Hands-on support engineering portfolio focused on Azure and AWS troubleshooting, identity and access management, logging, and technical investigation.
This repository combines scenario-based troubleshooting with live exercises completed in Microsoft Azure and AWS lab environments.
I generated activity in Azure, routed Activity Log data into Log Analytics, and used KQL to isolate and investigate specific operations.
AzureActivity
| where TimeGenerated > ago(30m)
| where OperationNameValue contains "TAGS/WRITE"
| project TimeGenerated, ResourceGroup, OperationNameValue, ActivityStatusValue, Caller
| order by TimeGenerated desc- Azure Activity Log
- Log Analytics
- Kusto Query Language (KQL)
- Resource and configuration change investigation
- Failed deployment analysis
- Azure RBAC troubleshooting
- AWS CloudTrail
- Amazon CloudWatch Logs Insights
- AWS IAM authorization troubleshooting
- Microsoft Entra ID concepts
- Conditional Access
- MFA troubleshooting
- Device compliance
- Authentication strength
- Sign-in risk
- Guest / B2B access
- Enterprise application assignments
- Application roles
- Authentication vs. authorization
- Refresh-token and session troubleshooting
whereprojectcontainsago()order bytakesummarizecount()distinct- combined conditions with
and
A real S3 CreateBucket request was captured in CloudTrail first as an AccessDenied event and then as a successful event after correcting IAM permissions through a user group.
CloudWatch Logs Insights was used to isolate error messages from a support-oriented log stream.
fields @timestamp, @message
| filter @message like /ERROR/
| sort @timestamp desc
Scenario-based investigations involving authentication, Conditional Access, device compliance, MFA, sign-in risk, guest access, application assignments, and token behavior.
View Entra troubleshooting scenarios
Investigations involving RBAC authorization, resource deletion, configuration changes, and failed deployments.
View Azure Activity Log scenarios
Hands-on exercises performed using real Azure Activity Log data and Log Analytics.
The goal of these labs is not syntax memorization.
The focus is on using available evidence to:
- Identify what succeeded and what failed
- Separate authentication, authorization, configuration, and resource failures
- Narrow logs to the relevant events
- Identify the likely cause
- Determine the appropriate next troubleshooting step
Additional hands-on support engineering labs:
- Neon Grove API Support Lab - REST APIs, HTTP, JSON, authentication, headers, Postman, and troubleshooting scenarios.
- SQL Learning Lab - SQL-based SaaS support investigation, ticket triage, customer impact, and resolution analysis.
Live exercises were completed in a personal Microsoft Azure environment.
Sensitive account, subscription, or credential information is redacted where appropriate.



