Scope of Work - NetApp Community

Report
Use Case:
Extracting
Performance data
from OnCommand
using APIs
Arda Oral - Professional Services Engineer
1
Agenda
 Scope of Work
 Environment
 Performance Collection
 Implementation – The Theory
 Implementation – The Praxis (Demonstration)
 SLA Thresholds
 Dashboard
Scope of Work
 Customer wants to retrieve and store performance
data of all storage controllers (NetApp and other
vendors) in his common “performance database”
 Customer defines SLAs to the performance values.
SLA violations are to be imported into the database
 Dashboard presenting SLA violations
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Scope of Work
 Oncommand „Performance Advisor“
responsible for data collection
 Performance data is stored in internal Sybase
database
 NMSDK APIs used to access Oncommand
Performance data
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Environment
 ~ 30 NetApp Storage Systems
 OnCommand5 on a Windows 2008 Server
 Oracle10 Database on AIX 5 (Performance DB)
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Environment
Windows 2008
AIX 5
http,https
OnCommand5
http,https
Oracle
NMSDK4.1
Performance DB
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Performance Collection
 NetApp performance data is being collected
by the CounterManager (CM) residing on the
storage controller
 CM groups data in objects, instances and
counters
 Data can be retrieved with „stats“ on a
storage controller
Performance Collection
 stats list objects
(aggregate, cifs, disk, lun, volume…)
 stats list instances
object name: aggregate, instance: aggr1
object name: system, instance: system
object name: volume, instance: vol0
 stats list counters
object name: aggregate, counter: user_reads
object name: system, counter: cpu_busy
object name: lun, counter: avg_latency
Implementation – The Theory
 Install NMSDK 4.1on AIX5 server
 Install required Perl Modules (SSL,LWP…)
 Check NMDSK examples (basic, advanced)
../netapp-manageability-sdk4.1/src/sample/DataFabric_Manager/API_Sample_Code/advanced/Perl/perf_cou
nters/
 Find appropriate API: perf-get-counter-data
../netapp-manageability-sdk-4.1/doc/WebHelp/index.htm
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NetApp Confidential - Internal Use Only
Implementation – The Theory (cont. 1)
perf-get-counter-data
start-time
end-time
sample-rate
instance-counter-info
object-name-or-id
time-consolidation-method
counter-info
perf-object-counter
API =
Object =
object-type
counter-name
string/int =
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Implementation – The Theory (cont. 2)
Object/Instance/Counter
Value
start-time
6h before now
end-time
now
sample-rate
5 minutes
objekt-name-or-id
storage controller
counter-name
cpu_busy
object-type
system
time-consolidation-method
average
Command on storage system:
stats show -i 1 system:*:cpu_busy
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SLA Thresholds
 CPU_BUSY
 Disk_BUSY
 LUN Latency
 TARGET
> 90%
> 90%
> 20ms
Queue Full
= SLA violation
= SLA violation
= SLA violation
= SLA violation

if 10% of collected counter data exceed SLA
threshold
 storage system counter is flagged yellow **
if 20% of collected counter data exceed SLA
threshold
 storage system counter is flagged red
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Dashboard (sample output)
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