HA scale-out cluster configuration guide for SAP HANA on SLES

This guide shows you how to deploy and configure a performance-optimized SUSE Linux Enterprise Server (SLES) high-availability (HA) cluster for an SAP HANA scale-out system on Google Cloud.

This guide includes the steps for:

• Configuring an internal passthrough Network Load Balancer to reroute traffic in the event of a failure
• Configuring a Pacemaker cluster on SLES to manage the SAP systems and other resources during a failover

This guide also includes steps for configuring SAP HANA system replication, but refer to the SAP documentation for the definitive instructions.

To deploy a SAP HANA system without a Linux high-availability cluster or a standby node host, use the SAP HANA deployment guide.

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

The system that this guide deploys

Following this guide, you will deploy a multi-node SAP HANA HA system configured for full zone-redundancy with an additional instance acting as a majority maker, also known as tie-breaker node, which ensures the cluster quorum is maintained in case of the loss of one zone.

The final deployment comprises of the following resources:

• A primary and secondary site where each instance has a zonal counterpart.
• Two sites configured for synchronous replication.
• A single compute instance to act as a majority maker.
• A Pacemaker high-availability cluster resource manager with a fencing mechanism.
• Persistent disk(s) for SAP HANA data and log volumes attached to each SAP HANA instance.

This guide has you use the Terraform templates that are provided by Google Cloud to deploy the Compute Engine virtual machines (VMs) and the SAP HANA instances, which ensures that the VMs and the base SAP HANA systems meet SAP supportability requirements and conform to current best practices.

SAP HANA Studio is used in this guide to test SAP HANA system replication. You can use SAP HANA Cockpit instead, if you prefer. For information about installing SAP HANA Studio, see:

• Installing SAP HANA Studio on a Compute Engine Windows VM
• SAP HANA Studio Installation and Update Guide

Prerequisites

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

• You have read the SAP HANA planning guide and the SAP HANA high-availability planning guide.
• You or your organization has a Google Cloud account and you have created a project for the SAP HANA deployment. For information about creating Google Cloud accounts and projects, see Setting up your Google account in the SAP HANA Deployment Guide.
• If you require your SAP workload to run in compliance with data residency, access control, support personnel, or regulatory requirements, then you must create the required Assured Workloads folder. For more information, see Compliance and sovereign controls for SAP on Google Cloud.

• The SAP HANA installation media is stored in a Cloud Storage bucket that is available in your deployment project and region. For information about how to upload SAP HANA installation media to a Cloud Storage bucket, see Downloading SAP HANA in the SAP HANA Deployment Guide.

• If OS login is enabled in your project metadata, you need to disable OS login temporarily until your deployment is complete. For deployment purposes, this procedure configures SSH keys in instance metadata. When OS login is enabled, metadata-based SSH key configurations are disabled, and this deployment fails. After deployment is complete, you can enable OS login again.

  For more information, see:

  • Enabling or disabling OS Login
  • Add SSH keys to VMs that use metadata-based SSH keys

• If you are using VPC internal DNS, the value of the vmDnsSetting variable in your project metadata must be either GlobalOnly or ZonalPreferred to enable the resolution of the node names across zones. The default setting of vmDnsSetting is ZonalOnly. For more information, see:

  • Configuring DNS names for your project or instances
  • Querying custom metadata
  • Setting project-wide custom metadata

• You have an NFS solution, such as the managed Filestore solution, for sharing the SAP HANA /hana/shared and /hanabackup volumes among the hosts in the scale-out SAP HANA system. To deploy Filestore NFS servers, see Creating instances.

  • Note that the primary and secondary sites must have access to their own dedicated NFS paths to avoid overwriting data. To use a single Filestore instance, you must configure the deployment to use distinct sub-directories as the mount path.

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 set up networking:

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.

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.

To create a firewall rule:

$ gcloud compute firewall-rules create firewall-name
--direction=INGRESS --priority=1000 \
--network=network-name --action=ALLOW --rules=protocol:port \
--source-ranges ip-range --target-tags=network-tags

Deploying the VMs and SAP HANA

To deploy a multi-node SAP HANA HA system configured for full zone-redundancy, you use the Cloud Deployment Manager template for SAP HANA as base for the configuration, as well as an additional template to deploy a majority maker instance.

The deployment consists of the following:

• Two matching SAP HANA systems, each with two or more worker nodes.
• A single majority maker instance also known as tie-breaker node, which ensures the cluster quorum is maintained in case of the loss of one zone.

You add definition for all systems to the same YAML file such that the Deployment Manager deploys all resources under one deployment. After the SAP HANA systems and the majority maker instance are deployed successfully, you define and configure the HA cluster.

The following instructions use the Cloud Shell, but are generally applicable to the Google Cloud CLI.

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

   Go to the quotas page

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

   Go to the Cloud Shell

3. Download the template.yaml configuration file template for the SAP HANA high-availability cluster to your working directory by entering the following command in the Cloud Shell or gcloud CLI:

   wget https://storage.googleapis.com/cloudsapdeploy/deploymentmanager/latest/dm-templates/sap_hana/template.yaml

4. Optionally, rename the template.yaml file to identify the configuration it defines.

5. Open the template.yaml file in the Cloud Shell code editor or, if you are using the gcloud CLI, the text editor of your choice.

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

6. In the template.yaml file, complete the definition of the primary SAP HANA system. Specify the property values by replacing the brackets and their contents with the values for your installation. The properties are described in the following table.

   To create the VM instances without installing SAP HANA, delete or comment out all of the lines that begin with sap_hana_.

   Property	Data type	Description
   type	String	Specifies the location, type, and version of the Deployment Manager template to use during deployment. The YAML file includes two type specifications, one of which is commented out. The type specification that is active by default specifies the template version as latest. The type specification that is commented out specifies a specific template version with a timestamp. If you need all of your deployments to use the same template version, use the type specification that includes the timestamp.
   instanceName	String	The name of the VM instance currently being defined. Specify different names in the primary and secondary VM definitions. Names must be specified in lowercase letters, numbers, or hyphens.
   instanceType	String	The type of Compute Engine virtual machine that you need to run SAP HANA on. If you need a custom VM type, 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 The minimum recommended instanceType for the majority maker instance is n1-standard-2 or the equivalent of at least 2 CPU cores and 2 GB memory.
   zone	String	The Google Cloud zone in which to deploy the VM instance that your are defining. Specify different zones in the same region for the primary HANA, secondary HANA, and majority maker instance definitions . The zones must be in the same region that you selected for your subnet.
   subnetwork	String	The name of the subnetwork you created in a previous step. If you are deploying to a shared VPC, specify this value as [SHAREDVPC_PROJECT]/[SUBNETWORK]. For example, myproject/network1.
   linuxImage	String	The name of the Linux operating-system image or image family that you are using with SAP HANA. To specify an image family, add the prefix family/ to the family name. For example, family/sles-15-sp1-sap. To specify a specific image, specify only the image name. For the list of available images and families, see the Images page in Google Cloud console.
   linuxImageProject	String	The Google Cloud project that contains the image you are going to use. This project might be your own project or a Google Cloud image project, such as suse-sap-cloud. For more information about Google Cloud image projects, see the Images page in the Compute Engine documentation.
   sap_hana_deployment_bucket	String	The name of the Google Cloud storage bucket in your project that contains the SAP HANA installation and revision files that you uploaded in a previous step. Any upgrade revision files in the bucket are applied to SAP HANA during the deployment process.
   sap_hana_sid	String	The SAP HANA system ID (SID). The ID must consist of three alphanumeric characters and begin with a letter. All letters must be uppercase.
   sap_hana_instance_number	Integer	The instance number, 0 to 99, of the SAP HANA system. The default is 0.
   sap_hana_sidadm_password	String	The password for the operating system (OS) administrator. Passwords must be at least eight characters and include at least one uppercase letter, one lowercase letter, and one number.
   sap_hana_system_password	String	The password for the database superuser. Passwords must be at least 8 characters and include at least one uppercase letter, one lowercase letter, and one number.
   sap_hana_sidadm_uid	Integer	The default value for the SID_LCadm user ID is 900 to avoid user-created groups conflicting with SAP HANA. You can change this to a different value if you need to.
   sap_hana_sapsys_gid	Integer	The default group ID for sapsys is 79. By specifying a value above you can override this value to your requirements.
   sap_hana_scaleout_nodes	Integer	Specify 1 or greater.
   sap_hana_shared_nfs	String	The NFS mount point for the /hana/shared volume. For example, 10.151.91.122:/hana_shared_nfs.
   sap_hana_backup_nfs	String	The NFS mount point for the /hanabackup volume. For example, 10.216.41.122:/hana_backup_nfs.
   networkTag	String	A network tag that represents your VM instance for firewall or routing purposes. If you specify publicIP: No and do not specify a network tag, be sure to provide another means of access to the internet.
   nic_type	String	Optional but recommended if available for the target machine and OS version. Specifies 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 linuxImage property. For the OS image list, see Operating system details. If you do not specify a value for this property, then the network interface is automatically selected based on the machine type that you specify for the instanceType property. This argument is available in Deployment Manager template versions 202302060649 or later.
   publicIP	Boolean	Optional. Determines whether a public IP address is added to your VM instance. The default is Yes.
   serviceAccount	String	Optional. Specifies a service account to be used by the host VMs and by the programs that run on the host VMs. Specify the email address of the service account. For example, svc-acct-name@project-id.iam.gserviceaccount.com. By default, the Compute Engine default service account is used. For more information, see Identity and access management for SAP programs on Google Cloud.

7. Create the definition of the secondary SAP HANA system by copying the definition of the primary SAP HANA system and pasting the copy after the primary SAP HANA system definition. See the example following these steps.

8. In the definition of the secondary SAP HANA system, specify different values for the following properties than you specified in the primary SAP HANA system definition:

   • name
   • instanceName
   • zone

9. Download the sap_majoritymaker.yaml majority maker instance configuration file:

   wget https://storage.googleapis.com/cloudsapdeploy/deploymentmanager/latest/dm-templates/sap_majoritymaker/template.yaml -O sap_majoritymaker.yaml

10. Copy and paste the YAML specification from the sap_majoritymaker.yaml file, starting from line #6 and below, to the bottom of the SAP HANA template.yaml file.

11. Complete the definition for the majority maker instance:

    • Specify a zone that is different from the two SAP HANA systems.
    • The minimum recommended instanceType is n1-standard-2 or the equivalent of at least 2 CPU cores and 2 GB memory.

    You should now have three resources listed in your YAML file, two SAP HANA clusters and one majority maker instance, along with their configurable properties.

12. Create the instances:

    gcloud deployment-manager deployments create DEPLOYMENT_NAME --config TEMPLATE_NAME.yaml

    The above command invokes the Deployment Manager, which deploys the VMs, downloads the SAP HANA software from your storage bucket, and installs SAP HANA, all according to the specifications in your template.yaml file.

    Deployment processing consists of two stages. In the first stage, Deployment Manager writes its status to the console. In the second stage, the deployment scripts write their status to Cloud Logging.

Example of a complete template.yaml configuration file

The following example shows a completed template.yaml configuration file that deploys two scale-out clusters with a SAP HANA system installed, and a single VM instance acting as the majority maker.

The file contains the definitions of two resources to deploy: sap_hana_primary and sap_hana_secondary. Each resource definition contains the definitions for a VM and a SAP HANA instance.

The sap_hana_secondary resource definition was created by copying and pasting the first definition, and then modifying the values of name, instanceName, and zone properties. All other property values in the two resource definitions are the same.

The properties networkTag, serviceAccount, sap_hana_sidadm_uid, and sap_hana_sapsys_gid are from the Advanced Options section of the configuration file template. The properties sap_hana_sidadm_uid and sap_hana_sapsys_gid are included to show their default values, which are used because the properties are commented out.

resources:
- name: sap_hana_primary
  type: https://storage.googleapis.com/cloudsapdeploy/deploymentmanager/latest/dm-templates/sap_hana/sap_hana.py
  #
  # By default, this configuration file uses the latest release of the deployment
  # scripts for SAP on Google Cloud.  To fix your deployments to a specific release
  # of the scripts, comment out the type property above and uncomment the type property below.
  #
  # type: https://storage.googleapis.com/cloudsapdeploy/deploymentmanager/yyyymmddhhmm/dm-templates/sap_hana/sap_hana.py
  #
  properties:
    instanceName: hana-ha-vm-1
    instanceType: n2-highmem-32
    zone: us-central1-a
    subnetwork: example-subnet-us-central1
    linuxImage: family/sles-15-sp1-sap
    linuxImageProject: suse-sap-cloud
    sap_hana_deployment_bucket: hana2-sp4-rev46
    sap_hana_sid: HA1
    sap_hana_instance_number: 22
    sap_hana_sidadm_password: Tempa55word
    sap_hana_system_password: Tempa55word
    sap_hana_scaleout_nodes: 2
    sap_hana_shared_nfs: 10.151.91.123:/hana_shared_nfs
    sap_hana_backup_nfs: 10.216.41.123:/hana_backup_nfs
    networkTag: cluster-ntwk-tag
    serviceAccount: limited-roles@example-project-123456.iam.gserviceaccount.com
    # sap_hana_sidadm_uid: 900
    # sap_hana_sapsys_gid: 79

- name: sap_hana_secondary
  type: https://storage.googleapis.com/cloudsapdeploy/deploymentmanager/latest/dm-templates/sap_hana/sap_hana.py
  #
  # By default, this configuration file uses the latest release of the deployment
  # scripts for SAP on Google Cloud.  To fix your deployments to a specific release
  # of the scripts, comment out the type property above and uncomment the type property below.
  #
  # type: https://storage.googleapis.com/cloudsapdeploy/deploymentmanager/yyyymmddhhmm/dm-templates/sap_hana/sap_hana.py
  #
  properties:
    instanceName: hana-ha-vm-2
    instanceType: n2-highmem-32
    zone: us-central1-c
    subnetwork: example-subnet-us-central1
    linuxImage: family/sles-15-sp1-sap
    linuxImageProject: suse-sap-cloud
    sap_hana_deployment_bucket: hana2-sp4-rev46
    sap_hana_sid: HA1
    sap_hana_instance_number: 22
    sap_hana_sidadm_password: Google123
    sap_hana_system_password: Google123
    sap_hana_scaleout_nodes: 2
    sap_hana_shared_nfs: 10.141.91.124:/hana_shared_nfs
    sap_hana_backup_nfs: 10.106.41.124:/hana_backup_nfs
    networkTag: cluster-ntwk-tag
    serviceAccount: limited-roles@example-project-123456.iam.gserviceaccount.com
    # sap_hana_sidadm_uid: 900
    # sap_hana_sapsys_gid: 79
    
- name: sap_majoritymaker
  type: https://storage.googleapis.com/cloudsapdeploy/deploymentmanager/latest/dm-templates/sap_majoritymaker/sap_majoritymaker.py
  #
  # By default, this configuration file uses the latest release of the deployment
  # scripts for SAP on Google Cloud.  To fix your deployments to a specific release
  # of the scripts, comment out the type property above and uncomment the type property below.
  #
  # type: https://storage.googleapis.com/cloudsapdeploy/deploymentmanager/202208181245/dm-templates/sap_majoritymaker/sap_majoritymaker.py
  properties:
    instanceName: sap-majoritymaker
    instanceType: n1-standard-2
    zone: us-central1-b
    subnetwork: example-subnet-us-central1
    linuxImage: family/sles-15-sp1-sap
    linuxImageProject: suse-sap-cloud
    publicIP: No
    

Create firewall rules that allow access to the host VMs

If you haven't done so already, create firewall rules that allow access to each host VM from the following sources:

• For configuration purposes, your local workstation, a bastion host, or a jump server
• For access between the cluster nodes, the other host VMs in the HA cluster

When you create VPC firewall rules, you specify the network tags that you defined in the template.yaml configuration file to designate your host VMs as the target for the rule.

To verify deployment, define a rule to allow SSH connections on port 22 from a bastion host or your local workstation.

For access between the cluster nodes, add a firewall rule that allows all connection types on any port from other VMs in the same subnetwork.

Make sure that the firewall rules for verifying deployment and for intra-cluster communication are created before proceeding to the next section. For instructions, see Adding firewall rules.

Verifying the deployment of the VMs and SAP HANA

To verify deployment, you check the deployment logs in Cloud Logging and check the disks and services on the VMs of primary and secondary hosts.

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. On the Deployment Manager Deployments page, delete the deployment to clean up the VMs and persistent disks from the failed installation.

     3. Rerun your deployment.

Check the deployment status of the majority maker

You can check the deployment status of the majority maker using the following command.

gcloud compute instances describe MAJORITY_MAKER_HOSTNAME --zone MAJORITY_MAKER_ZONE --format="table[box,title='Deployment Status'](name:label=Instance_Name,metadata.items.status:label=Status)"

If Complete status is displayed, then the deployment processing is successful for the majority maker instance. For an ongoing deployment, <blank> status is displayed.

Check the configuration of the VMs and SAP HANA

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.

   

2. Change to the root user.

   $ sudo su -

3. At the command prompt, enter df -h. On each VM, ensure that you see the /hana directories, such as /hana/data.

   Filesystem                        Size  Used Avail Use% Mounted on
   /dev/sda2                          30G  4.0G   26G  14% /
   devtmpfs                          126G     0  126G   0% /dev
   tmpfs                             126G     0  126G   0% /dev/shm
   tmpfs                             126G   17M  126G   1% /run
   tmpfs                             126G     0  126G   0% /sys/fs/cgroup
   /dev/sda1                         200M  9.7M  191M   5% /boot/efi
   /dev/mapper/vg_hana-shared        251G   49G  203G  20% /hana/shared
   /dev/mapper/vg_hana-sap            32G  240M   32G   1% /usr/sap
   /dev/mapper/vg_hana-data          426G  7.0G  419G   2% /hana/data
   /dev/mapper/vg_hana-log           125G  4.2G  121G   4% /hana/log
   /dev/mapper/vg_hanabackup-backup  512G   33M  512G   1% /hanabackup
   tmpfs                              26G     0   26G   0% /run/user/900
   tmpfs                              26G     0   26G   0% /run/user/899
   tmpfs                              26G     0   26G   0% /run/user/1000

4. Change to the SAP admin user by replacing SID_LC in the following command with the system ID that you specified in the configuration file template. Use lowercase for any letters.

   # su - SID_LCadm

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

   > HDB info

6. 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 .

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 Compute Engine 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 lets you create dashboards to visualize these metrics, set up alerts based on metric thresholds, and more.

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

(Optional) Create a list of instances for script automation

To partially automate some of the repetitive tasks during the configuration of SAP HANA system and Pacemaker cluster, you can use bash scripts. Throughout this guide, such bash scripts are used to speed up the configuration of your SAP HANA system and Pacemaker cluster. These scripts require a list of all deployed VM instances and their corresponding zones as an input.

To enable this automation, create a file named nodes.txt and include the details of all the deployed VM instances in the following format: zone name, whitespace, and then the VM instance name. The following sample file is used throughout this guide:

# cat nodes.txt
  us-west1-a hana-ha-vm-1
  us-west1-a hana-ha-vm-1w1
  us-west1-a hana-ha-vm-1w2
  us-west1-b hana-majoritymaker
  us-west1-c hana-ha-vm-2
  us-west1-c hana-ha-vm-2w1
  us-west1-c hana-ha-vm-2w2
 

Set up passwordless SSH access

To configure the Pacemaker cluster and to synchronize the SAP HANA secure store (SSFS) keys, passwordless SSH access is required between all nodes, including the majority maker instance. For passwordless SSH access, you need to add the SSH public keys to the instance metadata of all deployed instances.

The format of the metadata is USERNAME: PUBLIC-KEY-VALUE.

For more information about adding SSH keys to VMs, see Add SSH keys to VMs that use metadata-based SSH keys.

Manual steps

1. For each instance in the primary and secondary systems, as well as the majority maker instance, collect the public key for the user root.

   gcloud compute ssh --quiet --zone ZONE_ID INSTANCE_NAME -- sudo cat /root/.ssh/id_rsa.pub

2. Prepend the key with the string root: and write the key as a new line into the file called public-ssh-keys.txt, for example:

   root:ssh-rsa AAAAB3NzaC1JfuYnOI1vutCs= root@INSTANCE_NAME

3. After collecting all SSH public keys, upload the keys as metadata to all instances:

   gcloud compute instances add-metadata --metadata-from-file ssh-keys=public-ssh-keys.txt --zone ZONE_ID INSTANCE_NAME

Automated steps

Alternatively, to automate the process of setting up passwordless SSH access for all instances listed in nodes.txt, perform the following steps from Google Cloud console:

1. Create a list of public keys from all deployed instances:

   while read -u10 ZONE HOST ;  do echo "Collecting public-key from $HOST"; { echo 'root:'; gcloud compute ssh --quiet --zone $ZONE $HOST --tunnel-through-iap -- sudo cat /root/.ssh/id_rsa.pub; } | tr -ds '\n' " " >> public-ssh-keys.txt; done 10< nodes.txt

2. Assign the SSH public keys as metadata entries to all instances:

   while read -u10 ZONE HOST ;  do echo "Adding public keys to $HOST"; gcloud compute instances add-metadata --metadata-from-file ssh-keys=public-ssh-keys.txt --zone $ZONE $HOST; done 10< nodes.txt 

Disable SAP HANA autostart

Manual steps

For each SAP HANA instance in the cluster, make sure that SAP HANA autostart is disabled. For failovers, Pacemaker manages the starting and stopping of the SAP HANA instances in a cluster.

1. On each host as SID_LCadm, stop SAP HANA:

   > HDB stop

2. On each host, open the SAP HANA profile by using an editor, such as vi:

   vi /usr/sap/SID/SYS/profile/SID_HDBINST_NUM_HOST_NAME

3. Set the Autostart property to 0:

   Autostart=0

4. Save the profile.

5. On each host as SID_LCadm, start SAP HANA:

   > HDB start

Automated steps

Alternatively, to disable SAP HANA autostart for all instances listed in nodes.txt, run the following script from Google Cloud console:

while read -u10 ZONE HOST ;
 do gcloud compute ssh --verbosity=none --zone $ZONE $HOST -- "echo Setting Autostart=0 on \$HOSTNAME;
 sudo sed -i 's/Autostart=1/Autostart=0/g' /usr/sap/SID/SYS/profile/SID_HDBINST_NUM_\$HOSTNAME";
 done 10< nodes.txt
 

Enable SAP HANA Fast Restart

Google Cloud strongly recommends enabling SAP HANA Fast Restart for each instance of SAP HANA, especially for larger instances. SAP HANA Fast Restart reduces restart time in the event that SAP HANA terminates, but the operating system remains running.

As configured by the automation scripts that Google Cloud provides, the operating system and kernel settings already support SAP HANA Fast Restart. You need to define the tmpfs file system and configure SAP HANA.

To define the tmpfs file system and configure SAP HANA, you can follow the manual steps or use the automation script that Google Cloud provides to enable SAP HANA Fast Restart. For more information, see:

• Manual steps: Enable SAP HANA Fast Restart
• Automated steps: Enable SAP HANA Fast Restart

For the complete authoritative instructions for SAP HANA Fast Restart, see the SAP HANA Fast Restart Option documentation.

Manual steps

Configure the tmpfs file system

After the host VMs and the base SAP HANA systems are successfully deployed, you need to create and mount directories for the NUMA nodes in the tmpfs file system.

Display the NUMA topology of your VM

Before you can map the required tmpfs file system, you need to know how many NUMA nodes your VM has. To display the available NUMA nodes on a Compute Engine VM, enter the following command:

lscpu | grep NUMA

For example, an m2-ultramem-208 VM type has four NUMA nodes, numbered 0-3, as shown in the following example:

NUMA node(s):        4
NUMA node0 CPU(s):   0-25,104-129
NUMA node1 CPU(s):   26-51,130-155
NUMA node2 CPU(s):   52-77,156-181
NUMA node3 CPU(s):   78-103,182-207

Create the NUMA node directories

Create a directory for each NUMA node in your VM and set the permissions.

For example, for four NUMA nodes that are numbered 0-3:

mkdir -pv /hana/tmpfs{0..3}/SID
chown -R SID_LCadm:sapsys /hana/tmpfs*/SID
chmod 777 -R /hana/tmpfs*/SID

Mount the NUMA node directories to tmpfs

Mount the tmpfs file system directories and specify a NUMA node preference for each with mpol=prefer:

SID specify the SID with uppercase letters.

mount tmpfsSID0 -t tmpfs -o mpol=prefer:0 /hana/tmpfs0/SID
mount tmpfsSID1 -t tmpfs -o mpol=prefer:1 /hana/tmpfs1/SID
mount tmpfsSID2 -t tmpfs -o mpol=prefer:2 /hana/tmpfs2/SID
mount tmpfsSID3 -t tmpfs -o mpol=prefer:3 /hana/tmpfs3/SID

Update /etc/fstab

To ensure that the mount points are available after an operating system reboot, add entries into the file system table, /etc/fstab:

tmpfsSID0 /hana/tmpfs0/SID tmpfs rw,relatime,mpol=prefer:0
tmpfsSID1 /hana/tmpfs1/SID tmpfs rw,relatime,mpol=prefer:1
tmpfsSID1 /hana/tmpfs2/SID tmpfs rw,relatime,mpol=prefer:2
tmpfsSID1 /hana/tmpfs3/SID tmpfs rw,relatime,mpol=prefer:3

Optional: set limits on memory usage

The tmpfs file system can grow and shrink dynamically.

To limit the memory used by the tmpfs file system, you can set a size limit for a NUMA node volume with the size option. For example:

mount tmpfsSID0 -t tmpfs -o mpol=prefer:0,size=250G /hana/tmpfs0/SID

You can also limit overall tmpfs memory usage for all NUMA nodes for a given SAP HANA instance and a given server node by setting the persistent_memory_global_allocation_limit parameter in the [memorymanager] section of the global.ini file.

SAP HANA configuration for Fast Restart

To configure SAP HANA for Fast Restart, update the global.ini file and specify the tables to store in persistent memory.

Update the [persistence] section in the global.ini file

Configure the [persistence] section in the SAP HANA global.ini file to reference the tmpfs locations. Separate each tmpfs location with a semicolon:

[persistence]
basepath_datavolumes = /hana/data
basepath_logvolumes = /hana/log
basepath_persistent_memory_volumes = /hana/tmpfs0/SID;/hana/tmpfs1/SID;/hana/tmpfs2/SID;/hana/tmpfs3/SID

The preceding example specifies four memory volumes for four NUMA nodes, which corresponds to the m2-ultramem-208. If you were running on the m2-ultramem-416, you would need to configure eight memory volumes (0..7).

Restart SAP HANA after modifying the global.ini file.

SAP HANA can now use the tmpfs location as persistent memory space.

Specify the tables to store in persistent memory

Specify specific column tables or partitions to store in persistent memory.

For example, to turn on persistent memory for an existing table, execute the SQL query:

ALTER TABLE exampletable persistent memory ON immediate CASCADE

To change the default for new tables add the parameter table_default in the indexserver.ini file. For example:

[persistent_memory]
table_default = ON

For more information on how to control columns, tables and which monitoring views provide detailed information, see SAP HANA Persistent Memory.

Automated steps

The automation script that Google Cloud provides to enable SAP HANA Fast Restart makes changes to directories /hana/tmpfs*, file /etc/fstab, and SAP HANA configuration. When you run the script, you might need to perform additional steps depending on whether this is the initial deployment of your SAP HANA system or you are resizing your machine to a different NUMA size.

For the initial deployment of your SAP HANA system or resizing the machine to increase the number of NUMA nodes, make sure that SAP HANA is running during the execution of automation script that Google Cloud provides to enable SAP HANA Fast Restart.

When you resize your machine to decrease the number of NUMA nodes, make sure that SAP HANA is stopped during the execution of the automation script that Google Cloud provides to enable SAP HANA Fast Restart. After the script is executed, you need to manually update the SAP HANA configuration to complete the SAP HANA Fast Restart setup. For more information, see SAP HANA configuration for Fast Restart.

To enable SAP HANA Fast Restart, follow these steps:

1. Establish an SSH connection with your host VM.

2. Switch to root:

   sudo su -

3. Download the sap_lib_hdbfr.sh script:

   wget https://storage.googleapis.com/cloudsapdeploy/terraform/latest/terraform/lib/sap_lib_hdbfr.sh

4. Make the file executable:

   chmod +x sap_lib_hdbfr.sh

5. Verify that the script has no errors:

   vi sap_lib_hdbfr.sh
   ./sap_lib_hdbfr.sh -help

   If the command returns an error, contact Cloud Customer Care. For more information about contacting Customer Care, see Getting support for SAP on Google Cloud.

6. Run the script after replacing SAP HANA system ID (SID) and password for the SYSTEM user of the SAP HANA database. To securely provide the password, we recommend that you use a secret in Secret Manager.

   Run the script by using the name of a secret in Secret Manager. This secret must exist in the Google Cloud project that contains your host VM instance.

   sudo ./sap_lib_hdbfr.sh -h 'SID' -s SECRET_NAME 

   Replace the following:

   • SID: specify the SID with uppercase letters. For example, AHA.
   • SECRET_NAME: specify the name of the secret that corresponds to the password for the SYSTEM user of the SAP HANA database. This secret must exist in the Google Cloud project that contains your host VM instance.

   Alternatively, you can run the script using a plain text password. After SAP HANA Fast Restart is enabled, make sure to change your password. Using plain text password is not recommended as your password would be recorded in the command-line history of your VM.

   sudo ./sap_lib_hdbfr.sh -h 'SID' -p 'PASSWORD'

   Replace the following:

   • SID: specify the SID with uppercase letters. For example, AHA.
   • PASSWORD: specify the password for the SYSTEM user of the SAP HANA database.

For a successful initial run, you should see an output similar to the following:

INFO - Script is running in standalone mode
ls: cannot access '/hana/tmpfs*': No such file or directory
INFO - Setting up HANA Fast Restart for system 'TST/00'.
INFO - Number of NUMA nodes is 2
INFO - Number of directories /hana/tmpfs* is 0
INFO - HANA version 2.57
INFO - No directories /hana/tmpfs* exist. Assuming initial setup.
INFO - Creating 2 directories /hana/tmpfs* and mounting them
INFO - Adding /hana/tmpfs* entries to /etc/fstab. Copy is in /etc/fstab.20220625_030839
INFO - Updating the HANA configuration.
INFO - Running command: select * from dummy
DUMMY
"X"
1 row selected (overall time 4124 usec; server time 130 usec)

INFO - Running command: ALTER SYSTEM ALTER CONFIGURATION ('global.ini', 'SYSTEM') SET ('persistence', 'basepath_persistent_memory_volumes') = '/hana/tmpfs0/TST;/hana/tmpfs1/TST;'
0 rows affected (overall time 3570 usec; server time 2239 usec)

INFO - Running command: ALTER SYSTEM ALTER CONFIGURATION ('global.ini', 'SYSTEM') SET ('persistent_memory', 'table_unload_action') = 'retain';
0 rows affected (overall time 4308 usec; server time 2441 usec)

INFO - Running command: ALTER SYSTEM ALTER CONFIGURATION ('indexserver.ini', 'SYSTEM') SET ('persistent_memory', 'table_default') = 'ON';
0 rows affected (overall time 3422 usec; server time 2152 usec)

Download SUSE packages

Uninstall the resource agents used for scale-up deployments and replace them with the resource agents used for scale-out.

Manual steps

Perform the following steps on all hosts, including the majority maker instance:

1. Uninstall the HANA scale-up resource agents:

   zypper remove SAPHanaSR SAPHanaSR-doc

2. Install the HANA scale-out resource agents:

   zypper in SAPHanaSR-ScaleOut SAPHanaSR-ScaleOut-doc

3. Install socat:

   zypper install socat

4. Install the latest operating system patches:

   zypper patch

Automated steps

Alternatively, to automate this process for all instances listed in nodes.txt, run the following script from Google Cloud console:

while read -u10 HOST ;  do gcloud compute ssh --zone $HOST -- "sudo zypper remove -y SAPHanaSR SAPHanaSR-doc; sudo zypper in -y SAPHanaSR-ScaleOut SAPHanaSR-ScaleOut-doc socat; sudo zypper patch -y"; done 10< nodes.txt

Back up the databases

Create backups of your databases to initiate database logging for SAP HANA system replication and create a recovery point.

If you have multiple tenant databases in an MDC configuration, back up each tenant database.

The Deployment Manager template uses /hanabackup/data/SID as the default backup directory.

To create backups of new SAP HANA databases:

1. On the primary host, switch to SID_LCadm. Depending on your OS image, the command might be different.

   sudo -i -u SID_LCadm

2. Create database backups:

   • For a SAP HANA single-database-container system:

     > hdbsql -t -u system -p SYSTEM_PASSWORD -i INST_NUM \
       "backup data using file ('full')"

     The following example shows a successful response from a new SAP HANA system:

     0 rows affected (overall time 18.416058 sec; server time 18.414209 sec)

   • For a SAP HANA multi-database-container system (MDC), create a backup of the system database as well as any tenant databases:

     > hdbsql -t -d SYSTEMDB -u system -p SYSTEM_PASSWORD -i INST_NUM \
       "backup data using file ('full')"

     > hdbsql -t -d SID -u system -p SYSTEM_PASSWORD -i INST_NUM \
       "backup data using file ('full')"

   The following example shows a successful response from a new SAP HANA system:

   0 rows affected (overall time 16.590498 sec; server time 16.588806 sec)

3. Confirm that the logging mode is set to normal:

   > hdbsql -u system -p SYSTEM_PASSWORD -i INST_NUM \
     "select value from "SYS"."M_INIFILE_CONTENTS" where key='log_mode'"

   You should see:

   VALUE
   "normal"

Enable SAP HANA system replication

As a part of enabling SAP HANA system replication, you need to copy the data and key files for the SAP HANA secure stores on the file system (SSFS) from the primary host to the secondary host. The method that this procedure uses to copy the files is just one possible method that you can use.

1. On the primary host as SID_LCadm, enable system replication:

   > hdbnsutil -sr_enable --name=PRIMARY_HOST_NAME

2. On the secondary host:

   1. As SID_LCadm, stop SAP HANA:

      > sapcontrol -nr INST_NUM -function StopSystem

   2. As root, archive the existing SSFS data and key files:

      # cd /usr/sap/SID/SYS/global/security/rsecssfs/
      # mv data/SSFS_SID.DAT data/SSFS_SID.DAT-ARC
      # mv key/SSFS_SID.KEY key/SSFS_SID.KEY-ARC

   3. Copy the data file from the primary host:

      # scp -o StrictHostKeyChecking=no \
      PRIMARY_HOST_NAME:/usr/sap/SID/SYS/global/security/rsecssfs/data/SSFS_SID.DAT \
      /usr/sap/SID/SYS/global/security/rsecssfs/data/SSFS_SID.DAT

   4. Copy the key file from the primary host:

      # scp -o StrictHostKeyChecking=no \
      PRIMARY_HOST_NAME:/usr/sap/SID/SYS/global/security/rsecssfs/key/SSFS_SID.KEY \
      /usr/sap/SID/SYS/global/security/rsecssfs/key/SSFS_SID.KEY

   5. Update ownership of the files:

      # chown SID_LCadm:sapsys /usr/sap/SID/SYS/global/security/rsecssfs/data/SSFS_SID.DAT
      # chown SID_LCadm:sapsys /usr/sap/SID/SYS/global/security/rsecssfs/key/SSFS_SID.KEY

   6. Update permissions for the files:

      # chmod 644 /usr/sap/SID/SYS/global/security/rsecssfs/data/SSFS_SID.DAT
      # chmod 640 /usr/sap/SID/SYS/global/security/rsecssfs/key/SSFS_SID.KEY

   7. As SID_LCadm, register the secondary SAP HANA system with SAP HANA system replication:

      > hdbnsutil -sr_register --remoteHost=PRIMARY_HOST_NAME --remoteInstance=INST_NUM \
      --replicationMode=syncmem --operationMode=logreplay --name=SECONDARY_HOST_NAME

   8. As SID_LCadm, start SAP HANA:

      > sapcontrol -nr INST_NUM -function StartSystem

Validating system replication

On the primary host as SID_LCadm, confirm that SAP HANA system replication is active by running the following python script:

$ python $DIR_INSTANCE/exe/python_support/systemReplicationStatus.py

If replication is set up properly, among other indicators, the following values are displayed for the xsengine, nameserver, and indexserver services:

• The Secondary Active Status is YES
• The Replication Status is ACTIVE

Also, the overall system replication status shows ACTIVE.

Enable the SAP HANA HA/DR provider hooks

SUSE recommends that you enable the SAP HANA HA/DR provider hooks, which let SAP HANA to send out notifications for certain events and improves failure detection. The SAP HANA HA/DR provider hooks require SAP HANA 2.0 SPS 03 or a later version for the SAPHanaSR hook, and SAP HANA 2.0 SPS 05 or a later version for SAPHanaSR-angi hook.

On both the primary and secondary site, complete the following steps:

1. As SID_LCadm, stop SAP HANA:

   > sapcontrol -nr 00 -function StopSystem

1. As root or SID_LCadm, open the global.ini file for editing:

   > vi /hana/shared/SID/global/hdb/custom/config/global.ini

2. Add the following definitions to the global.ini file:

   [ha_dr_provider_saphanasrmultitarget]
   provider = SAPHanaSrMultiTarget
   path = /usr/share/SAPHanaSR-ScaleOut/
   execution_order = 1
   
   [ha_dr_provider_sustkover]
   provider = susTkOver
   path = /usr/share/SAPHanaSR-ScaleOut/
   execution_order = 2
   sustkover_timeout = 30
   
   [ha_dr_provider_suschksrv]
   provider = susChkSrv
   path = /usr/share/SAPHanaSR-ScaleOut/
   execution_order = 3
   action_on_lost = stop
   
   [trace]
   ha_dr_saphanasrmultitarget = info
   ha_dr_sustkover = info

3. As root, create a custom configuration file in the /etc/sudoers.d directory by running the following command. This new configuration file allows the SID_LCadm user to access the cluster node attributes when the srConnectionChanged() hook method is called.

   > sudo visudo -f /etc/sudoers.d/SAPHanaSR

4. In the /etc/sudoers.d/SAPHanaSR file, add the following text:

   Replace SID_LC with the SID in lowercase letters.

   SID_LCadm ALL=(ALL) NOPASSWD: /usr/sbin/crm_attribute -n hana_SID_LC_site_srHook_*
   SID_LCadm ALL=(ALL) NOPASSWD: /usr/sbin/crm_attribute -n hana_SID_LC_gsh *
   SID_LCadm ALL=(ALL) NOPASSWD: /usr/sbin/SAPHanaSR-hookHelper --sid=SID_LC *

5. In your /etc/sudoers file, make sure that the following text is included:

   • For SLES for SAP 15 SP3 and higher:

     @includedir /etc/sudoers.d

   • For versions up to SLES for SAP 15 SP2:

     #includedir /etc/sudoers.d

     Note that the # in this text is part of the syntax and does not mean that the line is a comment.

6. As SID_LCadm, start SAP HANA:

   > sapcontrol -nr 00 -function StartSystem

7. After you complete the cluster configuration for SAP HANA, you can verify that the hook functions correctly during a failover test as described in Troubleshooting the SAPHanaSR python hook and HA cluster takeover takes too long on HANA indexserver failure.

Configure the Cloud Load Balancing failover support

The internal passthrough Network Load Balancer service with failover support routes traffic to the active host in an SAP HANA cluster based on a health check service.

Reserve an IP address for the virtual IP

The virtual IP (VIP) address , which is sometimes referred to as a floating IP address, follows the active SAP HANA system. The load balancer routes traffic that is sent to the VIP to the VM that is currently hosting the active SAP HANA system.

1. Open Cloud Shell:

   Go to Cloud Shell

2. Reserve an IP address for the virtual IP. This is the IP address that applications use to access SAP HANA. If you omit the --addresses flag, an IP address in the specified subnet is chosen for you:

   $ gcloud compute addresses create VIP_NAME \
     --region CLUSTER_REGION --subnet CLUSTER_SUBNET \
     --addresses VIP_ADDRESS

   For more information about reserving a static IP, see Reserving a static internal IP address.

3. Confirm IP address reservation:

   $ gcloud compute addresses describe VIP_NAME \
     --region CLUSTER_REGION

   You should see output similar to the following example:

   address: 10.0.0.19
   addressType: INTERNAL
   creationTimestamp: '2020-05-20T14:19:03.109-07:00'
   description: ''
   id: '8961491304398200872'
   kind: compute#address
   name: vip-for-hana-ha
   networkTier: PREMIUM
   purpose: GCE_ENDPOINT
   region: https://www.googleapis.com/compute/v1/projects/example-project-123456/regions/us-central1
   selfLink: https://www.googleapis.com/compute/v1/projects/example-project-123456/regions/us-central1/addresses/vip-for-hana-ha
   status: RESERVED
   subnetwork: https://www.googleapis.com/compute/v1/projects/example-project-123456/regions/us-central1/subnetworks/example-subnet-us-central1

Create instance groups for your host VMs

1. In Cloud Shell, create two unmanaged instance groups and assign the primary master host VM to one and the secondary master host VM to the other:

   $ gcloud compute instance-groups unmanaged create PRIMARY_IG_NAME \
     --zone=PRIMARY_ZONE
   $ gcloud compute instance-groups unmanaged add-instances PRIMARY_IG_NAME \
     --zone=PRIMARY_ZONE \
     --instances=PRIMARY_HOST_NAME
   $ gcloud compute instance-groups unmanaged create SECONDARY_IG_NAME \
     --zone=SECONDARY_ZONE
   $ gcloud compute instance-groups unmanaged add-instances SECONDARY_IG_NAME \
     --zone=SECONDARY_ZONE \
     --instances=SECONDARY_HOST_NAME
   

2. Confirm the creation of the instance groups:

   $ gcloud compute instance-groups unmanaged list

   You should see output similar to the following example:

   NAME          ZONE           NETWORK          NETWORK_PROJECT        MANAGED  INSTANCES
   hana-ha-ig-1  us-central1-a  example-network  example-project-123456 No       1
   hana-ha-ig-2  us-central1-c  example-network  example-project-123456 No       1

Create a Compute Engine health check

1. In Cloud Shell, create the health check. For the port used by the health check, choose a port that is in the private range, 49152-65535, to avoid clashing with other services. The check-interval and timeout values are slightly longer than the defaults so as to increase failover tolerance during Compute Engine live migration events. You can adjust the values, if necessary:

   $ gcloud compute health-checks create tcp HEALTH_CHECK_NAME --port=HEALTHCHECK_PORT_NUM \
     --proxy-header=NONE --check-interval=10 --timeout=10 --unhealthy-threshold=2 \
     --healthy-threshold=2

2. Confirm the creation of the health check:

   $ gcloud compute health-checks describe HEALTH_CHECK_NAME

   You should see output similar to the following example:

   checkIntervalSec: 10
   creationTimestamp: '2020-05-20T21:03:06.924-07:00'
   healthyThreshold: 2
   id: '4963070308818371477'
   kind: compute#healthCheck
   name: hana-health-check
   selfLink: https://www.googleapis.com/compute/v1/projects/example-project-123456/global/healthChecks/hana-health-check
   tcpHealthCheck:
    port: 60000
    portSpecification: USE_FIXED_PORT
    proxyHeader: NONE
   timeoutSec: 10
   type: TCP
   unhealthyThreshold: 2

Create a firewall rule for the health checks

Define a firewall rule for a port in the private range that allows access to your host VMs from the IP ranges that are used by Compute Engine health checks, 35.191.0.0/16 and 130.211.0.0/22. For more information, see Creating firewall rules for health checks.

1. If you don't already have one, add a network tag to your host VMs. This network tag is used by the firewall rule for health checks.

   $ gcloud compute instances add-tags PRIMARY_HOST_NAME \
     --tags NETWORK_TAGS \
     --zone PRIMARY_ZONE
   $ gcloud compute instances add-tags SECONDARY_HOST_NAME \
     --tags NETWORK_TAGS \
     --zone SECONDARY_ZONE
   

2. If you don't already have one, create a firewall rule to allow the health checks:

   $ gcloud compute firewall-rules create RULE_NAME \
     --network NETWORK_NAME \
     --action ALLOW \
     --direction INGRESS \
     --source-ranges 35.191.0.0/16,130.211.0.0/22 \
     --target-tags NETWORK_TAGS \
     --rules tcp:HLTH_CHK_PORT_NUM

   For example:

   gcloud compute firewall-rules create  fw-allow-health-checks \
   --network example-network \
   --action ALLOW \
   --direction INGRESS \
   --source-ranges 35.191.0.0/16,130.211.0.0/22 \
   --target-tags cluster-ntwk-tag \
   --rules tcp:60000

Configure the load balancer and failover group

1. Create the load balancer backend service:

   $ gcloud compute backend-services create BACKEND_SERVICE_NAME \
     --load-balancing-scheme internal \
     --health-checks HEALTH_CHECK_NAME \
     --no-connection-drain-on-failover \
     --drop-traffic-if-unhealthy \
     --failover-ratio 1.0 \
     --region CLUSTER_REGION \
     --global-health-checks

2. Add the primary instance group to the backend service:

   $ gcloud compute backend-services add-backend BACKEND_SERVICE_NAME \
     --instance-group PRIMARY_IG_NAME \
     --instance-group-zone PRIMARY_ZONE \
     --region CLUSTER_REGION

3. Add the secondary, failover instance group to the backend service:

   $ gcloud compute backend-services add-backend BACKEND_SERVICE_NAME \
     --instance-group SECONDARY_IG_NAME \
     --instance-group-zone SECONDARY_ZONE \
     --failover \
     --region CLUSTER_REGION

4. Create a forwarding rule. For the IP address, specify the IP address that you reserved for the VIP. If you need to access the SAP HANA system from outside of the region that is specified below, include the flag --allow-global-access in the definition:

   $ gcloud compute forwarding-rules create RULE_NAME \
     --load-balancing-scheme internal \
     --address VIP_ADDRESS \
     --subnet CLUSTER_SUBNET \
     --region CLUSTER_REGION \
     --backend-service BACKEND_SERVICE_NAME \
     --ports ALL

   For more information about cross-region access to your SAP HANA high-availability system, see Internal TCP/UDP Load Balancing.

Test the load balancer configuration

Even though your backend instance groups won't register as healthy until later, you can test the load balancer configuration by setting up a listener to respond to the health checks. After setting up a listener, if the load balancer is configured correctly, the status of the backend instance groups changes to healthy.

The following sections present different methods that you can use to test the configuration.

Testing the load balancer with the socat utility

You can use the socat utility to temporarily listen on the health check port. You need to install the socatutility anyway, because you use it later when you configure cluster resources.

1. On both primary and secondary master host VMs as root, install the socat utility:

   # zypper install -y socat

2. Start a socat process to listen for 60 seconds on the health check port:

   # timeout 60s socat - TCP-LISTEN:HLTH_CHK_PORT_NUM,fork

3. In Cloud Shell, after waiting a few seconds for the health check to detect the listener, check the health of your backend instance groups:

   $ gcloud compute backend-services get-health BACKEND_SERVICE_NAME \
     --region CLUSTER_REGION

   You should see output similar to the following:

   ---
   backend: https://www.googleapis.com/compute/v1/projects/example-project-123456/zones/us-central1-a/instanceGroups/hana-ha-ig-1
   status:
    healthStatus:
    ‐ healthState: HEALTHY
      instance: https://www.googleapis.com/compute/v1/projects/example-project-123456/zones/us-central1-a/instances/hana-ha-vm-1
      ipAddress: 10.0.0.35
      port: 80
    kind: compute#backendServiceGroupHealth
   ---
   backend: https://www.googleapis.com/compute/v1/projects/example-project-123456/zones/us-central1-c/instanceGroups/hana-ha-ig-2
   status:
    healthStatus:
    ‐ healthState: HEALTHY
      instance: https://www.googleapis.com/compute/v1/projects/example-project-123456/zones/us-central1-c/instances/hana-ha-vm-2
      ipAddress: 10.0.0.34
      port: 80
    kind: compute#backendServiceGroupHealth

Testing the load balancer using port 22

If port 22 is open for SSH connections on your host VMs, you can temporarily edit the health checker to use port 22, which has a listener that can respond to the health checker.

To temporarily use port 22, follow these steps:

1. Click your health check in the console:

   Go to Health checks page

2. Click Edit.

3. In the Port field, change the port number to 22.

4. Click Save and wait a minute or two.

5. In Cloud Shell, check the health of your backend instance groups:

   $ gcloud compute backend-services get-health BACKEND_SERVICE_NAME \
     --region CLUSTER_REGION

   You should see output similar to the following:

   ---
   backend: https://www.googleapis.com/compute/v1/projects/example-project-123456/zones/us-central1-a/instanceGroups/hana-ha-ig-1
   status:
    healthStatus:
    ‐ healthState: HEALTHY
      instance: https://www.googleapis.com/compute/v1/projects/example-project-123456/zones/us-central1-a/instances/hana-ha-vm-1
      ipAddress: 10.0.0.35
      port: 80
    kind: compute#backendServiceGroupHealth
   ---
   backend: https://www.googleapis.com/compute/v1/projects/example-project-123456/zones/us-central1-c/instanceGroups/hana-ha-ig-2
   status:
    healthStatus:
    ‐ healthState: HEALTHY
      instance: https://www.googleapis.com/compute/v1/projects/example-project-123456/zones/us-central1-c/instances/hana-ha-vm-2
      ipAddress: 10.0.0.34
      port: 80
    kind: compute#backendServiceGroupHealth

6. When you are done, change the health check port number back to the original port number.

Set up Pacemaker

The following procedure configures the SUSE implementation of a Pacemaker cluster on Compute Engine VMs for SAP HANA.

For more information about the configuring high-availability clusters on SLES, see the SUSE Linux Enterprise High Availability Extension documentation for your version of SLES.

Initialize the cluster

On the primary host as root, initialize the cluster:

crm cluster init -y

ha-cluster-init -y

Ignore the warnings related to SBD and default password. SBD and default password are not used in this deployment.

Configure the cluster

Perform the following steps on the primary host as root.

Enable maintenance mode

Put the Pacemaker cluster in maintenance mode:

crm configure property maintenance-mode="true"

Configure the general cluster properties

Configure the following general cluster properties:

crm configure property stonith-timeout="300s"
crm configure property stonith-action="reboot"
crm configure property stonith-enabled="true"
crm configure property cluster-infrastructure="corosync"
crm configure property cluster-name="hacluster"
crm configure property placement-strategy="balanced"
crm configure property no-quorum-policy="freeze"
crm configure property concurrent-fencing="true"

crm configure rsc_defaults migration-threshold="50"
crm configure rsc_defaults resource-stickiness="1000"

crm configure op_defaults timeout="600"

Edit the corosync.conf default settings

1. Open the /etc/corosync/corosync.conf file using an editor of your choice.

2. Remove the consensus parameter.

3. Modify the remaining parameters according to Google Cloud's recommendations.

   The following table shows the totem parameters for which Google Cloud recommends values, along with the impact of changing the values. For the default values of these parameters, which can differ between Linux distributions, see the documentation for your Linux distribution.

   Parameter	Recommended value	Impact of changing the value
   secauth	off	Disables authentication and encryption of all totem messages.
   join	60 (ms)	Increases how long the node waits for join messages in the membership protocol.
   max_messages	20	Increases the maximum number of messages that might be sent by the node after receiving the token.
   token	20000 (ms)	Increases how long the node waits for a totem protocol token before the node declares a token loss, assumes a node failure, and starts taking action. Increasing the value of the token parameter makes the cluster more tolerant of momentary infrastructure events, such as a live migration. However, it can also make the cluster take longer to detect and recover from a node failure. The value of the token parameter also determines the default value of the consensus parameter, which controls how long a node waits for consensus to be achieved before it attempts to re-establish configuration membership.
   consensus	N/A	Specifies, in milliseconds, how long to wait for consensus to be achieved before starting a new round of membership configuration. We recommend that you omit this parameter. When the consensus parameter is not specified, Corosync sets its value to 1.2 times the value of the token parameter. If you use the token parameter's recommended value of 20000, then the consesus parameter is set with the value 24000. If you explicitly specify a value for consensus, then make sure that the value is 24000 or 1.2*token, whichever is greater.
   token_retransmits_before_loss_const	10	Increases the number of token retransmits that the node attempts before it concludes that the recipient node has failed and takes action.
   transport	For SLES: udpu For RHEL 8 or later: knet For RHEL 7: udpu	Specifies the transport mechanism used by corosync.

Join all hosts to Pacemaker cluster

Join all other hosts, including the majority maker, to the Pacemaker cluster on the primary host:

Manual steps

crm cluster join -y -c PRIMARY_HOST_NAME

ha-cluster-join -y -c PRIMARY_HOST_NAME

Automated steps

Alternatively, to automate this process for all instances listed in nodes.txt, run the following script from Google Cloud console:

while read -u10 HOST ;  do echo "Joining $HOST to Pacemaker cluster";
gcloud compute ssh --tunnel-through-iap --quiet --zone $HOST -- sudo ha-cluster-join -y -c PRIMARY_HOST_NAME;
done 10< nodes.txt

Ignore the error message ERROR: cluster.join: Abort: Cluster is currently active that is triggered when joining the primary node to itself.

From any host as root, confirm that the cluster shows all nodes:

# crm_mon -s

You should see output similar to the following:

CLUSTER OK: 5 nodes online, 0 resources configured

Set up fencing

You set up fencing by defining a cluster resource with a fence agent for each host VM.

To ensure the correct sequence of events after a fencing action, you also configure the operating system to delay the restart of Corosync after a VM is fenced. You also adjust the Pacemaker timeout for reboots to account for the delay.

Create the fencing device resources

Manual steps

On the primary host, as root, create the fencing resources for all nodes in the primary and secondary cluster:

1. Run the following command after replacing PRIMARY_HOST_NAME with the hostname of a node in the primary cluster:

   # crm configure primitive STONITH-"PRIMARY_HOST_NAME" stonith:fence_gce \
       op monitor interval="300s" timeout="120s" \
       op start interval="0" timeout="60s" \
       params port="PRIMARY_HOST_NAME" zone="PRIMARY_ZONE" project="PROJECT_ID" \
       pcmk_reboot_timeout=300 pcmk_monitor_retries=4 pcmk_delay_max=30

2. Repeat the previous step for all other nodes in the primary cluster.

3. Run the following command after replacing SECONDARY_HOST_NAME with the hostname of a node in the secondary cluster.

   # crm configure primitive STONITH-"SECONDARY_HOST_NAME" stonith:fence_gce \
       op monitor interval="300s" timeout="120s" \
       op start interval="0" timeout="60s" \
       params port="SECONDARY_HOST_NAME" zone="SECONDARY_ZONE" project="PROJECT_ID" \
       pcmk_reboot_timeout=300 pcmk_monitor_retries=4

4. Repeat the previous step for all other nodes in the secondary cluster.

5. Run the following command after replacing MAJORITY_MAKER_HOSTNAME with the hostname of the majority maker instance:

   # crm configure primitive STONITH-"MAJORITY_MAKER_HOSTNAME" stonith:fence_gce \
       op monitor interval="300s" timeout="120s" \
       op start interval="0" timeout="60s" \
       params port="MAJORITY_MAKER_HOSTNAME" zone="MAJORITY_MAKER_ZONE" project="PROJECT_ID" \
       pcmk_reboot_timeout=300 pcmk_monitor_retries=4

6. Set the location of the fencing device:

   # crm configure location LOC_STONITH_"PRIMARY_HOST_NAME" \
       STONITH-"PRIMARY_HOST_NAME" -inf: "PRIMARY_HOST_NAME"

7. Repeat the previous step for all other hosts on the primary and secondary clusters including the majority maker host.

Set a delay for the restart of Corosync

Manual steps

1. On all hosts as root, create a systemd drop-in file that delays the startup of Corosync to ensure the proper sequence of events after a fenced VM is rebooted:

   systemctl edit corosync.service

2. Add the following lines to the file:

   [Service]
   ExecStartPre=/bin/sleep 60

3. Save the file and exit the editor.

4. Reload the systemd manager configuration.

   systemctl daemon-reload

5. Confirm the drop-in file was created:

   service corosync status

   You should see a line for the drop-in file, as shown in the following example:

   ● corosync.service - Corosync Cluster Engine
      Loaded: loaded (/usr/lib/systemd/system/corosync.service; disabled; vendor preset: disabled)
     Drop-In: /etc/systemd/system/corosync.service.d
              └─override.conf
      Active: active (running) since Tue 2021-07-20 23:45:52 UTC; 2 days ago

Automated steps

Alternatively, to automate this process for all instances listed in nodes.txt, run the following script from Google Cloud console:

while read -u10 HOST;  do gcloud compute ssh --tunnel-through-iap --quiet --zone $HOST   --  "sudo mkdir -p /etc/systemd/system/corosync.service.d/; sudo echo -e '[Service]\nExecStartPre=/bin/sleep 60' | sudo tee -a /etc/systemd/system/corosync.service.d/override.conf; sudo systemctl daemon-reload"; done 10< nodes.txt

Create a local cluster IP resource for the VIP address

To configure the VIP address in the operating system, create a local cluster IP resource for the VIP address that you reserved earlier:

# crm configure primitive rsc_vip_int-primary IPaddr2 \
     params ip=VIP_ADDRESS cidr_netmask=32 nic="eth0" op monitor interval=3600s timeout=60s

Set up the helper health-check service

The load balancer uses a listener on the health-check port of each host to determine where the primary instance of the SAP HANA cluster is running.

To manage the listeners in the cluster, you create a resource for the listener.

These instructions use the socat utility as the listener.

1. On both hosts as root, install the socat utility:

   # zypper in -y socat

2. On the primary host create a resource for the helper health-check service:

   crm configure primitive rsc_healthcheck-primary anything \
   params binfile="/usr/bin/socat" \
   cmdline_options="-U TCP-LISTEN:HEALTHCHECK_PORT_NUM,backlog=10,fork,reuseaddr /dev/null" \
   op monitor timeout=20s interval=10s \
   op_params depth=0

3. Group the VIP and helper health-check service resources:

   # crm configure group g-primary rsc_vip_int-primary rsc_healthcheck-primary meta resource-stickiness="0"

Create the SAPHanaTopology primitive resource

You define the SAPHanaTopology primitive resource in a temporary configuration file, which you then upload to Corosync.

On the primary host as root:

1. Create a temporary configuration file for the SAPHanaTopology configuration parameters:

   # vi /tmp/cluster.tmp

2. Copy and paste the SAPHanaTopology resource definitions into the /tmp/cluster.tmp file:

   primitive rsc_SAPHanaTopology_SID_HDBINST_NUM ocf:suse:SAPHanaTopology \
    operations \$id="rsc_sap2_SID_HDBINST_NUM-operations" \
    op monitor interval="10" timeout="600" \
    op start interval="0" timeout="600" \
    op stop interval="0" timeout="300" \
    params SID="SID" InstanceNumber="INST_NUM"
   
   clone cln_SAPHanaTopology_SID_HDBINST_NUM rsc_SAPHanaTopology_SID_HDBINST_NUM \
    meta clone-node-max="1" target-role="Started" interleave="true"
   location SAPHanaTop_not_on_majority_maker cln_SAPHanaTopology_SID_HDBINST_NUM -inf: MAJORITY_MAKER_HOSTNAME

3. Edit the /tmp/cluster.tmp file to replace the variable text with the SID and instance number for your SAP HANA system.

4. On the primary as root, load the contents of the /tmp/cluster.tmp file into Corosync:

   crm configure load update /tmp/cluster.tmp

Create the SAPHana primitive resource

You define the SAPHana primitive resource by using the same method that you used for the SAPHanaTopology resource: in a temporary configuration file, which you then upload to Corosync.

1. Replace the temporary configuration file:

   # rm /tmp/cluster.tmp
   # vi /tmp/cluster.tmp

2. Copy and paste the SAPHana resource definitions into the /tmp/cluster.tmp file:

   primitive rsc_SAPHana_SID_HDBINST_NUM ocf:suse:SAPHanaController \
    operations \$id="rsc_sap_SID_HDBINST_NUM-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="SID" InstanceNumber="INST_NUM" PREFER_SITE_TAKEOVER="true" \
    DUPLICATE_PRIMARY_TIMEOUT="7200" AUTOMATED_REGISTER="true"
   
   ms msl_SAPHana_SID_HDBINST_NUM rsc_SAPHana_SID_HDBINST_NUM \
    meta master-node-max="1" master-max="1" clone-node-max="1" \
    target-role="Started" interleave="true"
   
   colocation col_saphana_ip_SID_HDBINST_NUM 4000: g-primary:Started \
    msl_SAPHana_SID_HDBINST_NUM:Master
   order ord_SAPHana_SID_HDBINST_NUM Optional: cln_SAPHanaTopology_SID_HDBINST_NUM \
    msl_SAPHana_SID_HDBINST_NUM
   location SAPHanaCon_not_on_majority_maker  msl_SAPHana_SID_HDBINST_NUM -inf: MAJORITY_MAKER_HOSTNAME

   For a multi-tier SAP HANA HA cluster, if you are using a version earlier than SAP HANA 2.0 SP03, set AUTOMATED_REGISTER to false. This prevents a recovered instance from attempting to self-register for replication to a HANA system that already has a replication target configured. For SAP HANA 2.0 SP03 or later, you can set AUTOMATED_REGISTER to true for SAP HANA configurations that use multitier system replication. For additional information, see:

   • SAP HANA System Replication Scale-Up
   • HANA Scale-Up HA with System Replication & Automated Failover

3. On the primary as root, load the contents of the /tmp/cluster.tmp file into Corosync:

   crm configure load update /tmp/cluster.tmp

Confirm SAP HANA system replication is active

On the primary host as SID_LCadm, check the replication status:

# python $DIR_INSTANCE/exe/python_support/systemReplicationStatus.py

Activate the cluster

1. On the primary host as root, take the cluster out of maintenance mode:

   # crm configure property maintenance-mode="false"

   If you receive a prompt that asks you to remove "maintenance", enter y.

2. Wait for 15 seconds and then on the primary host as root, check the status of the cluster:

   # crm status

   The following examples shows the status of an active, properly configured cluster:

7 nodes configured
21 resources configured
Online: [   hana-ha-vm-1 hana-ha-vm-1w1 hana-ha-vm-1w2 hana-ha-vm-2 hana-ha-vm-2w1 hana-ha-vm-2w2 sap-majoritymaker ]


Full list of resources:


 STONITH-hana-ha-vm-1   (stonith:fence_gce):  Started hana-ha-vm-1w2
 STONITH-hana-ha-vm-1w1 (stonith:fence_gce):  Started hana-ha-vm-1
 STONITH-hana-ha-vm-1w2 (stonith:fence_gce):  Started hana-ha-vm-2
 STONITH-sap-majoritymaker      (stonith:fence_gce):  Started hana-ha-vm-1w2
 STONITH-hana-ha-vm-2   (stonith:fence_gce):  Started hana-ha-vm-2w1
 STONITH-hana-ha-vm-2w1 (stonith:fence_gce):  Started hana-ha-vm-2w2
 STONITH-hana-ha-vm-2w2 (stonith:fence_gce):  Started sap-majoritymaker
 Clone Set: cln_SAPHanaTopology_HA1_HDB22 [rsc_SAPHanaTopology_HA1_HDB22]
     Started: [ hana-ha-vm-1 hana-ha-vm-1w1 hana-ha-vm-1w2 hana-ha-vm-2 hana-ha-vm-2w1 hana-ha-vm-2w2 ]
     Stopped: [ sap-majoritymaker ]
 Resource Group: g-primary
     rsc_vip_int-primary        (ocf::heartbeat:IPaddr2):       Started hana-ha-vm-1
     rsc_healthcheck-primary    (ocf::heartbeat:anything):      Started hana-ha-vm-1
 Clone Set: msl_SAPHana_HA1_HDB22 [rsc_SAPHana_HA1_HDB22] (promotable)
     Masters: [ hana-ha-vm-1 ]
     Slaves: [ hana-ha-vm-1w1 hana-ha-vm-1w2 hana-ha-vm-2 hana-ha-vm-2w1 hana-ha-vm-2w2 ]
     Stopped: [ sap-majoritymaker ]

Test failover

Test your cluster by simulating a failure on the primary host. Use a test system or run the test on your production system before you release the system for use.

Backup the system before the test.

You can simulate a failure in a variety of ways, including:

• HDB stop
• HDB kill
• reboot (on the active node)
• ip link set eth0 down for instances with a single network interface
• iptables ... DROP for instances with multiple network interfaces
• echo c > /proc/sysrq-trigger

These instructions use ip link set eth0 down or iptables to simulate a network disruption between your two hosts in the cluster. Use the ip link command on an instance with a single network interface and use the iptables command on instances with one or more network interfaces. The test validates both failover as well as fencing. In the case where your instances have multiple network interfaces defined, you use the iptables command on the secondary host to drop incoming and outgoing traffic based on the IP used by the primary host for cluster communication, thereby simulating a network connection loss to the primary.

1. On the active host, as root, take the network interface offline:

   # ip link set eth0 down

   Or, if multiple network interfaces are active, using the iptables on the secondary host:

   # iptables -A INPUT -s PRIMARY_CLUSTER_IP -j DROP; iptables -A OUTPUT -d PRIMARY_CLUSTER_IP -j DROP

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

3. Enter crm status to 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, as shown in the following example.

   Stack: corosync
      Current DC: hana-ha-vm-2 (version 2.0.1+20190417.13d370ca9-3.9.1-2.0.1+20190417.13d370ca9) - partition with quorum
      Last updated: Fri Jun 12 16:46:07 2020
      Last change: Fri Jun 12 16:46:07 2020 by root via crm_attribute on hana-ha-vm-2
   
      2 nodes configured
      8 resources configured
   
      Online: [ hana-ha-vm-1 hana-ha-vm-2 hana-ha-vm-1w1 hana-ha-vm-2w1]
   
      Full list of resources:
   
        STONITH-hana-ha-vm-1   (stonith:fence_gce):  Started hana-ha-vm-2
        STONITH-hana-ha-vm-2   (stonith:fence_gce):  Started hana-ha-vm-1
        STONITH-hana-ha-vm-1w1   (stonith:fence_gce):    Started hana-ha-vm-2w1
        STONITH-hana-ha-vm-1w1   (stonith:fence_gce):    Started hana-ha-vm-mm
        STONITH-hana-ha-vm-mm   (stonith:fence_gce):    Started hana-ha-vm-1w1
        Clone Set: cln_SAPHanaTopology_HA1_HDB22 [rsc_SAPHanaTopology_HA1_HDB22]
            Started: [ hana-ha-vm-1 hana-ha-vm-2 hana-ha-vm-1w1 hana-ha-vm-2w1
            Stopped: [ hana-ha-vm-mm ]]
        Resource Group: g-primary
            rsc_vip_int-primary        (ocf::heartbeat:IPaddr2):       Started hana-ha-vm-2
            rsc_healthcheck-primary        (ocf::heartbeat:anything):      Started hana-ha-vm-2
        Clone Set: msl_SAPHana_HA1_HDB22 [rsc_SAPHana_HA1_HDB22] (promotable)
            Masters: [ hana-ha-vm-2 ]
            Slaves: [ hana-ha-vm-1 hana-ha-vm-1w1 hana-ha-vm-2w1
            Stopped: [ hana-ha-vm-mm ]]

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.

Troubleshooting

To troubleshoot problems with high-availability configurations for SAP HANA on SLES, see Troubleshooting high-availability configurations for SAP.

Getting support for SAP HANA on SLES

If you need help resolving a problem with high-availability clusters for SAP HANA on SLES, gather the required diagnostic information and contact Cloud Customer Care. For more information, see High-availability clusters on SLES diagnostic information.

Support

For issues with Google Cloud infrastructure or services, contact Customer Care. You can find the contact information on the Support Overview page in the Google Cloud console. If Customer Care determines that a problem resides in your SAP systems, then you are referred to SAP Support.

For SAP product-related issues, log your support request with SAP support. SAP evaluates the support ticket and, if it appears to be a Google Cloud infrastructure issue, then SAP transfers that ticket to the appropriate Google Cloud component in its system: BC-OP-LNX-GOOGLE or BC-OP-NT-GOOGLE.

Support requirements

Before you can receive support for SAP systems and the Google Cloud infrastructure and services that they use, you must meet the minimum support plan requirements.

For more information about the minimum support requirements for SAP on Google Cloud, see:

• Getting support for SAP on Google Cloud
• SAP Note 2456406 - SAP on Google Cloud Platform: Support Prerequisites (An SAP user account is required)

Connecting to SAP HANA

If the host VMs don't have 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.

Post-deployment tasks

After you complete the deployment, finish with the following steps:

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

   sudo passwd SID_LCadm

   For information from SAP about changing the password, see Reset the SYSTEM User Password of the System Database.

2. Before using your SAP HANA instance, configure and backup your new SAP HANA database.

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.

For more information, see:

• SAP HANA operations guide.
• SAP HANA Installation and Update Guide.

What's next

See the following resource for more information: