To obtain the results in a dashboard I am using following things. 1.) First I created datamodel 2.) Datamodel I have used in macros which is running 1h and 1d basis. 3. pass those macros in saved search and collect the results in hourly and daily basis. 4. Results of the span_token is passing to macro from the below dashboard code. 5. As I am attaching macros and saved searches at the end of the dashboard code. Issue : I am not getting proper results by using this approach and dashboard is not populating results properly. I need gidance to fix the issue. ==================================================================== <form version="1.1" theme="light"> <label>Throughput : Highbay</label> <init> <set token="span_token">$form.span_token$</set> </init> <fieldset submitButton="false"></fieldset> <row> <panel> <input type="time" token="time" id="my_date_range" searchWhenChanged="true"> <label>Select the Time Range</label> <default> <earliest>-7d@h</earliest> <latest>now</latest> </default> <change> <eval token="time.earliest_epoch">if('earliest'="",0,if(isnum(strptime('earliest', "%s")),'earliest',relative_time(now(),'earliest')))</eval> <eval token="time.latest_epoch">if(isnum(strptime('latest', "%s")),'latest',relative_time(now(),'latest'))</eval> <eval token="macro_token">if($time.latest_epoch$ - $time.earliest_epoch$ &gt; 2592000, "throughput_macro_summary_1d",if($time.latest_epoch$ - $time.earliest_epoch$ &gt; 86400, "throughput_macro_summary_1h","throughput_macro_raw"))</eval> <eval token="form.span_token">if($time.latest_epoch$ - $time.earliest_epoch$ &gt; 2592000, "d", if($time.latest_epoch$ - $time.earliest_epoch$ &gt; 86400, "h", $form.span_token$))</eval> </change> </input> </panel> </row> <row> <panel> <chart> <title>Total Pallet</title> <search> <query>|`$macro_token$(span_token="$span_token$")` | search LocationQualifiedName="*/Aisle*Entry*" OR LocationQualifiedName="*/Aisle*Exit*" |strcat "raw" "," location group_name | timechart sum(count) as cnt by location</query> <earliest>$time.earliest$</earliest> <latest>$time.latest$</latest> </search> <option name="charting.chart">column</option> <option name="charting.chart.stackMode">stacked</option> <option name="charting.drilldown">none</option> <option name="refresh.display">progressbar</option> </chart> </panel> </row> <row> <panel> <chart> <title>Pallet IN</title> <search> <query>|`$macro_token$(span_token="$span_token$")` | search LocationQualifiedName="*/Aisle*Entry*" |strcat "raw" "," location group_name | timechart sum(count) as cnt by location</query> <earliest>$time.earliest$</earliest> <latest>$time.latest$</latest> </search> <option name="charting.chart">column</option> <option name="charting.chart.stackMode">stacked</option> <option name="charting.drilldown">none</option> <option name="refresh.display">progressbar</option> </chart> </panel> </row> <row> <panel> <chart> <title>Pallet OUT</title> <search> <query>|`$macro_token$(span_token="$span_token$")` | search LocationQualifiedName="*/Aisle*Exit*" |strcat "raw" "," location group_name | timechart sum(count) as cnt by location</query> <earliest>$time.earliest$</earliest> <latest>$time.latest$</latest> </search> <option name="charting.chart">column</option> <option name="charting.chart.stackMode">stacked</option> <option name="charting.drilldown">none</option> <option name="refresh.display">progressbar</option> </chart> </panel> </row> </form> ======================================= Macros: throughput_macro_raw(1) datamodel Walmart_throughput Highbay_throughput flat | bin _time span="$span_token$" | rename AsrTsuEventTrackingUpdate.LocationQualifiedName as LocationQualifiedName | table + _time LocationQualifiedName location date_hour date_mday date_minute date_month date_month date_second date_wday date_year throughput_macro_summary_1d(1) search index="tput_summary" sourcetype="tput_summary_1d" | bin _time span="$span_token$" | table + _time LocationQualifiedName location date_hour date_mday date_minute date_month date_month date_second date_wday date_year count throughput_macro_summary_1h(1) search index="tput_summary" sourcetype="tput_summary_1h" | bin _time span=$span_token$ | table + _time LocationQualifiedName location date_hour date_mday date_minute date_month date_month date_second date_wday date_year count saved searches: throughput_summary_index_1d | `throughput_macro_raw(span_token="1d")` |strcat "raw" "," location group_name |strcat "raw" "," location group_name | stats count by location _time LocationQualifiedName | collect index="tput_summary" sourcetype="tput_summary_1d" throughput_summary_index_1h | `throughput_macro_raw(span_token="1h")` |strcat "raw" "," location group_name | stats count by location _time LocationQualifiedName | collect index="tput_summary" sourcetype="tput_summary_1h"  

Hi AppDynamics Community, I'm integrating the AppDynamics Python Agent into a FastAPI project for monitoring purposes and have encountered a bit of a snag regarding log verbosity in my stdout. I'm launching my FastAPI app with the following command to include the AppDynamics agent: pyagent run -c appdynamics.cfg uvicorn my_app:app --reload My goal is to reduce the verbosity of the logs from both the AppDynamics agent and the proxy that are output to stdout, aiming to keep my console output clean and focused on more critical issues. My module versions: $ pip freeze | grep appdy appdynamics==23.10.0.6327 appdynamics-bindeps-linux-x64==23.10.0 appdynamics-proxysupport-linux-x64==11.64.3 Here's the content of my `appdynamics.cfg` configuration file: [agent] app = my-app tier = my-tier node = teste-local-01 [controller] host = my-controller.saas.appdynamics.com port = 443 ssl = true account = my-account accesskey = my-key [log] level = warning debugging = off I attempted to decrease the log verbosity further by modifying the `log4j.xml` file for the proxy to set the logging level to WARNING. However, this change didn't have the effect I was hoping for. The `log4j.xml` file I adjusted is located at: /tmp/appd/lib/cp311-cp311-63ff661bc175896c1717899ca23edc8f5fa87629d9e3bcd02cf4303ea4836f9f/site-packages/appdynamics_bindeps/proxy/conf/logging/log4j.xml Here are the adjustments I made to the `log4j.xml`: <appender class="com.singularity.util.org.apache.log4j.ConsoleAppender" name="ConsoleAppender"> <layout class="com.singularity.util.org.apache.log4j.PatternLayout"> <param name="ConversionPattern" value="%d{ABSOLUTE} %5p [%t] %c{1} - %m%n" /> </layout> <filter class="com.singularity.util.org.apache.log4j.varia.LevelRangeFilter"> <param name="LevelMax" value="FATAL" /> <param name="LevelMin" value="WARNING" /> </filter> Despite these efforts, I'm still seeing a high volume of logs from both the agent and proxy. Could anyone provide guidance or suggestions on how to effectively lower the log output to stdout for both the AppDynamics Python Agent and its proxy? Any tips on ensuring my changes to `log4j.xml` are correctly applied would also be greatly appreciated. Thank you in advance for your help! Example of logging messages I would like to remove from my stdout: 2024-03-23 11:15:28,409 [INFO] appdynamics.proxy.watchdog <22759>: Started watchdog with pid=22759 2024-03-23 11:15:28,409 [INFO] appdynamics.proxy.watchdog <22759>: Started watchdog with pid=22759 ... [AD Thread Pool-ProxyControlReq0] Sat Mar 23 11:15:51 BRT 2024[DEBUG]: JavaAgent - Setting AgentClassLoader as Context ClassLoader [AD Thread Pool-ProxyControlReq0] Sat Mar 23 11:15:52 BRT 2024[INFO]: JavaAgent - Low Entropy Mode: Attempting to swap to non-blocking PRNG algorithm [AD Thread Pool-ProxyControlReq0] Sat Mar 23 11:15:52 BRT 2024[INFO]: JavaAgent - UUIDPool size is 10 Agent conf directory set to [/home/wsl/.pyenv/versions/3.11.6/lib/python3.11/site-packages/appdynamics_bindeps/proxy/conf] ... 11:15:52,167 INFO [AD Thread Pool-ProxyControlReq0] BusinessTransactions - Starting BT Logs at Sat Mar 23 11:15:52 BRT 2024 11:15:52,168 INFO [AD Thread Pool-ProxyControlReq0] BusinessTransactions - ########################################################### 11:15:52,169 INFO [AD Thread Pool-ProxyControlReq0] BusinessTransactions - Using Proxy Version [Python Agent v23.10.0.6327 (proxy v23.10.0.35234) compatible with 4.5.0.21130 Python Version 3.11.6] 11:15:52,169 INFO [AD Thread Pool-ProxyControlReq0] JavaAgent - Logging set up for log4j2 ... 11:15:52,965 INFO [AD Thread Pool-ProxyControlReq0] JDBCConfiguration - Setting normalizePreparedStatements to true 11:15:52,965 INFO [AD Thread Pool-ProxyControlReq0] CallGraphConfigHandler - Call Graph Config Changed callgraph-granularity-in-ms Value -null