This blog contains experience gained over the years of implementing (and de-implementing) large scale IT applications/software.

SAP ASE HADR Overview – Part1

In this multi-part post, I’m going to attempt to explain (mainly for my own understanding – as usual), the basics behind how SAP Replication Server works when replicating from a SAP ASE database to a SAP ASE database as part of an HADR (ASE always-on) setup for a SAP Business Suite system.
The post will be based on SAP ASE (Adaptive Server Enterprise) 16.0 HADR with SAP Replication Server (SRS) 16.0.

‘And what is the use of a book,’ thought Alice, ‘without pictures or conversation?’“.
The quote is from the story, Alice in Wonderland, and I think you may find a picture is most definitely worth a thousand words when it comes to understanding the rabbit hole that is SAP Replication Server.

Hold onto your hats, it is about to get mighty bumpy!

What is SAP Replication Server (SRS)?

Replication Server was originally a Sybase product, ingested by SAP when it bought Sybase.
SAP Replication Server (SRS) is not database specific, it can support a number of other source and target database systems such as SAP ASE, SAP HANA, Oracle and SQLAnywhere. Because of this heterogeneous database support, SRS is quite a complex product, offering a multitude of replication scenarios.
In fact, the SRS product is the underpinning to a number of other SAP products such as SAP Landscape Transformation (SLT) and the Near-Zero Downtime (NZDT) option for database migrations.

SRS can be used to provide HA and/or DR for databases, but it can also be used to produce active-active setups with multi-regional replicas of databases for improved local access times.
This is somewhat of an exceptional case and most definitely rare with SAP Business Suite applications.

In this post, we will be using the simple example of just a primary and a secondary (companion) database.
This is known as either SAP ASE HADR or ASE always-on and is the most common use case. In SRS language our secondary database is referred to as the “companion” database.

With SRS it is also possible to have a three tiered architecture, primary, secondary and tertiary. In this three tier setup the secondary is known as the companion and the disaster recovery (DR) database is known as the “DR node” or tertiary database. You would usually use a three tier HADR architecture setup if you want HA in a primary datacentre or cloud region and also a separate DR in a secondary datacentre or cloud region.

There are multiple replication options: synchronous, near-synchronous or asynchronous, depending on your latency between source and target databases, your required RPO and also depending on your required use of HADR.

SRS is the recommended option for SAP ASE database replication.

What is the Basic Premise of HADR with SRS?

For SAP systems with SAP ASE HADR (always-on), the SRS provides replication of “transactions” from the source database(s) to secondary (companion) and/or DR database(s).

In a SAP landscape, the SAP system is configured to fail-over its connection to the companion in the event of a database failover. No cluster is needed for the database network connectivity, because the ASE database driver (dbsl) is “HA aware”.

Inside the primary database a process called the Replication Agent is responsible for sending the transactions to the Replication Server on the companion database and it is configured in Stream Replication mode. This is the only supported mode in HADR.
NOTE: Stream Replication is also known as “ci” (Component Interface) throughout the SRS administration manuals. There are many occasions where you will need to know this information.

In “ci” mode, the SRS proprietary language Log Transfer Language (LTL) is not used.
With “ci” mode, there are three possible synchronisation modes: synchronous, near-synchronous or asynchronous.

With SRS, the primary and secondary databases are NOT the same database (regarding layout, size, blocks), unlike HANA System Replication.
They are their own databases requiring all the usual care and attention that would be applied to the primary. Such as frequent transaction log backups, health checks etc.

With SRS enabled, database transactions that are started on the primary database are replicated to the secondary while still in the open state.

What is a Transaction?

A transaction is an ATOMIC unit of work with a beginning and an end, with work performed in between.


Each transaction can have one of two final states. It is either committed (saved) to the database, or it can be rolled-back (undone).

A transaction that is not yet in a final state, is called an “open” transaction. Any transaction in the “open” state, is still in progress and occupies space in the database transaction (tran) log. Used space in the tran log cannot be used by other transactions.
In a HADR system, the oldest open transaction executing on the primary database, is usually what is responsible for the position of the Secondary Truncation Point (STP) in the primary database.
The STP is a marker point placed into the primary database transaction log by the Replication Agent and is used to determine the current commit point in the companion database (i.e. it shows the latest transaction that is not yet committed on the companion database).

That’s it for part 1.
In part 2 we will go into the internals of SRS and how transactions are replicated through it.

ASE Issue During Setuphadr Removes Logins on Companion

There’s a specific scenario that can occur during the setup of SAP ASE HADR, which can leave the companion (secondary) database with no logins or roles. You will be unable to log into it. It will be completely unusable.

This issue could apply to any ASE SP03 where auditing is turned on (default for PL06 and above) but I have seen this in two systems, one on ASE SP03 PL08 and one on PL08-HF1.

The symptoms are seen during setuphadr in the step for materialisation of the master database; the setuphadr screen output doesn’t change. Eventually it displays a timeout.
When doing a “ps” on the primary ASE server, you can see a number of BCP processes that appear to be “stuck”. They are connecting to the companion database.
Inside the repdata directory location, the BCP data and out files are present and but they do not change.

When attempting to restart the setuphadr, the process fails as it cannot log into the companion ASE.
When trying manually to log into the companion ASE using isql, you are unable to log in as sapsa, sapsso. You can log in as “sa” only, but you have no roles/privs to do anything.
You check the list of logins and roles in the companion master DB (table master..syslogins) and the tables are empty, all logins have been removed!
You may also see login errors mentioned in the RMA log file on the companion server (the active SRS) with “SQLState: ZZZZZ“.

From what I can see, the cause of the issue is ASE auditing. It is enabled on the companion DB (the sp_configure parameter “auditing” has value of “1”).
The audit table is full or nearly full and/or the sybsecurity database is full or nearly full or the sybsecurity database tran log is full or nearly full.
This prevents the BCP processes from successfully loading the table data from the primary.
It doesn’t seem to prevent the truncation of the companion master DB table data, leaving it with no table data for roles and logins in the master DB.

The workaround that I have found that works most effectively is to completely disable ASE auditing (auditing = 0) in the companion ASE instance, to prevent the issue from happening in the first place.
There are a couple of params that can change the way auditing works and maybe adjusting the filtering to prevent auditing of system users would also solve the problem, but this is the setup of replication so I don’t see why you would want that process audited at all. You can always re-enable auditing after the HADR setup is completed.

Another prevention tip is to ensure that sybsecurity database and tran log have space before the setuphadr process is started.

What if you have already hit the above issue and are looking for help right now?
If the above issue is hit, then the companion master DB could be restored from backup, except you cannot log into it to start the LOAD command.
You could copy the master.dat from primary, but the inbuilt GUID that gets set on DB creation would then be identical to primary (companion and primary should be different).

This leaves two possible options:

  • Re-create the companion master db following SAP note 2631728 “How to rebuild master device and master database from backup – SAP ASE”.
  • Restore master DB from backup (could be a backup from primary master DB).
  • If backup from primary was used, then you may need to re-create the SID database (to be on the safe side), using the DDLGEN commands.

or:

  • Blast the companion ASE away and re-install using SWPM.

Good luck, and make sure you take regular backups 🙂

Best Disk Topology for SAP ASE Databases on Azure

Maybe you are considering migration of on-premise SAP ASE databases to Microsoft Azure, or you may be considering migrating from your existing database vendor to SAP ASE on Azure.
Either way, you will benefit from understanding a good, practical disk topology for SAP ASE on Azure.

In this post, I show how you can optimise use of the SAP ASE, Linux and Azure technical layers to provide a balanced approach to disk use, considering both performance and disk (ASE device) management.

The Different Layers

In an ASE on Linux on Azure (IaaS) setup, you have the following layers:

  • Azure Storage Services
  • Azure Data Disk Cache Settings
  • Linux Physical Disks
  • Linux Logical Volumes
  • Linux File Systems
  • ASE Database Data Devices
  • ASE Instance

Each layer has different options around tuning and setup, which I will highlight below.

Azure Storage Services

Starting at the bottom of the diagram we need to consider the Azure Disk Storage that we wish to use.
There are 2 design considerations here:

  • size of disk space required.
  • performance of disk device.

For performance, you are more than likely tied by the SAP requirements for running SAP on Azure.
Currently these require a minimum of Premium SSD storage, since it provides a guaranteed SLA. However, as of June 2020, Standard SSD was also given an SLA by Microsoft, potentially paving the way for cheaper disk (when certified by SAP) provided that it meets your SLA expectations.

Generally, the size of disk determines the performance (IOPS and MBps), but this can also be influenced by the quantity of data disk devices.
For example, by using 2 data disks striped together you can double the available IOPS. The IOPS are an important factor for databases, especially on high throughput database systems.

When considering multiple data disks, you also need to remember that each VM has limitations. There is a VM level IOPS limit, a VM level throughput limit (megabytes per second) plus a limit to the number of data disks that can be attached. These limit values are different for different Azure VM types.

Also remember that in Linux, each disk device has its own set of queues and buffers. Making use of multiple Linux disk devices (which translates directly to the number of Azure data disks) usually means better performance.

Essentials:

  • Choose minimum of Premium SSD (until Standard SSD is supported by SAP).
  • Spread database space requirements over multiple data disks.
  • Be aware of the VM level limits.

Azure Data Disk Cache Settings

Correct configuration of the Azure data disk cache settings on the Azure VM can help with performance and is an easy step to complete.
I have already documented the best practice Azure Disk Cache settings for ASE on Azure in a previous post.

Essentials:

  • Correctly set Azure VM disk cache settings on Azure data disks at the point of creation.

Use LVM For Managing Disks

Always use a logical volume manager, instead of formatting the Linux physical disk devices directly.
This allows the most flexibility for growing, shrinking and striping the disks for size and performance.

You should stripe the data logical volumes with a minimum of 2 physical disks and a maximum stripe size of 128KB (test it!). This fits within the window of testing that Microsoft have performed in order to achieve the designated IOPS for the underlying disk. It’s also the maximum size that ASE will read at. Depending on your DB read/write profile, you may choose a smaller stripe size such as 64KB, but it depends on the amount of Large I/O and pre-fetch. When reading the Microsoft documents, consider ASE to be the same as MS SQL Server (they are are from the same code lineage).

Stripe the transaction log logical volume(s) with a smaller stripe size, maybe start at 32KB and go lower but test it (remember HANA is 2KB stripe size for log volumes, but HANA uses Azure WriteAccelerator).

Essentials:

  • Use LVM to create volume groups and logical volumes.
  • Stipe the data logical volumes with (max) 128KB stripe size & test it.

Use XFS File System

You can essentially choose to use your preferred file system format; there are no restrictions – see note 405827.
However, if you already run or are planning to run HANA databases in your landscape, then choosing XFS for ASE will make your landscape architecture simpler, because HANA is recommended to run on an XFS file system (when on local disk) on Linux; again see SAP note 405827.

Where possible you will need to explicitly disable any Linux file system write barrier caching, because Azure will be handling the caching for you.
In SUSE Linux this is the “nobarrier” setting on the mount options of the XFS partition and for EXT4 partitions it is option “barrier=0”.

Essentials:

  • Choose disk file system wisely.
  • Disable write barriers.

Correctly Partition ASE

For SAP ASE, you should segregate the disk partitions of the database to avoid certain system specific databases or logging areas, from filling other disk locations and causing a general database system crash.

If you are using database replication (maybe SAP Replication Server a.k.a HADR for ASE), then you will have additional replication queue disk requirements, which should also be segregated.

A simple but flexible example layout is:

Volume
Group
Logical
Volume
Mount PointDescription
vg_aselv_ase<SID>/sybase/<SID>For ASE binaries
vg_sapdatalv_sapdata<SID>_1./sapdata_1One for each ASE device for SAP SID database.
vg_saploglv_saplog<SID>_1./saplog_1One for each log device for SAP SID database.
vg_asedatalv_asesec<SID>./sybsecurityASE security database.
lv_asesyst<SID>./sybsystemASE system databases (master, sybmgmtdb).
lv_saptemp<SID>./saptempThe SAP SID temp database.
lv_asetemp<SID>./sybtempThe ASE temp database.
lv_asediag<SID>./sapdiagThe ASE saptools database.
vg_asehadrlv_repdata<SID>./repdataThe HADR queue location.
vg_backupslv_backups<SID>./backupsDisk backup location.

The above will allow each disk partition usage type to be separately expanded, but more importantly, it allows specific Azure data disk cache settings to be applied to the right locations.
For instance, you can use read-write caching on the vg_ase volume group disks, because that location is only for storing binaries, text logs and config files for the ASE instance. The vg_asedata contains all the small ASE system databases, which will not use too much space, but could still benefit from read caching on the data disks.

TIP: Depending on the size of your database, you may decide to also separate the saptemp database into its own volume group. If you use HADR you may benefit from doing this.

You may not need the backups disk area if you are using a backup utility, but you may benefit from a scratch area of disk for system copies or emergency dumps.

You should choose a good naming standard for volume groups and logical volumes, because this will help you during the check phase, where you can script the checking of disk partitioning and cache settings.

Essentials:

  • Segregate disk partitions correctly.
  • Use a good naming standard for volume groups and LVs.
  • Remember the underlying cache settings on those affected disks.

Add Whole New ASE Devices

Follow the usual SAP ASE database practices of adding additional ASE data devices on additional file system partitions sapdata_2, sapdata_3 etc.
Do not be tempted to constantly (or automatically) expand the ASE device on sapdata_1 by adding new disks, you will find this difficult to maintain because striped logical volumes need at least 2 disks in the stripe set.
It will get complicated and is not easy to shrink back from this.

When you add new disks to an existing volume group and then expand an existing lv_sapdata<SID>_n logical volume, it is not as clean as adding a whole new logical volume (e.g. lv_sapdata<SID>_n+1) and then adding a whole new ASE data device.
The old problem of shrinking data devices is more easily solved by being able to drop a whole ASE device, instead of trying to shrink one.

NOTE: The Microsoft notes suggest enabling automatic DB expansion, but on Azure I don’t think it makes sense from a DB administration perspective.
Yes, by adding a new ASE device, as data ages you may end up with “hot” devices, but you can always move specific devices around and add more underlying disks and re-stripe etc. Keep the layout flexible.

Essentials:

  • Add new disks to new logical volumes (sapdata_n+1).
  • Add big whole new ASE devices to the new LVs.

Summary:

We’ve been through each of the layers in detail and now we can summarise as follows:

  • Choose a minimum of Premium SSD.
  • Spread database space requirements over multiple data disks.
  • Correctly set Azure VM disk cache settings on Azure data disks at the point of creation.
  • Use LVM to create volume groups and logical volumes.
  • Stipe the logical volumes with (max) 128KB stripe size & test it.
  • Choose disk file system wisely.
  • Disable write barriers.
  • Segregate disk partitions correctly.
  • Use a good naming standard for volume groups (and LVs).
  • Remember the underlying cache settings on those affected disks.
  • Add new disks to new logical volumes (sapdata_n).
  • Add big whole new ASE devices to the new LVs.

Useful Links:

SAP ASE Error – Process No Longer Found After Startup

This post is about a strange issue I was hitting during the configuration of SAP LaMa 3.0 to start/stop a SAP ABAP 7.52 system (with Kernel 7.53) that was running with a SAP ASE 16.0 database.

During the LaMa start task, the task would fail with an error message: “ASE process no longer found after startup. (fault code: 127)“.

When I logged directly onto the SAP server Linux host, I could see that the database had indeed started up, eventually.
So what was causing the failure?

The Investigation

At first I thought this was related to the Kernel, but having checked the versions of the Kernel components, I found that they were the same as another SAP system that was starting up perfectly fine using the exact same LaMa system.

The next check I did was to turn on tracing on the hostagent itself. This is a simple task of putting the trace value to “3” in the host_profile of the hostagent and restarting it:

service/trace = 3

The trace output is shown in a number of different trace files in the work directory of the hostagent but the trace file we were interested in is called dev_sapdbctrl.

The developer trace file for the sapdbctrl binary executable is important, because the sapdbctrl binary is executed by SAP hostagent (saphostexec) to perform the database start. If you observe the contents of the sapdbctrl trace output, you will see that it loads the Sybase specific shared library which contains the required code to start/stop the ASE database.

The same sapdbctrl also contains the ability to load the required libraries for other database systems.

As a side note, it is still not known to me, how the Sybase shared library comes to exist in the hostagent executable directory. When SAP ASE is patched, this library must also be patched, otherwise how does the hostagent stay in-step with the ASE database that it needs to talk with?

Once tracing was turned on, I shut the SAP ASE instance down again and then used SAP LaMa to initiate the SAP system start once again.
Sure enough, the LaMa start task failed again.

Looking in the trace file dev_sapdbctrl I could see the same error message that I was seeing in SAP LaMa:

Error: Command execution failed. : ASE process no longer found after startup. 
(fault code: 127) Operation ID: 000D3A3862631EEAAEDDA232BE624001
----- Log messages ---- 
Info: saphostcontrol: Executing StartDatabase 
Error: sapdbctrl: ASE process no longer found after startup. 
Error: saphostcontrol: StartDatabase failed (sapdbctrl exit code = 1)

This was great. It confirmed that SAP LaMa was just seeing the symptom of some other issue, since LaMa just calls the hostagent to do the start.

Now I knew the hostagent was seeing the error, I tried using the hostagent directly to perform the start, using the following:

/usr/sap/hostctrl/exe/saphostctrl -debug -function StartDatabase -dbname <SID> -dbtype syb -dbhost <the-ASE-host>

NOTE: The hostagent “-debug” command line option puts out the same information without the need for the hostagent tracing to be turned on in the host_profile.

Once again, the start process failed and the same error message was present in the dev_sapdbctrl trace file.

This was now really strange.
I decided that the next course of action was to start the process of raising the issue with SAP via an incident.
If you suspect that something could take a while to fix, then it’s always best to raise it with SAP early and continue to look at the issue in parallel.

Continuing the Diagnosis

While the SAP incident was in progress, I continued the process of trying to self-diagnose the issue further.
I tried a couple more things such as:

  • Starting and stopping SAP ASE manually using stopdb/startdb commands.
  • Restarting the whole server (this step has a place in every troubleshooting process, eventually).
  • Checking the server patch level.
  • Checking the environment of the Linux user, the shell, the profile files, the O/S limits applied.
  • Checking what happens if McAfee anti-virus was disabled (I’ve seen the ePO blocking processes before).

Eventually exhaustion set in and I decided to give the SAP support processor time to get back to me with some hints.

Some Sleep

I spend a lot of time solving SAP problems. A lot of time.
Something doesn’t work according to the docs, something did work but has stopped working, something has never worked well…
It builds up in your mind and you carry this stuff around in your head.
Subconsciously you think about these problems.

Then, at about 3am when you can’t get back to sleep, you have a revelation.
The hostagent is forking the process to start the database as the syb<sid> Linux user (it uses “su”), from the root user (hostagent runs as the root user).

Linux Domain Users

The revelation I had regarding the forking of the user, was just the trigger I needed to make me consider the way the Linux authentication was setup on this specific server with the problem ASE startup.

I remembered at the beginning of the project that I had hit an issue with the SSSD Linux daemon, which is responsible for interfacing between Linux and Microsoft Active Directory. At that time, the issue was causing the hostagent to hang when operations were executed which required a switch to another Linux user.
This previous issue was actually a hostagent issue that was fixed in a later hostagent patch. During that particular investigation, I requested that the Linux team re-configure the SSSD daemon to be more efficient with its Active Directory traversals, when it was looking to see if the desired user account was local to Linux or if it was a domain account.

With this previous issue in mind, I checked the SSSD configuration on the problem server. This is a simple conf file in /etc/sssd.

The Solution

After all the troubleshooting, the raising of the incident, the sleeping, I had finally got to the solution.

After checking the SSSD daemon configuration file /etc/sssd/sssd.conf, I could clearly see that there was one entry missing compared to the other servers that didn’t experience the SAP ASE start error.

The parameter: “subdomain_enumerate = none” was missing.
Looking at the manual page for SSSD it would seem that without this parameter there is additional overhead during any Active Directory traversal.

I set the parameter accordingly in the /etc/sssd/sssd.conf file and restarted the SSSD daemon using:

service sssd restart

Then I retried the start of the database using the hostagent command shown previously.
It worked!
I then retried with SAP LaMa and that also now started ASE without error messages.

Root Cause

What it seems was happening, was some sort of internal pre-set timeout in the sapdbctrl binary, when hit, the sapdbctrl just abandons and throws the error that I was seeing. This leaves the ASE database to continue and start (the process was initiated), but in the hostagent it looked like it had failed to start.
By adding the “subdomain_enumerate = none” parameter, any “delay”, caused by inappropriate call to Active Directory was massively reduced and subsequent start activities were successful.

Azure Disk Cache Settings for an SAP Database on Linux

One of your go-live tasks once you have built a VM in Azure, should be to ensure that the Azure disk cache settings on the Linux VM data disks, are set correctly in accordance with the Microsoft recommended settings.
In this post I explain the disk cache options and how they apply to SAP and especially to SAP databases such as SAP ASE and SAP HANA, to ensure you get optimum performance.

What Are the Azure Disk Cache Settings?

In Microsoft Azure you can configure different disk cache settings on data disks that are attached to a VM.
NOTE: You do not need to consider changing the O/S root disk cache settings, as by default they are applied as per the Azure recommendations.

Only specific VMs and specific disks (Standard or Premium Storage) have the ability to use caching.
If you use Azure Standard storage, the cache is provided by local disks on the physical server hosting your Linux VM.
If you use Azure Premium storage, the cache is provided by a combination of RAM and local SSD on the physical server hosting your Linux VM.

There are 3 different Azure disk cache settings:

  • None
  • ReadOnly (or “read-only”)
  • ReadWrite (or “read/write”)

The cache settings can influence the performance and also the consistency of the data written to the Azure storage service where your data disks are stored.

Cache Setting: None

By specifying “None” as the cache setting, no caching is used and a write operation at the VM O/S level is confirmed as completed once the data is written to the storage service.
All read operations for data not already in the VM O/S file system cache, will be read from the storage service.

Cache Setting: ReadOnly

By specifying “ReadOnly” as the cache setting, a write operation at the VM O/S level is confirmed as completed once the data is written to the storage service.
All read operations for data not already in the VM O/S file system cache, will be read from the read cache on the underlying physical machine, before being read from the storage service.

Cache Setting: ReadWrite

By specifying “ReadWrite” as the cache setting, a write operation at the VM O/S level is confirmed as completed once the data is written to the cache on the underlying physical machine.
All read operations for data not already in the VM O/S file system cache, will be read from the read cache on the underlying physical machine, before being read from the storage service.

Where Do We Configure the Disk Cache Settings?

The disk cache settings are configured in Azure against the VM (in the Disks settings), since the disk cache is both physical host and VM series dependent. It is *not* configured against the disk resource itself, as explained in my previous blog post: Listing Azure VM DataDisks and Cache Settings Using Azure Portal JMESPATH & Bash

Any Recommendations for Disk Cache Settings?

There are specific recommendations for Azure disk cache settings, especially when running SAP and especially when running databases like SAP ASE or SAP HANA.

In general, the rules are:

Disk UsageAzure Disk Cache Setting
Root O/S disk (/)ReadWrite – ALWAYS!
HANA SharedReadOnly
ASE Home
(/sybase/<SID>)
ReadOnly
Database DataHANA=None, ASE=ReadOnly
Database LogNone

The above settings for SAP ASE have been obtained from SAP note 2367194 (SQL Server is same as ASE) and from the general deployment guide here: https://docs.microsoft.com/en-us/azure/virtual-machines/workloads/sap/dbms_guide_general
The use of write caching on the ASE home is optional, you could choose ReadOnly, it would help protect the ASE config file in a very specific scenario. It is envisaged that using ASE 16.0 with SRS/HADR you would have a separate data disk for the Replication Server data (I’ll talk about this in another post).

The above settings for HANA have been taken from the updated guide here: https://docs.microsoft.com/en-us/azure/virtual-machines/workloads/sap/hana-vm-operations-storage which is designed to meet the KPIs mentioned in SAP note 2762990.

The reason for not using a write cache every time, is because an issue at the physical host level, affecting the cache, could cause the application (e.g database) to think it has committed data, when it actually isn’t written to disk. This is not good for databases, especially if the issue affects the transaction/redo log area. Data loss could occur.

It’s worth noting that this cache “issue” has always been true of every caching technology ever created, on which databases run. Storage tech vendors try to mitigate this by putting batteries into the storage appliances, but since the write cache in Azure is at the physical host level, there’s just no guarantee that when the VM O/S thinks the write operation has committed to disk, that it has actually been written to disk.

How About Write Accelerator?

There are specific Azure VM series (M-series at current) that support something known as “Write Accelerator”.
This is an extra VM level setting for Premium Storage disks attached to M-series VMs.

Enabling the Write Accelerator setting is a requirement by Microsoft for production SAP HANA transaction log disks on M-Series VMs. This setting ebales the Azure VM to meet the SAP HANA key performance indicators in note 2762990. Azure Write Accelerator is designed to provide lower latency write times on Premium Storage.

You should ensure that the Write Accelerator setting is enabled where appropriate, for your HANA database transaction log disks. You can check if it is enabled following my previous blog post: Listing Azure VM DataDisks and Cache Settings Using Azure Portal JMESPATH & Bash

I’ve tried my best to find more detailed information on how the Write Accelerator feature is actually provided, but unfortunately it seems very elusive. Robert Boban (of Microsoft) commented on a LinkedIn post here: “It is special caching impl. for M-Series VM to fulfill SAP HANA req. for <1ms latency between VM and storage layer.“.

Check the IOPS

Once you have configured your disks and the cache settings, you should ensure that you test the IOPS achieved using the Microsoft recommended process.
You can follow similar steps as my previous post: Recreating SAP ASE Database I/O Workload using Fio on Azure

As mentioned in other places in the Microsoft documentation and SAP notes such as 2367194, you need to ensure that you choose the correct size and series of VM to ensure that you align the required VM maximum IOPS with the intended amount of data disks and their potential IOPS maximum. Otherwise you could hit the VM max IOPS before touching the disk IOPS maximum.

Enable Accelerated Networking

Since the storage is itself connected to your VM via the network, you should ensure that Accelerator Networking is enabled in your VMs Network Settings:

Checking Cache Settings Directly on the VM

As per my previous post Checking Azure Disk Cache Settings on a Linux VM in Shell, you can actually check the Azure disk cache settings on the VM itself. You can do it manually, or write a script (better option for whole landscape validation).

Summary:

I discussed the two types of storage (standard or premium) that offer disk caching, plus where in Azure you need to change the setting.
The table provided a list of cache settings for both SAP ASE and SAP HANA databases and their data disk areas, based on available best-practices.

I mentioned Write Accelerator for HANA transaction log disks and ensuring that you enable Accelerated Networking.
Also provided was a link to my previous post about running a check of IOPS for your data disks, as recommended by Microsoft as part of your go-live checks.

A final mention was made another post of mine, with a great way of checking the disk cache settings across the VMs in the landscape.

Useful Links:

Windows File Cache

https://docs.microsoft.com/en-us/azure/virtual-machines/linux/premium-storage-performance

https://docs.microsoft.com/en-us/azure/virtual-machines/windows/how-to-enable-write-accelerator

https://docs.microsoft.com/en-us/azure/virtual-machines/workloads/sap/hana-vm-operations-storage#production-storage-solution-with-azure-write-accelerator-for-azure-m-series-virtual-machines

https://petri.com/digging-into-azure-vm-disk-performance-features

https://techcommunity.microsoft.com/t5/running-sap-applications-on-the/sap-on-azure-general-update-march-2019/ba-p/377456

https://docs.microsoft.com/en-us/azure/virtual-machines/workloads/sap/dbms_guide_general

https://docs.microsoft.com/en-us/azure/virtual-machines/workloads/sap/hana-vm-operations-storage

SAP Note 2762990 – How to interpret the report of HWCCT File System Test

SAP Note 2367194 – Use of Azure Premium SSD Storage for SAP DBMS Instance