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Buying Database Hardware Adam Backman – President White Star Software, LLC.

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Presentation on theme: "Buying Database Hardware Adam Backman – President White Star Software, LLC."— Presentation transcript:

1 Buying Database Hardware Adam Backman – President White Star Software, LLC.

2 About the speaker President – White Star Software One of the oldest and most respected consulting and training companies in the Progress OpenEdge sector Vice President – DBAppraise Managed database services backed up by experienced Progress OpenEdge professionals not rookies off the bench Author – Progress Softwares Expert Series Over 25 years of Progress OpenEdge experience Technical support Training Consulting (Database and System configuration, management and tuning)

3 No need to buy hardware – Progress Pacific will take care of it!

4 Agenda Understanding system resources Picking the right vendor Where to spend your money CPU fast vs. many Memory – can you ever have too much Disk – where all the data starts Network and other parts of the system Conclusion

5 Understanding system resources Supported architectures Understand your options Performance tradeoffs

6 Main types of architectures supported by OpenEdge Database engine Database with no portion of the application Host-based system Database, clients and background all on one system Pure client/server Database on one machine and clients on other machines Part of an n-tier architecture Database and background on Machine A AppServers on Machine B Clients on individual machines

7 Understand your options Single large system vs. 2 or more smaller machines Virtualization Single platform or multi-platform Cloud vendors SAN vs. Direct attached storage Network considerations

8 Single large machine vs. 2 or more smaller machines Single large machine Pros Highest potential performance by eliminating network layer Easier to manage as everything is in one place Cons A single machine will have limited scalability Usually two mid-range systems are more cost effective than a single high-end system Potential license cost issues (CPU-Based pricing)

9 Single large machine vs. 2 or more smaller machines (cont.) Multi-machine Pros Flexibility – ability to repurpose machines Scalability – ability to add additional machines to solution Recoverability – ability to use AppServer machine as the database engine Cons Cost – duplication of items, power, maintnenace Adding network layer can hurt performance Management – more machines to manage Maintenance – more things to break

10 Purchase guidance Databases tend to use disk extensively Spend on disk subsystem Allow for a minimum of 10% of the database size for database buffers (-B memory) Do not forget other memory allocations OS buffers can be reduced to 10% or less of total memory Applications are memory and CPU intensive Generally better to buy more cores vs. fewer faster cores but not always some apps have major single-threaded operations Memory can greatly reduce I/O via –B -Bp -Bt, -mmax, … Examine your use cases for the machine and buy with both primary use and most likely alternative uses in mind

11 Purchase guidance Most people over spend on CPU You can have all the CPU in the world but it will do you no good unless you can get data to them efficiently People should focus on the performance food chain Network Disk Memory CPU Slower resources should be addressed before faster resources

12 Virtualization Everyone is doing it but why? Ability to build new environments Ability to recover quickly (part of a DR solution) Reduction in common resource use per server Power Cooling Floor/rack space Potential for better resource saturation (unused CPU) Why not? Complexity Cost (VMWare is not free :-) More applications affected by an outage

13 Options: N-tier option Database engine Fast Disk Moderate memory (over 10% of DB + OS and extras) Relatively little CPU AppServer machine Internal disk – setup well but not crazy Higher memory usage CPU intensive Client machine Web/Mobile Desktops Citrix/Windows terminal server

14 Cloud: Make it someone elses problem

15 Cloud Watch for variable performance Measure throughput (Disk and memory) Measure compute capacity Measure at different days/times Performance guaranty from vendor Iops/sec. vs. perception (real measurements) Amazon (HPC) high performance computing

16 Why is disk important CPU capacity doubles every 18 months Network bandwidth doubling every 12 months Memory is 37,000+ times faster than disk Disk (per disk I/O rate) fairly static (150 – 200 iops/sec.) Storage will generally cost more than servers and this is particularly true for database servers

17 Buy better storage Many disks 150 iops/sec. per disk Look at you buffer hit rate and total request load Dont forget temporary file I/O which can account for a significant percentage of your total I/O load Larger cache Some systems require you to expand cache when you expand your storage but most dont Adding cache is akin to adding database buffers to a database SSD – save money buy fewer devices SSDs are a real solution now and prices are competitive though not cheap when compared to conventional storage on a per GB basis

18 Do better disk configuration Still no RAID 5, No RAID S, No RAID 6, No RAID 7 RAID 10 still king for database storage – really there are a bunch of really cool stats to prove this out Large stripe widths Performance improved with stripe width through 2MB Use best portion of rotating disk (rotating rust) Using outer edge of disk will provide the best performance which may be as much as 15% better vs. inner portion of disk Even usage across all disks Eliminate disk variance Think of ALL sources of I/O (DB, BI, AI, Temp files, OS, …)

19 Storage Direct attached Less expensive in most cases Less complex – Single machine tuning OS and Array High performance – Disks dedicated SAN – generalized business storage NAS – file optimized storage SAN – Purpose-built high performance Why SAN twice? There is a huge difference in SANs and you need to buy for your need not for their marketing

20 Direct-attached storage Pros Not shared with other hosts (isolation is bliss) Easier problem resolution Massive controller throughput for little money Cheaper to maintain Cons Not shared with other hosts (no cost sharing)

21 SAN: Generalized business storage Pros Best option in virtualized environment Share one powerful storage system with many hosts One stop storage system for all hosts Cons High initial cost Single point of failure unless array mirroring/clustering is in place Not optimized to individual tasks Complex

22 SAN: Purpose-built Pros: Excellent performance Additional control at array level Massively scalable Ability to dedicate resources to hosts Reliable (fault tolerant) Cons Single point of failure unless array mirroring is in place Cost Complexity

23 SAN monitoring More difficult as there are many moving parts Multiple hosts need to be monitored SAN needs to be monitored Monitoring data needs to be synchronized Work loads need to be balanced across hosts

24 NAS: file optimized storage Pros Sharable across hosts Generally cheaper than SAN Good service for application files Cons File optimized not block optimized Not database optimized Not client temporary file optimized

25 Storage network Should be isolated Physically Separate vlan if physical is not possible Use large MTU size (ALL must be the same) Host Guest Switch Array

26 Network options Simple Put a single quad card in the server and bind the ports for performance Moderate Multiple cards bound with a two networks. One for Data and the other for client traffic Complex Multiple machine Multiple networks (vlan) Dedicated networks for DB, replication, client traffic, AppServer

27 Network Try to use your network efficiently -Mm 8192 to increase throughput Remember to move to jumbo frames (client, server, switches, …) Move invasive processes to separate network Backup Replication System syncronizations

28 Picking the right vendor – The less of two evils

29 Picking the right vendor Better support nearly always beats a better upfront price Look at quality of local support infrastructure Response time (SLA) In country In the correct language Always comparison shop even if you know what you want This keeps vendors honest Choosing historic rivals helps drive down price Simplify to enhance support Bundle Linux support under hardware contract Single vendor simplicity

30 Paying for support Buy all support with the initial purchase Allows easier (capital) write-off Years 4+ of support can cost as much as the initial price if purchased later

31 Picking the wrong solution NetApp for database storage. Performance will be non- optimal NUMA Architecture – Good vendors make bad solutions All CPUs allocated to a Progress domain must come from the same book/shelf/node All Memory must meet the same criteria as CPU Using client/server for reporting Kill the network access whenever possible Use AppServer for complex OLTP

32 Where to spend your money Disks Storage SAN SSD Really, look at storage first then concern yourself with other trivial issues such as memory and CPU This is the problem over 9 out of 10 times

33 Questions, Comments, … Preguntas

34 THANK YOU Thank you for your time

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