1. Why does my perfectly working App Crash and Burn in Production? Matt Kramer Project Manager, STL Boeing Scalability Test Lab 206-240-4260 cell

2. The Business Need for Load & Stress  Time, Money, & Chaos impacts on core businesses Can the application support the users it needs to?  Lost productivity if the product is slow Will it slow down when user counts get too high?  Impacts on customer retention if your product becomes unstable or slows to a crawl What kind of response times can we expect in production?  Life span of products How many users can the system support? Do we need more servers?  Getting product support form 3 rd party solution providers while they are still under contract and before the big checks have been written Did the partner deliver on the contracted deliverable and should we pay them?  Support costs Will it still take 30 seconds to login if we have 300 people on the system?

3. Key Challenges  Getting good End User information- Ask a lot of questions, dig, mine the database for session info  Developing a good load profile- How many users, how long will they be on the system, how often will they complete tasks, are there peaks caused by work hours?  Getting a good, production like environment- Is it networked correctly, if not a full prod copy then at least have everything to scale.  Getting workable code- in enough time to develop results before a release- the age old balance between functionality and access.  Under the hood of the Database- Getting good a Good view into what is happening in the database. I3 for Oracle solutions is great.

4. Product Pre-Screening (if possible)  Code Quality  Product Overall Maturity  Coding standards  SQL Quality  Architecture

5. Risk of OutSourced and 3 rd Party  Revenue - Cost = Profit. Capitalism as a system is always looking for ways to reduce cost. Even if a company has a product  Good Talent makes good Products  Good Talent costs $ - Ranked by cost (not by value)  1 st world Talent  1 st world mediocrity  3 rd world Talent  3 rd world mediocrity  Talent Vacuum- Industry wide issue with more demand than talent  History- India as a traditional supply of individual talent not products.  Talent market in India- short supply, workers are more likely to switch jobs for promotions, the largest and most aggressive customers tend to get the best resources for as long as they are noisy.  Communication Gaps caused by  Language  Culture  Time zones  distance  Dirty Laundry- Technical Salespeople don’t know, or won’t share the dirty secrets  The Deal vs the Real-Technologically illiterate executives commonly make purchasing decisions  Lack of Access- Getting access to fixes, answers, or details is next to impossible

6. Load & Performance Risk Factors  Code Maturity  Over all architecture  Has the product been migrated from another OS, platform, from client server?  Has there been any re-architecture of the product recently  Degree of Product Customization possible  Is the product cross platform?  Are there implementations in use of the type and size that your company needs (users & transaction size)?  Are there implementations in use with similar data set, database size, and data growth curve?  Stability of the underlying technologies being used  The number and complexity of integrations with different products  Degree of change in recent releases  High turn over of the development and support staff writing and supporting the application  Quality of the Database schema, normalization, upkeep, best practices  Degree that the product is being customized for your company

7. Information Needed (what will Production look like?)  Architectural understanding  User types-  Batch jobs or other system impacts  Integrations  Networking  Any load balancing

8. Typical Issues/BottleNecks  SQL statements without any indexes that quietly increase response times.  Memory not being released by processes- shows up in longer test runs  De-normalized databases which cause lots of large multi-table joins and slow response times-  Load Balancing or Clustering solutions not fit for the volume of data they are supporting- common with Master/slave configurations or applications not meant to support clustering. Check the resource usage on the different servers.  Un-tuned Servers or services- memory allocation, buffer sizes  Code touching Technology Solution weaknesses- windows hot-folders with extreme amounts of data  Poor Architecture  Chatty applications- How large and how many round trips does a transaction take? Lots of round trips for an application act as a multiplier on response times  Reports- At large Companies Executive reports or reporting applications can have huge impacts on the database.