Key metrics for effective storage performance and capacity reporting

Key metrics for effective storage performance and capacity reporting

Key Metrics for Effective Storage Performance and Capacity Reporting Objectives This white paper will cover the key metrics in storage that you can use to get a handle on your storage capacity. Storage Architecture basic concepts Two distinct aspects of storage capacity Virtualization Key metrics from the host and backend storage view Reporting on what is most important Space Capacity History Storage increasing in complexity from left to right on the diagram below. Large environments have gone from megabytes to petabytes in terms of storage, growth can result in increasing cost and complexity. 2 Key metrics for effective storage performance and capacity reporting

Two Distinct Aspects of Storage Capacity Data can come from all different directions to the disk. Disc occupancy Disks used to be very expensive but now the costs have come down dramatically and this cost factor has accelerated the growth of storage. You may have too little storage resulting in performance problems but conversely you may have storage over-allocated. A lot of times people put excessive storage space out there to ensure that they never run out and don t pay attention to how much they really need and what their growth really is going to be. Below is a typical service center queuing diagram. Key metrics for effective storage performance and capacity reporting 3

Disk Performance Capacity Response, IOPs In many cases the requests are being sent out by an application or applications. There is a finite limitation on the requests per second that can be satisfied and then a queue begins to form. The queuing theory comes in to play where you have limitations on the throughput of your I/O and at some point this will have a response impact. The response impact transfers up through the application to the user and results in a slow response time, a performance problem. Space Capacity Space Utilization What does storage Utilization mean in your environment? Utilization can be a variable definition and there are many factors to take in to account, these include RAID/DR, Raw/Configured, Host/SAN, Backups, Compression, Etc... The term utilization can depend on whether you are including any of these factors and it is useful to know exactly what you wish to include and report on when determining whether you have under or over-utilized storage capacity. 4 Key metrics for effective storage performance and capacity reporting

Occupancy Visibility Once you have defined what you wish to include in your reports you can start collecting the data. The chart below illustrates space used on a file system and is a regular trend chart with a threshold, as you can see moving out in to the future it is going to exceed the threshold. You can use trending to report on a number of metrics but when an application is going to run out of space it is going to be at this level. It s advisable to be pro-active with trending to ensure that you can deal with any problems before they turn in to real performance problems. Technical solutions can then be implemented to optimize storage space management, including databases. Key metrics for effective storage performance and capacity reporting 5

Space Capacity Trending One thing to keep in mind for trending is to understand the limitations of linear regression when trending and forecasting data. I ve used the graphs below as an example of this. In the second graph you can see what will happen eventually when that bottoms out or someone goes in and allocates more storage or frees more storage up it skews the trend line. 6 Key metrics for effective storage performance and capacity reporting

Space Capacity Different Viewpoints We ve talked about different viewpoints when looking at your data, reports, trending and now I m going to look at how useful it is to look at things in Groups. You can group by Business, Application, Host, Storage Array, Billing Tier and what that really boils down to is providing more of a business or application view. Below you can see this has been grouped to provide a commercial/business and a technical view. Application owners can go in and see how much storage they are consuming, particularly useful if you also include billing information. Key metrics for effective storage performance and capacity reporting 7

Space Capacity Host Metrics Moving on to the metrics, for occupancy the key metric is utilization. How much storage are we using and how much is available? Below are some host metrics that are typically available, these metrics are available at the file system, volume, or logical disk levels. 8 Key metrics for effective storage performance and capacity reporting

Space Capacity Array Metrics The illustration below shows an example of occupancy metrics from the array perspective. This an example of a Netapp filer with an aggregate (down at the aggregate level) A lot of these Storage arrays, from the different vendors, have different ways to carve up the storage. You can set up as storage groups or as in this example, using Netapp, aggregates which can have many occupancy metrics at different levels. Some of the Netapp occupancy levels here are not available on the host in general. I ll pick out a few of the metrics: De-dupe If this is turned on you can finds out how much space you re saving Total Committed space A lot of vendors now offer thin provisioning where storage can be over-committed so it looks as though there is more storage than is really available, this allows you to see how over-committed you really are. athene, our capacity management solution, can bring in metrics from any time series data source so can allow storage metrics to be brought in to the capacity management process. Key metrics for effective storage performance and capacity reporting 9

Virtual Environments and Clusters Managing storage in clustered and/or virtual environments can be challenging because it is shared among all hosts and virtual machines running on it. Below is an example of a VMware cluster, just a simple 3 node cluster going to some shared storage. Features that are available Thin provisioning Storage can be viewed at many levels. Could be different tiers allocated to the same cluster Overhead at various points How do you know what the overhead is? Aggregate all the storage up, compare it to what is allocated and calculate the difference, this will give you a good indication of your overhead. 10 Key metrics for effective storage performance and capacity reporting

Storage Virtualization There are advantages to the layered system it allows a caching layer so that you may not have to go all the way to the backend to satisfy an I/O request there are a lot of administrator features regarding allocation and replication Pooling physical storage from multiple sources into logical groupings is useful Can be a centralized source for collecting data If using as a data source beware of double counting with backend There are a wide variety of techniques for virtualizing storage, be aware of the implications for data collection and reporting. Key metrics for effective storage performance and capacity reporting 11

Performance Capacity Response Impacts SAN or storage array performance problems can be identified at the host or backend storage environment. The diagram below shows the storage evolving in to a more complex environment. With SAN attached storage you can share storage across multiple servers, one of the downsides of this is that you can have storage response impact across multiple servers too. 12 Key metrics for effective storage performance and capacity reporting

Performance Capacity Host Metrics It is important that you understand the limitations of certain host metrics. A selection of host metrics are shown below: Measured response is the best metric for identifying trouble. Host utilization only shows busy time, it doesn t give capacity for SAN. Physical IOPs is an important measure of throughput, all disks have their limitation. Queue Length is a good indicator that a limitation has been reached somewhere. Key metrics for effective storage performance and capacity reporting 13

Performance Capacity Host Metrics Metrics like host utilization can indicate impactful events, but ample capacity might still be available. The high utilization can be seen generating large amounts of I/O in the chart below. 14 Key metrics for effective storage performance and capacity reporting

Queue lengths indicate that it may not currently be impacting response, but headroom is unknown. Response time is the key, as users will be impacted if it goes up. Key metrics for effective storage performance and capacity reporting 15

Performance Capacity Array Architecture This is an example of an enterprise type array comprising of Front End Processors Shared Cache Back End Processors Disk Storage A lot of time these disks can be striped across the entire array, a very large number of spindles tied together to provide a very large resource. Quite often on these large arrays bottlenecks will occur on the front end processor, requests coming in will queue up there. 16 Key metrics for effective storage performance and capacity reporting

Performance Capacity Array Metrics As mentioned front end processors are typically the first to bottleneck, below is an example showing just one day. This is ideal information for trending, if you picked up these processors over a period of time you could do a trend going forward and figure out when and where bottlenecks are likely to occur. Key metrics for effective storage performance and capacity reporting 17

Performance Capacity Backend Metrics Below are some back end metrics available on the back end storage array. These are typical performance metrics showing throughput and response times, the type of thing you need to report on regularly so that you can be on top of performance before incidents start being generated. 18 Key metrics for effective storage performance and capacity reporting

Performance Capacity Array Metrics The key metrics that you need to get a handle on at volume level are throughput, response and latency. Below is an example of Netapp metrics at volume level Below an example of metrics within EMC at the volume level The read/write ratio can give you an idea of what your work profile looks like. Key metrics for effective storage performance and capacity reporting 19

Performance Capacity Component Breakdown The example below, using athene, shows a component breakdown for the server. It s essential to know whether you have any queuing going on (shown in yellow above)as if queuing is happening you are exceeding the devices throughput rate. Performance Capacity Workload Profiles As mentioned previously the Read/Write metrics can help you to get a handle on your workload profiles. Application type is important in estimating performance risk, for instance, something like Exchange is a heavy I/O user. I ve also seen examples where virtual workstations were being installed and resulted in a large I/O hit that could have impacted other applications sharing storage. 20 Key metrics for effective storage performance and capacity reporting

Performance Capacity Scorecards This is an example of a score card, where you can have a large amount of information condensed in to one easy to view dashboard. Dashboards An example below is how you can set up a dashboard and bring key trending and standard reports to you all in one place. Trending, forecasting, and exceptions with athene Key metrics for effective storage performance and capacity reporting 21

Storage Key Metrics Summary Knowledge of your storage architecture is critical, you may need to talk to a separate storage team to get this information Define storage occupancy versus performance Discuss space utilization and define Review virtualization and clustering complexities Explore key metrics and their limitations Identify key report types and areas that are most important, start with the most critical 22 Key metrics for effective storage performance and capacity reporting

Key metrics for effective storage performance and capacity reporting 23

Metron Metron, Metron-Athene and the Metron logo as well as athene and other names of products referred to herein are trade marks or registered trade marks of Metron Technology Limited. Other products and company names mentioned herein may be trade marks of the respective owners. Any rights not expressly granted herein are reserved. www.metron-athene.com