Optimizely London Dev Meetup 2025 @ The Lighthouse
Wifi at the back of the room
Organized and Sponsored By
Meetup Agenda
18:30 – 18:50 :: Minesh Shah (Netcel) - Frontend Hosting With Optimizely
18:55 - 19:15 :: Tom Bramley (Optimizely) - Content Manager, AI translations, Opal and CMS 13
19:20 - 19:40 :: Scott Reed (Niteco) - Application Insights, Refining Data and View Logs
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19:40 - 20:10 :: BREAK
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20:10 - 20:30 :: Andrew Markham (UNRVLD) - Introduction to the new Opti Connect Platform
20:35 - 20:55 :: Jacob Pretorius (Niteco) – Edge Logs
22:00 - 22:20 :: Daniel Halse (Netcel) - Graph Integration with Configured Commerce
22:25 - 22:45 :: Jermey Brown (UNRVLD) - Laying the Foundation: PaaS CMS for Greenfield Projects
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Finish & Social :: Drinks + social nearby for anyone staying
Wifi at the back of the room
Application Insights, Refining Data and Viewing Logs �(In The Opti DXP)
Scott Reed
Presenters
Scott Reed
Solution Architect @
Optimizely Platinum MVP (since 2022)
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About Me
Agenda
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DXP & Application Insights Overview
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Optimizely DXP comes with Application Insights as default on Azure. Application Insights allow for application metrics to be collected from both the backend .NET and the frontend JavaScript layer. ��Using Application insight we can view, monitor and diagnose application performance, health and identify issues.
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DXP & Application Insights Overview
DXP & Application Insights Overview
Application Map + Customizing Application Insights Telemetry
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The Application Map allows you to see all the front end and backend dependency calls and explore slow calls in a graphical way.
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Useful for getting an understanding of all the core calls that are being made without digging around in logs
Useful for understanding the dependency tapestry of the application
Useful for seeing the core slowest calls easily
Application Map
By customizing the application insights metrics, we can
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Customizing Application Insights Telemetry
Inject SQL Queries information into SQL calls
Remove “Junk” data
Customize Log Levels
Disable Live Metrics
Inject extra data where needed
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Customizing Application Insights Telemetry
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Customizing Application Insights Telemetry
Startup configuration
Performance + Failures + Metrics + Raw Logs (KQL)
Using the performance section, we can see the performance of front end and backend operations and dependencies
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Performance
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Filter dataset to “Server” or “Browser” to look at either backend or front-end performance
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Filter the timing and the role (often to exclude the scheduler) or filter specific data that we want to focus on
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Use Average or focus on 99th percentile to see outliers and slow calls
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Switch secondary graph to correlate operations to requests, CPU, memory or storage
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Narrow down durations to focus on specific slow operations where profiler traces exist
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View operation details and drill into profiler traces and hot paths
Using the performance section code optimization feature we can see any recommended code Optimization. This can also be seen in the right pane when filtering
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Code Optimization
Within the failures section we can see any logged failures. These could be failed HTTP responses or errors from the backend or front-end
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Failures
View Exceptions
Drill into exception end to end details
View event details and call stack information
Metics will allow you to see information on several areas such as CPU, Memory, load times to help you identify issues
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Metrics
The log area contains the raw log information. The data is in tables customized to the Optimizely logger. The new interface is selectable but master KQL for real power
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Raw Logs
Note: Time ranges in this area are in UTC
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Connecting the Dots Between Metrics and Raw Logs – Finding Performance Issues
Navigate to the Monitoring -> Logs area and set the following KQL, replacing the INSTANCE with your noted instance. ��Also in the run area set the time frame in UTC to the 10 minute range noted above
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Connecting the Dots Between Metrics and Raw Logs – Extracting Buckets Info
Now navigate to Investigate -> Transaction Search��Set the filter Event Types = Request and in the search copy and of the id values from our list and search. You can then open the request and drill into dependency issues or profiler traces, in our case to see a slow Find quer
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Connecting the Dots Between Metrics and Raw Logs – Viewing Request Details
Other Features + Missing Features
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Dashboards can group information with specific filters for easier views
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Dashboards
*New Dashboard feature doesn’t seem to work on the DXP
Workbooks are a bit like PowerBi reports. You can create reports which allow drill in functions to view data on reported data
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Workbooks
There are some application insights features that would be great to have but we don’t get on the DXP
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Missing Features
Alerts / Automation
Create DevOps Tickets
Limited Dashboard Features
DXP Pass Portal Logs + Docker
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Q&A
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