Tag Archives: block

Example Architectural Decision – Datastore (LUN) and Virtual Disk Provisioning (Thin on Thin)

Posted on by
2

Problem Statement

In a vSphere environment, What is the most suitable disk provisioning type to use for the LUN and the virtual machines to ensure minimum storage overhead and optimal performance?

Requirements

1. Ensure optimal storage capacity utilization
2. Ensure storage performance is both consistent & maximized

Assumptions

1. vSphere 5.0 or later
2. VAAI is supported and enabled
3. The time frame to order new hardware (eg: New Disk Shelves) is <= 4 weeks
4. The storage solution has tools for fast/easy capacity management

Constraints

1. Block Based Storage

Motivation

1. Increase flexibility
2. Ensure physical disk space is not unnecessarily wasted

Architectural Decision

“Thin Provision” the LUN at the Storage layer and “Thin Provision” the virtual machines at the VMware layer

(Optional) Do not present more LUNs (capacity) than you have underlying physical storage (Only over-commitment happens at the vSphere layer)

Justification

1. Capacity management can be easily managed by using storage vendor tools such eg: Netapp VSC / EMC VSI / Nutanix Command Center
2. Thin Provisioning minimizes the impact of situations where customers demand a lot of disk space up front when they only end up using a small portion of the available disk space
3. Increases flexibility as all unused capacity of all datastores and the underlying physical storage remains available
4. Creating VMs with “Thick Provisioned – Eager Zeroed” disks would unnessasarilly increase the provisioning time for new VMs
5. Creating VMs as “Thick Provisioned” (Eager or Lazy Zeroed) does not provide any significant benefit (ie: Performance) but adds a serious capacity penalty
6. Using Thin Provisioned LUNs increases the flexibility at the storage layer
7. VAAI automatically raises an alarm in vSphere if a Thin Provisioned datastore usage is at >= 75% of its capacity
8. The impact of SCSI reservations causing performance issues (increased latency) when thin provisioned virtual machines (VMDKs) grow is no longer an issue as the VAAI Atomic Test & Set (ATS) primitive alleviates the issue of SCSI reservations.
9. Thin provisioned VMs reduce the overhead for Storage vMotion , Cloning and Snapshot activities. Eg: For Storage vMotion it eliminates the requirement for Storage vMotion (or the array when offloaded by VAAI XCOPY Primitive) to relocate “White space”
10. Thin provisioning leaves maximum available free space on the physical spindles which should improve performance of the storage as a whole
11. Where there is a real or perceved issue with performance, any VM can be converted to Thick Provisioned using Storage vMotion not disruptivley.
12. Using Thin Provisioned LUNs with no actual over-commitment at the storage layer reduces any risk of out of space conditions while maintaining the flexibility and efficiency with significantly reduce risk and dependency on monitoring.
13. The VAAI UNMAP primitive provides automated space reclamation to reduce wasted space from files or VMs being deleted

Alternatives

1.  Thin Provision the LUN and thick provision virtual machine disks (VMDKs)
2.  Thick provision the LUN and thick provision virtual machine disks (VMDKs)
3.  Thick provision the LUN and thin provision virtual machine disks (VMDKs)

Implications

1. If the storage at the vSphere and array level is not properly monitored, out of space conditions may occur which will lead to downtime of VMs requiring disk space although VMs not requiring additional disk space can continue to operate even where there is no available space on the datastore
2. The storage may need to be monitored in multiple locations increasing BAU effort
3. It is possible for the vSphere layer to report sufficient free space when the underlying physical capacity is close to or entirely used
4. When migrating VMs from one thin provisioned datastore to another (ie: Storage vMotion), the storage vMotion will utilize additional space on the destination datastore (and underlying storage) while leaving the source thin provisioned datastore inflated even after successful completion of the storage vMotion.
5.While the VAAI UNMAP primitive provides automated space reclamation this is a post-process, as such you still need to maintain sufficient available capacity for VMs to grow prior to UNMAP reclaiming the dead space

Related Articles

1. Datastore (LUN) and Virtual Disk Provisioning (Thin on Thick)CloudXClogo

 

Storage DRS Configuration – Architectural Decision making flowchart

Posted on by
Reply

I was speaking to a number of people recently, who were trying to come up with a one size fits all Storage DRS configuration for a reference architecture document.

As Storage DRS is a reasonably complicated feature, it was my opinion that a one size fits all would not be suitable, and that multiple examples should be provided when writing a reference architecture.

A collegue suggested a flowchart would assist in making the right decision around Storage DRS, so I took up the challenge to put one together.

The below is my version 0.1 of the flowchart, which I thought I would post and hopefully get some good feedback from the community, and create a good guide for those who may not have the in-depth knowledge or experience, too choose what should be in most cases an appropriate configuration for SDRS.

This also compliments some of my previous example architectural decisions which are shown in the related topic section below.

As always, feedback is always welcomed.

I hope you find this helpful.

* Updated to include the previously missing “NO” option for Data replication.

SDRS flowchart V0.2

Related Articles

1. Example Architectural Decision – Storage DRS configuration for NFS datastores

2. Example Architectural Decision – Storage DRS configuration for VMFS datastores

Example Architectural Decision – Host Isolation Response for FC Based storage

Posted on by
2

Problem Statement

What are the most suitable HA / host isolation settings where the environment uses Storage (IBM SVC) with FC connectivity via a dedicated highly available Storage Area Network (SAN) fabric where ESXi Management and Virtual Machine traffic run over a highly available data network?

Requirements

1. Ensure in the event of one or more hosts becoming isolated, the environment responds in an automated manner to recover VMs where possible

Assumptions

1.The Network is highly available (>99.999% availability)
2. The Storage is highly available (>99.999% availability)
3. vSphere 5.0 or later
4. ESXi hosts are connected to the network via two physical separate switches via two physical NICs

Constraints

1. FC (Block) based storage

Motivation

1. Meet/Exceed availability requirements
2. Minimize the chance of a false positive isolation event

Architectural Decision

Turn off the default isolation address by setting the below advanced setting

“das.usedefaultisolationaddress” = False

Configure three (3) isolation addresses by setting the below advanced settings

“das.isolationaddress1″ = 192.168.1.1 (Core Router)

“das.isolationaddress2″ = 192.168.1.2 (Core Switch 1 )

“das.isolationaddress3″ = 192.168.1.3 (Core Switch 2 )

Configure Datastore Heartbeating with “Select any of the clusters datastores”

Configure Host Isolation Response to: “Shutdown”

Justification

1. When using FC storage, it is possible for the Management and Virtual Machine Networks to be unavailable, while the Storage network is working perfectly. In this case Virtual machines may not be able to communicate to other servers, but can continuing reading/writing from disk. In this case, they will likely not be servicing customer workloads, as such, Shutting the VM down gracefully allows HA to restart the VM/s on host/s which are not isolated gives the VM a greater chance of being able to resume servicing workloads than remaining on an isolated host.
2. Datastore heartbeating will allow HA to confirm if the host is “isolated” or “failed”. In either case, Shutting down the VM will allow HA to recover the VM on a surviving host.
3. As all storage is presented via Active/Active IBM SVC controllers, there is no benefit is specifying specific datastores to be used for heartbeating
4. The selected isolation addresses were chosen as they are both highly available devices in the network which are essential for network communication and cover the core routing and switching components in the network.
5. In an environment where the Network is highly available an isolation event is extremely unlikely  as such, where the three (3) isolation addresses cannot be contacted, it is unlikely the network can be restored in a timely manner OR the host has suffered multiple concurrent failures (eg: Multiple Network Cards) and performing a controlled shutdown helps ensure when the network is recovered, the VMs are brought back up in a consistent state, OR in the event the isolation impacts only a subset of ESXi hosts in the cluster, the VM/s can be recovered by HA and resume normal operations.

Alternatives

1. Set Host isolation response to “Leave Powered On”
2. Do not use Datastore heartbeating
3. Use the default isolation address

Implications

1. In the event the host cannot reach any of the isolation addresses, virtual machines will be Shutdown
2.  Using “Shutdown” as opposed to “Power off” ensures a graceful shutdown of the guest operating system, however this will delay the HA restart of the VM for up to 5 mins (300 seconds) if VMware Tools is unable to do a controlled shutdown, in which case after 300 seconds a “Power Off” will be executed.
3. In the unlikely event of network instability, VMs may be Shutdown prematurely.

CloudXClogo