Thursday, February 12, 2026

Power Platfrom


  • Can you walk me through your overall IT experience and key projects?

  • What kind of Power BI solutions have you implemented end-to-end?

  • How have you used ADF (Azure Data Factory) in your projects?

  • What was your role in Power Apps and Power Automate implementations?

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Power BI – Core Skills

2️⃣ Power BI Desktop & Service

 

1️⃣ Difference between Power BI Desktop and Power BI Service

  • Power BI Desktop → Development tool (create reports, data models, DAX, transformations).

  • Power BI Service → Cloud platform (publish, share, collaborate, schedule refresh, governance).

2️⃣ Deployment Approach (Desktop → Service)

  • Develop & test report in Desktop

  • Validate data model & performance

  • Publish to Service Workspace

  • Configure Gateway (if on-prem data)

  • Set Scheduled Refresh

  • Apply RLS & Permissions

  • Promote to higher workspace (Dev → Test → Prod)

3️⃣ What are Workspaces? How do you manage access?

  • Workspaces → Collaboration containers for reports, dashboards & datasets

  • Used for Dev/Test/Prod separation

Access Roles:

  • Admin → Full control

  • Member → Edit & publish

  • Contributor → Publish only

  • Viewer → Read-only

Access managed via:

  • Azure AD security groups (preferred)

  • Direct user assignment

  • App-level access for business users

=========================================================

Power BI – Core Skills -

 Reports & Dashboards

1️⃣ How do you gather & translate business requirements into reports?

  • Conduct stakeholder workshops / interviews

  • Identify KPIs, metrics & business definitions

  • Understand data sources & refresh needs

  • Create mockups / wireframes

  • Define data model & relationships

  • Build iterative prototype → take feedback → refine

2️⃣ Difference between Report and Dashboard

  • Report → Multi-page, interactive, built in Power BI Desktop

  • Dashboard → Single-page summary, built in Power BI Service

  • Report = Detailed analysis

  • Dashboard = High-level snapshot (tiles from reports)

3️⃣ How do you optimize report performance?

  • Use Star Schema model

  • Remove unnecessary columns

  • Optimize DAX measures

  • Reduce visuals per page

  • Use Import mode when possible

  • Enable Aggregation tables

  • Monitor using Performance Analyzer

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Power BI – Core Skills

Data Import & Modeling

1️⃣ How do you handle data from multiple sources?

  • Connect using Power Query

  • Perform data cleansing & transformation

  • Standardize formats (date, currency, keys)

  • Create common keys for joins

  • Merge/Append queries as needed

  • Build a centralized data model

  • Validate data consistency before publishing

2️⃣ Relationships: One-to-Many vs Many-to-Many

  • One-to-Many (1:*)

    • One unique value in parent table

    • Multiple related rows in child table

    • Example: Customer → Orders

    • Most recommended & efficient

  • Many-to-Many (:)

    • Multiple matches on both sides

    • Example: Students ↔ Courses

    • Requires bridge table for better performance

3️⃣ What is Star Schema? Have you implemented it?

  • Data modeling approach with:

    • Fact table (transactions, measures)

    • Dimension tables (Customer, Date, Product)

  • Fact table at center → dimensions around it (star shape)

  • Improves performance & clarity

  • Yes, implemented in multiple Power BI projects for optimized reporting and scalable models.

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Power BI – Core Skills

 DAX (Calculated Columns & Measures)

1️⃣ Difference between Calculated Column and Measure

  • Calculated Column

    • Computed row by row

    • Stored in the model (increases size)

    • Used for relationships / categorization

  • Measure

    • Calculated at query time

    • Depends on filter context

    • Used for aggregations (SUM, COUNT, YTD, etc.)

    • More memory efficient

2️⃣ Context in DAX

  • Row Context

    • Calculation happens per row

    • Exists in calculated columns

    • Example: Sales[Qty] * Sales[Price]

  • Filter Context

    • Applied by slicers, filters, visuals

    • Measures respond dynamically

    • Modified using CALCULATE()

👉 CALCULATE() transforms filter context.

3️⃣ DAX for YTD Calculation

Sales YTD = 
TOTALYTD(
    SUM(Sales[Amount]),
    'Date'[Date]
)

OR using CALCULATE:

Sales YTD = 
CALCULATE(
    SUM(Sales[Amount]),
    DATESYTD('Date'[Date])
)

4️⃣ How do you optimize DAX performance?

  • Use Star Schema

  • Avoid unnecessary calculated columns

  • Use variables (VAR) in measures

  • Prefer measures over calculated columns

  • Reduce use of complex iterators (e.g., SUMX)

  • Optimize relationships (1:* preferred)

  • Monitor with Performance Analyzer

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6️⃣ Visualizations

1️⃣ When do you use Matrix vs Table?

  • Table

    • Flat structure (rows & columns)

    • No grouping or hierarchy

    • Used for detailed transaction-level data

  • Matrix

    • Supports row/column grouping

    • Enables hierarchies & subtotals

    • Used for summary reports (e.g., Year → Month → Product)

👉 Use Matrix for analysis, Table for raw details.

2️⃣ How do slicers impact performance?

  • Each slicer adds filter context

  • Multiple slicers increase query complexity

  • High-cardinality fields (e.g., Customer ID) slow performance

  • Sync slicers across pages can increase load time

Best Practice:

  • Use low-cardinality fields

  • Limit number of slicers per page

  • Avoid unnecessary cross-filtering

3️⃣ What is Drill-through & how is it implemented?

  • Drill-through → Navigate from summary page to detailed page based on selected value.

Implementation Steps:

  1. Create a new detail page

  2. Add a field to Drill-through filter pane

  3. Design detailed visuals

  4. Right-click value → Select Drill-through page

👉 Used for deep analysis without cluttering main report

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Power BI – Core Skills

 Maps & Filters

1️⃣ Difference between Filled Map and Shape Map

Image

Image

Image

Image

  • Filled Map

    • Uses Bing Maps (online)

    • Best for country/state/city level data

    • Auto-detects geographic fields

    • Requires internet

  • Shape Map

    • Uses custom TopoJSON files

    • Best for custom regions (sales territories, zones)

    • Works offline

    • More flexible for non-standard boundaries

👉 Use Filled Map for standard geo data, Shape Map for custom regions.

2️⃣ Page-level vs Report-level vs Visual-level Filters

  • Visual-level Filter

    • Applies to only one visual

    • Used for specific chart control

  • Page-level Filter

    • Applies to all visuals on that page

  • Report-level Filter

    • Applies to entire report (all pages)

👉 Scope increases from Visual → Page → Report.

3️⃣ Have you implemented Drill-down and Drill-through together?

Yes.

  • Drill-down → Navigate within same visual (Year → Quarter → Month)

  • Drill-through → Navigate to another detailed page

Used together for:

  • Hierarchical analysis (drill-down)

  • Detailed investigation (drill-through)

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Power BI – Core Skills

Time Intelligence (YTD, MTD, QTD, YOY)

1️⃣ How do you create YTD / YOY Growth measures?

YTD Measure

Sales YTD =
TOTALYTD(
    SUM(Sales[Amount]),
    'Date'[Date]
)

Last Year Sales

Sales LY =
CALCULATE(
    SUM(Sales[Amount]),
    SAMEPERIODLASTYEAR('Date'[Date])
)

YOY Growth %

YOY Growth % =
DIVIDE(
    [Sales] - [Sales LY],
    [Sales LY]
)

👉 Use a proper Date table connected to fact table.

2️⃣ What is SAMEPERIODLASTYEAR?

  • Returns the same date range from previous year

  • Used inside CALCULATE()

  • Enables Year-over-Year comparison

  • Works only with a continuous Date table

3️⃣ Issues if Date table is not marked properly?

  • Time intelligence functions won’t work correctly

  • YTD / YOY calculations may return incorrect values

  • Missing dates cause gaps in trends

  • Errors in filter context behavior

👉 Always:

  • Create a separate Date dimension

  • Ensure no missing dates

  • Mark as Date Table in model view

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Power BI – Core Skills

 Publishing & Sharing

1️⃣ Steps to publish report to Power BI Service

  • Finalize report in Power BI Desktop

  • Click Publish

  • Select target Workspace

  • Validate dataset & report in Service

  • Configure Gateway (if needed)

  • Set Scheduled Refresh

  • Apply RLS & permissions

  • Share via App or direct access

2️⃣ What are Gateways? When are they required?

  • Gateway = Secure bridge between on-premises data and Power BI Service

  • Required when data source is:

    • SQL Server (on-prem)

    • Excel on local server

    • Any on-prem database

Not required for:

  • Cloud sources (Azure SQL, SharePoint Online, etc.)

👉 Enables scheduled refresh & live connection.

3️⃣ Difference between App and Workspace sharing

  • Workspace Sharing

    • Direct access to users

    • Used for developers / internal team

    • Users see full workspace content (based on role)

  • App Sharing

    • Published from workspace

    • Used for business users

    • Controlled & read-only access

    • More secure & scalable

👉 Workspace = Collaboration
👉 App = Controlled distribution

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Power BI – Core Skills

Advanced Formatting

1️⃣ How do you implement Conditional Formatting?

  • Select visual → Go to Format pane

  • Choose field → Click fx (Conditional formatting)

  • Apply based on:

    • Rules (e.g., >100 = Green)

    • Field value (color from DAX measure)

    • Color scale

  • Can apply to:

    • Background color

    • Font color

    • Data bars

    • Icons

👉 Best practice: Use DAX measure for dynamic logic.

2️⃣ What are Tooltip Pages?

  • Custom report pages shown on hover

  • Used to display additional details without clutter

  • Steps:

    • Create new page

    • Enable Tooltip = On

    • Set page size → Tooltip

    • Assign page under visual → Tooltip section

👉 Improves UX & detailed insights.

3️⃣ How do you implement Dynamic Titles?

Create a DAX measure:

Dynamic Title =
"Sales Report - " & SELECTEDVALUE('Date'[Year], "All Years")

Then:

  • Select visual → Title → Click fx

  • Bind title to the measure

👉 Title changes based on slicer/filter selection.

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Power Apps (Canvas & Model-Driven)

1️⃣1️⃣ Canvas Apps

1️⃣ Difference between Canvas App and Model-Driven App

  • Canvas App

    • UI-first approach (drag & drop design)

    • Full control over layout

    • Connects to multiple data sources

    • Best for custom UI & task-based apps

  • Model-Driven App

    • Data-first approach (Dataverse-driven)

    • Auto-generated UI

    • Based on tables, forms, views

    • Best for complex business processes

👉 Canvas = Flexible UI
👉 Model-Driven = Structured enterprise apps

2️⃣ How do you connect Power Apps to SharePoint / Dataverse?

  • Go to Data → Add Data Source

  • Select:

    • SharePoint → Provide site URL → Choose list

    • Dataverse → Select tables directly

  • Use formulas like:

    • Patch()

    • Collect()

    • Filter()

    • LookUp()

3️⃣ What is Delegation?

  • Delegation = Processing data at data source level instead of locally

  • Improves performance

  • Avoids 500/2000 record limit issue

  • Non-delegable functions cause warning (blue underline)

👉 Always use delegable functions when working with large data.

4️⃣ How do you handle large datasets?

  • Use Delegation-friendly queries

  • Apply indexed columns (SharePoint)

  • Use Dataverse for enterprise-scale data

  • Filter data early (server-side)

  • Avoid loading full dataset into collections

  • Implement pagination / lazy loading

👉 Optimize data at source, not in app.

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Power Apps (Canvas & Model-Driven)

Model-Driven Apps

1️⃣ When would you choose Model-Driven App over Canvas?

  • When using Dataverse as primary data source

  • Complex business processes & relationships

  • Need for security roles & governance

  • Standardized UI is acceptable

  • Enterprise-scale applications

👉 Choose Model-Driven for process-driven, data-centric apps.

2️⃣ Business Rules vs Plugins

Business Rules

  • No-code / low-code

  • Runs on form (client-side & server-side basic logic)

  • Used for validations, field visibility, required fields

  • Limited complexity

Plugins

  • Written in C#

  • Server-side execution

  • Handles complex validations & integrations

  • Runs on Create / Update / Delete events

👉 Business Rules = Simple logic
👉 Plugins = Complex backend logic

3️⃣ What is a Solution in Power Platform?

  • A Solution is a container for components:

    • Apps

    • Tables

    • Flows

    • Plugins

    • Security roles

  • Used for:

    • ALM (Dev → Test → Prod)

    • Deployment & version control

  • Types:

    • Managed

    • Unmanaged

👉 Solution = Packaging & deployment mechanism.

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Power Apps (Canvas & Model-Driven)

 Inventory Management App

1️⃣ What was the Architecture?

Power Platform-based architecture:

  • Model-Driven App → Inventory operations (Create/Update stock)

  • Dataverse → Tables (Products, Stock, Vendors, Transactions)

  • Power Automate → Approval workflows & notifications

  • Plugins (C#) → Stock validation & business rules

  • Power BI → Inventory analytics dashboard

👉 Scalable, secure, and fully integrated within Power Platform.

2️⃣ How did you manage Roles & Security?

  • Used Dataverse Security Roles

    • Admin → Full access

    • Inventory Manager → Create/Approve

    • Store User → Read/Update limited

  • Implemented:

    • Role-based access control (RBAC)

    • Business Unit-level security

    • Field-level security (for cost fields)

    • Row-level security where required

👉 Ensured least-privilege access model.

3️⃣ Did you implement Approvals?

Yes.

  • Used Power Automate Approval flow

  • Triggered on:

    • Stock request above threshold

    • Purchase order creation

  • Multi-level approval:

    • Supervisor → Finance → Admin

  • Email & Teams notifications enabled

  • Status updated automatically in Dataverse

👉 Fully automated approval lifecycle integrated with app.

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Power Automate

1️⃣4️⃣ Workflow Creation

1️⃣ Difference between Instant, Automated, and Scheduled Flows

  • Instant Flow

    • Triggered manually (button click)

    • Used for ad-hoc tasks

    • Example: Send report on demand

  • Automated Flow

    • Triggered by an event

    • Example: When item is created in SharePoint

  • Scheduled Flow

    • Runs at fixed intervals

    • Example: Daily data sync at 8 AM

👉 Instant = Manual
👉 Automated = Event-based
👉 Scheduled = Time-based

2️⃣ How do you handle error handling in flows?

  • Use Scope actions (Try–Catch pattern)

  • Configure Run After settings

  • Use Terminate action for controlled failure

  • Log errors into:

    • SharePoint / Dataverse table

  • Send failure notifications (Email/Teams)

  • Enable retry policies for transient failures

👉 Always design flows with controlled failure handling.

3️⃣ What are Concurrency Controls?

  • Controls how many flow runs execute simultaneously

  • Helps prevent:

    • Duplicate processing

    • Data conflicts

  • Configured in:

    • Trigger settings → Concurrency Control

  • Can limit to 1 run at a time for sequential processing

👉 Used for data consistency & performance control.

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Power Automate

Approval Flows

1️⃣ How do you implement Multi-Stage Approvals?

  • Use Power Automate → Start and wait for an approval

  • Design sequential stages:

    • Stage 1 → Manager

    • Stage 2 → Finance

    • Stage 3 → Admin

  • Use Condition after each approval

  • Proceed only if status = Approved

  • Update status field in Dataverse/SharePoint after each stage

👉 Can be Sequential or Parallel approvals based on business need.

2️⃣ How do you store Approval History?

  • Create an Approval History table/list (Dataverse/SharePoint)

  • Store:

    • Request ID

    • Approver name

    • Decision (Approve/Reject)

    • Comments

    • Timestamp

  • Use Append record action after each approval stage

👉 Ensures audit trail & reporting capability.

3️⃣ How do you handle Delegation in Approvals?

  • Use built-in Reassign option in approval email

  • Configure Alternate approver logic in flow

    • Check Out-of-Office

    • Use backup approver field

  • Maintain delegation mapping table (Manager → Delegate)

  • Dynamically route approval using lookup

👉 Ensures business continuity during leave/unavailability.

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SharePoint Online

1️⃣6️⃣ Office Tenant Setup

1️⃣ Steps involved in setting up an Office 365 Tenant

  • Register tenant via Microsoft 365 Admin Center

  • Verify custom domain

  • Configure:

    • Users & Groups

    • Licenses

    • Security policies (MFA)

  • Setup SharePoint Online, Teams, Exchange

  • Configure:

    • Conditional Access

    • Data Loss Prevention (DLP)

  • Create governance & naming conventions

👉 Foundation: Identity, Security, Compliance first.

2️⃣ How do you manage User Roles & Licenses?

  • Create users in Azure AD / Entra ID

  • Assign:

    • Admin roles (Global, SharePoint, etc.)

    • Security groups

  • Assign licenses:

    • Microsoft 365 E3/E5

    • Power BI Pro

    • Power Apps/Automate

  • Use Group-based licensing (best practice)

  • Review access periodically

👉 Follow least-privilege principle.

3️⃣ Best Practices for Governance

  • Define naming conventions

  • Use Security Groups instead of individual users

  • Implement MFA & Conditional Access

  • Setup DLP policies

  • Control external sharing

  • Monitor via Audit Logs

  • Maintain Dev/Test/Prod environments

👉 Governance = Security + Control + Standardization.

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SharePoint Online

Team Sites & Communication Sites

1️⃣ Difference between Team Site and Communication Site

  • Team Site

    • Collaboration-focused

    • Connected to Microsoft 365 Group

    • Used by internal team (documents, tasks, lists)

    • Members can contribute content

  • Communication Site

    • Broadcast-focused

    • Not group-connected (by default)

    • Used for announcements, news, policies

    • Mostly read-only for users

👉 Team Site = Collaboration
👉 Communication Site = Information sharing

2️⃣ How do you manage Permissions?

  • Use SharePoint Groups:

    • Owners (Full Control)

    • Members (Edit)

    • Visitors (Read)

  • Prefer Security Groups (Azure AD)

  • Avoid item-level permissions (performance impact)

  • Break inheritance only when necessary

  • Periodic access review

👉 Follow least privilege & group-based access.

3️⃣ What are Site Features and List Features?

  • Site Features

    • Enable functionality at site level

    • Example: Publishing, Document ID service

  • List Features

    • Enable functionality at list/library level

    • Example: Versioning, Content Types

👉 Features extend capabilities at different scopes.

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SharePoint Online

SharePoint Workflows & Libraries

1️⃣ How do you create Document Libraries?

  • Go to Site Contents

  • Click New → Document Library

  • Provide name & description

  • Configure:

    • Columns (metadata)

    • Versioning settings

    • Permissions (if needed)

  • Enable content types (if required)

👉 Best practice: Use metadata instead of folders.

2️⃣ What are Content Types?

  • Reusable collection of:

    • Columns (metadata)

    • Document templates

    • Workflows

  • Used to standardize document structure

  • Can be created at:

    • Site level (recommended)

    • Library level

👉 Example: Invoice, Contract, Policy (each with different metadata).

3️⃣ How do you manage Versioning?

  • Go to Library Settings → Versioning Settings

  • Enable:

    • Major versions (1.0, 2.0)

    • Major & Minor versions (Drafts)

  • Set version limit (e.g., keep last 50)

  • Enable Require Check-in/Check-out (if needed)

👉 Versioning ensures document history & audit tracking.

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Data Integration (ADF)

1️⃣9️⃣ Azure Data Factory

1️⃣ What is a Pipeline in Azure Data Factory?

  • A Pipeline is a logical grouping of activities

  • Used to orchestrate:

    • Data movement

    • Data transformation

    • Control flow tasks

  • Can include:

    • Copy Activity

    • Data Flow

    • Stored Procedures

    • Web/Custom activities

👉 Pipeline = Workflow orchestration in ADF.

2️⃣ Difference between Copy Activity and Data Flow

  • Copy Activity

    • Moves data from Source → Destination

    • No complex transformation

    • Fast & lightweight

    • Used for ETL data movement

  • Data Flow

    • Performs transformations

    • Data cleansing, joins, aggregations

    • Runs on Spark cluster

    • Used for complex ETL logic

👉 Copy = Move data
👉 Data Flow = Transform data

3️⃣ How do you schedule Pipelines?

  • Create a Trigger

    • Schedule trigger (time-based)

    • Tumbling window trigger

    • Event-based trigger

  • Configure:

    • Start date & time

    • Frequency (Hourly/Daily/etc.)

  • Publish changes

👉 Trigger controls pipeline execution timing.

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Soft Skills

2️⃣0️⃣ Communication & Team Skills

1️⃣ Tell me about a challenging stakeholder

  • Stakeholder had unclear & changing KPIs

  • Conducted focused requirement workshop

  • Created mockups & data definitions document

  • Set clear sign-off checkpoints

  • Result: Reduced rework & improved trust

👉 Key: Clear communication + structured approach.

2️⃣ How do you handle requirement changes?

  • Assess impact on scope, timeline, effort

  • Discuss trade-offs with stakeholders

  • Update BRD / user stories

  • Get formal approval before implementation

  • Follow change control process

👉 Control scope, avoid scope creep.

3️⃣ Have you worked independently in client-facing roles?

Yes.

  • Managed end-to-end delivery

  • Conducted client meetings & demos

  • Handled requirement gathering & UAT

  • Provided post-production support

👉 Comfortable in independent & ownership-driven roles.

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1️⃣ Power BI report is slow — How do you troubleshoot?

  • Use Performance Analyzer to identify slow visuals

  • Check data model (Star Schema?)

  • Remove unnecessary columns & relationships

  • Optimize DAX (avoid heavy iterators like SUMX)

  • Reduce visuals per page

  • Check cardinality & relationship direction

  • Validate Import vs DirectQuery mode

👉 80% issues come from poor data modeling.

2️⃣ Power Apps hitting delegation limit — What do you do?

  • Identify non-delegable functions (blue underline)

  • Replace with delegable alternatives

  • Filter at data source level

  • Use indexed columns (SharePoint)

  • Move large data to Dataverse if needed

  • Avoid loading full dataset into collections

👉 Always push logic to server-side processing.

3️⃣ Approval flow is stuck — How do you debug?

  • Check Run History in Power Automate

  • Identify failed action

  • Verify:

    • Trigger condition

    • Approval response pending?

    • Expired approval?

  • Check Run After settings

  • Validate connectors & permissions

  • Add logging (Compose / Scope blocks)

👉 Debug from trigger → each action step-by-step.

4️⃣ Users complain about incorrect YOY numbers — What will you check?

  • Is the Date table marked properly?

  • Is relationship active between Date & Fact?

  • Are there missing dates?

  • Check SAMEPERIODLASTYEAR() logic

  • Verify filter context (slicers applied?)

  • Validate base measure logic

👉 Most issues come from improper date model.

5️⃣ SharePoint permissions broken inheritance — How do you fix?

  • Go to Library/List → Manage Access

  • Identify unique permissions

  • Decide:

    • Restore inheritance (recommended)

    • Or reconfigure correctly

  • Remove direct user permissions

  • Assign access via SharePoint groups / Azure AD groups

  • Audit access periodically

👉 Avoid excessive item-level permission breaks (performance risk).

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Based on your profile (Power BI + Power Apps + Power Automate + SharePoint + ADF), here are technical deep-dive questions only — senior level:

🔹 Power BI – Advanced

1️⃣ Explain VertiPaq engine and how compression works

  • VertiPaq is an in-memory columnar storage engine (used in Import mode).

  • Stores data column-wise, enabling high compression.

  • Compression techniques:

    • Dictionary Encoding (unique values stored once)

    • Value Encoding (small integers instead of original values)

    • Run-Length Encoding (RLE) (compress repeated values)

  • Data split into segments (~1M rows each).

  • Low-cardinality columns compress best.

👉 Smaller model size = Faster Storage Engine scans.

2️⃣ Difference between Storage Engine vs Formula Engine

Storage Engine (SE)

  • Scans compressed data

  • Multi-threaded

  • Handles basic aggregations (SUM, COUNT)

  • Very fast

Formula Engine (FE)

  • Executes DAX logic

  • Single-threaded

  • Handles iterators, complex logic

  • Can be performance bottleneck

👉 Optimize DAX to push work to Storage Engine, reduce FE workload.

3️⃣ How does CALCULATE() modify filter context internally?

  • Captures existing filter context

  • Performs context transition (if row context exists)

  • Adds/replaces/removes filters

  • Reevaluates expression in new filter context

Internally:

  1. Evaluate filter arguments

  2. Modify filter context

  3. Recalculate expression

👉 CALCULATE() = Core filter context modifier in DAX.

4️⃣ Explain Context Transition with example

Context transition = Converting row context → filter context.

Example:

Total Sales =
SUMX(Sales, Sales[Qty] * Sales[Price])

SUMX creates row context.

If inside a calculated column:

Measure =
CALCULATE(SUM(Sales[Amount]))

CALCULATE() converts current row context into filter context.

👉 Happens when CALCULATE() is used inside row context.

5️⃣ When would you use USERELATIONSHIP()?

  • When model has multiple relationships between same tables.

  • One active, others inactive.

  • Used to activate inactive relationship temporarily inside measure.

Example:

  • Order Date (active)

  • Ship Date (inactive)

Sales by Ship Date =
CALCULATE(
    SUM(Sales[Amount]),
    USERELATIONSHIP(Sales[ShipDate], Date[Date])
)

👉 Useful for role-playing date dimensions.

6️⃣ How do you debug complex DAX performance issues?

  • Use Performance Analyzer

  • Use DAX Studio

    • Check query plan

    • Server timings (SE vs FE time)

  • Look for:

    • Heavy iterators (SUMX, FILTER)

    • High cardinality columns

    • Bidirectional relationships

  • Optimize:

    • Star schema

    • Reduce calculated columns

    • Use variables (VAR)

👉 Identify whether bottleneck is SE or FE.

7️⃣ Difference between Import vs DirectQuery vs Composite (Internals)

Import

  • Data stored in VertiPaq (in-memory)

  • Fastest performance

  • Refresh required

DirectQuery

  • Queries source at runtime

  • No data stored

  • Performance depends on source DB

  • Limited DAX support

Composite

  • Mix of Import + DirectQuery

  • Supports Aggregations

  • More flexible but complex model

👉 Import = Performance
👉 DirectQuery = Real-time
👉 Composite = Hybrid optimization

8️⃣ How does Bidirectional filtering impact performance?

  • Filters propagate both directions

  • Increases filter propagation paths

  • Can create ambiguity & circular dependencies

  • Forces more FE processing

👉 Use only when necessary (e.g., many-to-many).
Default should be Single direction (1:*).

9️⃣ Explain Aggregation Tables implementation

Used to improve performance for large datasets.

Steps:

  1. Create aggregated summary table (e.g., Sales by Month)

  2. Import it into model

  3. Configure Manage Aggregations

  4. Map aggregation table to detail table

  5. Set storage mode correctly

When query matches aggregation level → Uses aggregated table
Else → Falls back to detailed table.

👉 Reduces scan size drastically.

🔟 How do you implement Incremental Refresh with partitions?

Steps:

  1. Create RangeStart & RangeEnd parameters

  2. Apply filter on date column

  3. Configure Incremental Refresh policy:

    • Store last X years

    • Refresh last X days/months

  4. Publish to Service

  5. Service creates partitions automatically

Benefits:

  • Only refresh recent data

  • Historical partitions remain untouched

  • Improves refresh performance

👉 Enterprise-level optimization for large datasets.

================================================================

================================================================

🔹 Power Apps – Advanced

1️⃣ Explain Delegation architecture internally

  • Power Apps sends delegable queries to data source (SQL, Dataverse, SharePoint).

  • Query translated into OData/SQL.

  • Filtering, sorting, aggregation executed server-side.

  • Only result set returned to client.

  • Non-delegable functions → processed client-side (500/2000 record limit).

👉 Delegation = Push computation to data source to avoid local limits.

2️⃣ How does Power Apps handle data caching & collection memory limits?

  • Data is cached temporarily in:

    • Collections

    • Local variables

  • Collections stored in device memory (browser/mobile RAM).

  • No fixed hard limit, but performance degrades with large collections.

  • Large datasets increase:

    • App load time

    • Memory consumption

    • Formula recalculation time

👉 Best practice: Avoid loading full datasets into collections.

3️⃣ Difference between Patch vs SubmitForm vs UpdateIf (Performance)

Patch()

  • Direct record update

  • More flexible

  • Faster for single-record updates

  • Best for custom forms

SubmitForm()

  • Works with EditForm control

  • Handles validation automatically

  • Slight overhead due to form lifecycle

UpdateIf()

  • Updates multiple records

  • Often non-delegable

  • Can cause performance issues on large datasets

👉 Patch = Most efficient & flexible.

4️⃣ How do you design apps for 10k+ records scalability?

  • Use delegable functions only

  • Filter at source (avoid Collect full dataset)

  • Use Dataverse over SharePoint

  • Use indexed columns

  • Implement pagination / lazy loading

  • Reduce controls in galleries

  • Avoid heavy formulas inside gallery items

👉 Server-side filtering + lightweight UI.

5️⃣ How do you secure Dataverse data at row & column level?

Row-Level Security

  • Use Security Roles

  • Business Units

  • Ownership-based access

  • Teams for group-level access

Column-Level Security

  • Enable Field Security Profile

  • Assign profile to specific users/teams

👉 Dataverse security enforced server-side (not app-level).

6️⃣ Explain Component Library usage in enterprise apps

  • Centralized reusable UI components

  • Shared across multiple apps

  • Ensures:

    • UI consistency

    • Maintainability

    • Version control

  • Updates in component library propagate to dependent apps

👉 Essential for enterprise governance & standardization.

7️⃣ How do you implement role-based UI rendering dynamically?

  • Store user role in:

    • Dataverse table OR

    • Use User().Email lookup

  • On App start:

    Set(varUserRole, LookUp(Roles, Email = User().Email).Role)

  • Use conditional visibility:

    Visible = varUserRole = "Admin"

👉 UI hides elements, but security must be enforced in Dataverse.

8️⃣ How do you optimize slow OnStart formulas?

  • Avoid heavy data loading in OnStart

  • Move logic to OnVisible of screens

  • Use Concurrent() for parallel calls

  • Load only required data

  • Avoid nested LookUps

  • Cache only filtered data

Example:

Concurrent(
   ClearCollect(colProducts, Filter(Products, Status="Active")),
   ClearCollect(colUsers, Users)
)

👉 Keep OnStart lightweight; load data lazily.


🔹 Power Automate – Advanced

1️⃣ Explain Run-After configuration & Parallel branches execution model

Run-After

  • Defines execution dependency between actions.

  • Can run after:

    • Success

    • Failure

    • Skipped

    • Timed out

  • Used to build Try–Catch–Finally pattern with Scopes.

Parallel Branches

  • Multiple actions run simultaneously.

  • Engine executes branches independently.

  • Flow waits until all parallel branches complete (unless terminated).

👉 Useful for performance optimization & controlled error handling.

2️⃣ What happens internally when Concurrency is enabled?

  • Multiple flow instances run in parallel threads.

  • Trigger processes multiple events simultaneously.

  • Risk:

    • Data conflicts

    • Duplicate updates

  • If set to 1 → Sequential processing (FIFO behavior).

👉 Concurrency improves speed but must be controlled for data consistency.

3️⃣ How do you design Idempotent flows?

Idempotent = Same input processed multiple times → Same result.

Techniques:

  • Use Unique ID check before insert

  • Maintain processed flag/status

  • Use Upsert logic instead of create

  • Store transaction logs

  • Avoid blind duplicate writes

👉 Prevents duplicate records during retries.

4️⃣ Difference between Child Flow vs Solution-Aware Flow

Child Flow

  • Reusable flow triggered by another flow

  • Requires Solution

  • Uses “Run a Child Flow” action

  • Helps modular architecture

Solution-Aware Flow

  • Created inside a Solution

  • Supports ALM (Dev → Test → Prod)

  • Can use connection references

  • Required for enterprise deployments

👉 Child flow = Reusable module
👉 Solution-aware = ALM-ready deployment

5️⃣ How do you handle API Throttling (429 errors)?

  • Enable Retry Policy (Exponential backoff)

  • Reduce concurrency

  • Add Delay between calls

  • Batch operations where possible

  • Use pagination properly

  • Monitor connector limits

👉 Respect API limits to avoid throttling loops.

6️⃣ How do you implement Transaction Rollback pattern?

Power Automate doesn’t support true transactions, so:

  • Use Scope (Try)

  • Track created record IDs

  • On failure:

    • Trigger Compensating actions

    • Delete/undo previously created records

  • Maintain transaction log table

👉 Implement compensating logic manually.

7️⃣ How to secure sensitive data in flow run history?

  • Enable Secure Inputs/Outputs in action settings

  • Use Azure Key Vault for secrets

  • Avoid storing passwords in variables

  • Use connection references

  • Restrict flow run history access via security roles

👉 Secure at connector + action + environment level.

================================================================

================================================================

🔹 SharePoint Online – Advanced

1️⃣ Explain Permission Inheritance Model Architecture

  • SharePoint follows a hierarchical security model:

    • Site Collection

    • Site

    • Library/List

    • Folder

    • Item

  • By default, permissions inherit from parent.

  • Breaking inheritance creates unique security scope.

  • Each unique scope increases:

    • Permission checks

    • Performance overhead

👉 Best practice: Use group-based permissions, avoid excessive item-level breaks.

2️⃣ How does SharePoint handle Large Lists (>5000 items) internally?

  • Uses List View Threshold (5000 items) to prevent heavy SQL queries.

  • Data stored in SQL Azure backend.

  • Queries must use indexed columns to avoid full table scans.

  • If query exceeds threshold → blocked unless indexed.

  • Supports:

    • Indexed filtering

    • Folder partitioning

    • Modern UI optimized queries

👉 Threshold protects database performance.

3️⃣ What are Indexed Columns and how do they improve performance?

  • Indexed column = SQL index on a list column.

  • Improves:

    • Filter queries

    • Sorting

    • Lookup performance

  • Prevents full table scan.

  • Required when list >5000 items.

👉 Always index frequently filtered columns.

4️⃣ Difference between Site Collection Admin vs Site Owner

Site Collection Admin

  • Full control across entire site collection

  • Cannot be restricted

  • Manages features & global settings

Site Owner

  • Full control only for that specific site

  • Subject to inheritance limits

  • Cannot override collection-level settings

👉 Site Collection Admin = Highest privilege.

5️⃣ Explain Modern vs Classic Page Rendering Architecture

Classic

  • ASP.NET-based

  • Server-side rendering

  • Uses Master Pages & Page Layouts

  • Heavy customization (JSLink)

Modern

  • Client-side rendering (SPFx-based)

  • React-based components

  • Faster & responsive

  • No master page dependency

  • Better performance & mobile support

👉 Modern architecture is lightweight & cloud-optimized.

6️⃣ How do you migrate large libraries with metadata preservation?

  • Use:

    • SharePoint Migration Tool (SPMT)

    • Migration Manager

    • PowerShell (PnP)

  • Ensure:

    • Content types pre-created

    • Columns mapped correctly

  • Migrate in batches

  • Preserve:

    • Metadata

    • Version history

    • Permissions (if required)

  • Validate post-migration with audit checks

👉 Plan schema first, migrate data next.

================================================================

================================================================

🔹 Azure Data Factory – Advanced

1️⃣ How does Integration Runtime (IR) work? (Azure vs Self-hosted)

Integration Runtime = Compute infrastructure used by ADF to move & transform data.

Azure IR

  • Fully managed by Microsoft

  • Used for:

    • Cloud-to-cloud data movement

    • Data Flow (Spark execution)

  • Auto-scales

  • No infrastructure management

Self-hosted IR

  • Installed on on-prem server/VM

  • Used for:

    • On-prem → Cloud data movement

    • Private network access

  • Maintains secure outbound connection to Azure

  • Requires maintenance & monitoring

👉 Azure IR = Cloud-native
👉 Self-hosted IR = Hybrid connectivity

2️⃣ Explain Mapping Data Flow execution architecture (Spark clusters)

  • Built on Azure Databricks / Spark engine

  • Executes on:

    • Ephemeral Spark clusters

  • Steps:

    1. ADF provisions Spark cluster

    2. Data loaded into Spark memory

    3. Transformations executed (Join, Aggregate, Derived Column)

    4. Results written to sink

  • Cluster auto-terminates after execution

👉 Distributed processing → Handles big data transformations.

3️⃣ Difference between Tumbling Window vs Schedule Trigger

Schedule Trigger

  • Time-based (e.g., daily at 8 AM)

  • Independent executions

  • No dependency between runs

Tumbling Window Trigger

  • Time-sliced windows (fixed intervals)

  • Each window depends on previous completion

  • Ensures:

    • No data overlap

    • No missing window

👉 Tumbling Window = Reliable incremental loads
👉 Schedule = Simple time trigger

4️⃣ How do you implement Incremental Load (Watermarking)?

Steps:

  1. Maintain watermark column (LastModifiedDate or ID)

  2. Store last processed value in:

    • Control table OR

    • Pipeline parameter

  3. Source query:

    WHERE LastModifiedDate > @LastWatermark

  4. After successful load → Update watermark value

  5. Handle late-arriving data if needed

👉 Efficient delta loading without full refresh.

5️⃣ How do you handle Pipeline Failure Recovery?

  • Enable Retry policies

  • Use:

    • On Failure path

    • Alert notifications

  • Log errors into monitoring table

  • Implement:

    • Checkpointing logic

    • Idempotent design

  • Use Tumbling Window for guaranteed sequential execution

👉 Design for restartability & idempotency.

6️⃣ How do you parameterize Linked Services securely?

  • Use ADF parameters in Linked Services

  • Store secrets in:

    • Azure Key Vault

  • Reference Key Vault secret dynamically

  • Avoid hardcoding credentials

  • Use Managed Identity where possible

👉 Secure = Key Vault + Managed Identity + Parameterization.

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================================================================

🔹 Architecture / Cross-Platform

  1. Design an enterprise-grade Inventory System architecture using:

    • Power Apps

    • Dataverse

    • Power Automate

    • Power BI

    • ADF

  2. How do you implement Dev → Test → Prod ALM using solutions + pipelines?

  3. Explain your approach for performance tuning across entire Power Platform stack.

If you want, I can now give model answers for senior-level interviews (crisp & strong impact responses).

=======================================================================

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🔥 Top 5 Deep-Dive Questions – Power Apps (Power Fx)

1️⃣ Explain the difference between Patch(), SubmitForm(), and UpdateIf().

  • When to use each?

  • Performance implications?

  • How do they behave with delegation?

2️⃣ What is Delegation in Power Fx?

  • Which functions are non-delegable?

  • How do Filter(), LookUp(), Sort() behave with large datasets?

  • How do you design formulas to avoid delegation warnings?

3️⃣ Explain Record Scope & ThisRecord.

  • How does ForAll() create row context?

  • Difference between ThisItem, ThisRecord, and global variables?

  • Example using nested ForAll().

4️⃣ Difference between Context Variables, Global Variables, and Collections.

  • When to use UpdateContext() vs Set() vs Collect()?

  • Memory impact?

  • App lifecycle behavior?

5️⃣ How do you optimize complex formulas in Power Fx?

  • Using With() for readability & performance

  • Avoiding multiple data calls inside ForAll()

  • Reducing nested If statements

  • Caching data strategically

If needed, I can also provide senior-level model answers with examples.

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By at No comments:

Wednesday, January 14, 2026

Study guide for Exam AZ-204: Developing Solutions for Microsoft Azure

 

Azure: Implement Containerized Solutions (Points Only)

1) ✅ Create and Manage Container Images for Solutions

✅ What a container image is

  • A packaged application with:

    • App code

    • Runtime (like .NET/Node/Python)

    • Libraries and dependencies

    • OS-level required files

  • Built using a Dockerfile

  • Runs the same across environments (Dev/Test/Prod)

✅ Best practices for container image creation

  • Use lightweight base images:

    • Alpine / slim images when possible

  • Use multi-stage builds:

    • Build stage → runtime stage (smaller final image)

  • Keep images secure:

    • Avoid storing secrets in image

    • Use environment variables / Key Vault instead

  • Standardize tagging:

    • appname:v1.0.0

    • appname:latest (use carefully in prod)

  • Include health check endpoint in app:

    • /health for readiness/liveness

  • Scan images for vulnerabilities:

    • Use ACR image scanning/security tools

2) ✅ Publish an Image to Azure Container Registry (ACR)

⭐ Azure Container Registry (ACR) purpose

  • Private container image registry for Azure

  • Stores:

    • Docker images

    • Helm charts (optional)

  • Supports:

    • Role-based access control (RBAC)

    • Integration with AKS, Container Apps, ACI

✅ Steps to push image to ACR (high-level)

  • Create ACR:

    • Choose SKU (Basic/Standard/Premium)

  • Login to ACR from CLI:

    • az acr login

  • Tag local image:

    • <acrname>.azurecr.io/appname:version

  • Push image:

    • docker push <acrname>.azurecr.io/appname:version

✅ Best practices for ACR

  • Use Managed Identity for pulling images (avoid secrets)

  • Enable private networking:

    • Private Endpoint (enterprise)

  • Use separate registries per environment (optional)

  • Keep a retention policy for old images

3) ✅ Run Containers Using Azure Container Instances (ACI)

⭐ What ACI is best for

  • Run containers without managing servers

  • Best use cases:

    • Quick deployments

    • Dev/Test workloads

    • Batch jobs and one-off tasks

    • Simple APIs (light traffic)

✅ Key ACI features

  • Fast startup

  • Supports:

    • Linux and Windows containers

  • Networking:

    • Public IP or VNet integration (advanced)

  • Storage:

    • Azure Files mount support

✅ When NOT to use ACI

  • Complex microservices needing scaling + service discovery

  • Production workloads requiring advanced traffic routing

  • Kubernetes-level orchestration

✅ Best practice usage

  • Use ACI for:

    • Job execution (ETL, scripts)

    • Temporary processing workloads

  • Add monitoring:

    • Azure Monitor logs for container output

4) ✅ Create Solutions Using Azure Container Apps (ACA)

⭐ Azure Container Apps = best managed container platform (recommended)

  • Runs containers with Kubernetes power but simplified operations

  • Best for:

    • Microservices

    • API backends

    • Background workers

    • Event-driven apps

✅ Key Container Apps features

  • Autoscaling (including scale to zero)

  • HTTPS ingress built-in

  • Revision management:

    • Blue/green and traffic splitting

  • Supports:

    • Dapr (optional for service-to-service messaging)

  • Easy integration with ACR

✅ Best design patterns with Container Apps

  • Frontend app → public ingress enabled

  • Backend services → internal ingress only

  • Worker services → no ingress (queue/event driven)

  • Use:

    • Managed Identity for ACR pull and secrets access

    • Environment variables for config

    • Key Vault references for sensitive data

✅ When to choose Container Apps vs AKS

  • Choose Container Apps when:

    • You want managed simplicity + autoscaling

    • You don’t want cluster management

  • Choose AKS when:

    • You need full Kubernetes control

    • Complex networking + policies + advanced workloads

✅ Recommended Enterprise Container Flow (End-to-End)

  • Build container image (Dockerfile)

  • Push image to Azure Container Registry

  • Deploy to:

    • ACI for simple/temporary/batch workloads

    • Azure Container Apps for production microservices with scaling

  • Secure and operate:

    • Managed Identity + Key Vault

    • Azure Monitor + Log Analytics

✅ Final Interview Summary (Perfect Answer)

  • Build images → Dockerfile + multi-stage builds + version tagging

  • Publish images → push to Azure Container Registry (ACR)

  • Run containers quickly → Azure Container Instances (ACI)

  • Production microservices → Azure Container Apps (autoscale + revisions + ingress)

#Azure #Containers #Docker #ACR #AzureContainerRegistry #ACI #AzureContainerInstances #ContainerApps #Microservices #DevOps #CloudArchitecture #AzureArchitecture

Implement Azure App Service Web Apps (Points Only)

1) ✅ Create an Azure App Service Web App

✅ Core components required

  • Resource Group

  • App Service Plan

    • Defines OS + region + pricing tier + scale

  • Web App

    • Hosts code or container

⭐ Best practices while creating Web App

  • Choose runtime:

    • .NET / Node.js / Java / Python / PHP

  • Pick correct OS:

    • Windows (if required)

    • Linux (common for containers + modern stacks)

  • Use naming standards:

    • app-<project>-<env>-<region>

  • Enable managed identity (recommended for secure access)

2) ✅ Configure and Implement Diagnostics and Logging

✅ Best diagnostics tools for App Service

  • App Service Logs

    • Application logs

    • Web server logs

    • Detailed error messages

    • Failed request tracing

  • Azure Monitor + Log Analytics

    • Centralized logging and queries using KQL

  • Application Insights (Recommended)

    • Request tracking, dependencies, exceptions, performance

✅ What to enable (production ready)

  • Enable Application Insights

    • Distributed tracing + live metrics

  • Send logs to Log Analytics Workspace

  • Enable diagnostic settings for:

    • AppServiceHTTPLogs

    • AppServiceConsoleLogs

    • AppServiceAuditLogs

✅ Troubleshooting benefits

  • Detect slow responses + failures

  • Track exceptions and root cause

  • Monitor CPU/memory and scaling behavior

3) ✅ Deploy Code and Containerized Solutions

✅ Code deployment options (most used)

  • GitHub Actions

    • Automated CI/CD

  • Azure DevOps Pipelines

    • Enterprise release pipelines

  • ZIP Deploy

    • Quick manual deployment

  • FTP (not recommended for production)

✅ Containerized deployment (recommended approach)

  • Use App Service for Containers:

    • Docker image from ACR

    • Or Docker Hub (less secure)

  • Best practices for container deployment:

    • Use private registry (Azure Container Registry)

    • Use Managed Identity to pull image (avoid passwords)

    • Use image tagging for version control

4) ✅ Configure Settings (TLS, API Settings, Service Connections)

✅ Transport Layer Security (TLS)

  • Enforce HTTPS:

    • HTTPS Only = ON

  • Set TLS version:

    • Use latest supported TLS (recommended)

  • Bind custom domain + SSL certificate:

    • App Service Managed Certificate (when available)

    • Or Key Vault certificate

✅ API settings (common configuration)

  • Enable CORS only for allowed domains

  • Configure Authentication/Authorization:

    • Microsoft Entra ID (Azure AD)

  • Configure API routing:

    • Use API Management if multiple APIs exist

✅ Service connections (secure connectivity)

  • Use Managed Identity

    • Access Key Vault, Storage, SQL securely

  • Use Key Vault references in App Settings

    • Avoid storing secrets in app config

  • Use VNet Integration

    • Access private resources (SQL/Storage via private endpoints)

✅ App configuration settings

  • Application settings:

    • Environment variables (Dev/Test/Prod separation)

  • Connection strings:

    • Store securely (prefer Key Vault)

  • Deployment settings:

    • Build during deployment (if needed)

5) ✅ Implement Autoscaling

⭐ Autoscale works on App Service Plan

  • Scale out = increase instances

  • Scale up = move to bigger plan (more CPU/RAM)

✅ When to use Scale Out (recommended)

  • Spiky traffic workloads

  • High concurrent users

✅ Autoscale rules (common)

  • CPU > 70% for 10 min → add 1 instance

  • Memory > 75% → add 1 instance

  • Queue length > threshold → scale out (for worker apps)

✅ Best practices

  • Set minimum instances for production (avoid cold start)

  • Use schedule-based scaling:

    • Scale up during business hours

    • Scale down at night

  • Always monitor costs with scaling rules

6) ✅ Configure Deployment Slots

⭐ What deployment slots provide

  • Separate environments within same Web App:

    • production, staging, dev

  • Support:

    • Zero-downtime deployments

    • Quick rollback

✅ Recommended slot usage

  • Deploy to staging slot

  • Validate health

  • Swap to production

✅ Slot settings (very important)

  • Mark configs as slot-specific when needed:

    • Connection strings

    • API keys

    • Environment variables like ENV=UAT

  • Use swap safely:

    • Warm-up settings to avoid cold start post swap

✅ Best deployment strategies with slots

  • Blue/Green deployment

  • Canary releases (limited traffic routing with advanced setup)

✅ Final Interview Summary (Perfect Answer)

  • Create Web App → App Service Plan + Web App + Managed Identity

  • Diagnostics → Application Insights + Log Analytics + App Service logs

  • Deploy → GitHub Actions/Azure DevOps + ACR container deployments

  • Configure → HTTPS/TLS, CORS, Entra ID auth, Key Vault references, VNet integration

  • Autoscale → scale-out rules based on CPU/memory/schedule

  • Slots → staging slot + swap for zero downtime + slot-specific settings

#Azure #AppService #WebApps #ApplicationInsights #AzureMonitor #DeploymentSlots #Autoscale #ACR #Containers #TLS #EntraID #KeyVault #DevOps #AzureArchitecture

Implement Azure Functions (Points Only)

1) ✅ Create and Configure an Azure Functions App

✅ Required components for a Function App

  • Resource Group

  • Function App

  • Hosting plan

    • Consumption (serverless pay-per-execution)

    • Premium (no cold start + VNet + better scale)

    • Dedicated (App Service Plan)

  • Storage Account (mandatory)

    • Used internally for function state and triggers

  • Runtime stack

    • .NET / Node.js / Python / Java

  • Region

    • Choose closest to users/data for low latency

⭐ Best plan selection

  • Consumption

    • Best for event-driven workloads

    • Lowest cost when usage is unpredictable

  • Premium

    • Best for production APIs and enterprise needs

    • Use when you need:

      • VNet integration

      • predictable performance

      • no cold start

  • Dedicated

    • Best when:

      • already using App Service Plan

      • fixed capacity required

✅ Core configuration settings (must-do)

  • Enable Managed Identity

    • Access Key Vault, Storage, Dataverse, etc.

  • Configure Application Settings

    • Connection strings, endpoints, environment flags

  • Enable monitoring:

    • Application Insights

  • Secure access:

    • Use HTTPS only

    • Restrict inbound access if needed (Private endpoints / VNet)

2) ✅ Implement Input and Output Bindings

✅ What bindings do

  • Connect your function to services without writing full integration code

  • Bindings reduce boilerplate and improve productivity

✅ Common input bindings

  • Blob input

    • Read content from Azure Storage blobs

  • Queue input

    • Get messages from Storage queue

  • Service Bus input

    • Read messages from queue/topic

  • Cosmos DB input

    • Read documents or change feed data

✅ Common output bindings

  • Blob output

    • Write results to Blob storage

  • Queue output

    • Push new messages to a queue

  • Service Bus output

    • Send messages to queue/topic

  • Cosmos DB output

    • Write documents to database

✅ Best practices for bindings

  • Keep bindings simple and focused

  • Use managed identity where supported

  • Handle failures:

    • dead-letter queues (Service Bus)

    • poison messages (Storage queues)

  • Avoid large payloads in queue messages

    • store file in Blob and pass reference URL

3) ✅ Implement Function Triggers (Data Operations, Timers, Webhooks)

✅ A) Data operations triggers

⭐ Storage Queue trigger

  • Best for:

    • Background processing

    • Async workload handling

  • Use cases:

    • Process requests from apps/flows

    • Run batch processing safely

⭐ Service Bus trigger

  • Best for:

    • Enterprise messaging (reliable + scalable)

  • Use cases:

    • Decoupled microservices processing

    • Integration pipelines

  • Features:

    • Topics/subscriptions

    • Dead-letter queues (DLQ)

⭐ Blob trigger

  • Best for:

    • File-based workloads

  • Use cases:

    • File uploaded → extract metadata → store into DB

    • Process images, PDFs, CSV files

⭐ Cosmos DB trigger

  • Best for:

    • Change feed based processing

  • Use cases:

    • React to document updates in NoSQL

✅ B) Timer triggers (Scheduled jobs)

⭐ Timer trigger

  • Best for:

    • Scheduled tasks using CRON

  • Use cases:

    • Daily sync jobs

    • Cleanup and archival tasks

    • SLA monitoring jobs

✅ Best practice

  • Make scheduled tasks idempotent (safe re-run)

  • Log run history for auditing

✅ C) Webhook / HTTP triggers

⭐ HTTP trigger

  • Best for:

    • APIs and webhooks

    • Called from:

      • Power Apps

      • Power Automate

      • External systems

  • Use cases:

    • Validate request → start job → return response

    • Integrate external system callbacks

✅ Security best practices

  • Prefer Entra ID authentication (OAuth)

  • Avoid exposing function keys publicly

  • Use APIM in front for enterprise control:

    • throttling, auth, logging

✅ Recommended Azure Functions Design Pattern (Enterprise)

  • Power Automate / App → HTTP trigger function

  • Function writes request to Service Bus queue

  • Service Bus trigger function processes job

  • Results stored in Dataverse/SQL/Storage

  • Monitoring via Application Insights + alerts

✅ Final Interview Summary (Perfect Answer)

  • Create Function App → choose plan (Consumption/Premium), storage account, enable App Insights + Managed Identity

  • Bindings → use input/output bindings for Storage/Service Bus/Cosmos DB to reduce code

  • Triggers → use Queue/ServiceBus/Blob for data events, Timer for schedules, HTTP for webhooks and APIs

#AzureFunctions #Serverless #Bindings #Triggers #ServiceBus #StorageQueue #BlobTrigger #TimerTrigger #HTTPTrigger #AppInsights #ManagedIdentity #AzureArchitecture

Develop Solutions that Use Azure Cosmos DB (Points Only)

1) ✅ Perform Operations on Containers and Items Using the SDK

✅ Cosmos DB core concepts

  • Account → top-level Cosmos resource

  • Database → logical grouping of containers

  • Container → stores items (like a table/collection)

  • Item → JSON document (record)

  • Partition key → drives scalability + performance

⭐ Best SDK choice (common)

  • .NET SDK / Java SDK / Python SDK / Node.js SDK

✅ Required setup for SDK operations

  • Cosmos endpoint URI

  • Key or Managed Identity (preferred in Azure)

  • Database + container name

  • Partition key value for item operations

✅ Common operations (CRUD)

  • Create:

    • Insert new item into container

  • Read:

    • Read item by id + partition key

  • Update:

    • Replace item (full update)

    • Patch item (partial update)

  • Delete:

    • Delete item by id + partition key

✅ Query operations

  • SQL API query examples:

    • SELECT * FROM c WHERE c.status = "Active"

  • Best practices:

    • Always filter using partition key when possible

    • Return only required fields

    • Use pagination for large results

✅ Performance + cost best practices (RU/s)

  • Choose a good partition key

    • High cardinality (many unique values)

    • Even distribution (avoid “hot partition”)

  • Use point reads when possible

    • Cheapest and fastest operation

  • Avoid cross-partition scans unless required

  • Use bulk mode for high volume inserts/updates

  • Use indexing policy tuning for write-heavy workloads

2) ✅ Set the Appropriate Consistency Level for Operations

✅ What consistency means in Cosmos DB

  • Balance between:

    • data accuracy

    • latency

    • availability

    • cost

⭐ Cosmos DB consistency levels (most important)

  • Strong

    • Highest correctness (like single-master strict order)

    • Higher latency, lower availability across regions

    • Best for: financial-like critical reads (rare use)

  • Bounded Staleness

    • Reads can lag behind by “N” versions or time window

    • Predictable consistency

    • Best for: global apps needing near-strong behavior

  • Session (Most common default)

    • Guarantees user/session sees its own writes

    • Best for: typical user apps, e-commerce, portals

  • Consistent Prefix

    • Order preserved, but may not be newest

    • Best for: event/log style workloads

  • Eventual

    • Fastest + cheapest, but can return stale reads

    • Best for: analytics, counts, non-critical data

✅ Recommendation cheat sheet

  • Most apps → Session

  • Global apps + predictable lag → Bounded staleness

  • Critical correctness → Strong

  • Maximum performance + lowest cost → Eventual

✅ Best practice

  • Set account-level consistency first

  • Override at request level only when required

  • Avoid Strong consistency in multi-region write-heavy workloads

3) ✅ Implement Change Feed Notifications

⭐ What is Change Feed

  • Continuous stream of changes (inserts + updates) in a container

  • Used for event-driven processing and downstream sync

  • Enables near real-time integrations

✅ Best use cases

  • Real-time notifications

  • Data replication to another system

  • Materialized views / projections

  • Audit and downstream analytics

  • Trigger workflows when items change

✅ Best options to consume Change Feed

✅ Option A: Azure Functions Trigger (Recommended)

  • Cosmos DB trigger listens to change feed

  • Best for:

    • Serverless processing

    • Scaling automatically

  • Common flow:

    • Item updated → Function triggered → push to Service Bus / update another container

✅ Option B: Change Feed Processor (SDK-based)

  • Runs inside your app/service

  • Best for:

    • Custom hosted microservices

    • Advanced checkpoint control

  • Needs lease container for checkpointing

✅ Option C: Event-driven integration pattern

  • Cosmos change feed → Function → Service Bus/Event Hub

  • Best for:

    • Multiple downstream consumers

    • Reliable processing + retries

✅ Change feed best practices

  • Use a lease container for checkpoints (Change Feed Processor)

  • Ensure idempotency:

    • Same event should not create duplicates

  • Use batching for efficiency

  • Monitor lag and failures

  • Store processing status/logs for audit

✅ Final Interview Summary (Perfect Answer)

  • SDK operations → use container CRUD, point reads with id + partition key, efficient queries, RU optimization

  • Consistency → choose Session for most apps, Bounded staleness for global predictability, Strong only for critical correctness

  • Change feed → use Cosmos trigger in Azure Functions or Change Feed Processor for event-driven notifications

#Azure #CosmosDB #NoSQL #PartitionKey #ConsistencyLevels #ChangeFeed #AzureFunctions #CloudArchitecture #Dataverse #EventDrivenArchitecture #DatabaseDesign

Develop Solutions that Use Azure Blob Storage (Points Only)

1) ✅ Set and Retrieve Properties and Metadata

✅ Difference between properties and metadata

  • Properties

    • System-defined values managed by Blob Storage

    • Examples:

      • Content-Type, Content-Length

      • ETag, Last-Modified

      • Access tier (Hot/Cool/Archive)

  • Metadata

    • Custom key-value pairs added by you

    • Examples:

      • Department=Finance

      • DocType=Invoice

      • Owner=Sreekanth

      • Retention=7Years

✅ Common operations for metadata/properties

  • Set metadata:

    • Add tags used by apps and governance

  • Get metadata:

    • Use for filtering, validation, processing decisions

  • Update properties:

    • Set Content-Type correctly (PDF, PNG, JSON)

    • Set cache control for performance

✅ Best practices

  • Keep metadata values small and meaningful

  • Follow consistent naming rules for metadata keys

  • Don’t store secrets or sensitive info in metadata

  • Use Blob Index Tags (if needed) for searchable tags at scale

2) ✅ Perform Operations on Data Using the Appropriate SDK

⭐ Most used SDK: Azure Storage Blob SDK

  • Available for:

    • .NET, Java, Python, Node.js

✅ Core objects in SDK

  • BlobServiceClient (account level)

  • BlobContainerClient (container level)

  • BlobClient (blob level)

✅ Common blob operations

  • Container operations:

    • Create container

    • List containers

    • Set container access level (private recommended)

  • Blob operations:

    • Upload blob

    • Download blob

    • Delete blob

    • Copy blob (async copy)

    • List blobs with prefix/folder style

✅ Handling large files (important)

  • Use block blobs

  • Upload using:

    • chunking / parallel upload

  • Use streaming:

    • don’t load full file into memory

✅ Access and security options (recommended)

  • Prefer Managed Identity from Azure services

  • Prefer SAS token only when temporary access is needed

  • Use RBAC + Storage Blob Data Contributor/Reader

  • Use Private Endpoint for internal-only access

✅ Performance best practices

  • Use CDN for public content delivery

  • Use correct blob type:

    • Block blobs (most common)

  • Use parallelism for large uploads/downloads

  • Avoid frequent small writes (bundle where possible)

3) ✅ Implement Storage Policies and Data Lifecycle Management

✅ Why lifecycle policies matter

  • Reduce storage cost automatically

  • Enforce retention and compliance rules

  • Move older data to cheaper tiers

⭐ Storage lifecycle management (best feature)

  • Create rules to automatically:

    • Move blobs between tiers:

      • Hot → Cool → Archive

    • Delete blobs after retention period

    • Handle snapshots and versions cleanup

✅ Common lifecycle rules (real-world)

  • Logs:

    • Hot for 7 days → Cool for 30 days → Archive for 180 days → Delete after 1 year

  • Backups:

    • Hot 30 days → Archive 7 years

  • Documents:

    • Hot for active usage → Cool after inactivity

✅ Versioning + soft delete (data protection)

  • Enable:

    • Soft delete (recover deleted blobs)

    • Blob versioning (recover overwritten files)

    • Point-in-time restore (where supported)

  • Best for:

    • Protecting against accidental delete/overwrite

    • Ransomware recovery readiness

✅ Governance and access policies

  • Use:

    • Immutability policies (WORM) for compliance (if required)

    • Storage account firewall

    • Private endpoints

  • Monitor with:

    • Diagnostic settings → Log Analytics

✅ Final Interview Summary (Perfect Answer)

  • Metadata/properties → set Content-Type + custom metadata for classification, retrieve for processing decisions

  • SDK operations → use BlobServiceClient/ContainerClient/BlobClient for upload/download/list/copy/delete

  • Policies/lifecycle → apply lifecycle rules (Hot→Cool→Archive), enable soft delete + versioning for protection and cost savings

#Azure #BlobStorage #AzureStorage #Metadata #SDK #LifecycleManagement #HotCoolArchive #SoftDelete #Versioning #DataProtection #CloudStorage #AzureArchitecture

Implement User Authentication and Authorization (Azure + Microsoft Identity) — Points Only

1) ✅ Authenticate & Authorize Users Using Microsoft Identity Platform

⭐ What Microsoft Identity Platform provides

  • OAuth 2.0 and OpenID Connect based authentication

  • Supports:

    • Work/school accounts (Entra ID)

    • Personal Microsoft accounts (MSA)

    • External users (B2B / External ID)

  • Used for:

    • Secure login (sign-in)

    • Token-based access to APIs (authorization)

✅ Recommended app architecture (common)

  • Frontend (Web/Mobile) → sign-in using Microsoft Identity

  • Backend API → validates JWT access token

  • Access resources:

    • Microsoft Graph

    • Azure services

    • Custom APIs

✅ Key concepts to mention in interview

  • ID Token

    • Used for user authentication (who the user is)

  • Access Token

    • Used to call APIs (what user/app can access)

  • Refresh Token

    • Used to get new access tokens (long session)

✅ Best practices

  • Use Authorization Code Flow (most secure for web apps)

  • Use PKCE for SPA/mobile apps

  • Validate tokens in API:

    • issuer, audience, signature, expiry

  • Use scopes + roles to control authorization

2) ✅ Authenticate & Authorize Users and Apps Using Microsoft Entra ID

✅ Best identity provider in Azure: Microsoft Entra ID

  • Provides:

    • SSO across apps

    • MFA and Conditional Access

    • App registrations + service principals

    • RBAC integration across Azure

✅ Authentication options

  • User-based authentication (Delegated)

    • User signs in and acts on their own behalf

    • Best for:

      • Web apps, portals, internal systems

  • App-only authentication (Application permissions)

    • Background services run without user context

    • Best for:

      • Scheduled jobs

      • System-to-system integrations

      • Automation scripts

✅ Authorization methods (Entra + Azure)

  • App-level authorization:

    • Scopes (API permissions)

    • App roles (role claims in token)

  • Azure resource authorization:

    • Azure RBAC (Owner/Contributor/Reader/custom roles)

  • Conditional Access:

    • Require MFA

    • Restrict sign-in location/device compliance

✅ Best practices

  • Prefer Managed Identity for Azure-to-Azure access

  • Use least privilege roles and permissions

  • Use PIM for admin roles (just-in-time access)

3) ✅ Create and Implement Shared Access Signatures (SAS)

⭐ What SAS is

  • A secure token that grants temporary limited access to Azure Storage resources

  • Supports:

    • Blob

    • File shares

    • Queues

    • Tables

✅ Types of SAS

  • User Delegation SAS (Recommended)

    • Uses Entra ID authentication

    • Stronger security (no account key sharing)

  • Service SAS

    • Created using storage account key (more risk)

  • Account SAS

    • Broad access across services (use carefully)

✅ Common SAS parameters

  • Scope:

    • Container / Blob

  • Permissions:

    • Read / Write / Delete / List

  • Expiry time:

    • Short-lived recommended

  • IP range restriction (optional)

  • HTTPS only (recommended)

✅ Best practices

  • Use short expiry (minutes/hours)

  • Use least privilege permissions

  • Prefer User Delegation SAS

  • Rotate keys if Service SAS is used

  • Never hardcode SAS tokens in apps/repos

4) ✅ Implement Solutions That Interact with Microsoft Graph

⭐ What Microsoft Graph provides

  • Unified API for Microsoft 365 + Entra ID data

  • Common resources:

    • Users, groups, roles

    • Mail, calendar

    • Teams, chats

    • SharePoint, OneDrive

    • Devices and directory objects

✅ Typical Microsoft Graph use cases

  • Read user profile details after login

  • Manage groups and group membership

  • Send mail or create calendar events (with permissions)

  • Teams notifications / automation

  • Read SharePoint files and lists

✅ Authentication for Microsoft Graph

  • Use Entra ID app registration

  • Permissions types:

    • Delegated permissions

      • Actions on behalf of signed-in user

    • Application permissions

      • Background service access (admin consent required)

✅ Best practices for Graph

  • Request only required scopes

  • Use admin consent carefully (for application permissions)

  • Handle throttling:

    • Respect 429 + Retry-After

  • Use paging for lists:

    • NextLink pagination

  • Secure secrets:

    • Use certificates or Managed Identity (when available)

    • Store secrets in Key Vault if needed

✅ Final Interview Summary (Perfect Answer)

  • Microsoft Identity platform → use OAuth2/OIDC, tokens (ID/access), auth code flow + PKCE

  • Entra ID → SSO, MFA, Conditional Access, scopes/roles, app-only or delegated access

  • SAS → temporary storage access, prefer User Delegation SAS, short expiry + least privilege

  • Microsoft Graph → access M365 data securely using delegated/app permissions with throttling and paging

#Azure #MicrosoftIdentityPlatform #EntraID #OAuth2 #OpenIDConnect #Authorization #RBAC #SAS #MicrosoftGraph #Security #ManagedIdentity #ConditionalAccess

Implement Secure Azure Solutions (Points Only)

1) ✅ Secure App Configuration Data (Azure App Configuration vs Azure Key Vault)

⭐ Use Azure App Configuration for

  • Non-secret configuration values

  • Feature flags and app settings

  • Environment-based configuration (Dev/UAT/Prod)

  • Centralized configuration for multiple apps

✅ Examples (safe to store)

  • API base URL

  • Feature toggle: EnableNewUI=true

  • Timeout values, limits, thresholds

  • App theme settings

  • Environment name

✅ Benefits

  • Central config store (no redeploy needed for changes)

  • Feature flags support

  • Easy integration with App Service / Functions / AKS

⭐ Use Azure Key Vault for

  • Secrets, keys, and certificates (high security)

✅ Examples (must store here)

  • Database passwords / connection strings

  • API keys / tokens

  • Certificates (TLS/SSL)

  • Encryption keys (CMK)

✅ Benefits

  • Strong access control (RBAC)

  • Secret rotation and versioning

  • Audit logging

  • HSM-backed security options

✅ Best practice approach (recommended architecture)

  • Store app settings in Azure App Configuration

  • Store secrets in Azure Key Vault

  • Reference Key Vault secrets from:

    • App Service settings (Key Vault references)

    • Functions configuration

    • Apps using SDK

2) ✅ Develop Code Using Keys, Secrets, and Certificates from Azure Key Vault

✅ Common access methods

  • Azure SDK (Recommended)

    • DefaultAzureCredential to authenticate securely

  • Key Vault supports managing:

    • Secrets (passwords, tokens)

    • Keys (encryption keys)

    • Certificates (TLS certs)

✅ Best practices for Key Vault usage in code

  • Never hardcode secrets in code or pipelines

  • Always authenticate using Managed Identity

  • Use secret versioning:

    • Handle secret rotation without breaking apps

  • Cache secrets in memory (short TTL) to reduce latency and calls

  • Enable:

    • Soft delete + purge protection

    • Diagnostic logging to Log Analytics

✅ Typical secure patterns

  • Retrieve secret → use it → do not log it

  • Use Key Vault certificate for:

    • HTTPS/mTLS

    • app authentication to external systems

  • Use Key Vault keys for:

    • Encryption at rest (CMK)

    • Signing tokens or messages

3) ✅ Implement Managed Identities for Azure Resources

⭐ What Managed Identity solves

  • Removes need for storing credentials (client secrets/passwords)

  • Azure automatically manages token issuance and rotation

  • Best for:

    • App Service → Key Vault

    • Function App → Storage / Dataverse / SQL

    • AKS → Key Vault + ACR

✅ Types of managed identity

  • System-assigned

    • Auto created per resource

    • Deleted when resource is deleted

    • Best for: single app resource usage

  • User-assigned

    • Standalone identity reused across multiple resources

    • Best for: shared access across apps/services

✅ Steps to implement (standard)

  • Enable Managed Identity on:

    • App Service / Function App / VM / Container Apps

  • Grant permissions using:

    • Azure RBAC roles

    • Key Vault role assignments

  • Use DefaultAzureCredential in application code

  • Test access:

    • Ensure the identity can fetch secrets/keys/certs

✅ Best practices

  • Follow least privilege:

    • Secret Get/List only if required

    • Separate identities per app/environment

  • Use Private Endpoints for Key Vault in enterprise environments

  • Monitor Key Vault access logs for suspicious activity

  • Avoid using access keys when managed identity is possible

✅ Final Interview Summary (Perfect Answer)

  • Config security → App Configuration for non-secrets, Key Vault for secrets/certs/keys

  • Code with Key Vault → use Azure SDK + Managed Identity, enable versioning + soft delete + auditing

  • Managed Identities → remove secrets, automatic rotation, grant RBAC permissions with least privilege

#AzureSecurity #KeyVault #AppConfiguration #ManagedIdentity #SecretsManagement #Certificates #EncryptionKeys #RBAC #CloudSecurity #AzureArchitecture

Azure Monitor + Application Insights: Monitor and Troubleshoot Solutions (Points Only)

1) ✅ Monitor and Analyze Metrics, Logs, and Traces

✅ What Application Insights monitors

  • Requests

    • Response time, failure rate, request count

  • Dependencies

    • SQL calls, REST APIs, Storage, Service Bus calls

  • Exceptions

    • Error stack traces + frequency

  • Performance

    • Slow operations, bottlenecks, latency patterns

  • Live Metrics

    • Near real-time health view for production

  • Distributed Tracing

    • End-to-end request tracking across microservices

✅ Metrics vs Logs vs Traces (easy interview explanation)

  • Metrics

    • Fast numeric measurements (CPU, request duration, failure rate)

  • Logs

    • Searchable records/events stored in Log Analytics (KQL queries)

  • Traces

    • Detailed operations flow across services (correlation IDs)

⭐ Best tools to analyze

  • Azure Monitor Metrics Explorer

    • Quick graphs + thresholds

  • Log Analytics (KQL)

    • Deep root-cause analysis

  • Application Insights (Performance + Failures + Dependencies)

    • End-to-end troubleshooting

✅ Best practices

  • Use sampling to reduce noise/cost (keep important logs)

  • Add custom dimensions:

    • userId, tenantId, environment, region

  • Track business events:

    • orders created, payments succeeded

  • Correlate across services:

    • use consistent operationId / traceId

2) ✅ Implement Availability Tests and Alerts

⭐ Availability Tests (Uptime Monitoring)

  • Purpose:

    • Ensure app endpoint is reachable and healthy

  • Types (common)

    • URL ping test (simple uptime check)

    • Standard test (improved version, modern approach)

    • Multi-step web test (legacy in many cases)

✅ Best availability test setup

  • Target:

    • /health endpoint (recommended)

  • Run frequency:

    • Every 1–5 minutes (based on criticality)

  • Test locations:

    • Multiple regions to detect geo routing issues

✅ Alerting (recommended approach)

  • Availability alerts

    • Trigger when test fails from multiple locations

  • Metric alerts

    • Response time high

    • Failed requests > threshold

  • Log query alerts

    • Custom detection using KQL

  • Action Groups

    • Notify via Email/SMS/Teams

    • Trigger Logic App / ITSM ticket

✅ Best practices for alerts

  • Avoid alert spam:

    • Use smart thresholds and aggregation windows

  • Separate alerts by severity:

    • Sev1 (outage), Sev2 (degradation), Sev3 (warnings)

  • Include runbook link in alert message:

    • troubleshooting steps, owner team

3) ✅ Instrument an App or Service to Use Application Insights

✅ Best instrumentation methods

  • Auto-instrumentation (easiest for supported runtimes)

    • Minimal code changes

  • SDK-based instrumentation (most control)

    • Add custom telemetry

✅ What to instrument (must-have telemetry)

  • Request telemetry:

    • response time, status codes

  • Dependency telemetry:

    • DB calls, external API calls

  • Exception telemetry:

    • catch and track errors

  • Trace telemetry:

    • custom logs for debugging

✅ Recommended enhancements (production ready)

  • Add custom events

    • OrderSubmitted, PaymentFailed

  • Add custom metrics

    • queue length, job duration

  • Implement distributed tracing

    • ensure correlation across services

  • Use OpenTelemetry where applicable

    • vendor-neutral instrumentation approach

✅ Secure instrumentation best practices

  • Don’t log secrets or PII

  • Use sampling + retention policies

  • Use different Application Insights resources per environment:

    • Dev / UAT / Prod

✅ Final Interview Summary (Perfect Answer)

  • Monitor → use metrics + logs (KQL) + traces in Application Insights

  • Availability tests → check /health endpoint from multiple locations + alert via Action Groups

  • Instrumentation → enable auto-instrumentation or SDK, track requests/dependencies/exceptions + add custom events and correlation

#AzureMonitor #ApplicationInsights #Observability #Logging #Metrics #Tracing #KQL #Alerts #AvailabilityTests #DistributedTracing #CloudMonitoring #DevOps #AzureArchitecture

Implement Azure API Management (APIM) — Points Only

1) ✅ Create an Azure API Management Instance

✅ What APIM is used for

  • Central API Gateway for:

    • Internal APIs

    • External partner APIs

    • Microservices APIs

  • Provides:

    • Security, throttling, transformations, monitoring

✅ Steps to create APIM instance (high-level)

  • Create a Resource Group

  • Create API Management service

  • Choose:

    • Region

    • Organization name + admin email

  • Select pricing tier:

    • Developer (non-prod, testing only)

    • Basic/Standard (small production)

    • Premium (enterprise: VNet + multi-region + SLA)

✅ Best practices

  • Use separate instances for:

    • Dev / UAT / Prod

  • Enable diagnostics logging to:

    • Log Analytics / Application Insights

  • Use custom domains for production endpoints

2) ✅ Create and Document APIs

✅ Ways to add APIs into APIM

  • Import from OpenAPI (Swagger) (best)

  • Import from Azure Functions / App Service

  • Create manually (basic)

  • SOAP to REST (supported scenarios)

✅ API documentation features

  • API operations:

    • GET/POST/PUT/DELETE endpoints

  • Add:

    • Request/response schemas

    • Examples

    • Error codes and messages

  • Use Developer Portal

    • Interactive testing

    • Subscription key management

    • Easy onboarding

✅ Best practices for API design in APIM

  • Keep versioning strategy:

    • URL versioning /v1/

    • Header versioning

    • Query string versioning

  • Create products:

    • Public product

    • Partner product

    • Internal product

3) ✅ Configure Access to APIs

✅ Common access control methods

  • Subscription keys

    • Simple API consumer onboarding

    • Per product / per API

  • OAuth 2.0 / OpenID Connect (Recommended)

    • Authenticate users via Microsoft Entra ID

  • Client certificates

    • High-security B2B integrations

  • IP filtering

    • Allow only specific networks

  • JWT validation

    • Validate token claims before allowing access

✅ Best practice access model

  • External APIs:

    • OAuth2 + subscription keys

  • Internal APIs:

    • Entra ID auth + private networking

  • Use Managed Identity when APIM calls backend services

✅ Security hardening checklist

  • Enable HTTPS only

  • Use WAF in front (Front Door/App Gateway) if needed

  • Restrict admin access using RBAC + PIM

  • Use Private Endpoints / VNet integration (premium tier scenarios)

4) ✅ Implement Policies for APIs

⭐ Policies are the strongest APIM feature

  • They apply rules to:

    • Inbound request

    • Outbound response

    • Backend calls

    • Errors

✅ Most commonly used APIM policies

✅ Security policies

  • validate-jwt

    • Validate Entra ID token and claims

  • check-header

    • Ensure required headers exist

  • ip-filter

    • Allow only approved client IPs

✅ Traffic management policies

  • rate-limit

    • Requests per time window

  • quota

    • Total calls per day/month

  • retry

    • Retry backend failures safely

✅ Transformation policies

  • set-header

    • Add correlation IDs, auth headers

  • rewrite-uri

    • Route to correct backend path

  • set-body

    • Modify request/response body

✅ Caching policies

  • cache-lookup + cache-store

    • Improve performance for read APIs

✅ Observability policies

  • Add correlation ID:

    • x-correlation-id

  • Enable diagnostics to App Insights/Log Analytics

✅ Best practices for policies

  • Apply policies at correct level:

    • Global → Product → API → Operation

  • Keep policy logic simple and maintainable

  • Use named values for reusable config

  • Avoid excessive transformations that add latency

✅ Final Interview Summary (Perfect Answer)

  • Create APIM → choose tier (Developer for dev, Premium for enterprise), enable logs + custom domain

  • Create/document APIs → import OpenAPI, publish via Developer Portal with versioning strategy

  • Configure access → subscription keys + Entra ID OAuth/JWT validation, restrict IPs and use HTTPS

  • Policies → apply validate-jwt, rate limiting, retry, rewrite, caching, headers, and logging

#Azure #APIM #APIGateway #AzureAPIM #OAuth2 #EntraID #JWT #RateLimiting #APIManagement #Policies #DeveloperPortal #CloudSecurity #AzureArchitecture

Develop Event-Based Solutions (Azure) — Points Only

1) ✅ Implement Solutions That Use Azure Event Grid

⭐ What Azure Event Grid is best for

  • Event routing (react when something happens)

  • Lightweight, push-based events

  • Best use cases:

    • Blob created/deleted events

    • Resource group changes

    • Key Vault secret events

    • Custom business events

✅ Key Event Grid components

  • Event Source

    • Storage, Key Vault, Azure services, custom apps

  • Event Topic

    • System topic (Azure resource events)

    • Custom topic (your own events)

  • Event Subscription

    • Routes events to a destination

    • Supports filtering and retry

  • Event Handler (Destination)

    • Azure Functions

    • Logic Apps

    • Webhook

    • Service Bus / Storage Queue

✅ Common architecture pattern

  • Storage event → Event Grid → Azure Function → process → update DB/Dataverse

✅ Filtering and routing best practices

  • Filter by:

    • Event type (BlobCreated only)

    • Subject patterns (specific container/folder)

  • Use dead-letter storage (recommended)

  • Use retries + exponential backoff (built-in behavior)

  • Design event handlers idempotent (safe if event delivered twice)

✅ When Event Grid is the best choice

  • You need:

    • Immediate reaction (near real time)

    • Fan-out to multiple consumers

    • Simple event routing without heavy streaming

2) ✅ Implement Solutions That Use Azure Event Hubs

⭐ What Azure Event Hubs is best for

  • High-throughput event streaming platform

  • Best use cases:

    • Telemetry and logging ingestion

    • IoT events and device streams

    • Clickstream data

    • Real-time pipeline into analytics systems

✅ Key Event Hubs components

  • Event Hub Namespace

    • Container for hubs and policies

  • Event Hub

    • The stream endpoint (like Kafka topic concept)

  • Partitions

    • Parallel consumption and scaling

  • Consumer Groups

    • Separate independent readers (apps/teams)

  • Throughput Units / Capacity

    • Scale based on load

✅ Common architecture pattern

  • Devices/apps → Event Hubs → Stream Analytics/Databricks → Data Lake → Power BI

✅ Best practices for Event Hubs

  • Choose partition key carefully

    • even distribution to avoid hot partitions

  • Keep events small and structured (JSON/Avro)

  • Use batching for producers to improve throughput

  • Plan retention:

    • short retention for streaming

    • archive to Data Lake for long-term storage

  • Use checkpointing in consumers:

    • Event Processor Client (SDK)

    • Azure Functions Event Hub trigger

✅ When Event Hubs is the best choice

  • You need:

    • Millions of events per second

    • Streaming analytics

    • Large-scale ingestion pipeline

✅ Event Grid vs Event Hubs (Interview Comparison)

✅ Choose Event Grid when

  • You want event routing and automation

  • Events are discrete business/system events

  • Fan-out to multiple targets is required

✅ Choose Event Hubs when

  • You want streaming ingestion at massive scale

  • Telemetry/log/IoT data is continuous

  • You need partitions + consumer groups for parallel reads

✅ Final Interview Summary (Perfect Answer)

  • Event Grid → best for reactive event routing, push delivery, filtering, fan-out, Functions/Logic Apps integration

  • Event Hubs → best for high-throughput streaming ingestion, partitions, consumer groups, analytics pipelines

#Azure #EventGrid #EventHubs #EventDrivenArchitecture #Streaming #Serverless #AzureFunctions #IoT #CloudIntegration #AzureArchitecture

Develop Message-Based Solutions (Azure) — Points Only

1) ✅ Implement Solutions That Use Azure Service Bus

⭐ What Azure Service Bus is best for

  • Enterprise messaging with guaranteed delivery

  • Best use cases:

    • Microservices communication

    • Financial/transaction systems

    • Order processing workflows

    • Reliable integration between apps

✅ Service Bus main components

  • Queue (1-to-1 messaging)

    • One message consumed by one receiver

  • Topic + Subscriptions (1-to-many pub/sub)

    • One message can be delivered to many subscribers

  • Dead-Letter Queue (DLQ)

    • Stores failed/poison messages automatically

✅ Key Service Bus features (interview must-know)

  • Message durability (stored until processed)

  • At-least-once delivery

  • Sessions for FIFO and ordered processing

  • Duplicate detection (avoid double-processing)

  • Scheduled messages (deliver later)

  • Retry and lock management (Peek-Lock mode)

  • Transactions (send/receive in one transaction)

✅ Recommended design patterns

  • Queue for:

    • Order creation → processing service

  • Topic for:

    • Order created → billing + shipping + notifications subscribers

  • DLQ handling:

    • Monitor DLQ and reprocess safely

✅ Best practices

  • Use Peek-Lock mode (default recommended)

  • Complete message only after successful processing

  • Use retry with backoff for transient failures

  • Design idempotent consumers (safe repeated processing)

  • Use message correlation IDs for traceability

  • Use Managed Identity for secure access

2) ✅ Implement Solutions That Use Azure Queue Storage

⭐ What Azure Queue Storage is best for

  • Simple, low-cost messaging for async workloads

  • Best use cases:

    • Background job processing

    • Simple producer/consumer pattern

    • Lightweight task queues

✅ Key Queue Storage features

  • Stores messages in a storage account

  • Simple API and easy integration

  • Works well with:

    • Azure Functions (Queue trigger)

    • WebJobs / Worker services

✅ Recommended design patterns

  • App pushes task message → Queue → Function processes task

  • Use blob + queue pattern:

    • Put file in Blob → queue message contains file URL

✅ Best practices

  • Keep message payload small

  • Store large data in Blob/DB and pass reference in queue message

  • Set visibility timeout correctly:

    • Prevent duplicate processing

  • Implement poison message handling:

    • After N failures → move to poison queue

  • Use retry strategy for failures

✅ Service Bus vs Queue Storage (Interview Comparison)

✅ Choose Azure Service Bus when

  • You need enterprise features:

    • Topics/subscriptions

    • FIFO ordering (sessions)

    • DLQ, transactions, duplicate detection

    • Strong reliability and governance

✅ Choose Azure Queue Storage when

  • You need simple, cheap async messaging

  • You don’t need advanced routing/features

  • You want easy serverless processing with Functions

✅ Final Interview Summary (Perfect Answer)

  • Service Bus → enterprise messaging with queues + topics, DLQ, sessions, transactions, reliable processing

  • Queue Storage → simple low-cost queue for background jobs with Azure Functions triggers

#Azure #ServiceBus #QueueStorage #Messaging #Microservices #DeadLetterQueue #EventDriven #AzureFunctions #CloudIntegration #AzureArchitecture
==============================================================

Azure Developer: Complete Notes (Points Only)

1) Implement Containerized Solutions

✅ Create and manage container images for solutions

  • Use Docker to package app + runtime + dependencies

  • Create Dockerfile

    • Use multi-stage build (smaller image)

    • Use lightweight base images (slim/alpine)

  • Best practices

    • Don’t store secrets in image

    • Add health endpoint /health

    • Tag images properly: app:v1.0.0, app:latest

    • Scan images for vulnerabilities

✅ Publish an image to Azure Container Registry (ACR)

  • ACR = private image registry for Azure

  • Steps

    • Create ACR (Basic/Standard/Premium)

    • Tag image: acrname.azurecr.io/app:1.0

    • Push image: docker push ...

  • Best practices

    • Use Managed Identity for pull

    • Enable private endpoint for enterprise security

    • Cleanup old images (retention)

✅ Run containers using Azure Container Instances (ACI)

  • Best for

    • Dev/test, quick runs, batch tasks

  • Features

    • No cluster management

    • Public IP or private VNet support

  • Best practices

    • Use ACI for short-lived workloads

    • Store logs in Log Analytics

✅ Create solutions using Azure Container Apps (ACA)

  • Best for production containers without managing Kubernetes

  • Features

    • Autoscale + scale to zero

    • Revision traffic splitting (blue/green)

    • HTTPS ingress built-in

    • Dapr support (optional)

  • Best practices

    • Use internal ingress for backend services

    • Managed Identity + Key Vault references

2) Implement Azure App Service Web Apps

✅ Create an Azure App Service Web App

  • Required components

    • Resource group

    • App Service Plan

    • Web App (runtime or container)

  • Best practices

    • Enable Managed Identity

    • Use proper naming: app-name-env-region

✅ Configure diagnostics and logging

  • Enable

    • Application Insights (recommended)

    • App Service logs (HTTP logs, console logs)

    • Diagnostic settings → Log Analytics

  • Monitor

    • failures, latency, dependencies, exceptions

✅ Deploy code and containerized solutions

  • Code deploy options

    • GitHub Actions / Azure DevOps pipelines

    • Zip deploy (quick)

  • Container deploy

    • Pull from ACR (recommended)

    • Use Managed Identity to access ACR

✅ Configure settings (TLS, API, service connections)

  • Security

    • HTTPS Only = ON

    • Latest TLS supported

  • API settings

    • CORS allow only required domains

    • Entra ID authentication for APIs

  • Service connections

    • Key Vault references for secrets

    • VNet integration for private access

    • Private endpoints for DB/Storage

✅ Implement autoscaling

  • Works on App Service Plan

  • Rules

    • CPU > 70% → scale out

    • Memory > 75% → scale out

    • Scheduled scaling for business hours

  • Best practices

    • Minimum instances in production

    • Monitor cost impact

✅ Configure deployment slots

  • Slots: staging, production

  • Benefits

    • Zero-downtime deploy

    • Easy rollback via swap

  • Best practices

    • Mark slot settings as “slot specific”

    • Use warm-up settings before swap

3) Implement Azure Functions

✅ Create and configure an Azure Functions app

  • Needs

    • Function App + Storage account

    • Hosting plan: Consumption / Premium / Dedicated

  • Best practices

    • Enable Application Insights

    • Enable Managed Identity

    • Store config in App Settings / App Configuration

✅ Implement input and output bindings

  • Bindings reduce code for integrations

  • Common bindings

    • Storage Blob input/output

    • Queue input/output

    • Service Bus input/output

    • Cosmos DB input/output

  • Best practices

    • Keep payload small

    • Store large files in Blob and pass reference

✅ Implement triggers (data operations, timers, webhooks)

  • Data triggers

    • Service Bus trigger (enterprise messaging)

    • Storage Queue trigger (simple background tasks)

    • Blob trigger (file processing)

    • Cosmos DB trigger (change feed processing)

  • Timers

    • Timer trigger for CRON schedules

  • Webhooks/APIs

    • HTTP trigger (Power Apps/Power Automate/external)

4) Develop Solutions Using Azure Cosmos DB

✅ Perform operations on containers and items using SDK

  • Core objects

    • Account → Database → Container → Item (JSON)

  • Operations

    • Create / Read / Update / Delete

    • Query with SQL API

  • Best practices

    • Use partition key in queries

    • Use point reads (fast + cheap RU)

    • Avoid cross-partition scans

    • Bulk execution for large loads

✅ Set the appropriate consistency level

  • Strong (highest correctness, slower)

  • Bounded staleness (controlled lag)

  • Session (best default for apps)

  • Consistent prefix (ordered, may lag)

  • Eventual (fastest, may be stale)

  • Recommendation

    • Most apps → Session

    • Global with control → Bounded staleness

    • Critical finance → Strong

✅ Implement change feed notifications

  • Change feed = stream of inserts/updates

  • Best consumers

    • Azure Functions Cosmos DB trigger

    • Change Feed Processor (SDK)

  • Best practices

    • Idempotent processing

    • Use lease container for checkpointing

    • Send to Service Bus/Event Hub for fan-out

5) Develop Solutions Using Azure Blob Storage

✅ Set and retrieve properties and metadata

  • Properties (system)

    • Content-Type, ETag, Last-Modified, tier

  • Metadata (custom key-value)

    • DocType, Owner, Department

  • Best practices

    • Don’t store secrets in metadata

    • Use consistent metadata keys

✅ Perform operations using SDK

  • SDK clients

    • BlobServiceClient

    • BlobContainerClient

    • BlobClient

  • Operations

    • Upload/download/delete/list/copy

  • Best practices

    • Use chunk upload for large files

    • Use managed identity + RBAC

    • Use private endpoints for secure access

✅ Implement lifecycle management

  • Policies to move data

    • Hot → Cool → Archive

    • Delete after retention

  • Protection

    • Soft delete

    • Versioning

    • Point-in-time restore (supported configs)

6) Implement User Authentication and Authorization

✅ Microsoft Identity platform

  • OAuth2 + OpenID Connect

  • Tokens

    • ID token (login)

    • Access token (API)

  • Best flows

    • Auth code flow (web apps)

    • PKCE (SPA/mobile)

✅ Microsoft Entra ID authentication/authorization

  • Supports

    • SSO, MFA, Conditional Access

  • Authorization

    • Scopes + App roles

    • Azure RBAC for Azure resources

  • Best practices

    • Least privilege

    • Use Managed Identity for Azure-to-Azure

✅ Shared Access Signatures (SAS)

  • Temporary scoped access to Storage

  • Types

    • User Delegation SAS (best)

    • Service SAS (uses account key)

  • Best practices

    • Short expiry

    • Minimum permissions

    • HTTPS only

✅ Microsoft Graph interactions

  • Access M365 resources

    • users, groups, mail, Teams, SharePoint

  • Permissions

    • Delegated (user context)

    • Application (app-only)

  • Best practices

    • Request minimum scopes

    • Handle throttling (429 + Retry-After)

7) Implement Secure Azure Solutions

✅ Secure config using App Configuration / Key Vault

  • App Configuration

    • non-secret settings + feature flags

  • Key Vault

    • secrets, keys, certificates

✅ Code using Key Vault secrets/keys/certs

  • Use Azure SDK + DefaultAzureCredential

  • Best practices

    • Soft delete + purge protection

    • Audit logs + monitoring

    • Cache secrets short-term (reduce calls)

✅ Implement Managed Identities

  • System assigned

    • tied to resource

  • User assigned

    • reusable identity

  • Best practices

    • RBAC with least privilege

    • Avoid access keys when MI works

8) Azure Monitor + Application Insights

✅ Monitor metrics, logs, traces

  • Metrics

    • requests, failures, duration

  • Logs (KQL)

    • deep analysis

  • Traces

    • distributed tracing across services

  • Best practices

    • add custom telemetry

    • sampling for cost control

    • correlate with traceId

✅ Availability tests and alerts

  • Use availability test against /health

  • Alerts

    • Availability failure

    • High response time

    • High exceptions

  • Action groups

    • Email/Teams/SMS + automation

✅ Instrument app/service

  • Auto-instrumentation (easy)

  • SDK instrumentation (custom control)

  • Track

    • requests + dependencies + exceptions + events

9) Implement Azure API Management (APIM)

✅ Create APIM instance

  • Tier choice

    • Developer (non-prod)

    • Standard (prod)

    • Premium (enterprise VNet + multi-region)

  • Best practices

    • Separate Dev/UAT/Prod

    • Enable diagnostics to Log Analytics

✅ Create and document APIs

  • Import OpenAPI (best)

  • Enable developer portal

  • Add versioning strategy /v1

✅ Configure access to APIs

  • Subscription keys

  • OAuth2 (Entra ID) + JWT validation

  • IP restrictions

  • mTLS (if required)

✅ Implement policies

  • Security

    • validate-jwt

  • Traffic management

    • rate-limit, quota

  • Transformations

    • set-header, rewrite-uri

  • Reliability

    • retry

  • Performance

    • caching

10) Develop Event-Based Solutions

✅ Azure Event Grid

  • Best for event routing (react to changes)

  • Source → Topic → Subscription → Handler

  • Best handlers

    • Azure Functions / Logic Apps / Webhooks

  • Best practices

    • filtering + dead-letter storage

    • idempotent consumers

✅ Azure Event Hubs

  • Best for high-throughput streaming (telemetry, IoT)

  • Concepts

    • partitions + consumer groups

  • Best consumers

    • Stream Analytics, Functions, Databricks

  • Best practices

    • partition key design

    • checkpointing

11) Develop Message-Based Solutions

✅ Azure Service Bus

  • Enterprise messaging

  • Queue (1:1), Topic (1:many)

  • Features

    • DLQ, sessions (FIFO), duplicate detection, transactions

  • Best practices

    • Peek-lock + complete after success

    • DLQ monitoring + reprocessing

✅ Azure Queue Storage

  • Simple low-cost queue

  • Best for background jobs

  • Best practices

    • small messages

    • poison message handling

    • store large payload in Blob and pass reference

#Azure #AzureDeveloper #Containers #ACR #ACI #ContainerApps #AppService #AzureFunctions #CosmosDB #BlobStorage #EntraID #MicrosoftIdentity #KeyVault #ManagedIdentity #AppInsights #AzureMonitor #APIM #EventGrid #EventHubs #ServiceBus #QueueStorage

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