esri best practices: tuning, testing, and monitoring · 2019-08-12 · esri best practices: tuning,...
TRANSCRIPT
![Page 1: Esri Best Practices: Tuning, Testing, and Monitoring · 2019-08-12 · Esri Best Practices: Tuning, Testing, and Monitoring Andrew Sakowicz, asakowicz@esri.com Frank Pizzi, fpizzi@esri.com](https://reader031.vdocument.in/reader031/viewer/2022013021/5f1e88522c355670e252b513/html5/thumbnails/1.jpg)
Esri Best Practices:
Tuning, Testing, and MonitoringAndrew Sakowicz, [email protected]
Frank Pizzi, [email protected]
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Section Subhead
Process and tools
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Process and toolsEsri tools
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Process and toolsEsri tools
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Tools download location
• ArcGIS Monitor
- https://my.esri.com/
• Others
- http://www.arcgis.com
- owner:EnterpriseImp
- Show ArcGIS Desktop Content
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Enterprise Implementation Maturity Model
Level Architectural
Design and
Capacity Planning
Performance and
Scalability Testing
Monitoring Trend Analysis
and
Quantification
0 No No No No
1 Yes No No No
2 Yes Yes No No
3 Yes Yes Yes No
4 Yes Yes Yes Yes
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Section Subhead
Tuning
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Tuning methodologyProfile each tier starting from the top
Browser
Web Server
ArcGIS Server
ArcSOC
Total Response
Time (t1-t2)
Wait Time
Search &
Retrieval Time
Usage Time
ArcSDE/DBMS
t1 t2
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Profile applicationFiddler measurement approximately 5.2 seconds
Application performance narrowed down to specific request and map service
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Review historical stats of the culprit serviceArcGIS Monitor
• https://enterprise.arcgis.com/en/monitor/
• https://arcgismonitor.esri.com
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Profile mxd of the culprit map serviceMxdperfstat
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Oracle TraceCompare elapsed time
Elapsed time slightly changed due to different test runs
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Oracle Execution plan
Inefficient spatial index
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Section Subhead
Testing
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Performance
• Speed, e.g. response time (seconds)
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Scalability
• The ability to increase output and maintain acceptable performance
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Capacity
• The maximum level of output the system can produce, e.g.
• X cars/sec
• X maps/sec
At capacity Over capacity
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Bottleneck
• Resource(s) limiting the performance or capacity
Not bottleneck bottleneckThink of :
Lanes -as CPU processor
Toll -as ArcGIS Server instances
Cars -as map requests
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Step Load and Response Time
Response Time (sec)
time
Step Load (users)
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Throughput (request/hr)
Throughput(req/hr)
Response Time (sec)
time
Step Load (users)
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Resource utilization: CPU, Memory, Network
Throughput(req/hr)
CPU Utilization (%)
Memory used (Mb)
Network used (Mbps)
Response Time (sec)
time
Step Load (users)
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Capacity
Throughput(req/hr)
CPU Utilization (%)
Memory used (Mb)
Network used (Mbps)
Content length (bytes)
Response Time (sec)
Time
User load
Capacity (~ 85% utilization)
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Testing Objectives
- Meet Service-Level Agreement (SLA)
- Bottlenecks analysis
- Capacity planning
- Benchmarking different alternatives
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Testing process
Application
GIS Services
Infrastructure: Hardware and Software
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Required skill set Configuration, Tuning, Testing
Testing
Configuration
Tuning
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System Test for WebGIS Test Automation
• ArcGIS Services
- Mapping
- Feature Service
- OGC
- Geocoding
- Image Service
- Network Analyst
- Geoprocessing
- Tile Cache
• Application Testing
• Discipline relevant report
Application
GIS Services
Infrastructure
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Web test tools feature comparison
Tool Cost Learning
Curve
OS Metrics GIS Data
Generation
GIS Test
Automation
Load Runner High High Windows/Linux No No
Visual Studio Medium High Windows No No
JMeter Free High Requires additional
plugin
No No
System Test Free Low Windows/Linux Yes Yes
Tech Support by Esri PS as part of consulting support
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System Test for WebDynamic Map Service
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System Test for WebReal time dashboard
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Test Results as Input into Capacity PlanningService time and Mb/tr models as input into capacity planning
ST - CPU service time (sec)
#CPU – number of physical CPU cores
%CPU - percent CPU
TH – throughput (tr/sec)
100
%3600#
=
TH
CPUCPUST
ThinkTimesponseTime
UsersTH
+=
Re
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CPU capacity
1. User load: Concurrent users or throughput
2. Operation CPU service time (model)—performance
3. CPU SpecRate
This method is used in capacity planning tools like System Designer or CPT
subscript t = target
subscript b = benchmark
ST = CPU service time
TH = throughput
%CPU = percent CPU
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Section Subhead
Workload separation
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ArcGIS Server sites
• Pre-planning is important
• Isolate hosting server site from traditional GIS Server duties
• Have dedicated GIS Server sites for various purposes:
• heavily used map services, geoprocessing services, …
Portal
for ArcGIS
Hosting
Server
ArcGIS
Data Store
(relational + tile cache)
Web Adaptor
GeoEvent
Server
ArcGIS
Server
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Section Subhead
Provide adequate
infrastructure capacity
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Provide sufficient hardware resources
GIS Systems are bound by:
1. CPU - typically
2. Memory – when large number of services
3. Disk – Image Service, Synchronization
4. Network – low bandwidth deployment
5. Poorly configured virtualization can result in 30% or higher performance degradation
Most systems are CPU bound
Most well-configured and tuned GIS systems are CPU bound.
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InfrastructureMemory requirements
Wide ranges of memory consumptions
Item Low High
ArcSOC Map 50 MB 500 MB
ArcSOC Image 20 MB 1,024 MB
ArcSOC GP 100 MB 2,000 MB
XenApp Session 500 MB 1.2 GB
Database Session 10 MB 75 MB
Database Cache 200 MB 200 GB
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Server CPU Spec
• Performance is impacted by SPEC Rate Per Core
• Scalability is impacted by number of cores and SPEC Rate Per Core
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Network Planning Establish and Configure DNS Appropriately!
Trace Route: LA Workstation → Phoenix DNS
LA Database Server
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VM – watch out for overallocations
88/314=0.28 cpu/vm
92/176=0.52 cpu/vm
119722 vMotion Migrations
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Scaling Direction
• Scaling up
- Adding resources to your existing machine
- Usually RAM
- Commonly, due to lots of service instances
• Scaling out
- Add more machines
- Usually to get more compute power, sometimes for high availability
- Commonly, due to increased user demand
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Configure
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File Geodatabase
• Local file geodatabase data
- Better than shapefiles
- Fastest
- Scales with hardware
- Best with static data
- Make your FGDB read-only
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Enterprise Geodatabase
Enterprise Geodatabase
- Fast
- Live data
- Requires database expert
- Traditional Versioning
- fine for desktop editing, may be problematic for server
- Branch Versioning
- New with Pro 2.1 and Enterprise 10.6. Not supported with ArcMap.
- Designed for better scalability with many concurrent users and a
web editing model
Keep statistics up-to-date
Index fields that will be queried
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Configure Web MapCache and generalize data
• Use generalized data if applicable
• Cache (tiles) may reduce the amount of traffic
• Large amounts of data can be slow and overwhelming
- Aggregate data using smart mapping
- on-the-fly generalization and smaller data transfer (quantization)
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Consolidate and reduce number of services
Enterprise portal GIS Server Data Store
Dataset
GIS Service
GIS Service
GIS Service
Web Layer
Web Layer
Web Layer
• Common setup today:
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Consolidate and reduce number of services
GIS Server Data Store
DatasetGIS Service
Web Layer
Web Layer
Web Layer
Enterprise portal
• More efficient: consolidate layers with like security into a single service
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Consolidate and reduce number of services
GIS Server Data Store
WellsWells
Active Wells
Proposed Wells
Wells by Status
Enterprise portal
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Configure login for your Enterprise portal
Login settings
- Identity and group stores can affect login performance
significantly
- Example: Active Directory where users are in many groups can
affect performance (newer releases handle this better)
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Configure ArcGIS Server- instance tuning
• For predictable performance use min = max
• Default is min = 1, max = 2. Consider changing this!
• Allocate required swap space/page file
• Cached service : set max = 1 to conserve memory. Individual tile requests not
serviced by the SOC process.
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ArcSOC Optimizer
• Decrease or increase instances, based on:
• 1. historical usage
• 2. available memory and process count
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New ArcGIS Server 10.7 shared instances
• Recommended for services that receive infrequent requests, particularly when the server
site hosts many services
• Pool of processes supporting multiple services
• Conserves memory
Currently supports only map services published from ArcGIS Pro
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Geonet serieshttps://community.esri.com/thread/231451-arcgis-architecture-series-tools-of-an-architect
https://community.esri.com/community/implementing-arcgis/content?filterID=contentstatus%5Bpublished%5D~category%5Barchitecture-
security%5D&itemView=thumbnail
![Page 54: Esri Best Practices: Tuning, Testing, and Monitoring · 2019-08-12 · Esri Best Practices: Tuning, Testing, and Monitoring Andrew Sakowicz, asakowicz@esri.com Frank Pizzi, fpizzi@esri.com](https://reader031.vdocument.in/reader031/viewer/2022013021/5f1e88522c355670e252b513/html5/thumbnails/54.jpg)
Section Subhead
Monitoring
![Page 55: Esri Best Practices: Tuning, Testing, and Monitoring · 2019-08-12 · Esri Best Practices: Tuning, Testing, and Monitoring Andrew Sakowicz, asakowicz@esri.com Frank Pizzi, fpizzi@esri.com](https://reader031.vdocument.in/reader031/viewer/2022013021/5f1e88522c355670e252b513/html5/thumbnails/55.jpg)
What is monitored?
CPUMemoryDiskNetworkEvents
Hardware
Software
Services Response TimeBusy TimeThroughputSOC Usage
Health ChecksLog EntryUsage StatisticsConfigurationSecurity
Health
Performance
Usage
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Usage
![Page 57: Esri Best Practices: Tuning, Testing, and Monitoring · 2019-08-12 · Esri Best Practices: Tuning, Testing, and Monitoring Andrew Sakowicz, asakowicz@esri.com Frank Pizzi, fpizzi@esri.com](https://reader031.vdocument.in/reader031/viewer/2022013021/5f1e88522c355670e252b513/html5/thumbnails/57.jpg)
Usage
• Usage (or user load) is typically measured using:
- Transactions or requests per time, e.g. per seconds, 5 min, day.
- User IP per time, e.g. per seconds, 5 min, day.
- Users per time, e.g. per seconds, 5 min, day.
• Measured at:
- Load balancer (LB)
- Web server
- ArcGIS Server
- Database
• Format:
- Chart time series
- Table
- Map
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Usage at LB: transactions (or requests)Categories > Usage > Tr/Interval
• Chart format
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Usage at LB : users and transactionsCategories > GeoInfo > IP Location
• Map format
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Usage at LB : usersCategories > Usage > IP / Interval
• Chart format
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Usage at ArcGIS Server: transactionsCategories > ArcGIS > Tr
• Chart format
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Usage at ArcGIS Server : transactionsReports > ArcGIS > Tr
• Table format
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Usage at ArcGIS Server: CPU timeCategories > ArcGIS > Busy Time (sec)
• CPU time a given service took at ArcGIS Server level.
• Use to identify top cpu consumers at ArcGIS Server.
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Performance
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Performance at LBReports > Usage > Response Time (sec)
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Performance at ArcGIS ServerCategories > ArcGIS > Busy Time per Tr (sec)
• Busy Time per Tr (sec) is the total time (seconds) per transaction consumed by
ArcGIS Server service.
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Performance at ArcGIS ServerCategories > ArcGIS > Busy Time per Tr (sec)
• Table format
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Typical cases and
Root Cause Analysis (RCA)
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Root Cause Analysis (RCA)“Source” - the most downstream failing component
“Impact” – all upstream failing components
Portal
for ArcGIS
Hosting
Server
ArcGIS
Data Store
(relational + tile cache)
Web Adaptor
GeoEvent
Server
ArcGIS
Server
“Impact”
Portal
for ArcGIS
Hosting
Server
ArcGIS
Data Store
(relational + tile cache)
Web Adaptor
ArcGIS
Server
“Impact”
GeoEvent
Server
Example 1 Example 2
“Source”
“Source”
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Overloaded systemLoad exceeds the designed capacity
Source Impact
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RCA: Usage spike Throughput (tr/s)
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Bottleneck
Source Impact
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RCA: Free instances = 0 Bottleneck are often created by increased load
![Page 74: Esri Best Practices: Tuning, Testing, and Monitoring · 2019-08-12 · Esri Best Practices: Tuning, Testing, and Monitoring Andrew Sakowicz, asakowicz@esri.com Frank Pizzi, fpizzi@esri.com](https://reader031.vdocument.in/reader031/viewer/2022013021/5f1e88522c355670e252b513/html5/thumbnails/74.jpg)
Unstable InfrastructureInterruption to the underlying resources
Source Impact
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RCA: CPU spike by unexpected process, e.g. virous scan
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RCA: Portal for ArcGIS Server service stopped
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RCA: ArcGIS Server machine rebooted
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RCA: Database not running
![Page 79: Esri Best Practices: Tuning, Testing, and Monitoring · 2019-08-12 · Esri Best Practices: Tuning, Testing, and Monitoring Andrew Sakowicz, asakowicz@esri.com Frank Pizzi, fpizzi@esri.com](https://reader031.vdocument.in/reader031/viewer/2022013021/5f1e88522c355670e252b513/html5/thumbnails/79.jpg)
Please Share Your Feedback in the App
Download the Esri
Events app and find
your event
Select the session
you attended
Scroll down to
“Survey”
Log in to access the
survey
Complete the survey
and select “Submit”
![Page 80: Esri Best Practices: Tuning, Testing, and Monitoring · 2019-08-12 · Esri Best Practices: Tuning, Testing, and Monitoring Andrew Sakowicz, asakowicz@esri.com Frank Pizzi, fpizzi@esri.com](https://reader031.vdocument.in/reader031/viewer/2022013021/5f1e88522c355670e252b513/html5/thumbnails/80.jpg)
Please Share Your Feedback in the App
Download the Esri
Events app and find
your event
Select the session
you attended
Scroll down to
“Survey”
Log in to access the
survey
Complete the survey
and select “Submit”
![Page 81: Esri Best Practices: Tuning, Testing, and Monitoring · 2019-08-12 · Esri Best Practices: Tuning, Testing, and Monitoring Andrew Sakowicz, asakowicz@esri.com Frank Pizzi, fpizzi@esri.com](https://reader031.vdocument.in/reader031/viewer/2022013021/5f1e88522c355670e252b513/html5/thumbnails/81.jpg)
Presentation TitlePresenter Names
![Page 82: Esri Best Practices: Tuning, Testing, and Monitoring · 2019-08-12 · Esri Best Practices: Tuning, Testing, and Monitoring Andrew Sakowicz, asakowicz@esri.com Frank Pizzi, fpizzi@esri.com](https://reader031.vdocument.in/reader031/viewer/2022013021/5f1e88522c355670e252b513/html5/thumbnails/82.jpg)
Presentation TitlePresenter Names
![Page 83: Esri Best Practices: Tuning, Testing, and Monitoring · 2019-08-12 · Esri Best Practices: Tuning, Testing, and Monitoring Andrew Sakowicz, asakowicz@esri.com Frank Pizzi, fpizzi@esri.com](https://reader031.vdocument.in/reader031/viewer/2022013021/5f1e88522c355670e252b513/html5/thumbnails/83.jpg)
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Section Subhead
Section Header
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Presenter(s)
Demo Title