29 August 2024

#Google_BigQuery

#Google BigQuery
Level Topic Subtopics
Basic Introduction to BigQuery What is BigQuery, Key Features, Use Cases, BigQuery vs Traditional Databases, Serverless Architecture
BigQuery Console & UI Web UI Overview, Query Editor, Job History, Project & Dataset Navigation, Schema Exploration
Datasets & Tables Creating Datasets, Creating Tables, Table Schema, Data Types, Partitioned & Clustered Tables
SQL Basics in BigQuery SELECT Statements, WHERE Clause, ORDER BY, LIMIT, GROUP BY, Aggregations
Data Loading & Export Loading CSV/JSON/Parquet, Streaming Inserts, Exporting Data, Storage Options
Intermediate BigQuery Functions & Operators String Functions, Date & Time Functions, Array Functions, JSON Functions, Mathematical Functions
Joins & Subqueries INNER JOIN, LEFT/RIGHT JOIN, CROSS JOIN, Self Joins, Nested Queries
Views & Materialized Views Creating Views, Benefits, Materialized Views, Use Cases, Performance Considerations
Performance Optimization Partitioning, Clustering, Query Caching, Table Decorators, Query Execution Plan
BigQuery ML Basics Introduction to BigQuery ML, Creating Models, Types of Models (Linear Regression, Classification), Training & Evaluation
Advanced Advanced SQL Features Window Functions, CTEs, Arrays, Structs, UNNEST, ARRAY_AGG, WITH Clauses
BigQuery ML Advanced Hyperparameter Tuning, Feature Engineering, Evaluation Metrics, Model Export, Predict Queries
Security & Access Control IAM Roles, Dataset/Table Permissions, Authorized Views, Row-Level Security, Column-Level Security
Data Transfer & Integration BigQuery Data Transfer Service, Cloud Storage, Google Analytics, External Data Sources, Federated Queries
Scripting & Stored Procedures BigQuery Scripting, Variables, Loops, IF/ELSE, Stored Procedures, Error Handling
Expert Advanced BigQuery ML Deep Learning Models, Time Series Forecasting, TensorFlow Integration, Vertex AI Integration, AutoML
Cost Management & Optimization Query Cost Estimation, Slot Reservations, Reservations & Flex Slots, Optimizing Storage & Queries
BigQuery for Analytics & BI Integrating with Looker, Data Studio, Tableau, Power BI, Real-time Analytics
Multi-Region & Multi-Project Architecture Data Replication, Cross-Project Queries, Federated Queries, Data Sharing Best Practices
Emerging Trends & Best Practices BigQuery Omni, BigLake, Serverless Analytics, Data Mesh, Governance, Performance Tuning

1. BigQuery Basics

  1. What is Google BigQuery?
  2. Explain key features of BigQuery.
  3. Difference between BigQuery and traditional databases.
  4. What is serverless architecture in BigQuery?
  5. What are BigQuery datasets?
  6. What are BigQuery tables?
  7. How do you create a table in BigQuery?
  8. Explain table schema and data types.
  9. What are partitioned tables?
  10. What are clustered tables?
  11. How do you load data into BigQuery?
  12. Difference between batch load and streaming inserts.
  13. How do you export data from BigQuery?
  14. Explain storage options in BigQuery.
  15. How do you navigate the BigQuery console?
  16. What is the query editor in BigQuery?
  17. How do you view job history?
  18. Explain SELECT statements in BigQuery SQL.
  19. How do you use WHERE clauses?
  20. How do you sort data using ORDER BY?
  21. How do you limit query results?
  22. How do you perform aggregations using GROUP BY?
  23. Difference between BigQuery Standard SQL and Legacy SQL.
  24. How do you explore schemas of existing tables?
  25. How do you monitor query performance in BigQuery?

2. Intermediate BigQuery

  1. Explain common BigQuery functions: STRING, DATE, ARRAY functions.
  2. How do you work with JSON data in BigQuery?
  3. Difference between INNER JOIN, LEFT JOIN, RIGHT JOIN, CROSS JOIN.
  4. What is a subquery and how is it used?
  5. How do you create views in BigQuery?
  6. Difference between normal views and materialized views.
  7. When should you use materialized views?
  8. How do you optimize query performance?
  9. What is query caching?
  10. How do you use table decorators?
  11. How do you implement clustering and partitioning for optimization?
  12. Explain the BigQuery ML basics.
  13. How do you create a linear regression model in BigQuery ML?
  14. How do you create a classification model in BigQuery ML?
  15. How do you train and evaluate a model in BigQuery ML?
  16. How do you make predictions using BigQuery ML?
  17. How do you integrate BigQuery with external tools?
  18. Explain IAM roles and dataset permissions.
  19. How do you use authorized views for security?
  20. How do you implement row-level security?
  21. How do you use column-level security?
  22. Explain BigQuery Data Transfer Service.
  23. How do you query external data sources?
  24. How do you perform federated queries?
  25. How do you schedule recurring queries in BigQuery?

3. Advanced BigQuery

  1. How do you use window functions in BigQuery?
  2. What are CTEs and how are they used?
  3. How do you work with arrays and structs?
  4. How do you use the UNNEST function?
  5. Explain ARRAY_AGG and ARRAY functions.
  6. How do you write complex nested queries?
  7. How do you create stored procedures in BigQuery?
  8. How do you use scripting in BigQuery?
  9. How do you handle errors in BigQuery scripts?
  10. How do you perform hyperparameter tuning in BigQuery ML?
  11. How do you engineer features in BigQuery ML?
  12. How do you export trained models?
  13. How do you use advanced evaluation metrics in BigQuery ML?
  14. Explain integration with TensorFlow.
  15. How do you use Vertex AI with BigQuery ML?
  16. How do you manage query cost?
  17. How do you optimize storage usage?
  18. How do you implement efficient table design for large datasets?
  19. How do you perform cross-dataset queries?
  20. How do you monitor and log queries for performance analysis?
  21. How do you handle streaming large datasets?
  22. Explain best practices for query optimization.
  23. How do you implement partition pruning?
  24. How do you use approximate aggregation functions?
  25. How do you manage multi-project BigQuery environments?

4. Expert-Level BigQuery

  1. How do you implement deep learning models with BigQuery ML?
  2. How do you perform time series forecasting in BigQuery ML?
  3. How do you integrate BigQuery ML with AutoML?
  4. How do you handle multi-modal data analysis in BigQuery?
  5. How do you implement BigQuery Omni for multi-cloud analytics?
  6. How do you implement BigLake for unified data lake analytics?
  7. How do you implement cost-effective query optimization at scale?
  8. How do you implement real-time analytics with BigQuery?
  9. How do you integrate BigQuery with Looker, Tableau, and Power BI?
  10. How do you implement cross-region replication?
  11. How do you design multi-project architecture for large enterprises?
  12. How do you implement federated queries across multiple clouds?
  13. How do you implement secure data sharing in BigQuery?
  14. How do you perform data governance and access auditing?
  15. How do you implement monitoring and alerts for large datasets?
  16. How do you handle query concurrency and slot management?
  17. How do you manage reservation and flex slots for optimization?
  18. How do you implement advanced security controls for sensitive data?
  19. How do you integrate AI/ML pipelines with BigQuery?
  20. How do you benchmark BigQuery for enterprise workloads?
  21. How do you debug complex queries at scale?
  22. How do you implement disaster recovery and backup strategies?
  23. What are best practices for BigQuery performance tuning?
  24. How do you implement governance and compliance in multi-cloud analytics?
  25. What are emerging trends and innovations in BigQuery and serverless analytics?
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28 August 2024

#AVRO

#AVRO
What is Apache Avro?
State some Key Points about Apache Avro?
What Avro Offers?
Who is intended audience to Learn Avro?
What are prerequisites to learn Avro?
Explain Avro schemas?
Explain Thrift and Protocol Buffers and Avro?
Why Avro?
How to use Avro?
Name some primitive types of Data Types which Avro Supports.
Name some complex types of Data Types which Avro Supports.
What are best features of Apache Avro?
Explain some advantages of Avro.
Explain some disadvantages of Avro.
What do you mean by schema declaration?
Explain the term Serialization?
What do you mean by Schema Resolution?
Explain the Avro Sasl profile?
What is the way of creating Avro Schemas?
Name some Avro Reference Apis?
When to use Avro?
Explain sort order in brief?
What is the advantage of Hadoop Over Java Serialization?
What are the disadvantages of Hadoop Serialization?
AVRO
Question Option A Option B Option C Option D
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26 August 2024

#Augmented_Reality

#Augmented_Reality
Augmented_Reality
Question Option A Option B Option C Option D
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#Prompt_Engineering

#Prompt_Engineering
Basic LLM Concepts
  • LLMs
  • Types of LLMs
  • How are LLMs Built?
  • Vocabulary
Prompting
  • Basic Prompting
  • Need for Prompt Engineering
Prompting
  • Basic Prompting
    • Use Delimiters to distinguish the data from the prompt.
    • Ask for Structured Output e.g. JSON, XML, HTML etc.
    • Include style information to modify the tone of output.
    • Give conditions to the model and ask if they are verified.
    • Give successful examples of completing tasks then ask.
    • Specify the steps required to perform a task.
    • Instruct model to work out its own solution before giving answers.
    • Iterate and Refine your prompts.
  • Need for Prompt Engineering
Prompting Techniques
  • Role Prompting
  • Few Shot Prompting
  • Chain of Thought Prompting
  • Zero Shot Chain of Thought
  • Least to Most Prompting
  • Dual Prompt Approach
  • Combining Techniques
  • Prompting Techniques
  • Parts of a Prompt
Real World Usage Examples
  • Structured Data
  • Inferring
  • Writing Emails
  • Coding Assistance
  • Study Buddy
  • Designing Chatbots
Pitfalls of LLMs
  • Citing Sources
  • Bias
  • Hallucinations
  • Math
  • Prompt Hacking
Improving Reliability
  • Prompt Debiasing
  • Prompt Ensembling
  • LLM Self Evaluation
  • Calibrating LLMs
  • Math
LLM Settings
  • Temperature
  • Top P
  • Other Hyperparameters
Image Prompting
  • Style Modifiers
  • Quality Boosters
  • Weighted Terms
  • Fix Deformed Generations
Prompt Hacking
  • Prompt Injection
  • Prompt Leaking
  • Jailbreaking
  • Defensive Measures
  • O!ensive Measures
Prompt_Engineering
Question Option A Option B Option C Option D
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#Generative_AI

#Generative_AI
Generative_AI
Question Option A Option B Option C Option D
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19 August 2024

#BigData

#BigData
What are the five V?s of Big Data?
What is Dala Cleansing?
What are the sources of Unstructured data in Big Data?
What are the different approaches to deal with Big Data?
What are the different platforms to deal with Big Data?
What kind of projects are better suitable for Big Data?
What are the factors or issues to be considered while building Big Data Models?
What are the tools used to extract Big Data?
What are the tools/languages to query Big Data?
What is features selection?
What is overfitting?
What are outliers?
What do you mean by model optimization?
What is Data Enrichment?
What is Lamda Architecture?
What is Graph Analytics concerning Big Data?
What is Dimensionality Reduction?
What are the different techniques for Dimensionality Reduction?
Name some tools or systems used in big data processing?
Explain the steps to be followed to deploy a Big Data solution.
Explain the ETL process concerning Big Data.
Explain data preparation in Big Data.
Why is Hadoop more suitable for Big Data?
Which are the best tools that can be used by a Data-Analyst?
Which language is preferred for Big Data - R, Python or any other language?
How is Hadoop related to Big Data?
How is big data analysis helpful in increasing business revenue?
How is Big data different?
How can big data support organizations?
How can you process Big Data?
How are Big Data and Data Science related?
How are missing values handled in Big Data?
How should you deal with outliers?
Describe Big Data deployment.
Is a cloud-based solution a good option for Big Data?
Is Hadoop different from other parallel computing systems? How?
  • Data Storage - HDFS, HBase, Apache Kudu, Amazon S3
  • Data Processing and Analysis - MapReduce, Apache Spark, Apache Pig, Apache Flink, Apache Hive, Apache Tez
  • Data Ingestion - Apache Sqoop, Apache Flume, Apache Kafka
  • Data Management- Apache ZooKeeper, Apache Oozie
  • Data Access- Apache HCatalog, Presto
  • Data Security and Governance - Apache Ranger, Apache Atlas
  • Machine Learning and Data Science - Apache Mahout, Apache Spark MLlib
  • Data Streaming - Apache Kafka, Apache Storm
  • Data Visualization - Apache Zeppelin, Hue
  • Data Serialization - Apache Avro, Protocol Buffers, Apache Parquet
  • Data Integration and ETL - Apache NiFi, Talend, Apache Airflow
  • Data Governance and Metadata Management - Apache Atlas, Apache Knox
  • Job Scheduling and Workflow Management - Apache Oozie, Apache Airflow, Apache Azkaban
  • Cluster Management - Apache Ambari, Cloudera Manage, Hortonworks Data Platform (HDP)
  • Data Indexing and Search- Apache Solr, Elasticsearch, Lucene
  • Data Backup and Disaster Recovery - Apache Falcon, DistCp (Distributed Copy), Terasort
  • Real-time Data Processing- Apache Storm, Apache Samza
  • Graph Processing - Apache Giraph, Apache Hama
  • SQL on Hadoop - Apache Drill, Impala, Presto
  • Data Quality - Apache Griffin:, Deequ
  • Data Archiving - Apache Hadoop Archive (HAR)
  • In-Memory Data Processing - Apache Ignite, Apache Spark
  • Data Versioning - Delta Lake, Apache Hudi
  • Resource Management and Monitoring - Ganglia, Nagios
  • Data Wrangling and Transformation - Trifacta, DataWrangler
  • Data Lake Management - Apache Hadoop Ozone, Azure Data Lake Stor
  • Query Optimization- Apache Calcite, Cost-Based Optimizer (CBO) in Hive
  • Data Sampling -Apache SAMOA, Reservoir Sampling
  • Data Federation - Apache Drill, Presto
  • Data Anonymization - Apache Kylin, Aircloak
  • Time Series Data - Apache Druid, OpenTSDB
  • Data Compression - Apache ORC (Optimized Row Columnar, Apache Parquet, LZO (Lempel-Ziv-Oberhumer)
  • Graphical Interfaces - Apache Hue, Kibana
  • Streaming SQL - Apache Flink SQL, Apache Beam
  • Multi-Tenant Security - Apache Sentry, Apache Ranger
BigData
Question Option A Option B Option C Option D
The _________ Server assigns regions to the region servers and takes the help of Apache ZooKeeper for this task. Region Master Zookeeper All of the mentioned
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17 August 2024

#IoT

#Internet_of_things (IOT)
What is IoT?
How does IoT work?
What are the core components of an IoT system?
Define smart devices.
What is the difference between M2M and IoT?
Name the layers of the IoT architecture.
What are some common use cases of IoT?
What is Industrial IoT (IIoT)?
What is Consumer IoT?
Explain the concept of a "connected ecosystem."
What are sensors? Give examples.
What are actuators?
How does a microcontroller differ from a microprocessor?
Compare Arduino and Raspberry Pi.
What is the function of an IoT gateway?
How does a GPS sensor work in an IoT device?
What is an ADC (Analog to Digital Converter)?
What is GPIO in hardware?
Name common power sources for IoT devices.
How do you select sensors for an IoT application?
What is MQTT? How does it work?
What is the use of a broker in MQTT?
Compare MQTT and HTTP.
What is CoAP?
Explain LoRa and its advantages.
What is Zigbee and where is it used?
What is BLE (Bluetooth Low Energy)?
What is 6LoWPAN?
What is the role of a MAC address in IoT?
Compare LPWAN vs Wi-Fi for IoT.
What is an IoT platform?
Compare AWS IoT Core, Azure IoT Hub, and Google IoT Core.
What is ThingSpeak?
What is Node-RED?
What is EdgeX Foundry?
What is device provisioning in IoT platforms?
How do you monitor device status remotely?
What is a digital twin?
What is OTA (Over-the-Air) update?
How do you debug IoT software remotely?
What is the OSI model and how does it relate to IoT?
What are PAN, LAN, and WAN in IoT networks?
What is an IPv6 address and why is it important for IoT?
How is NAT traversal handled in IoT?
What is mesh networking?
Compare star, mesh, and tree topologies in IoT.
What is a SIM card used for in IoT?
What are narrowband communications?
What is a MAC layer protocol?
What is NB-IoT?
Why is security critical in IoT?
What are the most common IoT security threats?
What is a DDoS attack in IoT?
What is secure boot?
How do you encrypt communication in IoT?
What is mutual authentication?
How do you ensure firmware integrity?
What is role-based access control (RBAC)?
What is TLS/SSL and how is it used in IoT?
How do you store sensitive data securely on a device?
What are the types of data collected in IoT?
What is real-time analytics in IoT?
How is big data related to IoT?
What is data aggregation?
What is stream processing?
What is time-series data?
How do you visualize sensor data?
How does edge analytics work?
What is latency in IoT data flow?
What is the role of AI/ML in IoT?
What is edge computing?
Compare edge and cloud computing.
Why use edge computing in IoT?
What is fog computing?
What are the benefits of edge AI?
How do edge nodes communicate with the cloud?
What are serverless functions in IoT?
What is a cloud-to-device message?
What is the latency difference between cloud and edge?
What are the main challenges in cloud-IoT integration?
What operating systems are used in IoT devices?
What is TinyOS?
What is Contiki OS?
What is RIOT OS?
What programming languages are used for IoT development?
What is FreeRTOS?
What is an RTOS and why is it important for IoT?
What is firmware in IoT?
What tools are used for debugging embedded software?
What IDEs support IoT development?
How do you test IoT hardware?
What are the key metrics for IoT performance testing?
What is stress testing in IoT?
How do you simulate IoT devices?
What is device provisioning?
What is lifecycle management in IoT?
How do you handle failed firmware updates?
What is remote device management?
What is device health monitoring?
How do you scale an IoT solution?
  • IoT Architecture
  • IoT Communication Protocols (MQTT, CoAP, HTTP, etc.)
  • IoT Sensors and Actuators
  • Embedded Systems and Microcontrollers (e.g., Arduino, Raspberry Pi)
  • Wireless Technologies (Wi-Fi, Zigbee, LoRa, NB-IoT, Bluetooth)
  • Edge Computing in IoT
  • Cloud Platforms for IoT (AWS IoT, Azure IoT, Google Cloud IoT)
  • IoT Security and Privacy
  • Data Analytics and Visualization in IoT
  • IoT Operating Systems (Contiki, RIOT, TinyOS)
  • IoT Standards and Protocols (6LoWPAN, IPv6, DDS)
  • Smart Home and Building Automation
  • Industrial IoT (IIoT)
  • IoT and Artificial Intelligence (AIoT)
  • IoT Device Management
  • IoT Testing and Debugging Tools
  • Low Power Wide Area Networks (LPWAN)
  • Digital Twins in IoT
  • IoT Product Development Lifecycle
  • Regulations and Compliance in IoT (GDPR, HIPAA, etc.)
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#Neural_Network

#Neural_Network
Neural_Network
Question Option A Option B Option C Option D
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11 August 2024

#GitHub_Actions

#GitHub_Actions
GitHub_Actions
Question Option A Option B Option C Option D
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#Azure_DevOps

#Azure_DevOps
Level Topic Subtopics
Basic Introduction to Azure DevOps What is Azure DevOps, Benefits, DevOps Principles, CI/CD Overview, Azure DevOps Services Overview
Azure DevOps Organizations & Projects Organizations, Projects, Users & Permissions, Access Control, Project Structure
Repositories & Version Control Git Basics, Azure Repos, Branching Strategies, Pull Requests, Merge Policies
Work Items & Boards Work Items Types, Boards, Backlogs, Sprints, Kanban Boards, Queries
Basic Pipelines Overview Build Pipelines, Release Pipelines, YAML vs Classic Pipelines, Pipeline Components, Pipeline Runs
Intermediate CI/CD Pipelines YAML Syntax, Pipeline Triggers, Build Tasks, Release Stages, Environment Configuration
Build & Release Management Artifacts, Build Agents, Self-hosted vs Microsoft-hosted Agents, Pipeline Variables, Pipeline Templates
Testing in Azure DevOps Unit Testing, Integration Testing, Test Plans, Test Suites, Automated Testing
Azure DevOps Integration GitHub, Azure Repos, Azure Boards, Azure Pipelines, Third-party Integrations
Security & Compliance Service Connections, Permissions, Secrets Management, Policies, Compliance Standards
Advanced Advanced Pipelines Multi-stage Pipelines, Conditional Tasks, Templates & Reuse, Pipeline Artifacts, Matrix Builds
Release Management Strategies Canary Deployments, Blue-Green Deployment, Rolling Deployment, Approvals & Gates, Deployment Slots
Infrastructure as Code (IaC) ARM Templates, Terraform, Bicep, Azure Resource Management, IaC Best Practices
Monitoring & Logging Azure Monitor, Application Insights, Pipeline Logs, Alerts, Dashboards
DevOps Metrics & Reporting Pipeline Analytics, Work Item Metrics, Lead Time, Deployment Frequency, Change Failure Rate
Expert DevOps at Scale Multi-repo Strategies, Monorepo Management, Large-scale Pipelines, Enterprise DevOps Practices, Governance
Advanced Security & Compliance Role-Based Access Control, Secrets Management, Security Scanning, Policy Enforcement, Compliance Audits
Advanced Integration & Automation Custom Tasks, REST APIs, Webhooks, Service Hooks, Automated Notifications
DevOps Best Practices & Strategy CI/CD Best Practices, Continuous Feedback, Release Management Strategies, Value Stream Mapping, DevOps Culture
Emerging Trends in Azure DevOps GitOps, AI-powered DevOps, Cloud-native DevOps, Multi-cloud Pipelines, DevSecOps

1. Azure DevOps Basics

  1. What is Azure DevOps?
  2. Explain the benefits of using Azure DevOps.
  3. What are the key DevOps principles?
  4. Difference between CI and CD.
  5. What are the main Azure DevOps services?
  6. What is an Azure DevOps organization?
  7. What is a project in Azure DevOps?
  8. How do you manage users and permissions in Azure DevOps?
  9. What is a work item in Azure DevOps?
  10. Explain different types of work items.
  11. What is a backlog?
  12. Difference between backlog and sprint.
  13. What are boards in Azure DevOps?
  14. Explain Kanban boards.
  15. Explain Scrum boards.
  16. How do you create and manage queries?
  17. What is Azure Repos?
  18. Difference between Git and TFVC in Azure DevOps.
  19. What is a pull request?
  20. How do you manage branches in Azure DevOps?
  21. What is a merge policy?
  22. Difference between YAML and classic pipelines.
  23. What are pipeline runs?
  24. How do you view pipeline history?
  25. How do you monitor project activity?

2. Intermediate Azure DevOps

  1. Explain YAML pipeline syntax.
  2. How do you trigger pipelines automatically?
  3. Difference between CI trigger and PR trigger.
  4. How do you define pipeline stages?
  5. Explain build tasks in Azure DevOps.
  6. How do you define variables in pipelines?
  7. What are pipeline templates?
  8. Difference between Microsoft-hosted and self-hosted agents.
  9. How do you publish and consume artifacts?
  10. What is release management?
  11. How do you configure release stages?
  12. Explain environment configuration in pipelines.
  13. How do you perform unit testing in pipelines?
  14. How do you perform integration testing?
  15. What is Azure Test Plans?
  16. Difference between test suite and test plan.
  17. How do you integrate GitHub with Azure DevOps?
  18. Explain Azure Boards integration with repos.
  19. How do you integrate third-party tools?
  20. What are service connections?
  21. How do you manage secrets in pipelines?
  22. Explain policy enforcement in Azure DevOps.
  23. How do you ensure compliance in pipelines?
  24. What is pipeline caching?
  25. How do you monitor pipeline performance?

3. Advanced Azure DevOps

  1. Explain multi-stage pipelines.
  2. What are conditional tasks in pipelines?
  3. How do you reuse pipeline templates?
  4. Explain matrix builds.
  5. What are pipeline artifacts and how are they used?
  6. Explain canary deployments.
  7. Explain blue-green deployments.
  8. Explain rolling deployments.
  9. How do you implement approvals and gates?
  10. What is Azure Resource Manager (ARM)?
  11. Explain Infrastructure as Code (IaC).
  12. How do you use Terraform with Azure DevOps?
  13. What is Bicep in Azure DevOps?
  14. How do you implement monitoring with Azure Monitor?
  15. How do you use Application Insights?
  16. How do you set up alerts and dashboards?
  17. Explain pipeline analytics.
  18. What is deployment frequency?
  19. Explain lead time for changes metric.
  20. Explain change failure rate metric.
  21. How do you handle high availability in deployments?
  22. What are best practices for release management?
  23. How do you manage large-scale pipelines?
  24. Explain branching strategies in large projects.
  25. How do you handle versioning and rollback in pipelines?

4. Expert-Level Azure DevOps

  1. How do you implement multi-repo strategies?
  2. How do you manage monorepos in Azure DevOps?
  3. Explain enterprise-scale DevOps practices.
  4. How do you implement role-based access control (RBAC)?
  5. How do you manage secrets securely at scale?
  6. How do you perform security scanning in pipelines?
  7. How do you enforce policies across pipelines?
  8. Explain CI/CD best practices for large teams.
  9. How do you implement automated notifications and alerts?
  10. How do you use REST APIs with Azure DevOps?
  11. How do you implement webhooks and service hooks?
  12. Explain value stream mapping in DevOps.
  13. How do you monitor deployed applications effectively?
  14. How do you manage pipeline failures at scale?
  15. Explain GitOps and its relevance to Azure DevOps.
  16. How do you implement DevSecOps practices?
  17. How do you enable continuous feedback in DevOps?
  18. Explain cloud-native DevOps practices.
  19. How do you handle multi-cloud pipelines?
  20. How do you implement enterprise governance in DevOps?
  21. What are AI-powered DevOps tools?
  22. How do you scale release management for large enterprises?
  23. How do you implement continuous compliance?
  24. Explain emerging trends in Azure DevOps.
  25. How do you optimize cost and efficiency in Azure DevOps pipelines?
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09 August 2024

#Spring_LDAP

#Spring_LDAP
Spring_LDAP
Question Option A Option B Option C Option D
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