Posts Tagged ‘Data ONTAP’

EMC Isilon Overview

February 20, 2014

isilon_logo_188x110OneFS Overview

EMC Isilon OneFS is a storage OS which was built from the ground up as a clustered system.

NetApp’s Clustered ONTAP for example has evolved from being an OS for HA-pair of storage controllers to a clustered system as a result of integration with Spinnaker intellectual property. It’s not necessarily bad, because cDOT shows better performance on SPECsfs2008 than Isilon, but these systems still have two core architectural differences:

1. Isilon doesn’t have RAIDs and complexities associated with them. You don’t choose RAID protection level. You don’t need to think about RAID groups and even load distribution between them. You don’t even have spare drives per se.

2. All data on Isilon system is kept on one volume, which is a one big distributed file system. cDOT use concept of infinite volumes, but bear in mind that each NetApp filer has it’s own file system beneath. If you have 24 NetApp nodes in a cluster, then you have 24 underlying file systems, even though they are viewed as a whole from the client standpoint.

This makes Isilon very easy to configure and operate. But its simplicity comes at a price of flexibility. Isilon web interface has few options to configure and not very feature rich.

Isilon Nodes and Networking

In a nutshell Isilon is a collection of a certain number of nodes connected via 20Gb/s DDR InfiniBand back-end network and either 1GB/s or 10GB/s front-end network for client connections. There are three types of Isilon nodes S-Series (SAS + SSD drives) for transactional random access I/O, X-Series (SATA + SSD drives) for high throughput applications and NL-series (SATA drives) for archival or not frequently used data.

If you choose to have two IB switches at the back-end, then you’ll have three subnets configured for internal network: int-a, int-b and failover. You can think of a failover network as a virtual network in front of int-a and int-b. So when the packet comes to failover network IP address, the actual IB interface that receives the packet is chosen dynamically. That helps to load-balance the traffic between two IB switches and makes this set up an active/active network.

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On the front-end you can have as many subnets as you like. Subnets are split between pools of IP addresses. And you can add particular node interfaces to the pool. Each pool can have its own SmartConnect zone configured. SmartConnect is a way to load-balance connections between the nodes. Basically SmartConnect is a DNS server which runs on the Isilon side. You can have one SmartConnect service on a subnet level. And one SmartConnect zone (which is simply a domain) on each of the subnet pools. To set up SmartConnect you’ll need to assign an IP address to the SmartConnect service and set a SmartConnect zone name on a pool level. Then you create an “A” record on DNS for the SmartConnect service IP address and delegate SmartConnect DNS zone to this IP. That way each time you refer to the SmartConnect zone to get access to a file share you’ll be redirected to dynamically picked up node from the pool.

SmartPools

Each type of node is automatically assigned to what is called a “Node Pool”. Nodes are grouped to the same pool if they are of the same series, have the same amount of memory and disks of the same type and size. Node Pool level is one of the spots where you can configure protection level. We’ll talk about that later. Node Pools are grouped within Tiers. So you can group NL node pool with 1TB drives and NL node pool with 3TB drives into an archive tier if you wish. And then you have File Pool Policies which you can use to manage placement of files within the cluster. For example, you can redirect files with specific extension or file size or last access time to be saved on a specific node pool or tier. File pool policies also allow you to configure data protection and override the default node pool protection setting.

SmartPools is a concept that Isilon use to name Tier/Node Pool/File Pool Policy approach. File placement is not applied automatically, otherwise it would cause high I/O overhead. It’s implemented as a job on the cluster instead which runs at 22:00 every day by default.

Data Layout and Protection

Instead of using RAIDs, Isilon uses FEC (Forward Error Correction) and more specifically a Reed-Solomon algorithm to protect data on a cluster. It’s similar to RAID5 in how it generates a protection block (or blocks) for each stripe. But it happens on a software level, instead of hardware as in storage arrays. So when a file comes in to a node, Isilon splits the file in stripe units of 128KB each, generates one FEC protection unit and distributes all of them between the nodes using back-end network. This is what is called “+1” protection level, where Isilon can sustain one disk or one node failure. Then you have “+2”, “+3” and “+4”. In “+4” you have four FECs per stripe and can sustain four disk or node failures. Note however that there is a rule that the number of data stripe units in a stripe has to be greater than number of FEC units. So the minimum requirement for “+4” protection level is 9 nodes in a cluster.

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The second option is to use mirroring. You can have from 2x to 8x mirrors of your data. And the third option is “+2:1” and “+3:1” protection levels. These protection levels let you balance between the data protection and amount of the FEC overhead. For example “+2:1” setting compared to “+2” can sustain two drive failures or one node failure, instead of two node failure protection that “+2” offers. And it makes sense, since simultaneous two node failure is unlikely to happen. There is also a difference in how the data is laid out. In “+2” for each stripe Isilon uses one disk on each node and in “+2:1” it uses two disks on each node. And first FEC in this case goes to first subset of disks and second goes to second.

One benefit of not having RAID is that you can set protection level with folder or even file granularity. Which is impossible with conventional RAIDs. And what’s quite handy, you can change protection levels without recreation of storage volumes, as you might have to do while transitioning between some of the RAID levels. When you change protection level for any of the targets, Isilon creates a low priority job which redistributes data within the cluster.

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NetApp SSH Connection Times Out

May 31, 2013

PuTTYPortable_128There is one tricky thing about SSH connections to NetApp filers. If you use PuTTY or PuTTY Connection Manager and you experience frequent timeouts from ssh sessions, you might need to fiddle around with PuTTY configuration options. It seems that there is some issue with how Data ONTAP implements SSH key exchanges, which results in frequent annoying disconnections.

In order to fix that, on PuTTY Configuration screen go to Connection -> SSH -> Bugs and change “Handles SSH2 key re-exchange badly” to ‘On’. That should fix it.

Unexpected Deduplication Impact on VMware I/O Latency

May 28, 2013

NetApp deduplication is a postponed process. During normal operation Data ONTAP only calculates hashes for the data blocks. Actual deduplication is carried out off-hours as per configured schedule. Hash calculation doesn’t affect performance in most cases. I talked about that in my previous post. NetApp states in its documentation that deduplication is a low-priority process:

When one deduplication process is running, there is 0% to 15% performance degradation on other applications.

Once I faced a situation when deduplication was configured to be carried out during business hours on one of the volumes. No one noticed that at some point volume run out of space and Data ONTAP wasn’t able to perform deduplication from that time. Situation became worse when Data ONTAP was upgraded from version 7.3.2 to 8.1.0. Now during deduplication filer tried to upgrade the fingerprint metadata to a new version at 15:00 every day with the message: “Fingerprint is being upgraded” and failed. It seems that the metadata upgrade is a very resource-intensive process and heavily affects I/O latency.

This volume was not a VMware datastore, but it sit on the same aggregate together with the several VMFS LUNs. Here what happened to the VMware I/O latency every day at 15:00 (click to enlarge):

dedup_issue_ed

I deleted the host name and the datastores names from the graph. You can see the large latency spike, which won’t turn yourVMs into kernel panic, but it’s not the thing you would want your production environment to experience every day.

The solution was simple. After space was increased on this volume, deduplication metadata upgrade performed successfully and problem went away. Additionally, deduplication was shifted to off-hours.

The simple lesson to learn: don’t schedule deduplication during the day, you never know what could possibly go wrong.

NetApp Deduplication in a Nutshell

May 12, 2013

NetApp-Dedupe2NetApp uses Write Anywhere File Layout (WAFL) filesystem which is a key for NetApp’s efficient snapshot technology. If you’re already familiar with how snapshots are implemented in Data ONTAP, then understanding underlying mechanisms of deduplication is simple. Filer calculates hash for each data block it receives and preserves this in the form of metadata on the volume level. Then according to deduplication schedule (usually on weekends), filer runs metadata processing and for each duplicate hash changes data pointer to the original block of data.

Since for each data block filer needs to calculate hash on the fly, it has its penalty. On systems with CPU loaded by less than 50% performance impact is negligible. For heavily loaded systems, where CPU is nearly 100% busy, performance impact can be around 15%. For high-end 6000 systems penalty can jump up to 35% for random writes. Heavy sequential read operations can also suffer from deduplication, because read operations can be rerouted in random way across physical storage, depending on where the original data block actually is. In general, deduplication has low impact on system performance. But you can’t use it blindly and should keep in mind that in particular cases it can slow down your storage system.

Deduplication configuration is pretty simple. First of all, you need to activate deduplication on particular volume:

> sis on “targetvol”

If you already have data on the volume, you need to scan it. Otherwise, it won’t be deduped. It’s a common mistake. Deduplication is a low priority task, but keep in mind, however, that it can slightly impact your storage performance when done during business hours, especially if you run deduplication for several volumes simultaneously.

> sis start -s “targetvol”

To show the status of deduplication for particular volume:

> sis status “targetvol”

To see the deduplication schedule:

> sis config “targetvol”

And the most pleasant command to find out how much data you’ve saved:

> df -s “targetvol”

If you want to undo deduplication, first switch it off and then undo it using the following commands:

> sis off “targetvol”
> priv set advanced
*> sis undo “targetvol”
*> priv set

I, personally, was able to achieve 40% deduplication rate for VMware VMFS datastores, which is rather impressive, considering these were mixed OS + application data LUNs.

As a final note, I would like to point out, that deduplication is suitable only for environments with high percentage of similar data. VMware is a good example of it. You won’t get any significant deduplication ratio for swap file volumes, Exchnage mailboxes or Symantec Enterprise Vault which is already deduped.

Further reading:

TR-3958: NetApp Data Compression and Deduplication Deployment and Implementation Guide: Data ONTAP 8.1 Operating in 7-Mode