Test

Debugging & Managing system performance

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Preguntas del test (34)

1Which feature in Pega Platform allows you to measure the overall quality of an application's design?
1. ACompliance score
2. BThe Tracer tool
3. CLive UI
4. DChannel interface manager
2If you are a Cloud Customer, what is the best way for you to set a performance threshold?
1. AAdjust the application compliance score.
2. BMonitor the alert logs.
3. CCreate a DSS record to adjust the threshold.
4. DAdjust the threshold through the prconfig.xml system file.
3In which two ways can you identify rule caching performance issues? (Choose Two)
1. AUse PAL to evaluate rule caching at the application level.
2. BUse PAL to determine which rules should be deleted.
3. CCount the number of rules that cache by running a report.
4. DUse the My Performance Detail along with the user ID to evaluate rule caching at the user level.
4Which three actions can you take to minimize the number of ruleset lists in use in an application? (Choose Three)
1. AMinimize the number of access groups.
2. BEliminate multiple ruleset versions by skimming rules to the next minor or major version.
3. CMerge branch rulesets before migrating an application.
4. DEliminate unnecessary personal rulesets.
5. ELimit the number of operators who access an application.
5Which two of the following statements about large tables in Pega Platform are true? (Choose Two)
1. AYou can archive old data to reduce database table size.
2. BYou can create database table records for one or more classes in a class group.
3. CLarge tables cause issues only if you have not archived the data that is stored in the large tables.
4. DOnly a database administrator (DBA) can tune Pega Platform to reduce issues that arise from large tables.
5. EUsing a BLOB prevents data compression.
6Which performance tool do you run to determine which specific step executed by your requestor session that is causing a problem?
1. AThe Database Trace tool
2. BThe Performance Profiler tool
3. CThe PegaRULES Log Analyzer (PLA)
4. DThe Performance Analyzer (PAL)
7Which two types of issues are identified by using Pega Platform alerts? (Choose Two)
1. APerformance
2. BFunctional
3. CSecurity
4. DConfiguration
8Which two approaches reduce the possibility of rule caching causing performance issues in your application? (Choose Two)
1. AOnly allow rule checkout for operators who need to work in checked out rules.
2. BCreate multiple access groups.
3. CRemove branch rulesets in your production system.
4. DClassify the nodes in your system.
9Which performance tool do you run to examine a query made to the database?
1. AThe PegaRULES Log Analyzer (PLA)
2. BThe Performance Profiler tool
3. CThe Database Trace tool
4. DThe Performance Analyzer (PAL)
10Which of the following options can you use along with system alerts to determine if your application performance needs optimization?
1. APerformance Profiler
2. BDatabase Trace
3. CLive UI tool
4. DPerformance Analyzer (PAL)

11Use "pega", "alert", or "alertsecurity":
A node was shut down for an update: [blank_start]PEGA[blank_end]
A database query exceeded the performance threshold: [blank_start]ALERT[blank_end]
A login attempt failed due to an incorrect password: [blank_start]ALERTSECURITY[blank_end]
An attempt to access a third-party service failed due to an incorrect user name: [blank_start]PEGA[blank_end]
1. APEGA
2. BALERT
3. CALERTSECURITY
4. DPEGA
12A SECU0006 alert is generated with the message PRPC detected excessive failed login attempts for the user:XXXX from IP:192.168.100.100. Brute force attack prevention measures were invoked. What three pieces of information do the alert ID and message provide? (Choose Three)
1. AIt is a security-related alert
2. BThe alert type
3. CIt is a performance-related alert
4. DThe requestor type
5. EA description of the alert
13The logging level identifies the severity of the issue.
[blank_start]FATAL[blank_end]: Severe errors that can cause the application to terminate.
[blank_start]ERROR[blank_end]: Serious errors that might allow the application to continue running.
[blank_start]ALERT[blank_end]: Performance-related issues, such as an exceeded performance threshold, or an event that affects performance, have occurred.
[blank_start]WARN[blank_end]: Potential issues that might cause an adverse performance result.
[blank_start]INFO[blank_end]: Notifications of runtime events, such as system startup or shutdown.
[blank_start]DEBUG[blank_end]: Informational events that are useful for debugging.
1. AFATAL
2. BERROR
3. CALERT
4. DWARN
5. EINFO
6. FDEBUG
14The [blank_start]PegaRULES Log Analyzer (PLA)[blank_end] is a standalone web application that developers and system administrators can use to view consolidated summaries of system log data. The [....] consolidates and summarizes the ALERT, PEGA, and Garbage Collection (GC) logs. The log data provides key information about operational and system health that developers and system administrators can use to quickly identify, diagnose, and address performance issues.
1. APegaRULES Log Analyzer
15The [blank_start]PegaRULES Log Analyzer (PLA)[blank_end] is a [blank_start]standalone web application[blank_end] that developers and system administrators can use to view [blank_start]consolidated summaries of system log[blank_end] data. The [....] consolidates and summarizes the [blank_start]ALERT, PEGA, and Garbage Collection (GC)[blank_end] logs. The log data provides key information about operational and system health that developers and system administrators can use to quickly [blank_start]identify, diagnose, and address[blank_end] performance issues.
1. APegaRULES Log Analyzer (PLA)
2. Bstandalone web application
3. Cconsolidated summaries of system log
4. DALERT, PEGA, and Garbage Collection (GC)
5. Eidentify, diagnose, and address
16Log files capture [blank_start]event notifications[blank_end] ranging from [blank_start]routine system status information[blank_end] to [blank_start]severe errors[blank_end] that can cause [blank_start]an application to quit unexpectedly[blank_end]. Each log is managed by an [blank_start]appender[blank_end], which determines the type of events written to the log file. The available log files vary, depending on the [blank_start]log file appenders[blank_end] that are configured in the [blank_start]system settings[blank_end].

The following log files are commonly used on Pega Platform systems:

The [blank_start]PEGA[blank_end] log contains warnings, errors, and information messages about internal operations. This log is also called the console log or system log and is used for debugging the application.
The [blank_start]ALERT[blank_end] log contains performance-related alerts triggered when an operation exceeds the specified performance threshold.
The [blank_start]ALERTSECURITY[blank_end] log contains alerts (identified by the prefix SECU) that suggest improper configuration of Internet Application Composer facilities, or overt attempts to bypass system security features on the Pega Platform node through URL tampering.
The [blank_start]BIX[blank_end] log contains entries generated by the Business Intelligence Exchange (BIX) during extract operations.
The [blank_start]SERVICES-PAL[blank_end] log contains performance data saved from services.
The [blank_start]CLUSTER[blank_end] log contains information about the setup and run-time behavior of the cluster.

Note: Pega Platform manages logs based on [blank_start]which appenders are configured[blank_end]. For example, to log performance data for services, you add [blank_start]SERVICES-PAL in the prlog4j2.xml[blank_end] configuration file for the node.

You access log files from the [blank_start]Log utilities section of the Logs tab[blank_end] in Dev Studio. The Log utilities section includes a list of log file [blank_start]appenders and an external log viewer[blank_end]. Clicking Log files displays a list of the log file appenders that are [blank_start]active on the system[blank_end]. Downloading a log file requires [blank_start]administrator credentials[blank_end] for the application server that hosts Pega Platform. You can also view log files using an external log viewer, such as [blank_start]Kibana[blank_end].

A system administrator can [blank_start]override log level settings[blank_end] in [blank_start]Admin Studio[blank_end] to control which logging events are displayed in the PEGA log by creating a [blank_start]log category[blank_end]. Events are recorded only for the [blank_start]selected logging level and higher[blank_end].

When debugging an activity, you can use the [blank_start]Log-Message method[blank_end] with the logging level set to [blank_start]InfoForced[blank_end] to add an event to the PEGA log regardless of settings in the [blank_start]prlog4j2.xml file or the Log Category[blank_end]. To reduce log entries and improve performance in production systems, remove InfoForced steps or convert them to comments when you finish debugging the activity.
1. Aevent notifications
2. Broutine system status information
3. Csevere errors
4. Dan application to quit unexpectedly
5. Eappender
6. Flog file appenders
7. Gsystem settings
8. HPEGA
9. IALERT
10. JALERTSECURITY
11. KBIX
12. LSERVICES-PAL
13. MCLUSTER
14. NNODES
15. OSERVICES
16. PBIX_LOGGING
17. QSECURITYALERT
18. RPERFORMANCE
19. SSYSTEMS
20. Twhich appenders are configured
21. USERVICES-PAL in the prlog4j2.xml
22. VLog utilities section of the Logs tab
23. Wappenders and an external log viewer
24. Xactive on the system
25. Yadministrator credentials
26. ZKibana
27. AAoverride log level settings
28. ABAdmin Studio
29. AClog category
30. ADselected logging level and higher
31. AELog-Message method
32. AFInfoForced
33. AGprlog4j2.xml file or the Log Category
17As a Pega Cloud client, you can download log files from the [blank_start]My Pega Cloud portal[blank_end] for internal analysis or to share with [blank_start]Pegasystems Global Client Support (GCS)[blank_end]. From the My Pega Cloud tab, you can download a [blank_start]bundle of specified log files[blank_end] created from your environment during the [blank_start]last 365 days[blank_end]. Each download you complete using the My Pega Cloud portal supports [blank_start]up to seven days of logs[blank_end]; to download more additional logs, you [blank_start]must initiate a separate request[blank_end] for the additional day's logs. The log bundle is a [blank_start]compressed TAR file[blank_end] you can download to your local computer.

At run time, the Pega [blank_start]generates alerts[blank_end] for [blank_start]performance and security-related[blank_end] application issues. Alerts are [blank_start]text-based messages[blank_end] that serve as important notifications about the [blank_start]functioning of your system[blank_end].

[blank_start]Performance alerts[blank_end] are generated when rule execution exceeds a [blank_start]performance threshold[blank_end]. [blank_start]Security alerts[blank_end] are generated when the security of a [blank_start]Pega Platform server is at risk[blank_end]. Analyze alerts to identify the root cause of a performance or security issue. You can access alerts from your session from the [blank_start]My Alerts display[blank_end]. The alert format provides information about the alert. You can determine whether the alert is [blank_start]performance or security[blank_end] related, the [blank_start]type of alert[blank_end], the [blank_start]type of requestor[blank_end] (for example, a browser), and [blank_start]the activity or stream[blank_end] that triggered the alert from the alert format.

The most frequently-generated alert is the [blank_start]PEGA0001[blank_end] alert, which occurs when the elapsed time for an HTTP interaction time exceeds the threshold setting.

The [blank_start]SECU0005[blank_end] alert is generated when Pega Platform encounters a thread name in the [blank_start]URL of an HTTP request[blank_end] that [blank_start]does not already exist in the requestor[blank_end] and whose name contains [blank_start]invalid characters[blank_end]. This alert allows you to identify potentially malicious scripts that have been inserted into the thread name portion of the URL so that you can research and [blank_start]correct the thread name[blank_end] or other issues as appropriate.
1. AMy Pega Cloud portal
2. BPegasystems Global Client Support (GCS)
3. Cbundle of specified log files
4. Dlast 365 days
5. Eup to seven days of logs
6. Fmust initiate a separate request
7. Gcompressed TAR file
8. Hgenerates alerts
9. Iperformance and security-related
10. Jtext-based messages
11. Kfunctioning of your system
12. Lperformance threshold
13. MPerformance alerts
14. NSecurity alerts
15. OPega Platform server is at risk
16. PMy Alerts display
17. Qperformance or security
18. Rtype of alert
19. Stype of requestor
20. Tthe activity or stream
21. UPEGA0001
22. VSECU0005
23. WURL of an HTTP request
24. Xdoes not already exist in the requestor
25. Yinvalid characters
26. Zcorrect the thread name
18Used to understand the system resources consumed by processing a single requestor session: [blank_start]Performance Analyzer (PAL)[blank_end]
Used to tune the application in case of any database performance issues: [blank_start]Database Trace[blank_end]
Used to get a detailed trace of performance information about the execution of activities, when rules, and data transforms executed by your requestor session: [blank_start]Performance Profiler[blank_end]
Used to actively gather, monitor, and analyze real-time performance and health indicators from all active Pega applications: [blank_start]Pega Predictive Diagnostic Cloud[blank_end]
1. APerformance Analyzer (PAL)
2. BDatabase Trace
3. CPerformance Profiler
4. DPega Predictive Diagnostic Cloud
19A developer collects baseline readings for a flow action in the system via Performance Analyzer. A change for the same flow actions comes later in the sprint. The developer collects the Performance Analyzer readings again for that flow action.

What might the comparison of the new and previous readings suggest?
1. ANegative performance change.
2. BPositive or negative performance change
3. CPositive performance change.
4. DNo performance change.
20DB Trace is best suited to diagnose a performance issue in which two of the following environments? (Choose Two)
1. ADevelopment
2. BProduction
3. CProduction Mirror
4. DStaging
21Which two statements about the Database Trace are true? (Choose Two)
1. AOperating the Database Trace tool might adversely affect performance by producing a large volume output.
2. BThe Database Trace provides a view of all the performance statistics that Pega Platform captures.
3. CThe Database Trace readings are grouped into three different types: Elapsed, CPU, and Count.
4. DThe data that you download from the Database Trace contains a sequential progression of trace events.
22The Performance Profiler is used to identify a step of a data transform that might have a performance issue.
1. AVerdadero
2. BFalso
23Which two metrics does the Performance Profiler tool measure? (Choose Two)
1. ANumber of alerts were shown during a test.
2. BNumber of rules that are used during the test.
3. CTime spent to complete a step.
4. DResults of when conditions.
24Which two of the following elements does PDC monitor? (Choose Two)
1. AHealth statistics
2. BInformational messages
3. CAlerts
4. DApplication errors
25Which statement about PDC is true?
1. APDC is designed for technical administrators and access should be limited to system administrators.
2. BPDC environment must be secured because monitored applications can inadvertently send confidential customer data in alert details.
3. CPDC provides a wide variety of application health and error alerts as well as tools to manage exceptions and recommended improvements.
4. DAlert thresholds should not be set too low because the increase in alert volume degrades application performance.
26As you run a case instance, you notice it takes a significant amount of time to advance from one view to the next view. You run the case multiple times and notice the same slow performance. How do you proceed?
1. AYou use the Performance Profiler tool.
2. BYou use Pega Predictive Diagnostic Cloud™ (PDC).
3. CYou use the Performance Analyzer (PAL).
4. DYou use the Database Trace tool.
27The reason you want to run a process immediately before you take performance readings is ____________.
1. Ato ensure that you know which buttons to click so you can test quickly
2. Bto ensure that there are no bugs in the system
3. Cto train the system which process you are going to measure
4. Dto allow the rules to assemble
28In which scenario is it most appropriate to leverage Predictive Diagnostic Cloud?
1. AA company has a Pega application and is interested in finding the cause of an error that occurs during case processing.
2. BA company has a Pega application and is interested in browsing a list of performance-related alerts.
3. CA company has multiple Pega and non-Pega Platform applications and is interested in receiving guidance to avoid system performance issues.
4. DA company has multiple Pega applications and is interested in monitoring the health of all active applications.
29Which performance tool do you use to collect performance data for individual steps in a data transform?
1. ADatabase Trace
2. BClipboard tool
3. CPerformance Profiler
4. DPerformance Analyzer (PAL)
30The [blank_start]Performance landing page[blank_end] provides access to the three performance tools: Performance Analyzer (PAL), Database Trace, and Performance Profiler. These tools are also available from the [blank_start]Performance tool in the toolbar[blank_end]. Performance statistics can help you distinguish between [blank_start]performance issues[blank_end] that arise in the [blank_start]Pega Platform server, the database[blank_end], [blank_start]or external systems called[blank_end]. In all cases, the statistics can help you determine how to improve performance.

[blank_start]Performance Analyzer (PAL)[blank_end]: Pega always gathers cumulative resource statistics. Use this tool to understand the system resources consumed by processing a single requestor session. It works on existing data; it does not degrade processing.
[blank_start]Database Trace[blank_end]: This tool is useful to tune the application in case of any database performance issues.
[blank_start]Performance Profiler[blank_end]: Use this to obtain a detailed trace of performance information about the execution of activities, when condition rules, and data transforms executed by your requestor session.
1. APerformance Analyzer (PAL)
2. BDatabase Trace
3. CPerformance Profiler
4. DPerformance landing page
5. EPerformance tool in the toolbar
6. Fperformance issues
7. GPega Platform server, the database
8. Hor external systems called
31Performance Analyzer (PAL)
The first step to measuring your application performance is to [blank_start]take measurements[blank_end]. Start by clicking [blank_start]Reset Data[blank_end] to clear any data in the tool. Because the system continuously monitors performance, you are [blank_start]eliminating any previously recorded[blank_end] entries from your results by resetting data.

There are two options for adding a reading: [blank_start]Add Reading[blank_end] and [blank_start]Add Reading with Clipboard Size[blank_end]. The only difference between the two readings is the clipboard size, which [blank_start]takes extra time to calculate[blank_end].

When adding a reading, the best practice is to [blank_start]define points[blank_end] that identify [blank_start]what occurred during that reading[blank_end]. For example, use one reading [blank_start]per flow action[blank_end] or [blank_start]screen render[blank_end], depending on what process you are measuring. You can download the results to an Excel file by clicking [blank_start]Save Data[blank_end].

The [blank_start]INIT[blank_end] row displays the totals from [blank_start]the first time[blank_end] the Performance tool made a reading. This bottom row shows the totals since the [blank_start]first intitialzation[blank_end] of the Performance tool. Most readings in this row at the outset are [blank_start]near zero[blank_end]. If the readings are [blank_start]not near zero[blank_end], click Reset Data to reset the readings. Each subsequent reading is labeled as a [blank_start]DELTA[blank_end], which indicates the [blank_start]change from a previous reading[blank_end]. Delta rows are displayed as you [blank_start]interact with Pega Platform[blank_end]. Each row shows values that [blank_start]accumulated[blank_end] from the [blank_start]previous Delta or Init row[blank_end]. The [blank_start]FULL[blank_end] reading reflects the [blank_start]totals[blank_end] since [blank_start]that start of your session[blank_end] [blank_start]or the most recent Reset Data operation[blank_end].

Clicking INIT, DELTA, or FULL displays more details about the reading. Many different results are available to you for analyzing the performance. Be mindful of [blank_start]first use assembly (FUA)[blank_end], as it can skew initial readings. To obtain results unaffected by FUA, run through the process once to ensure that [blank_start]all rules are assembled[blank_end] before taking any measurements.
[blank_start]Int #[blank_end]: Sequence number of the most recent completed interaction.
[blank_start]Int Count[blank_end]: Total number of interactions.
[blank_start]Total Elapsed[blank_end]: Total elapsed time for this interaction.
[blank_start]RA Elapsed[blank_end]: Rules assembly elapsed time.
[blank_start]Rule I/O Elapsed[blank_end]: Elapsed time spent finding rules.
[blank_start]RDB I/O Elapsed[blank_end]: Elapsed time executing SQL operations against the PegaRULES database; [blank_start]excludes Connect SQL executions[blank_end] for the PegaRULES database or external databases.
[blank_start]Connect Elapsed[blank_end]: Time spent waiting for an Connect rule execution [blank_start]to an external system[blank_end].
[blank_start]Other I/O Elapsed[blank_end]: Elapsed time accessing [blank_start]non-rule-resolved[blank_end] instances from the PegaRULES database plus the elapsed time [blank_start]retrieving non-rule database lists[blank_end].
[blank_start]Total CPU[blank_end]: Total CPU time used.
[blank_start]RA CPU[blank_end]: CPU time spent assembling Java classes.
1. Atake measurements
2. BReset Data
3. Celiminating any previously recorded
4. DAdd Reading
5. EAdd Reading with Clipboard Size
6. Ftakes extra time to calculate
7. Gdefine points
8. Hwhat occurred during that reading
9. Iper flow action
10. Jscreen render
11. KSave Data
12. LINIT
13. MDELTA
14. Nthe first time
15. Ofirst intitialzation
16. Pnear zero
17. Qnot near zero
18. Rchange from a previous reading
19. Sinteract with Pega Platform
20. Taccumulated
21. Uprevious Delta or Init row
22. VFULL
23. Wtotals
24. Xthat start of your session
25. Yor the most recent Reset Data operation
26. Zfirst use assembly (FUA)
27. AAall rules are assembled
28. ABInt #
29. ACInt Count
30. ADTotal Elapsed
31. AERA Elapsed
32. AFRule I/O Elapsed
33. AGRDB I/O Elapsed
34. AHConnect Elapsed
35. AIexcludes Connect SQL executions
36. AJto an external system
37. AKOther I/O Elapsed
38. ALnon-rule-resolved
39. AMretrieving non-rule database lists
40. ANTotal CPU
41. AORA CPU
32Database Trace
Run Database Trace if [blank_start]PAL readings[blank_end] indicate performance issues in the [blank_start]database operations[blank_end]. Database Trace can trace [blank_start]all the SQL operations[blank_end] like [blank_start]queries or commits[blank_end] that are performed.

The Database Trace produces a [blank_start]text file[blank_end] containing [blank_start]the SQL statements,[blank_end] [blank_start]rule cache hit statistics, timings, and[blank_end] [blank_start]other data that reflect the interactions[blank_end] of your requestor session with the [blank_start]Pega database[blank_end] or [blank_start]other relational databases[blank_end]. A basic familiarity of SQL Operations, (for example read, write, and insert), and BLOB is useful to interpret the output. Downloaded data contains a [blank_start]sequential progression[blank_end] of trace events.

Operating the Database Trace tool can [blank_start]adversely affect performance[blank_end] by producing a large volume output. Use the tool for [blank_start]short periods[blank_end], in [blank_start]non-production environments[blank_end] appropriate for debugging.

Click [blank_start]Trace Options[blank_end] to open the settings window. The settings window lists [blank_start]all possible events[blank_end] to trace. If an event is [blank_start]inapplicable to a situation[blank_end], remove it from the list to streamline the results. You also have the option to [blank_start]generate a stack trace[blank_end]. Generating the stack trace is an [blank_start]expensive[blank_end] process and should only be used when required.
1. APAL readings
2. Bdatabase operations
3. Call the SQL operations
4. Dqueries or commits
5. Etext file
6. Fthe SQL statements,
7. Grule cache hit statistics, timings, and
8. Hother data that reflect the interactions
9. IPega database
10. Jother relational databases
11. Ksequential progression
12. Ladversely affect performance
13. Mshort periods
14. Nnon-production environments
15. OTrace Options
16. Pall possible events
17. Qinapplicable to a situation
18. Rgenerate a stack trace
19. Sexpensive
33Performance Profiler
Use the Profiler to obtain a [blank_start]detailed trace[blank_end] of performance information about the execution of [blank_start]activities, when condition rules[blank_end], and [blank_start]data transforms executed[blank_end] by [blank_start]your requestor session[blank_end]. The Profiler traces [blank_start]every execution (in all Threads)[blank_end] of rules of [blank_start]these three types[blank_end] in [blank_start]all rulesets[blank_end]. The Performance Profiler should be run in conjunction with [blank_start]Performance Analyzer[blank_end] to narrow down the specific step of the cause. When you use the Performance Profiler, you [blank_start]first record readings[blank_end] of the application's performance, and then you [blank_start]analyze the readings[blank_end] to identify problems.

The Performance Profiler requires [blank_start]substantial processing overhead[blank_end]. Stop the Performance Profiler as soon as your data collection is complete.

In the Performance Profiler results table, click the Download icon to save the results in a [blank_start]comma-separated value file format[blank_end]. The results can then be opened by using any spreadsheet program, such as Excel, to review the Performance Profiler readings.

[blank_start]Sequence[blank_end]: Marks the beginning of each activity step or other row.
[blank_start]Interaction[blank_end]: Sequence number of the interaction, as recorded in the Performance tool. Starts with 1 on the initial display of the login form.
[blank_start]Activity[blank_end]: Handle of the activity, when condition, or data transform.
[blank_start]Caller[blank_end]: Handle of the activity that called the current rule.
[blank_start]Step[blank_end]: Step number. For when condition rules, this value is always [blank_start]W[blank_end]. For data transforms, this value is always [blank_start]M[blank_end].
[blank_start]Method Name or When Result[blank_end]: For activities, [blank_start]identifies the method in the step[blank_end]. For when condition rules, [blank_start]displays true or false[blank_end]. For data transforms, [blank_start]this value is blank[blank_end].
[blank_start]Total CPU time[blank_end]: Total CPU time in seconds for this step. If this step contains a [blank_start]Call or Java instruction[blank_end], the CPU time of [blank_start]called activities is included[blank_end].
[blank_start]CPU Time Without Children[blank_end]: Total CPU time in seconds for this step, excluding time for called processing. If this step contains a Call or Java instruction, the CPU time of [blank_start]called activities is not included[blank_end].
[blank_start]Total Wall Time[blank_end]: Elapsed time in seconds to complete this step. Values reflect the impact of other users on this server, waits for database operations and external events, and so on.
[blank_start]Wall Time Without Children[blank_end]: Elapsed time (wall time) in seconds, for this step, [blank_start]exclusive of any called processing[blank_end]. (This value is useful for isolating the performance of [blank_start]Java steps[blank_end] that may perform extensive processing in addition to calling activities.)
1. Adetailed trace
2. Bactivities, when condition rules
3. Cdata transforms executed
4. Dyour requestor session
5. Eevery execution (in all Threads)
6. Fthese three types
7. Gall rulesets
8. HPerformance Analyzer
9. Ifirst record readings
10. Janalyze the readings
11. Ksubstantial processing overhead
12. Lcomma-separated value file format
13. MSequence
14. NInteraction
15. OActivity
16. PCaller
17. QStep
18. RW
19. SM
20. TMethod Name or When Result
21. UTotal CPU time
22. Videntifies the method in the step
23. Wdisplays true or false
24. Xthis value is blank
25. YCall or Java instruction
26. Zcalled activities is included
27. AACPU Time Without Children
28. ABcalled activities is not included
29. ACTotal Wall Time
30. ADWall Time Without Children
31. AEexclusive of any called processing
32. AFJava steps
34Pega Predictive Diagnostic Cloud
The PDC is a Software as a Service (SaaS) tool that runs on Pega Cloud and actively [blank_start]gathers, aggregates, monitors[blank_end], [blank_start]and analyzes real-time performance[blank_end] and [blank_start]health indicators[blank_end] from [blank_start]all active Pega applications[blank_end] such as alerts and guardrail violations. PDC allows you to monitor [blank_start]several on-premise and cloud-based[blank_end] Pega applications.

Pega sends [blank_start]known and safe content[blank_end] to PDC by using only the clipboard parameter data that is [blank_start]required for analysis[blank_end]. The data is sent [blank_start]asynchronously[blank_end] to minimize any performance impact on the monitored Pega implementation. Data with [blank_start]identifying information[blank_end] is not sent due to privacy concerns, and PDC [blank_start]does not request information[blank_end] from the monitored application.

Pega gathers the following data for PDC:
[blank_start]Alerts[blank_end]: Identifies the type of alert and the metadata captured in an interaction.
[blank_start]Parameter page[blank_end]: Describes the parameters from the current parameter page, including important contextual information about the functions that run in the monitored application. All remaining parameters are filtered out and excluded.
[blank_start]Database alerts[blank_end]: Details the database query, excluding business data values.
[blank_start]Exceptions[blank_end]: Contains some contextual data that is a subset of the fields sent for alerts.
[blank_start]Performance statistics[blank_end]: Includes statistics for average response time and unique user count. PDC uses these statistics to identify overall performance and performance trends for monitored applications.
[blank_start]Database indexes[blank_end]: Includes database index information. PDC uses database index information to generate recommendations to improve query performance.

PDC [blank_start]analyzes and aggregates[blank_end] the data generated from Pega applications to produce [blank_start]trending dashboards (graphs)[blank_end]. The trending dashboards provide a [blank_start]graphical representation[blank_end] of daily [blank_start]average response usage[blank_end], [blank_start]interaction volume, and[blank_end] [blank_start]user sessions counts[blank_end]. The presentation of data in [blank_start]trend graphs[blank_end] helps to [blank_start]monitor, isolate and identify[blank_end] [blank_start]and anticipate issues[blank_end] by presenting behavior over time. PDC empowers [blank_start]business stakeholders[blank_end] and IT administrators to take preventative action by predicting potential system performance and business logic issues and providing remediation suggestions.

Use [blank_start]Improvement Plan[blank_end] to view a summary of issues that affect the performance of your monitored system. Use [blank_start]Event Viewer[blank_end] to conduct an in-depth investigation.

Pega Predictive Diagnostic Cloud generates [blank_start]notifications[blank_end] that you can receive as messages to help you address any issues that might occur. By default, PDC sends notifications by email. However you can configure PDC to send individual notifications by [blank_start]SMS, notification API, or to ServiceNow[blank_end].
1. Agathers, aggregates, monitors
2. Band analyzes real-time performance
3. Chealth indicators
4. Dall active Pega applications
5. Eseveral on-premise and cloud-based
6. Fknown and safe content
7. Grequired for analysis
8. Hasynchronously
9. Iidentifying information
10. Jdoes not request information
11. KAlerts
12. LParameter page
13. MDatabase alerts
14. NExceptions
15. OPerformance statistics
16. PDatabase indexes
17. Qanalyzes and aggregates
18. Rtrending dashboards (graphs)
19. Sgraphical representation
20. Taverage response usage
21. Uinteraction volume, and
22. Vuser sessions counts
23. Wtrend graphs
24. Xmonitor, isolate and identify
25. Yand anticipate issues
26. Zbusiness stakeholders
27. AAImprovement Plan
28. ABEvent Viewer
29. ACnotifications
30. ADSMS, notification API, or to ServiceNow

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Descripción: El usuario ha eliminado su información de asignaturas Test sobre Debugging & Managing system performance, creado por Usuario eliminado el 14/09/2022.
Autor: Usuario eliminado
Idioma: English
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Historial: Creado el 14 sep 2022 · actualizado el 15 sep 2022
Etiquetas: el usuario ha eliminado su información de asignaturas

Debugging & Managing system performance

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