in-booth presentation at 2:00 pm speed-up up... · all-flash storage learn why k2 is gartner's...

Speed-up Virtualized Databases with All-Flash StorageLearn why K2 is Gartner's highest ranked storage for OLTP workloads

In-Booth Presentation at 2:00 PM

Derek SwansonPrincipal Architect

2 | © 2017 Kaminario

275+Employees

Boston HQLocations in

Israel, London, Paris, Beijing &

Seoul

200+ Channel Partners

K2 All-Flash6th Generation of

ProductFully Integrated

HW and SW Platform

23 Patent Families

Software-defined arch, I/O

Optimization, Data Reduction

Kaminario and K2 All Flash Array At A Glance

Kaminario K2 All-Flash: A History of Continuous Innovation

Kaminario Founded

2008

Kaminario ForeSightTM &

ClarityTM

20162010

K2Gen1

2014

K2Gen5

2013

K2Gen4

2017

K2Gen6

2017 Magic QuadrantLeader

K2.N & Flex Product

Announcements

2018

K2.N NVMe

• Superior investment protection and NVMeleadership

• Strongest positioned leader with under $2B market cap

• Significantly differentiated with only scale-up and out SSA

Inaugural Gartner Magic Quadrant for

Solid State Arrays

2014 MQ

Kaminario a “Leader” in 2017 MQ for Solid State

Arrays

2017 MQ

From a ”Visionary” to an Industry “Leader” Kaminario 36 month MQ evolution2017

Gartner Ranks Kaminario K2 #1 in All-Flash Performance, Analytics and OLTP .. And #2 in every other use case and

category among 19 Solid State Arrays

ITS A SWEEP!Kaminario Ranks #1 in Critical Capabilities for SSAs

Use Case Ranking

High Performance Computing #1

OLTP #1

Analytics #1

VDI #2

Server Virtualization #2

Break the Storage I/O bottleneck with Kaminario K2 All-Flash

2X - 5X Better Oracle and SQL Server performance on K2 All-Flash

* Based on actual implementation data

• Manual configuration of RAID groups, Storage Pools, Snapshot Reserves, Hot Spares, etc.

• Considerations of Unbalanced capacities, Controller multi-pathing and failover load

Disk Partition Configuration Complexity

• SQL Server defaults can slow down - a gate built for legacy storage

ESX Defaults Throttle Performance

• Burst of random writes mainly during checkpoint creates bottleneck

• Storage architected for average, not peak

Burst/Peak loads affecting performance

• Sequential I/O gets blended with IO from other VMs, causing massive bottlenecks

• Inefficient scheduling of read vs write

VMware I/O Blender Effect & Mixed Block Workload

82%Storage I/O bottleneck

The symptoms of storage I/O bottleneck on virtualized databases

8 | ©2017 Kaminario

Disk Partition Configuration Complexity

Manually Configured –§ RAID Groups§ Storage Pools§ Snapshot Reserves§ Hot Spares§ Block Size Configurations

Wait States & Contention Created by Manual Placement of -§ OS Files§ SQL Data, Log Files§ Backups

How Kaminario K2 Solves This?

The K2 uses a single automatically tuned pool of storage for the entire storage cluster!

§ No RAID Configuration§ No Storage Pools to set up§ No Hot Spares or Hot Spots§ No Cache Allocations§ No Manual Block Size Configuration§ NO MANUAL CONFIGURATION AT ALL!


Handling Peak Load Latency

Architecting for Peak load too costly!

§ Cheaper to insert a small “caching” layer of DRAM or Flash.

§ Must rely on having a small data skew to store in cache.

§ Perpetually gambling that “pre-fetch” algorithms can keep “cache-miss” ratios low enough that bad performance doesn’t cause application failure.

§ Always breaks when hit with really large load spikes.


The K2 is NOT a caching engine, indeed it has no read cache in it at all.

§ The K2 architecture uses no cache.

§ No reliance on pre-fetch algorithms

§ Natively handles 100% data skew rates!

§ Symmetric active-active cluster

§ Fastest array under most unpredictable workloads with multiple applications.


ESX Defaults Throttle Performance

ESX and SQL default configurations are designed for slow storage.

§ SQL Server can issue a lot of outstanding IO operations

§ Queues of a particular guest can become full and IO is bottlenecked

§ ESX queue settings are small by design

§ This is a necessary gate for legacy storage, to prevent IO from overwhelming the storage array and breaking applications


Kaminario Best Practices§ K2 PowerCLI scripts discover and apply ESX cluster

setting optimizations to massively increasing performance from default settings.

§ Settings for Windows, Linux and SQL enable database parallelization and greater IO throughput to maximize performance

§ ESX optimization also built into plugin


VMware I/O Blender Effect

VMWare’s inherent scrambling up of IO wreaks havoc on legacy arrays

§ An application’s elegant coalesced sequential IOs get blended in with IO from other VMs

§ Cache based systems are overwhelmed by random IO, as IO schedulers cannot efficiently schedule read vs write ops

§ LUN alignment issues magnify this problem 2 to 3 times

§ The performance penalty can be as much as 50%!


“Log Structured Array” architecture is a 100% fix to the IO Blender.

§ Writes put into a Log in DRAM and mirrored, then write is fast-acked back to the host

§ Logs are held in DRAM until full of byte-aligned compressed data (0 padding or fragmentation), then written down in full stripes to all new locations

§ Small block or large block, random or sequential operations handled the same by the K2

§ No hot spots or drive contention exists, and sub millisecond performance is consistent across every type of workload profile


Mixed Block Workload Creates Bottleneck

SQL workload is heavily mixed. Fixed block arrays latency fluctuates dramatically depending on:

§ block size§ read vs write§ random vs sequential operations


Patented “Adaptive Variable Block” Algorithm Optimizes Performance

§ The K2 handles blocks in their native size without the need to carve up IO into a pre-determined fixed small block size.

§ Blocks are written contiguously with a single metadata entry, keeping MD overhead low.

§ Blocks are read and rehydrated on byte aligned boundaries with no wasted cycles.

§ Mixed workloads of all types are handled extremely efficiently

Adaptive block size provides optimal performance for any application

A read is processed as a SINGLE IO operation

16K128K

Patented algorithm adapts to specific block size of different application workloads to optimize performance without compromising on IOPS, latency, or bandwidth

Traditional Flash Array

Latency

Array Optimized for Mixed Workloads

Latency

Adaptive block size – optimized for all workloads

Selective deduplication helps speed up virtualized database performance

• Deduplication on databases is limited or non-existent

• Flexibility of turning off deduplication for Databases – no wasted CPU cycles

• 15-20% - Performance benefit on K2 for turning off deduplication

Real-time and Selective

Selective Deduplication

Dedupe

Non- Dedupe

✔X

Non-DB workload

Databases

Offloading compression to hardware frees up CPU to enhance virtualized database performance

• Compression uses CPU resources

• Stronger compression algorithms require more CPU cycles

• K2 makes the perfect tradeoff to maximize compression effectiveness at HW level while optimizing performance by freeing CPU

Summary: Built from the ground-up to provide extreme performance for Virtualized Database environments

Truly Active-Active

controllers

• Active-Active controllers ensure all CPUs serve database R/W needs• Start small, grow by adding additional active-active controllers (nodes)

• Natively adapt to incoming DB block size for concurrent OLTP/OLAP• No tuning required by the database or storage admin for different workloads

Adaptive block size

• Automatic, global distribution of data and metadata across all nodes• Future proof your investment with mixing and matching old and new gen K2s

Unique shared

metadata

• Consistent low latency and high throughput/IOPS for mixed workloads• Keeps OLTP and OLAP workloads highly responsive even under peak demands

Mixed workload

processing

§ Check out our Live Demos§ Meet-The-VMware-Experts§ See how much you can

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