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Data, data, everywhere, and not a bit to use. With the arrival of the cloud, and business focus on service based reporting, capturing data has never been.

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Presentation on theme: "Data, data, everywhere, and not a bit to use. With the arrival of the cloud, and business focus on service based reporting, capturing data has never been."— Presentation transcript:

1 Data, data, everywhere, and not a bit to use. With the arrival of the cloud, and business focus on service based reporting, capturing data has never been more important.

2 This is not a presentation about Big Data Big Data is a separate topic about new ways to store and retrieve very large amounts of data that exceed constraints of traditional data management systems.

3 Session Agenda Why Talk about data? Business demands My basic principles Data Capture Techniques Data Sources The Obligatory Cloud Part APM CMIS Reality

4 Why talk about data? Dashboard, Dashboard, Dashboard Alerts Automation CMIS What does that all sit on? Raw data Ever increasing number of requests to take data from an ever increasing number of sources

5 Frustration

6 A Problem Shared Data you want Cool data you got hold of Solutions you found Write them down, scrunch it up, and throw them up the front here. Put your name on it No prizes for hitting the presenter Or just ask later

7 Session Agenda Why Talk about data? Business demands My basic principles Data Capture Techniques Data Sources The Obligatory Cloud Part APM CMIS Reality

8 What businesses are asking for Have data for everything Internal to a system Across all infrastructure (build a service picture) Business volumes & transaction response times Don’t deploy more agents Ensure reliable data Minimal Storage No staff

9 Where a lot of people are A handful of tools for specific platforms Designed for sys admin roles No single person can access them all No business data Projections based on resource utilisations Huge volumes of “out of reach” data Some Agents, some SNMP capture, some stuff nobody understands anymore Limited staff

10 Session Agenda Why Talk about data? Business demands My basic principles Data Capture Techniques Data Sources The Obligatory Cloud Part APM CMIS Reality

11 Data Capture (My Basic Principals) More is (just this once), more At data capture time get everything you will need Time travel is still fiction Quality is important Put it under YOUR control Full service picture Resource Application Network SAN Business data

12 Session Agenda Why Talk about data? Business demands My basic principles Data Capture Techniques Data Sources The Obligatory Cloud Part APM CMIS Reality

13 Capture Techniques Agentless (SNMP, WMI, etc) Is subject to more security issues, and network quality. Broken communication = lost data Easier/Faster implementation (often), Less data of lower quality Agent Based Autonomous Data collected by a local process. If the server is up, data capture is running. Broken communication = catch up later Possibility to use existing Agents Overhead (system and human) Vote now! Blended Delivery Model Where most people are.

14 Session Agenda Why Talk about data? Business demands My basic principles Data Capture Techniques Data Sources The Obligatory Cloud Part APM CMIS Reality

15 Application/Service Data Databases Well thought out APIs or Windows Counters Well thought out Agents do this SAP Various transactions return Perf data (e.g. ST03) What if there is no designed interface? Logs, databases, write your own instrumentation APM Tools

16 Business/Application Transaction data (APM) A user action = A transaction Log on, Search, Add to Basket, Checkout, Payment = 5 transactions Benefits Common language Service based Defined SLAs Real workload volumes (Planning benefits) Usual Difficulties No tool capturing this data (Ask me for a recommendation) No access to the data held (Typically controlled by Operations) No import facility to capacity tool Avoid Exporting data from both tools into Excel and manually cutting and pasting to get combined reports

17 SANs Challenge IOPS remains the biggest bottleneck Surprising number of capacity managers are unaware of storage capacity available Where to get data SMI-S (Storage Management Initiative – Standard) PowerShell Plugins Learn PowerShell or learn to serve fries (some dude 2008) Storage Vendor central control server Operations Manager, StorageWorks, ControlCenter Using the data? Bring it into your capacity tool

18 In the last 6 months Business / Customer transaction reports (multiple types) Open VMS T4 data Historical CPU & Memory data from home grown scripts NetApp, HP EVA IP Pool allocation Datacenter temperature & power

19 More detailed example NetApp Operations Manager DFM CLI Export Occupancy and performance data for all LUNS, Volumes, Aggregates & Systems connected to Operations Manager. dfm data export run –d comma –t “5 mins” –f avg –h “1 day” Database tables in.csv Script to produce something “nicer” to import

20 Session Agenda Why Talk about data? Business demands My basic principles Data Capture Techniques Data Sources The Obligatory Cloud Part APM CMIS Reality

21 The Cloud

22 Basic Cloud Types & Challenges (IaaS) Public Cloud (Worst Case) No control You put your faith in the provider Monitor response times only? Private Cloud (Best Case) Full control You are responsible, but have all the data Community Cloud (Never seen) Potential control You are involved and may have access to the data Hybrid Cloud (Where you’re likely to be) Some control Full control of the Private Cloud portion only

23 Want to Benchmark the Public cloud? “How hard can it be” Jeremy Clarkson Get a VM up and running and see what workload it can handle AWS results all over the place Somebody else must have looked into this: Still working on it…. Join in ? (I’m short of the $10,000 required…) IaaS Cloud Benchmarking: Approaches, Challenges, and Experience Alexandru Iosup, Radu Prodan, and Dick Epema

24 Benchmarking the Cloud problems Cloud evolution Changes made under your feet We are no longer in the loop “commercial clouds such as Amazon EC2 add frequently new functionality to their systems. Thus, the benchmarking results obtained at any given time may be unrepresentative for the future behaviour of the system.” Alexandru Iosup, Radu Prodan, and Dick Epema So why don’t we continually benchmark the cloud? Because it’s complex and expensive (Challenge 1 = how to do it cheap) “A straightforward approach to benchmark both short-term dynamics and long-term evolution is to measure the system under test periodically, with judiciously chosen frequencies [26]. However, this approach increases the pressure of the so-far unresolved Challenge 1.” Alexandru Iosup, Radu Prodan, and Dick Epema

25 Benchmarking (more problems) Even with lots of data, you’ll have a hard time making it fit reality because you cannot replicate all the software involved. “We have surveyed in our previous work [26], [27] over ten performance studies that use common benchmarks to assess the virtualization overhead on computation (5–15%), I/O (10–30%), and HPC kernels (results vary). We have shown in a recent study of four commercial IaaS clouds [27] that virtualized resources obtained from public clouds can have a much lower performance than the theoretical peak, possibly because of the performance of the middleware layer.” Alexandru Iosup, Radu Prodan, and Dick Epema

26 Long term observation “We have observed the long-term evolution in performance of clouds since Then, the acquisition of one EC2 cloud resource took an average time of 50 seconds, and constantly increased to 64 seconds in 2008 and 78 seconds in The EU S3 service shows pronounced daily patterns with lower transfer rates during night hours (7PM to 2AM), while the US S3 service exhibits a yearly pattern with lowest mean performance during the months January, September, and October. Other services have occasional decreases in performance, such as SDB in March 2009, which later steadily recovered until December [26].” Alexandru Iosup, Radu Prodan, and Dick Epema

27 Final nail in the coffin “Depending on the provider and its middleware abstraction, several cloud overheads and performance metrics can have different interpretation and meaning.” Alexandru Iosup, Radu Prodan, and Dick Epema So you can’t trust the data from clouds to be what you expect. And you can’t trust your existing benchmarks to represent the future. So…what can you do?

28 Private Cloud You are in charge and you monitor the hardware utilisations The Cloud still has physical limits, and soft “limits” Resource Pools, Reservations etc Opportunity Resource Utilisation and Service Information combined Users, Processes, Transactions, Business Volumes Challenge Business decision based on easy capacity monitoring?

29 Session Agenda Why Talk about data? Business demands My basic principles Data Capture Techniques Data Sources The Obligatory Cloud Part APM Reality

30 APM Transaction times Transaction counts Transaction type End to end Per server All that information you could never get from the business, in one handy location

31 Combine APM & Resource Data

32 Session Agenda Why Talk about data? Business demands My basic principles Data Capture Techniques Data Sources The Obligatory Cloud Part APM CMIS Reality

33 CMIS DB1DB2 DB3DB4 CMIS DB

34 CMIS Centralise A single interface to all data Organise it Mirror the organisation Automate Computers are great at performing repetitive tasks. Use them.

35 Session Agenda Why Talk about data? Business demands My basic principles Data Capture Techniques Data Sources The Obligatory Cloud Part APM CMIS Reality

36 In reality how do people get data? From other internal teams Process and reprimands From the outsourcer Contract Enforce it The 1 st rule of data club: Data supplier uses their own tools Requires: Sponsor with teeth

37 So what conclusions do I draw? Be flexible You will have to take the data from whatever already exists Stand Your Ground Don’t make work for yourself (You don’t have the staff) They deliver the data, you keep it. Introduce APM/BTM tools The typical missing element Centralise the data at capture time Know your cloud strategy and get in early with requirements

38 Audience Participation & Questions


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