Tag Archives: capacity

Sizing assumptions for solutions with Erasure Coding (EC-X)

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A common question recently has been how should I size a solution with Erasure Coding (EC-X) from a capacity perspective.

As a general rule, any-time I size a solution using data reduction technology including Compression, De-duplication and Erasure Coding, I always size on the conservative side as the capacity savings these technologies provide can vary greatly from workload to workload and customer to customer.

To assist with sizing, I have created the below tables showing the RAW capacity, usable capacity based on RF, Maximum usable with EC-X and my recommended sizing range.

You will note the recommended sizing is a range between roughly 50-80% of the theoretical maximum capacity EC-X can provide.

This is because EC-X is a post process and is only applied to Write Cold data as per my earlier post: What I/O will Nutanix Erasure coding (EC-X) take effect on?

This means it is unlikely all data will have EC-X applied and as a result, the usable capacity will generally be less than the maximum.

The following are general recommendations, which may not be applicable to every environment. For example, if your workload is heavy on “overwrites”, your EC-X capacity savings will likely be minimal, but for general server workloads, the below can be used as a rule of thumb:

RF2 + EC-X Recommended Sizing Range

RF2ECXsizingassumptionsrange

 

 

RF3 + EC-X Recommended Sizing RangeRF3ECXsizingassumptionsrange

If you want to be conservative with sizing, I recommend choosing the lower value in the sizing range. If you are happy to be less conservative then the higher number in the range can be used.

If you decide to size based on a number outside the recommended range, please document the assumed EC-X data reduction ratio and a risk that states in the event EC-X savings are less than “insert your value here” additional nodes will need to be purchased.

Tip: Always size for at least N+1 at the capacity layer, meaning if your largest node is 10TB RAW and with EC-X and RF2 you expect to have for example 7.5TB usable, that your container is configured with an “Advertised Capacity” at least N-1 capacity of the storage pool. (Or N-2 for clusters using RF3)

I hope you find this helpful when sizing your Nutanix environments.

RF2 & RF3 Usable Capacity with Erasure Coding (EC-X)

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Over the past few weeks with the release of Acropolis base version 4.5 (formally known as NOS) on the horizon there has been a lot of interest in Erasure Coding (EC-X) which was announced at Nutanix .NEXT conference in June this year.

The most common questions are how does EC-X increase the effective SSD tier capacity and the overall cluster usable capacity. This post aims to cover these questions.

Resiliency Factor 2 (RF2) & Erasure Coding

Resiliency Factor 2 ensures that two copies of all data are written to persistent media prior to being acknowledged to the guest operating system. This ensures at N+1 level of redundancy which translates to being able to tolerate a single failure.

RF2 provides a usable capacity of ~50% of RAW.

The below figure shows an example of RF2 where six blocks store three pieces of data in a redundant fashion. In this configuration a single SSD/HDD or node can be lost without impacting data availability.

RF2normal

Now let’s take a look at how the same 6 blocks will be utilized with Erasure Coding enabled:

RF2plusECX

As we can see, we are now able to store four pieces of data (A,B,C,D) with single parity to ensure data can be rebuilt in the event of a drive or node failure. As with standard RF2, an RF2 + EC-X configuration can also tolerate a single SSD/HDD or node can be lost without impacting data availability. We also free up space to be used for another EC-X stripe.

As a result, the usable capacity increases from approx. 50% usable up to 80% usable for clusters of six (6) or larger.

The following table shows the maximum usable capacity for RF2 + EC-X based on cluster size:

Note: Assumes 20TB RAW per node

RF2table

Resiliency Factor 3 (RF3) & Erasure Coding

Resiliency Factor 3 ensures that three copies of all data are written to persistent media prior to being acknowledged to the guest operating system. This ensures at N+2 level of redundancy which translates to being able to tolerate two concurrent SSD/HDD or node failures.

RF3 provides a usable capacity of ~33% of RAW.

The below figure shows an example of RF3 where six blocks store two pieces of data in a redundant fashion. In this configuration the environment can tolerate two concurrent SSD/HDD or node failures without impacting data availability.

RF3normal

Now let’s take a look at how the same 6 blocks will be utilized with Erasure Coding enabled:

RF3ECX

Similar to the RF2 example, we can see we are now able to store more data with the same level of redundancy. In this case, five pieces of data (A,B,C, D) with dual parity to ensure data can be rebuilt in the event of dual concurrent drive or node failures. As with standard RF3, an RF3 + EC-X provides an N+2 level of availability while providing higher usable capacity.

The following table shows the usable capacity for RF3 + EC-X based on cluster size:

Note: Assumes 20TB RAW per node

RF3ECXtable

EC-X Parity Placement

To further increase the effective capacity of the SSD tier and there for supporting larger working set sizes with all flash performance, the Parity for containers with EC-X enabled is stored on the SATA tier.

The following figure shows a standard RF3 deployment:

RF3parityNormal

As we can see, 6 blocks of storage contain just 2 actual pieces of user data all of which reside in the SSD tier.

With RF3 + EC-X the same 6 blocks of storage contain 4 pieces of user data thus increasing the effective capacity of the SSD tier by 100% due to being able to store 4 piece of data compare to two with RF3. In addition the effective SSD capacity is further increased by moving the 2 parity blocks to SATA freeing up a further 33% SSD tier capacity.

RF3ECXparity

I hope that explains how EC-X works and why its such an advantage for Nutanix current and futures customers.

Related Articles:

  1. Nutanix Erasure Coding Deep Dive
  2. Increasing resiliency of large clusters with Erasure Coding
  3. What I/O will EC-X take effect on?
  4. Sizing assumptions for solutions with Erasure Coding (EC-X)

 

Nutanix – Erasure Coding (EC-X) Deep Dive

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I published a post earlier this month during the .NEXT conference titled “What’s .NEXT? – Erasure Coding!” which covered the basics of Nutanix EC-X implementation.

This post is a deep drive follow on to answer numerous questions I have received about EC-X such as:

1. Does it work with Compression and De-duplication?
2. Can I use EC-X to reduce the overhead of RF3?
3. Does it work on Hot or Cold data?
4. Does it work only on the SATA tier?
5. What is the performance impact?
6. When should I use/not use EC-X?
7. What’s different about Nutanix (Patent pending) EC-X compared to other EC algorithms?
8. How does EC-X impact Data Locality?
9. What Hypervisors is EC-X supported with?

So let’s start with What’s different about Nutanix (Patent pending) EC-X compared to other EC algorithms?

* Nutanix EC-X is optimized for a distributed platform, where data is spread across nodes, not individual disks to ensure optimal performance. This also ensures rebuild times are faster and lower impact as the rebuild is performed across all the nodes/drives.

* Nutanix EC-X is also performed as a background task and only on Write Cold data meaning the configured RF is completed as normal and then as a post process EC-X is performed to ensure the write process is not potentially slowed by requiring numerous nodes within the cluster to participate in the initial write I/O.

How does EC-X affect existing Nutanix Data Reduction technologies.

* Short answer, EC-X is complimentary to both compression and deduplication so you will get even more data reduction. Here is a sample screen shot from the Home screen in PRISM which shows a breakdown of Dedup, Compression and Erasure Coding savings.

CapacityOptimization

In the Storage Tab within PRISM, we can get further details on the capacity savings. Here we see an example Container with Compression and EC-X enabled:

CompplusECXhighlighted

Does it work only on the SATA tier?

No, EC-X works on all tiers, being SSD and SATA today, but in the future when newer technology or more than two tiers are used, EC-X works across all tiers.

Does EC-X work on Hot or Cold data?

EC-X waits until data written (via RF2 or RF3) is “Write Cold”, meaning the data is not being overwritten. The data might be white hot from a read I/O perspective, but as long as its not being overwritten the extent group (4MB) will be a candidate for EC-X.

This means for data which is Write Cold, the effective capacity of the SSD tier will be increased due to requiring less space thanks to EC-X.

What is the performance impact?

As EC-X is a post process task and EC-X waits until data is “Write Cold” before performing EC-X on the data, in general it will not impact the Write performance.

The exception to this is in the event data is Write Cold for a period of time, then the data is overwritten, this “overwrite” will incur a higher penalty than a typical RF2/RF3 write. As such some workloads may not be suitable for EC-X which I will discuss later.

Overall, if the workload is suitable, EC-X will keep the data in the SSD tier and the parity on the SATA tier which effectively extends the usable capacity of the SSD tier therefore helping to increase performance (as with compression and dedup).

What Hypervisors is EC-X supported with?

Everything in the Nutanix Distributed Storage Fabric (part of the Nutanix Xtreme Computing Platform or XCP) is designed to be hypervisor agnostic. So whatever Hypervisor/s you choose, you can benefit from EC-X!

How does EC-X impact Data Locality?

As the initial Write path is not impacted by enabling EC-X, Data Locality is still maintained and ensures one copy of data is written to the local node where the VM is running while replicating a further one or two copies (dependent on RF configuration) throughout the cluster.

This means that for newly written data as well as data being overwritten at frequencies of <60mins will always maintain data locality.

For data which meets the criteria for EC-X to be performed, such as Read Hot or Write Cold data, Data Locality can only be partially maintained as the data is by design striped across nodes. The result of this means that it is probable Read I/O will be performed over the network.

Importantly though Read Hot data will be maintained in the SSD tier and be distributed throughout the cluster. This means a single VMs read I/O can be served by multiple nodes concurrently which can lead to increased performance.

As EC-X also provides capacity savings, this allows for more data to be serviced by the SSD tier which enabled a larger active working set to perform at SSD speeds.

In summary, while Data Locality is not always maintained when using EC-X, the advantages of EC-X far outweigh the partial loss in Data Locality.

And finally, When should I use/not use EC-X?

As discussed earlier, EC-X is applied to Write Cold data and if/when that data is overwritten, the write penalty is higher than a typical RF2 write I/O. So if your dataset has a high percentage of overwrites, it is recommended not to use EC-X. The good news is storage can be assigned on a per VMDK level (or vDisk at the NDFS layer) so you can have one VM using EC-X for some data and RF2/3 for other data, again giving customers the best of both worlds.

The best workloads for EC-X are:

1. File Servers
2. Backup
3. Archive
4. Email
5. Logging

Summary:

Nutanix EC-X gives customers more choice without compromising functionality and performance while dramatically reduces the cost/GB of storage.

Related Articles:

  1. Large scale clusters and increased resiliency with RF3 + EC-X

  2. What I/O will Nutanix Erasure coding (EC-X) take effect on?

  3. Sizing assumptions for solutions with Erasure Coding (EC-X)