Database hidden disasters… …and planning against them FEODOR GEORGIEV 15

About me Background - .NET developer Started with - SQL 2000 and DTS Currently – SQL Server DBA for Enterprise OLTP and BI warehousing solutions 14

Disclaimer Real life examples - The examples and the demos in this presentation are inspired from real life experiences, which have been enhanced for the purpose of the presentation Lessons learned - nevertheless, to paraphrase Murphy, they can happen to anyone, anywhere, at any time Test notes here 13

Diesel engines and database disasters 12

All things start small ... The idea: Sell stuff online Hardware setup Challenge: Setup online shopping site Estimated size: Hardware setup Some disks, some memory, some CPU ... Data management requirements Limited user transactions (displaying products, registering users, purchasing) 11

Do your homework… Things to consider at this point: Installation and settings of the hardware and software Security policy and the volume maintenance tasks (demo) Creating a database Default settings… really? Filesize, log size, growth rate About filegroup… Why is the PRIMARY not enough 10

Growing pains… The online shopping site 1 year later ... Challenge: product inventory expansion and customer base growth Estimated size: Hardware setup Add some more disks, memory, CPU Time to rethink the setup yet? Data requirements Increasing volume of user transactions (displaying products, registering users, purchasing) Store more data: browsing patterns (target users with special offers, optimize operational costs) etc 9

Avoid obvious mistakes Things to consider at this point: Backup testing – who needs it, anyway Shrinking the DB(A)! Passwords audit (demo) Change management overhead Lack of change management 8

More growing pains… The online shopping site 2 years later ... Challenge: continuous product inventory expansion and customer base growth Estimated size: Hardware setup Add some more disks, memory, CPU Time to rethink the setup yet? Data requirements Handle increasing volume of user transactions (displaying products, registering users, purchasing) Process new transaction types (order cancellation, refunds etc) Store more data: track browsing patterns, product ratings (target users with special offers, optimize operational costs) etc Prevent fraud 7

Zoom in on the database Get ahead of the default settings Estimate the data throughput (new data, archived data, cost of different solutions) A stored procedure is worth … a thousand waits A stored procedure can reduce waits and is easily controlled 6

Measure twice, cut it once… Monitoring and analysis Setup alerts for severity greater than 17 Alert for file growth Monitor hardware performance Performance monitoring for applications Benchmarking & trending 5

Maturity… 4 The online shopping site some years later ... Challenges: Continuous product inventory expansion and customer base growth Scalability Estimated size: Hardware setup Add some more disks, memory, CPU Reactive improvements to the hardware setup Data requirements Handle increasing volume of user transactions (displaying products, registering users, purchasing, order cancellation, refunds ) Store more data: track browsing patterns, product ratings (target users with special offers, optimize operational costs) etc Prevent fraud Where has my scalability been all these years?! 4

Recap Hardware / software considerations Installation procedures and planning (reducing electricity costs or reducing performance?) Instance environment Settings, user rights, object settings Edition selection Application growth planning (volume, indexing, fragmentation, file grouping, scalability, reporting, monitoring, administration) Testing (backups, releases and rollbacks etc) Tools of the trade Best Practice Analyzer (BPA) System Center Advisor Own compentence 3

Expect the unexpected… Disaster recovery considerations: Segregate data so that it takes the minimum time to restore Consider NOT backing up the non-clustered indexes Document the segregated components by importance In case of a disaster, restore the most important data first 2

For attending this session and PASS SQLRally Nordic 2011, Stockholm THANK YOU! For attending this session and PASS SQLRally Nordic 2011, Stockholm 1