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Top 15 Data analyst Interview questions

1) Mention what is the responsibility of a Data analyst?

Responsibility of a Data analyst include,

  • Provide support to all data analysis and coordinate with customers and staffs
  • Resolve business associated issues for clients and performing audit on data
  • Analyze results and interpret data using statistical techniques and provide ongoing reports
  • Prioritize business needs and work closely with management and information needs
  • Identify new process or areas for improvement opportunities
  • Analyze, identify and interpret trends or patterns in complex data sets
  • Acquire data from primary or secondary data sources and maintain databases/data systems
  • Filter and “clean” data, and review computer reports
  • Determine performance indicators to locate and correct code problems
  • Securing database by developing access system by determining user level of access

2) What is required to become a data analyst?

To become a data analyst,

  • Robust knowledge on reporting packages (Business Objects), programming language (XML, Javascript, or ETL frameworks), databases (SQL, SQLite, etc.)
  • Strong skills with the ability to analyze, organize, collect and disseminate big data with accuracy
  • Technical knowledge in database design, data models, data mining and segmentation techniques
  • Strong knowledge on statistical packages for analyzing large datasets (SAS, Excel, SPSS, etc.)

3) Mention what are the various steps in an analytics project?

Various steps in an analytics project include

  • Problem definition
  • Data exploration
  • Data preparation
  • Modelling
  • Validation of data
  • Implementation and tracking

4) Mention what is data cleansing?

Data cleaning also referred as data cleansing, deals with identifying and removing errors and inconsistencies from data in order to enhance the quality of data.

5) List out some of the best practices for data cleaning?

Some of the best practices for data cleaning includes,

  • Sort data by different attributes
  • For large datasets cleanse it stepwise and improve the data with each step until you achieve a good data quality
  • For large datasets, break them into small data. Working with less data will increase your iteration speed
  • To handle common cleansing task create a set of utility functions/tools/scripts. It might include, remapping values based on a CSV file or SQL database or, regex search-and-replace, blanking out all values that don’t match a regex
  • If you have an issue with data cleanliness, arrange them by estimated frequency and attack the most common problems
  • Analyze the summary statistics for each column ( standard deviation, mean, number of missing values,)
  • Keep track of every date cleaning operation, so you can alter changes or remove operations if required

 

6) Explain what is logistic regression?

Logistic regression is a statistical method for examining a dataset in which there are one or more independent variables that defines an outcome.

7) List of some best tools that can be useful for data-analysis?

  • Tableau
  • RapidMiner
  • OpenRefine
  • KNIME
  • Google Search Operators
  • Solver
  • NodeXL
  • io
  • Wolfram Alpha’s
  • Google Fusion tables

8) Mention what is the difference between data mining and data profiling?

The difference between data mining and data profiling is that

Data profiling: It targets on the instance analysis of individual attributes. It gives information on various attributes like value range, discrete value and their frequency, occurrence of null values, data type, length, etc.

Data mining: It focuses on cluster analysis, detection of unusual records, dependencies, sequence discovery, relation holding between several attributes, etc.

9) List out some common problems faced by data analyst?

Some of the common problems faced by data analyst are

  • Common misspelling
  • Duplicate entries
  • Missing values
  • Illegal values
  • Varying value representations
  • Identifying overlapping data

10) Mention the name of the framework developed by Apache for processing large data set for an application in a distributed computing environment?

Hadoop and MapReduce is the programming framework developed by Apache for processing large data set for an application in a distributed computing environment.

11) Mention what are the missing patterns that are generally observed?

The missing patterns that are generally observed are

  • Missing completely at random
  • Missing at random
  • Missing that depends on the missing value itself
  • Missing that depends on unobserved input variable

12) Explain what is KNN imputation method?

In KNN imputation, the missing attribute values are imputed by using the attributes value that are most similar to the attribute whose values are missing. By using a distance function, the similarity of two attributes is determined.

13) Mention what are the data validation methods used by data analyst?

Usually, methods used by data analyst for data validation are

  • Data screening
  • Data verification

14) Explain what should be done with suspected or missing data?

  • Prepare a validation report that gives information of all suspected data. It should give information like validation criteria that it failed and the date and time of occurrence
  • Experience personnel should examine the suspicious data to determine their acceptability
  • Invalid data should be assigned and replaced with a validation code
  • To work on missing data use the best analysis strategy like deletion method, single imputation methods, model based methods, etc.

15) Mention how to deal the multi-source problems?

To deal the multi-source problems,

  • Restructuring of schemas to accomplish a schema integration
  • Identify similar records and merge them into single record containing all relevant attributes without redundancy

16) Explain what is an Outlier?

The outlier is a commonly used terms by analysts referred for a value that appears far away and diverges from an overall pattern in a sample. There are two types of Outliers

Univariate

  • Multivariate

17) Explain what is Hierarchical Clustering Algorithm?

Hierarchical clustering algorithm combines and divides existing groups, creating a hierarchical structure that showcase the order in which groups are divided or merged.

18) Explain what is K-mean Algorithm?

K mean is a famous partitioning method.  Objects are classified as belonging to one of K groups, k chosen a priori.

In K-mean algorithm,

  • The clusters are spherical: the data points in a cluster are centered around that cluster
  • The variance/spread of the clusters is similar: Each data point belongs to the closest cluster

19) Mention what are the key skills required for Data Analyst?

A data scientist must have the following skills

  • Database knowledge
  • Database management
  • Data blending
  • Querying
  • Data manipulation
  • Predictive Analytics
  • Basic descriptive statistics
  • Predictive modeling
  • Advanced analytics
  • Big Data Knowledge
  • Big data analytics
  • Unstructured data analysis
  • Machine learning
  • Presentation skill
  • Data visualization
  • Insight presentation
  • Report design

20) Explain what is collaborative filtering?

Collaborative filtering is a simple algorithm to create a recommendation system based on user behavioral data. The most important components of collaborative filtering are users- items- interest.

A good example of collaborative filtering is when you see a statement like “recommended for you” on online shopping sites that’s pops out based on your browsing history.

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Top 10 IOT Interview questions

Q1. What are the main parts of IoT systems?

Answer:
IoT system consists of three main parts:

  1. Sensors
  2. Network connectivity
  3. Data storage applications.

Q2. What are security concerns related to IoT?

Answer:
This is the common IoT Interview Questions asked in an interview. Data security and privacy are major concerns related to IoT. These devices are vulnerable to hacking and cloud endpoints could be used by hackers to attack servers. Software developers and device designers have to ensure adequate security and privacy measures.

Q3. Explain the IoT protocol stack.

Answer:
IoT has 4 protocol layers:

  1. Sensing and information: Includes various smart sensor devices based on GPS, RFID, Wi-Fi, etc.
  2. Network connectivity: Layer is based on a wired and wireless network such as WLAN, WMAN, Ethernet, optical fiber and more.
  3. Information processing layer
  4. Application layer

Let us move to the next IoT Interview Questions.

Q4. Explain the basic architecture of the IoT network.

Answer:
IoT has three main parts namely sensors, network connectivity and data storage applications. Sensors either communicate directly with the central server for data storage or communicate via gateway devices. A gateway can handle various wireless interfaces that’s why one gateway can handle multiple technologies and multiple sensors. The typical wireless technologies used widely are Zigbee, Zwave, RFID, NFC etc. gateway interfaces with the cloud using wireless or wired technologies such as Wi-Fi, Mobile or Fiber, DSL.

The IoT hardware system can be constructed using Micro-Controller Units. Choice of Micro-controller depends on the system on chip resources, the power required and interfaces needed as per different sensors and memory requirements.

To finalize the IoT hardware architecture following aspects are required to study:

  • Type of sensors/actuators.
  • Communication interface type.
  • Amount of data to be captured and transmitted.
  • A frequency of data transportation.

IoT software architecture is based on open source components like Arduino, Linux (Raspberry Pi)

Q5. Explain Bluetooth Low Energy protocol for an IOT?

Nokia originally introduced this protocol as wibree in 2006. Additionally, known as Bluetooth smart this protocol presents the same range coverage with a good deal of decreased strength intake because of the unique Bluetooth. It has comparable bandwidth with narrow spacing utilized by ZigBee. Low electricity latency and decrease complexity makeable greater appropriate to include into low-cost microcontrollers.

 

Part 2 – IoT Interview Questions (Advanced)

Let us now have a look at the advanced IoT Interview Questions and Answers.

Q6. What is the top 5 Machine to Machine (M2M) applications in the world?

Answer:
They are as follows:

  1. Asset tracking and monitoring in some form or some other (stolen automobiles, fleet, construction system, and many others seems to be the biggest.
  2. Insurance telematics is huge as it gives insurance groups the possibility to cut the threat and force higher/extra appealing pricing.
  3. Utilities/automatic meter reading/clever grids – plenty of regulation and funding into this in the intervening time. There a plenty of countrywide solutions because the requirements and business case are driven in very numerous ways.
  4. Automotive is also very big and is driven by consumer’s demand.
  5. mHealth is also present in small scale.

Q7. How might Internet Address (IPv6) affect the development and implementation of the Internet of Things?

Answer:
This is the most popular IoT Interview Questions asked in an interview. A barrier to the improvement of IoT is the technical boundaries of the version of the network protocol(IP) that is used most widely. IP is the set of rules that computers use to ship and receive statistics via the internet, including a specific address that every connected device or item should have to speak. Model four (ipv4) is presently in widest use. It can accommodate about four billion addresses and its miles near saturation, with few new addresses available in many parts of the sector.

Version 6 (ipv6) allows for a big increase within the wide variety IP addresses. With ipv4, the maximum number of particular addresses, 4.2 billion, is not sufficient to provide even one deal with for every of the 7.3 billion human beings on earth. Ipv6, in an evaluation, will accommodate over 1038 addresses extra than a thousand billion trillion per man or woman.

Q8. What is the difference between a wireless sensor network (WSN) and the Internet of Things(IoT) network?

Answer:
WSN: Wi-Fi sensor community is the foundation of IoT packages. WSN is a network of motes, fashioned to look at, to take a look at or to monitor bodily parameters of desired utility.

e.g. motes deployed in agricultural land, screen temp-humidity or maybe soil moisture, who gathers statistics and ideal statistics analysis procedure consequences approximately crop yields-high quality or amount.

IoT: IoT is a community of bodily objects managed and monitored over the internet. Now just as win, in its application, you will stumble upon the monitoring of physical parameters. But preferred results are little different. IoT is about M2M, it’s far greater than bringing smartness into daily gadgets.

e.g. device hooked in your thermostat monitors surrounding temperature and adjust it to maximum favored placing for.

Let us move to the next IoT Interview Questions.

Q9. What is meant by a smart city regarding the Internet of Things?

Answer:
As with IoT and different popular era terms, there is no established consensus definition or set of standards for characterizing what a smart metropolis is. Precise characterizations vary widely, however in fashionable they involve the use of IoT and related technologies to improve energy, transportation, governance, and other municipal offerings for certain desires which includes sustainability or advanced great of lifestyles.

Q10. What is Bluegiga APX4 protocol for an Internet of Things?

Answer:
Bluegiga and wireless together may be used without interference as they are compliable to coexistence protocols. The bluegiga apx4 supports both Bluetooth and Wi-Fi and is based on a 450mhz arm9 processor.

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Top 15 Digital marketing Interview questions

 

1) Explain what is digital marketing?

Digital marketing is the brand marketing tactics through the internet. It includes various techniques like SEO, SEM and link building.

2) How can you categorize the digital marketing?

The digital marketing/communication is categorized into two segments

  • Inbound Marketing: This techniques takes the help of social media, digital content in e-books, webinars or e-newsletter to increase the number of clicks on links and learn more about a company and its services.
  • Outbound Marketing: This segment includes placing ads, cold-calls, e-mails or reach out potential customers through digital mediums

3) Explain what is SEO?

Search Engine Optimization widely known as SEO is the process of improving the structure, content and organization of your site, so that the Search engines can index them correctly. It also involves doing promotional activities to boost your search engine rank.

4) Explain what is a keyword in digital marketing ? How important is it from the point of SEO?

“Keyword” in digital marketing is the word that a user’s or person enters into a search engine to find specific information.

From SEO point of view, for better page ranking keywords are very crucial. How and where you have used the keywords will reflect your site ranking.

5) Mention what are the key areas where you can use keywords to optimize the site ranking?

For better page ranking, you must use the keywords in following areas

  • Keyword in Website URL
  • Keyword in Website Title
  • Keyword in Meta tag
  • Keyword in Web page content
  • Keyword density in body text
  • Keywords in Headlines

 

6) Explain what is PPC or Pay Per Click advertising?

Pay Per Click also known as Cost Per Click, is a technique used to direct traffic to websites.  In this technique, advertisers pay the publisher ( website owner or host of the website) when the ad is clicked.  In other words, it is the amount spent to get an advertisement clicked.

7) Mention what are the primary models for determining Pay-Per-Click ?

The primary models for determining Pay-Per-Click are

  • Flat rate PPC :

In this type of model, both publisher and advertiser agree to a fixed amount that will be paid for each click. In most time, the publisher has a rate card for PPC plan based on different areas of their website or network.   The amount varies as per the content that generally attracts more or less people.

  • Bid based PPC :

In this type of model, the advertiser competes with other advertisers in a private auction hosted by a publisher.  The advertiser will inform publisher for the maximum amount of bid he is willing to pay.

8) Explain what is Google Adwords?

Google Adwords is the single most popular PPC advertising system in the world.   It works on Pay per click model.

The AdWords platform enables the business to create ads that appear on Google search engine and their other properties.

9) Mention what is an effective PPC keyword should be like?

An effective PPC keyword should be

Relevant : List out the targeted keywords

  • Exhaustive : Apart from most popular keywords it should include the “long tail of search”
  • Expansive: PPC is iterative, therefore the keyword list should be constantly growing and adapting

10) Mention what are the key elements to optimize the conversion rates per PPC?

Conversion rate is nothing but to bring more visitors to your site.  To increase the conversion rates you have to focus on following things

  • Write compelling content on your site that is relevant to the keyword or search query
  • Maintain a high degree of relevance between your ads and corresponding landing pages
  • The webpage should easy registering process, signing up for a newsletter or making a purchase
  • Check design of your landing page which should have right combination of color, layout and GUI to attract more customers

11) What should be the approach for effective Pay Per Click campaings?

For effective Pay Per Click campaign, you need to do following things

  • Add more PPC keywords: By adding more keywords that are relevant to your business, you can expand the reach of your pay per click
  • Split Ad groups: By splitting up your ad groups into smaller and more relevant ad groups, you can improve click-through-rate (CTR)
  • Review costly PPC keywords: Review expensive and under performing keywords
  • Refine landing page: To align with individual search queries modify the content and call-to-action of your landing page
  • Add negative keywords: To improve campaign relevancy and reduce wasted spend, add non-converting terms /negative keywords. ( When search with that keyword, it will not show your website/content)

12) List out some of the useful online marketing tools?

Some of the useful online marketing tools are

  • Google Analytics
  • Digital point keyword tracker
  • Crazy egg heat maps
  • Keyword discovery
  • StumbleUpon
  • XML Sitemap Generator
  • Favicon generator
  • SubmitExpress Link Popularity

13) Explain what is on-page and off page optimization?

Off page optimization: It is the process of boosting your search engine ranking by getting external links pointing back to it

On page optimization: On page optimization directly deals with the content and structure of the website.

14) What one should do to avoid the penalty?

  • Do not link to any other site with bad page rank
  • Avoid Poison words, for example word “link”, when you hypertext this text to give the link to your site it becomes poison words
  • Avoid stealing text or imagesfrom other domains
  • Avoid re-directing users to another page through refresh meta-tags – don’t immediately send user or visitors to another page even before he or she clicked on the web page link

15) Mention what are the characteristics of “bad links” ?

The characteristics of “bad links” are

  • Links from sites that are unrelated to your sites
  • Links from low Page Rank and Low traffic
  • Links from link exchanges
  • Links from those sites that are not in Google index
  • Paid links
  • Link from the same anchor texts coming from multiple sites
  • Spammy links from blogs or articles.
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Top 20 Data science Interview questions

 

1. What is Data Science?

Data Science is a combination of algorithms, tools, and machine learning technique which helps you to find common hidden patterns from the given raw data.

2. What is logistic regression in Data Science?

Logistic Regression is also called as the logit model. It is a method to forecast the binary outcome from a linear combination of predictor variables.

3. Name three types of biases that can occur during sampling

In the sampling process, there are three types of biases, which are:

  • Selection bias
  • Under coverage bias
  • Survivorship bias

4. Discuss Decision Tree algorithm

A decision tree is a popular supervised machine learning algorithm. It is mainly used for Regression and Classification. It allows breaks down a dataset into smaller subsets. The decision tree can able to handle both categorical and numerical data.

5. What is Prior probability and likelihood?

Prior probability is the proportion of the dependent variable in the data set while the likelihood is the probability of classifying a given observant in the presence of some other variable.

6. Explain Recommender Systems?

It is a subclass of information filtering techniques. It helps you to predict the preferences or ratings which users likely to give to a product.

7. Name three disadvantages of using a linear model

Three disadvantages of the linear model are:

  • The assumption of linearity of the errors.
  • You can’t use this model for binary or count outcomes
  • There are plenty of overfitting problems that it can’t solve

8. Why do you need to perform resampling?

Resampling is done in below-given cases:

  • Estimating the accuracy of sample statistics by drawing randomly with replacement from a set of the data point or using as subsets of accessible data
  • Substituting labels on data points when performing necessary tests
  • Validating models by using random subsets

9. List out the libraries in Python used for Data Analysis and Scientific Computations.

  • SciPy
  • Pandas
  • Matplotlib
  • NumPy
  • SciKit
  • Seaborn

10. What is Power Analysis?

The power analysis is an integral part of the experimental design. It helps you to determine the sample size requires to find out the effect of a given size from a cause with a specific level of assurance. It also allows you to deploy a particular probability in a sample size constraint.

11. Explain Collaborative filtering

Collaborative filtering used to search for correct patterns by collaborating viewpoints, multiple data sources, and various agents.

12. What is bias?

Bias is an error introduced in your model because of the oversimplification of a machine learning algorithm.” It can lead to underfitting.

13. Discuss ‘Naive’ in a Naive Bayes algorithm?

The Naive Bayes Algorithm model is based on the Bayes Theorem. It describes the probability of an event. It is based on prior knowledge of conditions which might be related to that specific event.

14. What is a Linear Regression?

Linear regression is a statistical programming method where the score of a variable ‘A’ is predicted from the score of a second variable ‘B’. B is referred to as the predictor variable and A as the criterion variable.

15. State the difference between the expected value and mean value

They are not many differences, but both of these terms are used in different contexts. Mean value is generally referred to when you are discussing a probability distribution whereas expected value is referred to in the context of a random variable.

16. What the aim of conducting A/B Testing?

AB testing used to conduct random experiments with two variables, A and B. The goal of this testing method is to find out changes to a web page to maximize or increase the outcome of a strategy.

17. What is Ensemble Learning?

The ensemble is a method of combining a diverse set of learners together to improvise on the stability and predictive power of the model. Two types of Ensemble learning methods are:

Bagging

Bagging method helps you to implement similar learners on small sample populations. It helps you to make nearer predictions.

Boosting

Boosting is an iterative method which allows you to adjust the weight of an observation depends upon the last classification. Boosting decreases the bias error and helps you to build strong predictive models.

18. Explain Eigenvalue and Eigenvector

Eigenvectors are for understanding linear transformations. Data scientist need to calculate the eigenvectors for a covariance matrix or correlation. Eigenvalues are the directions along using specific linear transformation acts by compressing, flipping, or stretching.

19. Define the term cross-validation

Cross-validation is a validation technique for evaluating how the outcomes of statistical analysis will generalize for an Independent dataset. This method is used in backgrounds where the objective is forecast, and one needs to estimate how accurately a model will accomplish.

20. Explain the steps for a Data analytics project

The following are important steps involved in an analytics project:

  • Understand the Business problem
  • Explore the data and study it carefully.
  • Prepare the data for modeling by finding missing values and transforming variables.
  • Start running the model and analyze the Big data result.
  • Validate the model with new data set.
  • Implement the model and track the result to analyze the performance of the model for a specific period.
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Introduction to DevOps and Interview questions

—>DOCKER:-

1. What is Docker-file, Docker-compose, Docker-stack and Docker-volumes?
2. What is Multistaging Docker-files?
3. What is DockerFile Ignores?
4. Docker-swarm VS Kubernetes?
5. What are Docker-network types? (overlay, bridge, host..)
6. How to enable DTR(Docker Trusted Registry)?
7. How to enable SSL encryption to pull and push the images?
8. Docker File for Tomcat

—>JENKINS:-

1. How your CI/CD pipeline is getting Integrated? And all the other pipelines (git, maven, docker,…)
2. How to integrate Jenkins with AWS Ec2 instance?
3. How to perform code quality check through SonarQube?
4. What are the alternate tools for Integration other than Jenkins?
5. How to enable remote SSH login from Jenkins?
6. How to copy build to another remote Node?
7. How to enable WebHook for git hub to Jenkins?
8. How to pole Automatically to test periodically whenever any new build has been committed?
9. How to take backup of Jenkins data?
10. How to configure Email alerts?
11. How to configure role based Authorizations and Authentications from Jenkins?
12. How to integrate Active Directory(AD) from Jenkins?
13. How to execute Jenkins-file?
14. How to configure multiple Nodes for Jenkins?

—>KUBERNETES:-
1. How to deploy your Application into Kubernetes?
2. How you are going to expose your Application from Kubernetes?
3. How we are monitoring kubernetes through Prometheus, Graffana and Elastic Surge?
4. Kubernetes Maximums?
5. What are Kubernetes services like Ingress and Ingress Controller?
6. How to Create K8s using Kops and Vagrant

—>ANSIBLE:-

1. What is Ansible Playbook?
2. How to write a Ansible playbook?
3. What is Handlers, Rules and Vaults?
4. What is Notify?
5. What is Inventory and Dynamic Ansible Inventory?
6. What is meant by Ansible Module?
7. What is meant by Ansible Tower?
8. What is meant by Ansible Galaxy?
9. Ansible Templets and JINJA2 templeting?
10. Compare Ansible VS Chef VS Puppet?
11. What are the advantages of using Ansible?
12. Explain in brief how Ansible works?

—>TERRAFORM:-

1. How to create resources through Terraform?
2. What are Terraform Input Variables, Output Variables and Module Variables?
3. Terraform VS Ansible?
4. What do you mean by IaC?
5. Can Terraform be used for on-prem Infrastructure?

—>GIT:-

1. What is the difference between GIT and SVN?
2. What is a distributed VCS?
3. What is the difference between Git and Github?
4. What are benefits of used Version control system?
5. Mention the various Git repository hosting functions?
6. What is ‘Conflict’ in git? And how to resolve a Conflict in git?
7. What is the difference between git pull and git fetch?
8. How to resolve git merge conflicts?

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Interview questions for Azure

1. What is Cloud Computing?

Cloud computing is a term referred to storing and accessing data over the internet. It doesn’t store any data on the hard disk of your personal computer. In cloud computing, you are allowed accessing data from a remote server.

2. What is Microsoft Azure?

Azure is a cloud computing platform which was launched by Microsoft in Feb 2010. It is a highly flexible cloud platform that offers development, data storage, service hosting, and service management.

3. Explain the Importance of the role and how many types of roles are available in Windows Azure?

Roles are a very important concept in Windows Azure, and learning them is the base for further programming.

Three types of roles in Windows Azure are:

  • Web Role: It is used to deploy website by using langue which is supported by the IIS platform customized to run the web apps.
  • Worker Role: It helps you to execute the process that runs in the background by
  • VM Role: It helps you to schedule the windows services and task.

4. Why should you use Azure CDN?

Azure CDN should be used to reduce load time and bandwidth as well as speed the responsiveness.

5. Name some important applications of Microsoft Azure

Most important application of Microsoft Azure are:

Infrastructure Services, Mobile Apps, Web Applications, Cloud Services, Storage, Media Services, etc.

6. What is Azure as PaaS?

PaaS is a computing platform that includes an operating system, programming language execution environment, database, or web services. Developers and application providers use this type of Azure services.

7. Explain the crucial benefits of Traffic Manager

Traffic management offers many advantages for the user:

  • Increase the performance
  • No Downtime required for update or Maintenance
  • You can easily configure Azure Traffic manager on Windows Azure portal.

8. What are Break-fix issues in Microsoft Azure?

In, Microsoft Azure, all the technical problem is called break-fix issues. This term uses when “work involved in support a technology when it fails in the normal course of its function.

9. Explain Diagnostics in Windows Azure

Windows Azure Diagnostic offers the facility to store diagnostic data. In Azure, some diagnostics data is stored in the table, while some are stored in a blob. The diagnostic monitor runs in Windows Azure as well as in the computer’s emulator for collecting data for a role instance.

10. State the difference between repetitive and minimal monitoring.

Verbose monitoring collects metrics based on performance. It allows a close analysis of data fed during the process of application.

On the other hand, minimal monitoring is a default configuration method. It makes the user of performance counters gathered from the operating system of the host.

11. What is the main difference between the repository and the powerhouse server?

The main difference between them is that repository servers are instead of the integrity, consistency, and uniformity while powerhouse server governs the integration of different aspects of the database repository.

12. Explain command task in Microsoft Azure

Command task is an operational window which set off the flow of either single or multiple common whiles when the system is running.

13. What are unconnected lookups?

Unconnected lookup the input ins take by the LKP operation. In this type of lookup method, User-defined values are disregarded in the unconnected lookups.

14.Explain Cmdlet command of Microsoft Azure

A cmdlet is a command which is utilized as a part of the Microsoft PowerShell environment. The cmdlet is called by the Windows PowerShell to automate the scripts which are in the command line.

15. What is the use of the Migration Assistant tool in Azure Websites?

Migration Assistant tool helps you to examine your IIS installation. It helps you to recognize which site can be migrated to the cloud. It is also featuring components which are either not migrated or unsupported on the Azure platform.

16. What is the use of Azure Active Directory?

Azure Active Directory is an identify and access management system. It is very much similar to the active directories. It allows you to grant your employee in accessing specific products and services within the network.

17. What is HDInsight in Microsoft Azure?

HDInsight is a could service which that makes it easy. It is fast and cost-effective to process a massive amount of data using with the help of open-source frameworks like Spark, Hadoop, Hive, Storm and R. HDInsight offers various type of scenarios which includes ETL, data warehousing, and Machine Learning.

18. Explain role instance in Microsoft Azure

A role instance is a virtual instance on which the application code and role configuration run. A role can have multiple instances, which are defined in the service configuration file.

19. Explain the term ‘service fabric’ in Azure

Service fabric is a middleware platform which gives more scalable outcome. It mostly renders with a more managed and reliable enterprise.

20. Explain Availability Set

It is a logical grouping of Virtual Machines. It allows the Azure cloud to build understand how the application for a user is built to provide availability and redundancy.

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Introduction to Citrix and Interview questions

1. Which all Citrix products you are working on?
2. What are your job roles and responsibilities?
3. What all configuration you need to make for a TD to boot from a vDisk image?
4. In PVS, suppose the TD is rebooting frequently, how will you troubleshoot?
5. In PVS, when a TD reboots, what are things happening in the background?
6. Are you aware of STA?
7. What is STA?
8. In XenApp, say many users are facing problems of accessing the application. When they click on
the icon, they see the “Protocol Driver Error”. What is the cause of the problem? How will you
troubleshoot?
9. Say users are facing some problems because of a XenApp server. How will you find out which
server has the problem?
10. In Licensing, suppose a user is accessing an application, how does the licensing procedure
happens in the background? Through which port the user license is checked?
11. If there is a licensing problem, what value of farm-load will you see?
12. What is merchandizing server?
13. What is the importance of Zone?
14. Say you have 100 XenApp Servers in different geographical locations. How will you direct users
to the XenApp servers closest to their current location?
15. What is session sharing? How will you do it?
16. Say a user has a session running in 1 device. Can he run another session simultaneously from
another device?
17. Say a user has 2 applications hosted from 2 different XA servers. Will they have same or
different Session IDs?
18. How will you know that there is an IMA issue if applications are not delivering?
19. If IMA has not started, what value of farm-load will you see?
20. Do you have work experience on NetScaler?

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AWS interview questions

  • How to change key pair for ec2 instance?
  • How to change ec2 instance from one zone to another zone &one region to another region?
  • Is it possible to reset windows password in AWS?
  • How to perform Vertical and Horizontal Auto Scaling?
  • How to take back up of your ec2 instance?
  • How to create Cloud Formation templates for automatic instance creation and termination?
  • How to restore data from an Amazon RDS?
  • How to connect the Linux instance with user name and password?
  • How to enable MFA for our IAM account?
  • How to create application load balancer for host based and path based routing?
  • How to enable load balancer to auto scaling groups?
  • How to pull and push Docker images to ECR?
  • How to create ECS services connect to application load balancer?
  • How to create IAM rules and permission from console and command line?
  • How to enable cloud watch metrics, alerts and notifications?
  • How to enable cloud trail events for multi zones?
  • How to deploy PHP based application with RDS and high availability in elastic beanstalk?
  • How to run python based lambda function?
  • How to enable VPN access on premises cloud?
  • How to enable web application firewall and shield for our website?
  • How to configure cloud front and provide the edge points and edge servers for content distribution?
  • How to migrate VM to AWS?
  • How to migrate database to RDS?
  • How to run code pipeline?
  • How to integrate cloud formation template deploy from code pipeline (or) GitHub and Jenkins?
  • How to integrate Jenkins with aws ec2 instance?
  • How to enable lambda function s for Load Balancers?
  • Types of ELB S in AWS?
  • Explain Auto Scaling policies?
  • What is pre requisites for ec2 VPC peering?
  • Differences between NAT gateway and NAT instance?
  • Differences between NAT gate way and INTERNET gateway?
  • What is route table?
  • What are default route table contents?
  • How to rotate keys automatically?
  • Deploy code from code deploy to ECS container?
  • What is Code Star?
  • What is X-ray?
  • What is Cloud9?
  • What is Glacier?
  • What is Snowball?
  • What is AWS Fargate?
  • What is AWS Serve less
  • Deployment?
  • How are Spot Instance, On-demand Instance, and Reserved Instance different from one another?
  • you have all the workload on the public cloud. But, due to certain security reasons, your organization decides to distribute some of the workload on private servers.You are asked to suggest a cloud architecture for your organization. What will be your suggestion?
  • The data on the root volumes of store-backed and EBS-backed instances get deleted by default when they are terminated. If you want to prevent that from happening, which instance would you use?
  • Which one of the storage solutions offered by AWS would you use if you need extremely low pricing and data archiving?
  • You have connected four instances to ELB. To automatically
    terminate your unhealthy instances and replace them with new ones, which functionality would you use?
  • How will you configure an Amazon S3 bucket to serve static assets for your public web application?
  • Why do we make subnets?
  • what is internet gateway?
  • what is nat gateway?
  • what is cidr block?
  • what is nat instance?
  • difference between public cloud and private cloud?
  • If you launched a standby RDS, will it be launched in the same availability zone as your primary?
  • What is the maximum number of S3 buckets you can create?
  • Is it possible to switch from an Instance-backed root volume to an EBS-backed root volume at any time?
  • How can you save the data on root volume on an EBS-backed machine?
  • When should you use the classic load balancer and the application load balancer?what is the difference?
  • Which one of the following is a structured data store that supports indexing and data queries to both EC2 and S3?
  • How many total VPCs per account/region and subnets per VPC can you have?
  • Can you change the private IP address of an EC2 instance while it is in running or in a stopped state?
  • What are the types of volumes in EBS?
  • What are the different types of instances?
  • What is an auto-scaling and what are the components?
  • What are reserved instances?
  • What is an EIP?
  • What is an AMI?
  • What is Cloudwatch?
  • What are the cloudwatch metrics that are available for EC2 instances?
  • What is the minimum and maximum size of individual objects that you can store in S3
  • What are the different storage classes in S3?
  • What is the default storage class in S3?
  • What is glacier?
  • How can you secure the access to your S3 bucket?
  • How can you encrypt data in S3?
  • What are the parameters for S3 pricing?
  • What are roles?
  • What are policies and what are the types of policies?
  • What is cloudfront?
  • What is VPC peering connection?
  • What are the different types of storage gateway?
  • What are the database types in RDS?
  • What is a redshift?
  • What is SNS?
  • What are the types of routing polices in route53?
  • What is the maximum size of messages in SQS?
  • What are the types of backups in RDS database?
  • What are the types of load balancers in EC2?
  • What are the two types of access that you can provide when you are creating users?
  • By default how many Ip address does aws reserve in a subnet?
  • Is it possible to stop a RDS instance, how can I do that?
  • How to change Instance from one Region to another Region?
  • How to change Instance from one vpc to another vpc?
  • How to take backup and Restore instance?
  • How to change type of instance from type to another?
  • How to optimise performance on aws instance?
  • Differences between nat gateway and nat instance?
  • What is the difference between application and network load balancer?
  • What is the difference between ACL and Security Groups
  • What is cloud formation? what is Stack and Stackset?
  • What is Drift ? how to recognise drift status?
  • What are the metrics you will monitor in instance?
  • What is fargate?

Docker Interview questions

  1. What is Container and Docker?
  2. What is Virtulization and How docker is diff from Virtulization?
  3. What are advantages and disadvantages of docker?
  4. What is container and Image?
  5. Explain Docker Container lifecycle
  6. What are the Networking adapters supported by docker?
  7. How we can persistent container data?
  8. How we can enter in to command or how to we can run command in container?
  9. What does the volume parameter do in a docker run command?
  10. What is the main difference between the approaches of Docker and standard hypervisor virtualization?
  11. what is the docker save and docker load commands?
  12. What is the default Docker network driver,
  13. What are a Docker container’s possible  states, and what do they mean? How can you change it when running a Docker image?
  14. What is a Docker image? What is a Docker image registry?
  15. What is container orchestration and why should we use it?
  16. What features are provided by Docker Enterprise Edition instead of Docker Community Edition?
  17. Is there any problem with just using the latest tag in a container orchestration environment? 
  18. What is considered best practice for image tagging?
  19. What is Docker Swarm and which network driver should be used with it?
  20. What are the possible ways of using insecure Docker image registries?
  21. What is Docker Compose? What can it be used for?
  22. How do you scale your Docker containers?
  23. How to build envrionment-agnostic systems with Docker?
  24. What are the most common instructions in Dockerfile?
  25. What type of applications – Stateless or Stateful are more suitable for Docker Container?
  26. Explain basic Docker usage workflow?
  27. How will you monitor Docker in production?
  28. What is an orphant volume and how to remove it?
  29. How is Docker different from a virtual machine?
  30. Can you explain Dockerfile ONBUILD instruction?
  31. Is it good practice to run stateful applications on Docker? What are the scenarios where Docker best fits in?
  32. Can you run Docker containers natively on Windows?
  33. How does Docker run containers in non-Linux systems?
  34. How containers works at low level?
  35. Name some limitations of containers vs VM?
  36. Why Docker compose does not wait for a container to be ready before moving on to start next service in dependency order?
  37. What is Docker file and how we can create image from Dockerfile?
  38. What are the Differances between Dockerfile and DockerCompose
  39. Tell Important Instructions used in Dockerfile
  40. What are the differences between COPY and ADD in Dockerfile
  41. What are the differences between CMD and RUN
  42. What are the differences between ENTRYPOINT and CMD
  43. What is dockerhub and DTR
  44. What are the disadvantages of using dockerhub
  45. What is Amazon ECR? how to push image to ECR?
  46. What is DTR and how we can secure image push to Docker Registry?
  47. What are the differences between Docker PUll and Docker push?
  48. What is docker commit command ? How we can create image from container?
  49. What is docker service ?command to create docker service
  50. What is docker stack ? How to create stack ?
  51. what are the differences between docker compose vs stack?
  52. What is .dockerignore file?why we will use in Dockerfile?
  53. What is docker machine? explain the command using drivers for AWS and Azure?
  54. What is docker swarm ? how we can create docker swarm and how we can add nodes?
  55. is docker swarm supports multi manager docker swarm cluster?
  56. How to promote docker worker in to manager in docker swarm
  57. How to list nodes in docker swarm?
  58. How to attach volume to Docker container and service
  59. What is docker tmpfs volume?
  60. What is multistage docker files?
  61. What are the advantages of using multistage docker file?
  62. How we can perform update and rollback in docker swarm?
  63. What are the differences between docker swarm and kubernetes
  64. Explain docker compose /docker stack file format
  65. How we can link two containers?
  66. Explain how we can integrate docker with Jenkins for CI and CD