Archive for the 'Oracle Performnce Monitoring' Category

EMC XtremIO – The Full-Featured All-Flash Array. Interested In Oracle Performance? See The Whitepaper.

NOTE: There’s a link to the full article at the end of this post.

I recently submitted a manuscript to the EMC XtremIO Business Unit covering some compelling lab results from testing I concluded earlier this year. I hope you’ll find the paper interesting.

There is a link to the full paper at the bottom of this block post. I’ve pasted the executive summary here:

Executive Summary

Physical I/O patterns generated by Oracle Database workloads are well understood. The predictable nature of these I/O characteristics have historically enabled platform vendors to implement widely varying I/O acceleration technologies including prefetching, coalescing transfers, tiering, caching and even I/O elimination. However, the key presumption central to all of these acceleration technologies is that there is an identifiable active data set. While it is true that Oracle Database workloads generally settle on an active data set, the active data set for a workload is seldom static—it tends to move based on easily understood factors such as data aging or business workflow (e.g., “month-end processing”) and even the data source itself. Identifying the current active data set and keeping up with movement of the active data set is complex and time consuming due to variability in workloads, workload types, and number of workloads. Storage administrators constantly chase the performance hotspots caused by the active dataset.

All-Flash Arrays (AFAs) can completely eliminate the need to identify the active dataset because of the ability of flash to service any part of a larger data set equally. But not all AFAs are created equal.

Even though numerous AFAs have come to market, obtaining the best performance required by databases is challenging. The challenge isn’t just limited to performance. Modern storage arrays offer a wide variety of features such as deduplication, snapshots, clones, thin provisioning, and replication. These features are built on top of the underlying disk management engine, and are based on the same rules and limitations favoring sequential I/O. Simply substituting flash for hard drives won’t break these features, but neither will it enhance them.

EMC has developed a new class of enterprise data storage system, XtremIO flash array, which is based entirely on flash media. XtremIO’s approach was not simply to substitute flash in an existing storage controller design or software stack, but rather to engineer an entirely new array from the ground-up to unlock flash’s full performance potential and deliver array-based capabilities that are unprecedented in the context of current storage systems.

This paper will help the reader understand Oracle Database performance bottlenecks and how XtremIO AFAs can help address such bottlenecks with its unique capability to deal with constant variance in the I/O profile and load levels. We demonstrate that it takes a highly flash-optimized architecture to ensure the best Oracle Database user experience. Please read more:  Link to full paper from emc.com.

It’s Your Choice: Collectl or Some Odd Collection of Sundry Commands

Some time back I made a blog entry about network performance monitoring tools with a slant towards monitoring Oracle over NFS. The blog entry contains a very long list of all the various tools out there, none of which did what I wanted.

That was then, this is now. Mark Seger (the author of collectl) commented as follows on that blog entry:

Sorry to hear you haven’t found any tools you like, but perhaps you haven’t looked at collectl yet.

Indeed I have looked into collectl. In fact, not only have I looked into it, but I absolutely love it and have been using it extensively for months. I recommend you take a gander at the collectl website.

In its simplest form, I feel it captures very good quick health check style information. The following is an example of a small Linux server performing a little over 200MB/s of disk and network throughput. As you can see, monitoring this sort of performance data would require several stock Linux commands.

# collectlwaiting for 1 second sample…#<——–CPU——–><———–Disks———–><———–Network———->#cpu sys inter ctxsw KBRead Reads KBWrit Writes netKBi pkt-in netKBo pkt-out

28 23 28325 57874 202880 562 0 0 5692 8414 227323 28862

29 25 28782 59234 222560 573 0 0 5616 8338 226129 28701

28 22 28333 57916 235776 634 2048 34 5517 8252 223717 28419

27 22 28874 58156 209848 597 1 1 5477 8162 222559 28290

28 23 28214 58068 220328 569 0 0 5620 8245 221651 28165

29 21 27871 57898 220224 582 0 0 5534 8213 225510 28606

28 24 27923 59021 223184 581 0 0 5536 8244 224676 28531

65 47 29300 57973 216152 580 316 16 5891 8364 226310 28725

Kudos, Mark. Great tool!


DISCLAIMER

I work for Amazon Web Services. The opinions I share in this blog are my own. I'm *not* communicating as a spokesperson for Amazon. In other words, I work at Amazon, but this is my own opinion.

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All content is © Kevin Closson and "Kevin Closson's Blog: Platforms, Databases, and Storage", 2006-2015. Unauthorized use and/or duplication of this material without express and written permission from this blog’s author and/or owner is strictly prohibited. Excerpts and links may be used, provided that full and clear credit is given to Kevin Closson and Kevin Closson's Blog: Platforms, Databases, and Storage with appropriate and specific direction to the original content.

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