conf file as shown in the following example:

     totem {
       version: 2
       secauth: off
       crypto_hash: sha1
       crypto_cipher: aes256
       cluster_name: hacluster
       clear_node_high_bit: yes
       token: 20000
       token_retransmits_before_loss_const: 10
       join: 60
       max_messages: 20
       transport: udpu
       interface {
         ringnumber: 0
         bindnetaddr: 10.128.1.63
         mcastport: 5405
         ttl: 1
       }
     }
     logging {
       fileline: off
       to_stderr: no
       to_logfile: no
       logfile: /var/log/cluster/corosync.log
       to_syslog: yes
       debug: off
       timestamp: on
       logger_subsys {
         subsys: QUORUM
         debug: off
       }
     }
     nodelist {
       node {
         ring0_addr: example-ha-vm1
         nodeid: 1
       }
       node {
         ring0_addr: example-ha-vm2
         nodeid: 2
       }
     }
     quorum {
       provider: corosync_votequorum
       expected_votes: 2
       two_node: 1
     }
    

Check the load balancer and the health of the instance groups

To confirm that the load balancer and health check were set up correctly, check the load balancer and instance groups in the Google Cloud console.

  1. Open the Load balancing page in the Google Cloud console:

    Go to Cloud Load Balancing

  2. In the list of load balancers, confirm that a load balancer was created for your HA cluster.

  3. On the Load balancer details page in the Healthy column under Instance group in the Backend section, confirm that one of the instance groups shows "1/1" and the other shows "0/1". After a failover, the healthy indicator, "1/1", switches to the new active instance group.

    Shows the load balancer details page with the active primary instance group
indicated by "1/1" and the inactive secondary indicated by "0/1".

Check the SAP HANA system using SAP HANA Studio

You can use either SAP HANA Cockpit or SAP HANA Studio to monitor and manage your SAP HANA systems in a high-availability cluster.

  1. Connect to the HANA system by using SAP HANA Studio. When defining the connection, specify the following values:

    • On the Specify System panel, specify the floating IP address as the Host Name.
    • On the Connection Properties panel, for database user authentication, specify the database superuser name and the password that you specified for the sap_hana_system_password argument in the sap_hana_ha.tf file.

    For information from SAP about installing SAP HANA Studio, see SAP HANA Studio Installation and Update Guide.

  2. After SAP HANA Studio is connected to your HANA HA system, display the system overview by double-clicking the system name in the navigation pane on the left side of the window.

    Screenshot of the navigation pane in SAP HANA Studio

  3. Under General Information on the Overview tab, confirm that:

    • The Operational Status shows "All services started".
    • The System Replication Status shows "All services are active and in sync".

    Screenshot of the Overview tab in SAP HANA Studio

  4. Confirm the replication mode by clicking the System Replication Status link under General Information. Synchronous replication is indicated by SYNCMEM in the REPLICATION_MODE column on the System Replication tab.

    Screenshot of the System Replication Status tab in SAP HANA Studio

Clean up and retry deployment

If any of the deployment verification steps in the preceding sections show that the installation wasn't successful, then you must undo your deployment and retry it by completing the following steps:

  1. Resolve any errors to ensure that your deployment doesn't fail again for the same reason. For information about checking the logs, or resolving quota related errors, see Check the logs.

  2. Open Cloud Shell or, if you installed the Google Cloud CLI on your local workstation, then open a terminal.

    Open Cloud Shell

  3. Go to the directory that contains the Terraform configuration file that you used for this deployment.

  4. Delete all resources that are part of your deployment by running the following command:

    terraform destroy

    When you are prompted to approve the action, enter yes.

  5. Retry your deployment as instructed earlier in this guide.

Perform a failover test

To perform a failover test, complete the following steps:

  1. Connect to the primary VM by using SSH. You can connect from the Compute Engine VM instances page by clicking the SSH button for each VM instance, or you can use your preferred SSH method.

  2. At the command prompt, enter the following command:

    sudo ip link set eth0 down

    The ip link set eth0 down command triggers a failover by severing communications with the primary host.

  3. Reconnect to either host using SSH and change to the root user.

  4. Confirm that the primary host is now active on the VM that used to contain the secondary host. Automatic restart is enabled in the cluster, so the stopped host will restart and assume the role of secondary host.

    RHEL

    pcs status

    SLES

    crm status

    The following examples show that the roles on each host have switched.

    RHEL

    [root@example-ha-vm1 ~]# pcs status
    Cluster name: hacluster
    Cluster Summary:
      * Stack: corosync
      * Current DC: example-ha-vm1 (version 2.0.3-5.el8_2.3-4b1f869f0f) - partition with quorum
      * Last updated: Fri Mar 19 21:22:07 2021
      * Last change:  Fri Mar 19 21:21:28 2021 by root via crm_attribute on example-ha-vm2
      * 2 nodes configured
      * 8 resource instances configured
    
    Node List:
      * Online: [ example-ha-vm1 example-ha-vm2 ]
    
    Full List of Resources:
      * STONITH-example-ha-vm1  (stonith:fence_gce):    Started example-ha-vm2
      * STONITH-example-ha-vm2  (stonith:fence_gce):    Started example-ha-vm1
      * Resource Group: g-primary:
        * rsc_healthcheck_HA1   (service:haproxy):  Started example-ha-vm2
        * rsc_vip_HA1_00    (ocf::heartbeat:IPaddr2):   Started example-ha-vm2
      * Clone Set: SAPHanaTopology_HA1_00-clone [SAPHanaTopology_HA1_00]:
        * Started: [ example-ha-vm1 example-ha-vm2 ]
      * Clone Set: SAPHana_HA1_00-clone [SAPHana_HA1_00] (promotable):
        * Masters: [ example-ha-vm2 ]
        * Slaves: [ example-ha-vm1 ]
    

    SLES

    example-ha-vm2:~ #
    Cluster Summary:
      * Stack: corosync
      * Current DC: example-ha-vm2 (version 2.0.4+20200616.2deceaa3a-3.9.1-2.0.4+20200616.2deceaa3a) - partition with quorum
      * Last updated: Thu Jul  8 17:33:44 2021
      * Last change:  Thu Jul  8 17:33:07 2021 by root via crm_attribute on example-ha-vm2
      * 2 nodes configured
      * 8 resource instances configured
    
    Node List:
      * Online: [ example-ha-vm1 example-ha-vm2 ]
    
    Full List of Resources:
      * STONITH-example-ha-vm1      (stonith:external/gcpstonith):   Started example-ha-vm2
      * STONITH-example-ha-vm2      (stonith:external/gcpstonith):   Started example-ha-vm1
      * Resource Group: g-primary:
        * rsc_vip_int-primary       (ocf::heartbeat:IPaddr2):        Started example-ha-vm2
        * rsc_vip_hc-primary        (ocf::heartbeat:anything):       Started example-ha-vm2
      * Clone Set: cln_SAPHanaTopology_HA1_HDB00 [rsc_SAPHanaTopology_HA1_HDB00]:
        * Started: [ example-ha-vm1 example-ha-vm2 ]
      * Clone Set: msl_SAPHana_HA1_HDB00 [rsc_SAPHana_HA1_HDB00] (promotable):
        * Masters: [ example-ha-vm2 ]
        * Slaves: [ example-ha-vm1 ]
  5. On the Load balancer details page in the console, confirm that the new active primary instance shows "1/1" in the Healthy column. Refresh the page, if necessary.

    Go to Cloud Load Balancing

    For example:

    Shows the load balancer details page with the "ig-example-ha-vm2" instance
showing "1/1" in the Healthy column.

  6. In SAP HANA Studio, confirm that you are still connected to the system by double-clicking the system entry in the navigation pane to refresh the system information.

  7. Click the System Replication Status link to confirm that the primary and secondary hosts have switched hosts and are active.

    Screenshot of the System Replication Status tab in SAP HANA Studio

Validate your installation of Google Cloud's Agent for SAP

After you have deployed a VM and installed your SAP system, validate that Google Cloud's Agent for SAP is functioning properly.

Verify that Google Cloud's Agent for SAP is running

To verify that the agent is running, follow these steps:

  1. Establish an SSH connection with your host VM instance.

  2. Run the following command:

    systemctl status google-cloud-sap-agent

    If the agent is functioning properly, then the output contains active (running). For example:

    google-cloud-sap-agent.service - Google Cloud Agent for SAP
    Loaded: loaded (/usr/lib/systemd/system/google-cloud-sap-agent.service; enabled; vendor preset: disabled)
    Active:  active (running)  since Fri 2022-12-02 07:21:42 UTC; 4 days ago
    Main PID: 1337673 (google-cloud-sa)
    Tasks: 9 (limit: 100427)
    Memory: 22.4 M (max: 1.0G limit: 1.0G)
    CGroup: /system.slice/google-cloud-sap-agent.service
           └─1337673 /usr/bin/google-cloud-sap-agent
    

If the agent isn't running, then restart the agent.

Verify that SAP Host Agent is receiving metrics

To verify that the infrastructure metrics are collected by Google Cloud's Agent for SAP and sent correctly to the SAP Host Agent, follow these steps:

  1. In your SAP system, enter transaction ST06.
  2. In the overview pane, check the availability and content of the following fields for the correct end-to-end setup of the SAP and Google monitoring infrastructure:

    • Cloud Provider: Google Cloud Platform
    • Enhanced Monitoring Access: TRUE
    • Enhanced Monitoring Details: ACTIVE

Set up monitoring for SAP HANA

Optionally, you can monitor your SAP HANA instances using Google Cloud's Agent for SAP. From version 2.0, you can configure the agent to collect the SAP HANA monitoring metrics and send them to Cloud Monitoring. Cloud Monitoring allows you to create dashboards to visualize these metrics, set up alerts based on metric thresholds, and more.

To monitor an HA cluster using Google Cloud's Agent for SAP, make sure to follow the guidance given in High-availability configuration for the agent.

For more information about the collection of SAP HANA monitoring metrics using Google Cloud's Agent for SAP, see SAP HANA monitoring metrics collection.

Connect to SAP HANA

Note that because these instructions don't use an external IP address for SAP HANA, you can only connect to the SAP HANA instances through the bastion instance using SSH or through the Windows server through SAP HANA Studio.

  • To connect to SAP HANA through the bastion instance, connect to the bastion host, and then to the SAP HANA instance(s) by using an SSH client of your choice.

  • To connect to the SAP HANA database through SAP HANA Studio, use a remote desktop client to connect to the Windows Server instance. After connection, manually install SAP HANA Studio and access your SAP HANA database.

Configure HANA Active/Active (Read Enabled)

Starting with SAP HANA 2.0 SPS1, you can configure HANA Active/Active (Read Enabled) in a Pacemaker cluster. For instructions, see:

Performing post-deployment tasks

Before using your SAP HANA instance, we recommend that you perform the following post-deployment steps. For more information, see SAP HANA Installation and Update Guide.

  1. Change the temporary passwords for the SAP HANA system administrator and database superuser.

  2. Update the SAP HANA software with the latest patches.

  3. If your SAP HANA system is deployed on a VirtIO network interface, then we recommend that you ensure the value of the TCP parameter /proc/sys/net/ipv4/tcp_limit_output_bytes is set to 1048576. This modification helps improve the overall network throughput on the VirtIO network interface without affecting the network latency.

  4. Install any additional components such as Application Function Libraries (AFL) or Smart Data Access (SDA).

  5. Configure and backup your new SAP HANA database. For more information, see the SAP HANA operations guide.

Evaluate your SAP HANA workload

To automate continuous validation checks for your SAP HANA high-availability workloads running on Google Cloud, you can use Workload Manager.

Workload Manager allows you to automatically scan and evaluate your SAP HANA high-availability workloads against best practices from SAP, Google Cloud, and OS vendors. This helps improve the quality, performance, and reliability of your workloads.

For information about the best practices that Workload Manager supports for evaluating SAP HANA high-availability workloads running on Google Cloud, see Workload Manager best practices for SAP. For information about creating and running an evaluation using Workload Manager, see Create and run an evaluation.

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