Top 20 Amazon Athena Interview Questions and Answers

 

        Amazon Athena is an interactive query service that makes it simple to use normal SQL to evaluate data in Amazon S3. Because Athena is serverless, you don't have to worry about maintaining infrastructure, and you just pay for the queries you run.

Athena is simple to operate. Simply point to your Amazon S3 data, define the schema, and begin querying using regular SQL. The majority of results arrive in seconds. There's no need for complicated ETL procedures to prepare your data for analysis with Athena. This makes it simple for anyone with SQL expertise to study massive datasets fast.

AWS Glue Data Catalog is pre-integrated with Athena, allowing you to construct a uniform metadata repository across multiple services, explore data sources to locate schemas, populate your Catalog with new and amended table and partition definitions, and maintain schema versioning.

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Ques. 1): What is Amazon Athena all about?

Answer:

Amazon Athena is an interactive query service that makes it simple to use normal SQL to evaluate data in Amazon S3. Because Athena is serverless, there is no infrastructure to set up or operate, and you can immediately begin analysing data. You don't even have to load your data into Athena; it works with S3 data immediately. Simply log into the Athena Management Console, create your schema, and begin querying. Amazon Athena works with a range of standard data formats, including CSV, JSON, ORC, Apache Parquet, and Avro, and leverages Presto with full SQL support. While Amazon Athena is great for interactive analytics and interacts with Amazon QuickSight for quick visualisation, it's not the most user-friendly platform. it can also handle complex analysis, including large joins, window functions, and arrays.

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Ques. 2): What makes Amazon Athena, Amazon EMR, and Amazon Redshift different?

Answer:

Different demands and use cases are addressed by query services like Amazon Athena, data warehouses like Amazon Redshift, and advanced data processing frameworks like Amazon EMR. All you have to do now is pick the correct tool for the job. For enterprise reporting and business intelligence workloads, Amazon Redshift provides the fastest query performance, especially for those utilising extremely sophisticated SQL with numerous joins and sub-queries. When compared to on-premises deployments, Amazon EMR makes running highly distributed processing frameworks like Hadoop, Spark, and Presto straightforward and cost effective. You can execute bespoke apps and code on Amazon EMR, as well as configure particular computing, memory, storage, and application parameters to maximise your analytic needs. Amazon Athena makes it simple to execute interactive queries over S3 data without having to set up or manage any servers.

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Ques. 3): When should I utilise Amazon EMR and when should I use Amazon Athena?

Answer:

Amazon EMR is capable of much more than just conducting SQL queries. You can use EMR to conduct a variety of scale-out data processing activities for applications like machine learning, graph analytics, data transformation, streaming data, and almost anything else you can think of. If you utilise custom code to handle and analyse extremely huge datasets with the latest big data processing frameworks like Spark, Hadoop, Presto, or Hbase, you should use Amazon EMR. Amazon EMR allows you complete control over the configuration and applications installed on your clusters.

If you want to conduct interactive SQL queries against data on Amazon S3 without having to manage any infrastructure or clusters, you should utilise Amazon Athena.

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Ques. 4): What data formats is Amazon Athena compatible with?

Answer:

Amazon Athena can handle a wide range of data formats, including CSV, TSV, JSON, and Textfiles, as well as open source columnar formats like Apache ORC and Apache Parquet. Snappy, Zlib, LZO, and GZIP compressed data formats are also supported by Athena. You can increase speed and lower costs by compressing, dividing, and adopting columnar formats.

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Ques. 5): I'm getting data from Kinesis Firehose. How can I use Athena to query it?

Answer:

You can use Amazon Athena to query your Kinesis Firehose data if it's hosted on Amazon S3. Simply construct an Athena schema for your data and begin querying. To improve efficiency, we recommend dividing the data into parts. ALTER TABLE DDL instructions can be used to add partitions produced by Kinesis Firehose. Get more information on partitions.

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Ques. 6): How can I make my query perform better?

Answer:

By compressing, splitting, or turning your data into columnar formats, you can increase the performance of your query. Apache Parquet and Apache ORC are two open source columnar data formats that Amazon Athena supports. By allowing Athena to scan less data from S3 when executing your query, converting your data into a compressed, columnar format minimizes your costs and increases query performance.

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Ques. 7): What is a federated query, exactly?

Answer:

If you have data in places other than Amazon S3, you may use Athena to query it or create pipelines to extract data from numerous sources and put it in Amazon S3. You can perform SQL queries against data stored in relational, non-relational, object, and custom data sources using Athena Federated Query.

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Ques. 8): Can I do ETL (Extract, Transform, Load) using federated queries?

Answer:

Athena stores query results in an Amazon S3 file. This means Athena may be used to make federated data accessible to other users and apps. Use Athena's CREATE TABLE AS function to perform analysis on the data without having to query the underlying source frequently. You may also query the data using Athena's UNLOAD function and save the results in a specific file format to Amazon S3.

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Ques. 9): What embedded ML use cases does Athena support?

Answer:

The following examples show how Athena can be used in a variety of sectors. What-if analysis and Monte Carlo simulations are available to financial risk data analysts. To aid in the creation of richer and forward-looking business dashboards that forecast revenues, business analysts may use linear regression or forecasting models to predict future values. K-means clustering methods could aid marketing analysts in determining their various client categories. Logical regression models could be used by security analysts to uncover abnormalities and detect security incidents in logs.

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Ques. 10): What capabilities does Athena ML have?

Answer:

Athena provides machine learning inference (prediction) capabilities using a SQL interface. You can also use an Athena UDF to perform pre- or post-processing logic on your result set. Multiple calls can be batched together for increased scalability, and inputs can be any column, record, or table. Inference can be performed during the Select or Filter phases.

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Ques. 11): Is Athena highly available?

Answer:

Yes. Amazon Athena is highly available, executing queries across many facilities and intelligently routing queries correctly if one of the facilities is unavailable. Athena's underlying data store is Amazon S3, which makes your data highly available and durable. Amazon S3 provides a reliable infrastructure for storing essential data, with 99.999999999 percent object durability. Your information is duplicated across numerous facilities and devices inside each facility.

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Ques. 12): What should I do to lower the costs?

Answer:

By compressing, splitting, and turning your data into columnar formats, you can save 30 percent to 90 percent on query costs while also improving performance. Each of these actions reduces the quantity of data that Amazon Athena must scan in order to complete a query. Apache Parquet and ORC, two of the most popular open-source columnar formats, are supported by Amazon Athena. On the Athena console, you can view how much data was scanned for each query.

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Ques. 13): Are there any other fees related with Amazon Athena?

Answer:

Your source data is invoiced at S3 rates because Amazon Athena queries data directly from Amazon S3. When you perform a query through Amazon Athena, the results are saved in an S3 bucket of your choosing, and you are charged at standard S3 rates for these result sets. We recommend that you keep an eye on these buckets and utilise lifecycle policies to limit how much data is kept.

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Ques. 14): Does the User Defined Functions (UDFs) are supported by Athena?

Answer:

User-defined functions (UDFs) in Amazon Athena allow you to create new scalar functions and utilise them in SQL queries. While Athena has built-in capabilities, UDFs allow you to conduct custom processing such as data compression and decompression, redaction of sensitive material, and bespoke decryption.

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Ques. 15): In Amazon Athena, how can I add new data to an existing table?

Answer:

If your data is partitioned, you'll need to run an ALTER TABLE ADD PARTITION metadata query to add the partition to Athena once new data is available on Amazon S3. If your data isn't partitioned, simply adding new data (or files) to an existing prefix will add them to Athena.

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Ques. 16): What exactly is a SerDe?

Answer:

Serializer/Deserializer are libraries that teach Hive how to understand different data formats. You must mention a SerDe in Hive DDL statements so that the system knows how to interpret the data you're pointing to. SerDes is used by Amazon Athena to analyse data read from Amazon S3. SerDes is the same notion in Athena as it is in Hive. The following SerDes are supported by Amazon Athena:

Apache Web Logs: "org.apache.hadoop.hive.serde2.RegexSerDe"

CSV: "org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe"

TSV: "org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe"

Custom Delimiters: "org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe"

Parquet: "org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe"

Orc: "org.apache.hadoop.hive.ql.io.orc.OrcSerde"

JSON: “org.apache.hive.hcatalog.data.JsonSerDe” OR org.openx.data.jsonserde.JsonSerDe

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Ques. 17): Can I query data processed with Amazon EMR using Amazon Athena?

Answer:

Yes, Amazon Athena and Amazon EMR both support many of the same data formats. The Athena data catalogue is compatible with the Hive metastore. If you're utilising EMR and already have a Hive metastore, you can query your data straight away without affecting your Amazon EMR operations by executing your DDL statements on Amazon Athena.

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Ques. 18): How are table definitions and schema stored in Amazon Athena?

Answer:

To keep information and schemas about the databases and tables you create for your data saved in Amazon S3, Amazon Athena employs a managed Data Catalog. You can use the AWS Glue Data Catalog with Amazon Athena in regions where AWS Glue is accessible. Athena uses an internal Catalog in regions where AWS Glue is not available.

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The catalogue can be modified using DDL statements or the AWS Management Console. Unless you delete them directly, any schemas you define are automatically stored. Athena leverages schema-on-read technology, which means that when queries are run, your table definitions are applied to your data on S3. There’s no data loading or transformation required. You can delete table definitions and schema without impacting the underlying data stored on Amazon S3.

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Ques. 19): Can I use Athena to run any Hive query?

Answer:

Hive is only used by Amazon Athena for DDL (Data Definition Language) and for creating, modifying, and deleting tables and partitions. For a complete list of statements that are supported, please check here. When you run SQL queries on Amazon S3, Athena uses Presto. To query your data in Amazon S3, you can use ANSI-Compliant SQL SELECT queries.

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Ques. 20): Is data partitioning possible with Amazon Athena?

Answer:

Yes. You can segment your data on any column with Amazon Athena. Partitions reduce the quantity of data scanned by each query, resulting in cost savings and faster performance. The PARTITIONED BY clause in the CREATE TABLE statement allows you to specify your partitioning plan.  

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Ques. 21): What is the purpose of data source connectors?

Answer:

A data source connector is a piece of AWS Lambda code that bridges the gap between your target data source and Athena. You can conduct SQL queries on federated data stores after using a data source connector to register a data store with Athena. When a query is conducted on a federated source, Athena invokes the Lambda function, which is tasked with executing the parts of your query that are unique to the federated source.

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Top 20 Apache Pig Interview Questions and Answers

 

            Pig is an Apache open-source project that runs on Hadoop and provides a parallel data flow engine. It contains the pig Latin language, which is used to express data flow. It includes actions such as sorting, joining, filtering, and scripting UDF (User Defined Functions) for reading, writing, and processing. Pig stores and processes the entire task using Map Reduce and HDFS.

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Ques. 1): What benefits does Pig have over MapReduce?

Answer:

The development cycle for MapReduce is extremely long. It takes a long time to write mappers and reducers, compile and package the code, submit tasks, and retrieve the results. Dataset joins are quite complex to perform. Low level and stiff, resulting in a large amount of specialised user code that is difficult to maintain and reuse is difficult.

Pig does not require the compilation or packaging of code. Pig operators will be turned into maps or jobs will be reduced internally. Pig Latin supports all common data-processing procedures, as well as high-level abstraction for processing big data sets.

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Ques. 2): Is Piglatin a Typographically Strong Language? If so, how did you arrive at your conclusion?

Answer:

In a strongly typed language, the type of all variables must be declared up front. When you explain the schema of the data in Apache Pig, it expects the data to be in the same format.

When the schema is unknown, however, the script will adjust to the actual data types at runtime. PigLatin can thus be described as firmly typed in most circumstances but gently typed in others, i.e. it continues to work with data that does not meet its expectations.

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Ques. 3): What are Pig's disadvantages?

Answer:

Pig has a number of flaws, including:

Pig isn't the best choice for real-time applications.

When you need to get a single record from a large dataset, Pig isn't very useful.

It works in batches since it uses MapReduce.

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Ques. 4): What is Pig Storage, exactly?

Answer:

Pig comes with a default load function called Pig Storage. Additionally, we may use pig storage to import data from a file system into the pig.

While loading data into pig storage, we may also provide the data delimiter (how the fields in the record are separated). We can also provide the data's schema as well as the data's type.

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Ques. 5): Explain Grunt in Pig and its characteristics.

Answer:

The Grunt takes on the role of an Interactive Shell Pig. Grunt's main characteristics are:

To move the cursor to the end of a line, press the ctrl-e key combination.

As a Grunt retains command history, the lines in the history buffer can be recalled using the up and down cursor keys.

Grunt supports the auto-completion method by attempting to finish Pig Latin keywords and functions when the Tab key is hit.

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Ques. 6): What Does Pig Flatten Mean?

Answer:

When there is data in a tuple or a bag, we may use the Flatten modifier in Pig to remove the level of nesting from that data. Un-nests bags and tuples should be flattened. The Flatten operation for tuples will substitute the fields of a tuple for a tuple, however un-nesting bags is a little more complicated because it necessitates the creation of new tuples.

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Ques. 7): Can you distinguish between logical and physical plans?

Answer:

Pig goes through a few processes while converting a Pig Latin Script into MapReduce jobs. Pig generates a logical plan after performing basic parsing and semantic testing. Pig's logical plan, which is executed during execution, describes the logical operators. Pig then generates a physical plan. The physical plan specifies the physical operators required to execute the script.

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Ques. 8): In Pig, what does a co-group do?

Answer:

Co-group unites the data collection by grouping only one of the data sets. It then groups the elements by their common field and provides a set of records with two distinct bags. The records of the first data set with the common data set are in the first bag, and the records of the second data set with the same data set are in the second bag.

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Ques. 9): Explain the bag.

Answer:

Pig includes several data models, including a bag. The bag is an unorganised collection of tuples with possibly duplicates that is used to store collections while they are being grouped. The size of the bag is equal to the size of the local disc, implying that the bag's size is limited. When the bag is full, Pig will empty it onto the local disc and only maintain a portion of it in memory. It is not necessary for the entire bag to fit into memory. With ", we signify bags.

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Ques. 10): Can you describe the similarities and differences between Pig and Hive?

Answer:

Both Hive and Pig have similar characteristics.

Both internally transform the commands to MapReduce.

High-level abstractions are provided by both technologies.

Low-latency queries are not supported by either.

OLAP and OLTP are not supported by either.

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Ques. 11): How do Apache Pig and SQL compare?

Answer:

The use of Apache Pig for ETL, lazy evaluation, storing data at any stage in the pipeline, support for pipeline splits, and explicit specification of execution plans set it apart from SQL. SQL is built around queries that return only one result. SQL doesn't have a built-in mechanism for separating a data processing stream into sub-streams and applying various operators to each one.

User code can be added at any step in the pipeline with Apache Pig, whereas with SQL, data must first be put into the database before the cleaning and transformation process can begin.

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Ques. 12): Can Apache Pig Scripts Join Multiple Fields?

Answer:

Yes, several fields can be joined in PIG scripts since join procedures take records from one input and combine them with records from another. This is accomplished by specifying the keys for each input and joining the two rows when the keys are equal.

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Ques. 13): What is the difference between the commands store and dumps?

Answer:

After running the dump command, the data appears on the console, but it is not saved. Whereas the output is executed in a folder and the store is stored in the local file system or HDFS. Most hadoop developers utilised the'store' command to store data in HDFS in a protected environment.

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Ques. 14):  Is 'FUNCTIONAL' a User Defined Function (UDF)?

Answer:

No, the keyword 'FUNCTIONAL' does not represent a User Defined Function (UDF). Some functions must be overridden while using UDF. You must certainly complete your tasks using only these functions. However, because the keyword 'FUNCTIONAL' is a built-in function (a pre-defined function), it cannot be used as a UDF.

 

Ques. 15): Which method must be overridden when writing evaluate UDF?

Answer:

When developing UDF in Pig, we must override the method exec(). While the base class may change, when developing filter UDF, we must extend FilterFunc, and when writing evaluate UDF, we must extend EvalFunc. EvaluFunc is parameterized, and the return type must be specified as well.

 

Ques. 16): What role does MapReduce play in Pig programming?

Answer:

Pig is a high-level framework that simplifies the execution of various Hadoop data analysis problems. A Pig Latin programme is similar to a SQL query that is executed using an execution engine. The Pig engine can convert programmes into MapReduce jobs, with MapReduce serving as the execution engine.

 

Ques. 17): What Debugging Tools Are Available For Apache Pig Scripts?

Answer:

The essential debugging utilities in Apache Pig are describe and explain.

When trying to troubleshoot or optimise PigLatin scripts, Hadoop developers will find the explain function useful. In the grunt interactive shell, explain can be applied to a specific alias in the script or to the entire script. The explain programme generates multiple text-based graphs that can be printed to a file.

When building Pig scripts, the describe debugging utility is useful since it displays the schema of a relation in the script. Beginners learning Apache Pig can use the describe utility to see how each operator alters data. A pig script can have multiple describes.

 

Ques. 18): What are the relation operations in Pig? Explain any two with examples.

Answer:

The relational operations in Pig:

foreach, order by, filters, group, distinct, join, limit.foreach: It takes a set of expressions and applies them to all records in the data pipeline to the next operator.A =LOAD ‘input’ as (emp_name :charrarray, emp_id : long, emp_add : chararray, phone : chararray, preferences : map [] );B = foreach A generate emp_name, emp_id;Filters: It contains a predicate and it allows us to select which records will be retained in our data pipeline.

Syntax: alias = FILTER alias BY expression;

Alias indicates the name of the relation, By indicates required keyword and the expression has Boolean.

Example: M = FILTER N BY F5 == 50;

 

Ques. 19): What are some Apache Pig use cases that come to mind?

Answer:

The Apache Pig large data tools are used for iterative processing, raw data exploration, and standard ETL data pipelines. Pig is commonly used by researchers who want to use the data before it is cleansed and placed into the data warehouse because it can operate in situations where the schema is unknown, inconsistent, or incomplete.

It can be used by a website to track the response of users to various sorts of adverts, photos, articles, and so on in order to construct behaviour prediction models.

 

Ques. 20): In Apache Pig, what is the purpose of illustrating?

Answer:

Illustrate is used to run Pig scripts on large datasets, which might take a long time. That is why developers run pig scripts on sample data, even though it is probable that the sample data selected will not execute the script correctly. If the script includes a join operator, for example, there must be a small number of records in the sample data with the same key, or the join operation will fail. Developers manage these issues by using the function illustrate, which takes data from the sample and ensures that some records pass through while others are restricted by modifying records in such a way that they follow the condition set whenever it encounters operators like the filter or join, which remove data. Illustrate displays each step's output but does not run MapReduce operations.

 

 

 

Top 20 C# Language Interview Questions and Answers

  

        Microsoft's C# is an object-oriented programming language. The.NET framework uses C# to create websites, applications, and games. C# is popular for a variety of reasons. C# is described as being easier to learn than other programming languages. You're more likely to construct online applications or gaming apps with C#. Automatic garbage collection, interfaces, and other features in C# enable developers create better apps.

Collaboration with Microsoft gives C# applications an advantage since they can reach a broader audience. Because C# is such a popular programming language, many large and small businesses utilise it to build their products. So, to ace the interviews, prepare yourself with basic and advanced level C# questions.

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Ques. 1): Is it possible to run several catch blocks?

Answer:

No, you cannot execute multiple catch blocks of the same type. Control is handed to the finally block after the correct catch code has been completed, and then the code that follows the finally block is executed.

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Ques. 2): What exactly are the distinctions between public, static, and void?

Answer:

Anywhere in the application, public stated variables or methods are accessible. Without generating an instance of the class, static declared variables or methods are globally available. The type of access modification used determines whether or not static members are globally available by default. The method's address is saved as the entry point, and the compiler utilises this information to start execution before any objects are generated. And Void is a type modifier that indicates that the method or variable returns nothing.

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Ques. 3): In C#, what is garbage collection?

Answer:

Garbage collection is the process of releasing memory held by undesirable things. When you create a class object, some heap memory space is automatically allocated to the object. After you've completed all of the activities on the item, the memory space it takes up becomes wasted. Memory must be made available. Garbage collection occurs in three situations:

• If the occupied memory by the objects exceeds the pre-set threshold value.
• If the garbage collection method is called
• If your system has low physical memory

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Ques. 4): Define Constructors in  C#.

Answer:

A function Object() { [native code] } is a member function that has the same name as the class it belongs to. When an object class is created, the function Object() { [native code] } is called automatically. While initialising the class, it constructs the values of data members.

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Ques. 5): What exactly are Jagged Arrays?

Answer:

The array with array elements is known as a jagged array. The elements can be of various shapes and sizes. An Array of arrays is another name for jagged Array.

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Ques. 6): What is the difference between Custom Control and User Control?

Answer:

Custom Controls are compiled code (Dll) controls that are easier to use and may be added to the toolbox. Developers can add controls to their web forms by dragging and dropping them. At design time, attributes can be used. Custom controls can be simply added to multiple applications (If Shared Dlls). If they are private, we can copy the dll to the web application's bin directory, add a reference, and use them.

User Controls are comparable to ASP include files in that they are simple to construct. It is not possible to drag and drop user controls into the toolbox. They have their own code and design. Ascx is the file extension for user controls.

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Ques. 7): What’s the difference between the Array.CopyTo() and Array.Clone()?

Answer:

The Clone() method copies an array shallowly. A shallow copy of an Array duplicates only the elements of the Array, regardless of whether they are reference or value types, but not the objects to which the references link. The references in the new Array point to the same objects as the previous Array's references.

The Array class's CopyTo() static function copies a piece of one array to another array. The CopyTo method transfers all of an array's items to a new one-dimensional array. Listing 9 shows how to copy the contents of an integer array to an array of object types.

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Ques. 8): In C#, what are the different types  of classes?

Answer:

A class is a logical unit that contains all of the properties of its objects and instances. There are four sorts of such classes in C#:

Static type: The keyword'static' defines a class that does not allow inheritance. As a result, you won't be able to construct an object for a static class.

static class classname 

{ 

  //static data members 

  //static methods 

}

Partial class: Partially divided or shared source (.cs) files are possible with the partial class, which is defined by the term 'partial.'

Abstract class: Abstract classes are classes that cannot be instantiated and cannot be used to construct objects. Abstract classes are based on the OOPS abstraction idea. Abstraction aids in separating important details from those that aren't.

Sealed class: A sealed class is one that can't be inherited. To prevent users from inheriting that class, use the keyword sealed.

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Ques. 9): What is IEnumerable<> in C#?

Answer:

 IEnumerable is the parent interface for all non-generic collections in System.Collections namespace like ArrayList, HastTable etc. that can be enumerated. For the generic version of this interface as IEnumerable<T> which a parent interface of all generic collections class in System.Collections.Generic namespace like List<> and more.

 In System.Collections.Generic.IEnumerable<T> have only a single method which is GetEnumerator() that returns an IEnumerator. IEnumerator provides the power to iterate through the collection by exposing a Current property and Move Next and Reset methods if we don’t have this interface as a parent so we can’t use iteration by foreach loop or can’t use that class object in our LINQ query.

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Ques. 10): In C#, what are extension methods? How may extension techniques be used?

Answer:

Extension methods allow you to add methods to existing types without having to create a new derived type, recompile it, or modify it in any way.

An extension method is a form of static method that is referred to as if it were an instance method on the extended type.

A static method of a static class with the "this" modifier appended to the first parameter is called an extension method. The extended type will be the type of the first parameter.

Extension methods are only in scope if you use a using directive to explicitly import the namespace into your source code.

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Ques. 11): What makes the System.String and System.Text.StringBuilder classes different?

Answer:

System.Strings are unchangeable. When we change the value of a string variable, the existing memory allocation is released and fresh memory is allocated to the new value. System. StringBuilder was created with the idea of a mutable string that can be used for a number of operations without requiring a separate memory address for the updated string.

Ques. 12): What are Generics in C#?

Answer:

In C# collections, defining any kind of object is termed okay which compromises C#’s basic rule of type-safety. Therefore, generics were included to type-safe the code by allowing re-use of the data processing algorithms. Generics in C# mean not linked to any specific data type. Generics reduce the load of using boxing, unboxing, and typecasting objects. Generics are always defined inside angular brackets <>. To create a generic class, this syntax is used:

GenericList<float> list1 = new GenericList<float>();

GenericList<Features> list2 = new GenericList<Features>();

GenericList<Struct> list3 = new GenericList<Struct>();

Here, GenericList<float> is a generic class. In each of these instances of GenericList<T>, every occurrence of T in the class is substituted at run time with the type argument. By substituting the T, we have created three different type-safe using the same class.

 

Ques. 13): In C#, how do you tell the difference between boxing and unboxing?

Answer:

Both boxing and unboxing are used to convert types, however they have some differences:

Boxing: Boxing is the conversion of a value type data type to an object or any interface data type that this value type implements. When the CLR converts a value type to an Object Type, it wraps the value in a System.Object and stores it in the application domain's heap region.

 

Unboxing: Unboxing is a technique for determining the value type of an object or any implemented interface type. Unboxing, on the other hand, must be done explicitly via code.

 The concept of boxing and unboxing underlies the C# unified view of the type system in which a value of any type can be treated as an object.

 

Ques. 14): What is the difference between a struct and a class in C#?

Answer:

Class and struct are both user-defined data types, but have some major differences:

Struct

• The struct is a value type in C# and it inherits from System.Value Type.
• Struct is usually used for smaller amounts of data.
• Struct can’t be inherited from other types.
• A structure can't be abstract.
• No need to create an object with a new keyword.
• Do not have permission to create any default constructor.

Class

• The class is a reference type in C# and it inherits from the System.Object Type.
• Classes are usually used for large amounts of data.
• Classes can be inherited from other classes.
• A class can be an abstract type.
• We can create a default constructor.

 

Ques. 15): What is the difference between the dispose and finalize methods in C#?

Answer:

Both finalise and dispose are strategies for releasing unmanaged resources.

 Finalize: 

• Finalize is used to liberate unmanaged resources in the application domain that are no longer in use, such as files and database connections.
• These are the resources that an object has before it is destroyed. Garbage Collector calls it in the internal process, and no user code or service can call it manual.
• Finalize belongs to System.Object class.
• When your code contains unmanaged resources, use it to ensure that these resources are removed when garbage collection occurs.

Dispose: 

• Dispose can also be used to liberate unmanaged resources in the Application domain, such as files and database connections, at any time.
• Manual user code directly calls dispose.
• We must implement the disposal method via the IDisposable interface if we want to use it.
• It's a part of the IDisposable interface.
• When building a custom class that will be used by other users, remember to include this.

 

Ques. 16): In C#, what is the difference between late and early binding?

Answer:

One of the key concepts of OOPS is polymorphism, which includes late binding and early binding.

For example, one function calculateBill() will calculate premium, basic, and semi-premium clients' bills differently depending on their plans. The calculations for all of the customer objects are done differently using the same polymorphism function.

The.NET framework conducts the binding when an object is allocated to an object variable in C#.

Early binding occurs when the binding function is performed at build time. It investigates and tests the static objects' methods and properties. The amount of run-time mistakes is significantly reduced with early binding, and it executes swiftly.

Late binding, on the other hand, occurs when the binding occurs at runtime. Late binding occurs when run-time objects are dynamic (determined by the data they contain). It's slower because it's looking through during the process.

 

Ques. 17): Is it possible to utilise "this" inside a static method?

Answer:

Because the keyword 'this' returns a reference to the current instance of the class containing it, we can't use it in a static method. Static methods (or any other static element) are not associated with a specific instance. We can't use this keyword in the body of static Methods since they exist without creating an instance of the class and are called with the name of the class, not by instance. In the case of Extension Methods, however, we can use the function's parameters.

Let's take a look at the keyword "this."

The "this" keyword in C# is a particular form of reference variable that is implicitly defined as the first parameter of the type class in which it is specified within each function Object() { [native code] } and non-static function.

 

Ques. 18): What are delegates in C# and how do you utilise them?

Answer:

A Delegate is an abstraction of one or more function pointers (as in C++; a detailed explanation is beyond the scope of this article). The concept of function pointers has been implemented in the form of delegates in.NET. You can use delegates to treat a function like data. Functions can be supplied as parameters, returned as a value, and saved in an array using delegates. The following are qualities of delegates:

• Delegates are derived from the System.MulticastDelegate class.
• They have a signature and a return type. A function that is added to delegates must be compatible with this signature.
• Delegates can point to either static or instance methods.
• Once a delegate object has been created, it may dynamically invoke the methods it points to at runtime.
• Delegates can call methods synchronously and asynchronously.

There are a few useful fields in the delegate. The first has an object reference, whereas the second contains a method pointer. The instance method on the contained reference is called when you call the delegate. If the object reference is nil, however, the runtime interprets this to suggest that the method is static. Furthermore, calling a delegate is syntactically identical to calling a regular function. Delegates are thus ideal for implementing callbacks.

 

Ques. 19): In C#, describe accessibility modifiers. Why should you use access modifiers?

Answer:

Access modifiers are keywords that specify a member's or type's declared accessibility.

Access modifiers are keywords that describe the accessibility of a type member or the type itself. A public class, for example, is open to the entire world, whereas an internal class is only open to the assembly.

Object-oriented programming relies heavily on access modifiers. To implement OOP encapsulation, access modifiers are utilised. You can use access modifiers to control who has and doesn't have access to particular functionalities.

In C# there are 6 different types of Access Modifiers:

public:    There are no restrictions on accessing public members.

Private:    Access is limited to within the class definition. This is the default access modifier type if none is formally specified

protected:    Access is limited to within the class definition and any class that inherits from the class

internal:    Access is limited exclusively to classes defined within the current project assembly

protected internal:    Access is limited to the current assembly and types derived from the containing class. All members in the current project and all members in derived class can access the variables.

private protected:    Access is limited to the containing class or types derived from the containing class within the current assembly.

 

Ques. 20): In C#, how do you use the using statement?

Answer:

The using keyword in C# can be used in two ways. One is in the form of a mandate, while the other is in the form of a statement. Let me clarify!

using Directive:

In code-behind and class files, we usually utilise the using keyword to add namespaces. Then it makes all the classes, interfaces, and abstract classes on the current page, as well as their methods and properties, available.

Using Statement :

Another approach to utilise the using keyword in C# is as follows. It is critical to enhance garbage collection performance.

Top 20 Oracle 10g Interview Questions and Answers

 

             The Oracle Database 10g Standard Edition is designed for medium-sized businesses. Oracle's Real Application Cluster features are included to protect against hardware failures. It's simple to set up and configure, and it includes its own clustering software, storage management, and other self-managing features. Oracle Database 10g Standard Edition maintains all of your data and lets all of your business applications to benefit from Oracle Database's renowned performance, security, and reliability. It also has full upward compatibility with Oracle Database 10g Enterprise Edition, ensuring that your investment is protected as your needs change.

Oracle Fusion Applications interview Questions and Answers

Ques. 1): What are the components of an Oracle database's logical database structure?

Answer:

The following are the components of Oracle's logical database structure:

Tablespaces: Tablespaces are the logical storage units that make up a database. This tablespace is a collection of logical structures that are linked together. To be more specific, tablespace groupings are linked to logical structures.

Database Schema Objects: A schema is a set of database objects that belong to a single user. Tables, indexes, views, stored procedures, and other objects are among the objects. The user is the account in Oracle, and the schema is the object. It is also possible to have a schema without specifying a user in database platforms.

Oracle Accounts Payables Interview Questions and Answers

Ques. 2): What is the connection between the database, tablespace, and data file?

Answer:

An Oracle database has one or more tablespaces, which are logical storage units. Each tablespace in an Oracle database is made up of one or more datafiles. The complete data of databases is stored in these tablespaces. When we talk about datafiles, we're talking about the physical structure that tells the operating system which Oracle software is running.

Oracle ADF Interview Questions and Answers

Ques. 3): What is the difference between DB file sequential read and DB File Scattered Read ?

Answer:

DB File Scattered Read is related to index read, whereas DB File Sequential Read is related to whole table scan. DB File sequential read reads blocks into contiguous memory, whereas DB File dispersed read reads multiple blocks into buffer cache.

Oracle Access Manager Interview Questions and Answers

Ques. 4): Which variables should be addressed when establishing a table index? How do I choose a column for indexing?

Answer:

The size of the database and the amount of data determine how an index is created. If the table is vast and only a few data points are required for selection or reporting, an index must be created. Cardinality and frequent usage in the where condition of a select query are two primary reasons for selecting columns for indexing. Because configuring main key or unique key immediately creates unique index, the business rule also forces the creation of indexes like primary keys.

It is important to note that creation of so many indexes would affect the performance of DML on table because in single transaction should need to perform on various index segments and table simultaneously.

Oracle Fusion HCM Interview Questions and Answers

Ques. 5): What does Oracle's ANALYZE command do?

Answer:

This command "Analyze" is used to conduct different operations on an index, table, or cluster. The following is a list of Oracle commands that use the ANALYZE command:

The Analyze command is used to find migrated and chained table or cluster rows.

It is used to verify an object's structure.

This assists in gathering statistics about the object that the user is using, which are subsequently put in the data dictionary.

It also aids in the deletion of statistics from the data dictionary that are used by an object.

Oracle SCM Interview Questions and Answers

Ques. 6): What is the DUAL table's data type?

Answer:

The Dual table is a single-column table in the Oracle database. Dummy is a single Varchar2(1) column in this table with the value 'X'.

Oracle Financials Interview questions and Answers

Ques. 7): Is it possible to create an index online?

Answer:

YES. Indexes can be created and rebuilt online. This allows you to change basic tables while also building or rebuilding indexes on those tables. DML actions are permitted while the index is being built, but DDL operations are not permitted.

When constructing or rebuilding an index online, parallel execution is not supported.

CREATE INDEX emp_name ON emp (mgr, emp1, emp2, emp3) ONLINE;

Oracle Cloud Interview Questions and Answers

Ques. 8): When the R/3 system is active, why is a small dump written during an offline backup?

Answer:

BRBACKUP terminates the database during an offline backup, however the present R/3 system is unaware of this. As a result, the first work process that loses its database connection creates a small dump. Until the database is available again, all work processes move into reconnect mode. As a result, because the database cannot be accessed, one (or more) brief dumps are usually produced during an offline backup.

Oracle PL/SQL Interview Questions and Answers

Ques. 9): How can you track a user's password change in Oracle?

Answer:

Oracle only keeps track of the password's expiration date based on when it was last modified. You may discover when a password was last changed by listing the view DBA USERS.EXPIRY DATE and subtracting PASSWORD LIFE TIME. The PTIME column in the USER$ database (on which the DBA USERS view is based) can also be used to check the last password change time. However, if PASSWORD REUSE TIME and/or PASSWORD REUSE MAX are configured in a profile given to a user account, you can look up the password change date in the dictionary table USER HISTORY$.

SELECT user$.NAME, user$.PASSWORD, user$.ptime, user_history$.password_date

FROM SYS.user_history$, SYS.user$

WHERE user_history$.user# = user$.user#;

Oracle SQL Interview Questions and Answers

Ques. 10): What is Secure External password Store (SEPS) ?

Answer:

You can store password credentials for connecting to databases using SEPS by utilising a client-side Oracle wallet, which also stores signing credentials. This capability has been available since Oracle 10g. Thus, embedded username and passwords were no longer required in application code, scheduled jobs, or scripts. This decreases risk because passwords are no longer accessible, and password management policies can be implemented more quickly without having to alter application code whenever the login and password change.

Oracle RDMS Interview Questions and Answers

Ques. 11): Why do we require the CASCADE option when using the DROP USER command to drop a user, and why do "DROP USER" instructions fail when we don't use it?

Answer:

If a user has an object, you will not be able to delete that user without using the CASCADE option. The DROP USER command with the CASCADE option deletes the user and all associated items. Because this is a DDL command, rollback is not possible after it has been executed.

BI Publisher Interview Questions and Answers

Ques. 12): What is the difference between Redo, Undo, and Rollback?

Answer:

When it comes to Redo, Rollback, and Undo, I always get a little confused. They all sound pretty much the same, or at least very similar.

Every Oracle database has a collection of redo log files (two or more). The redo log keeps track of all data changes, including both uncommitted and committed ones. Oracle saves archive redo logs in addition to online redo logs. In recovery scenarios, all redo logs are used. Rollback: More specifically, section rollback. The data in rollback segments is saved as it was before any modifications were made. The redo log, on the other hand, is a record of the inserts, updates, and deletions.

Undo: Rollback segments. They both are really one in the same. Undo data is stored in the undo tablespace. Undo is helpful in building a read consistent view of data.

 

Ques. 13): Do you have more than three Linux instances running? How do you figure out which shared memory and semaphores belong to which instance?

Answer:

Oracle provides an undocumented utility called Oradebug. The oradebug help command displays a list of oracle commands.

SQL>oradebug setmypid

SQL>oradebug ipc

SQL>oradebug tracfile_name

 

Ques. 14): Why aren't all Oracle faults recorded in the Alert Log?

Answer:

In the Alert Log, Oracle only logs critical problems. The majority of Oracle error codes are not recorded (unfortunately this may also include error codes that are genuinely critical). As a result, it's common to discover faults in the Oracle application that aren't visible in the Alert Log.

 

Ques. 15): There is no room available to add datafiles to enhance temp tablespace because it is completely full. What can you do to free up TEMP tablespace in that case?

Answer:

Closing some of the database's idle sessions will help you free up some TEMP space. You can also make use of:

Alter Tablespace PCTINCREASE 1' ;

'Alter Tablespace PCTINCREASE 0;

 

Ques. 16): What is the difference between row chaning and row migration?

Answer:

Row Migration:  When an update to a row causes it to no longer fit on the block, it migrates (with all of the other data that exists there currently). A migration means that the entire row will be moved, with only the «forwarding address» remaining. As a result, the original block only has the new block's rowid and the entire row is transferred.

Row Chaining: A single database block cannot hold more than one row. For example, if your database uses a 4KB blocksize and you need to insert an 8KB row, Oracle will use three blocks and save the information in pieces. Row chaining can occur under the following circumstances: Tables with a rowsize greater than the blocksize. Chained rows are common in tables containing LONG and LONG RAW columns. Oracle breaks broad tables split into sections, therefore tables with more than 255 columns will have chained rows. Rather of having a forwarding address on one block and data on another, we now have data on two or more blocks.

 

Ques. 17): How can I erase a data file that I accidentally created?

Answer:

In most circumstances, you can use RESIZE or RENAME to fix a data file that was generated with the improper size or in the wrong location. You have the following alternatives if you want to drop the data file again:

A produced data file can only be erased during a tablespace reorganization up to and including Oracle 9i. There are no other viable alternatives.

As of Oracle 10g, an empty data file can also be dropped with the following command:

ALTER TABLESPACE DROP DATAFILE ' ';

If there are still extents in the data file, this command fails with ORA-03262. In this case, the affected segments must first be relocated so that the extents are released.

 

Ques. 18): What is the ideal file size for data files?

Answer:

It is impossible to provide a straightforward solution to this topic. In most cases, the size of the data files has no bearing on database activity. However, keep the following considerations in mind:

Make sure the Oracle parameter DB FILES is set high enough. Otherwise, once this limit is reached, new data files cannot be produced.

The fewer the datafiles, the faster they can be restored individually during a backup.

BEGIN BACKUP processes in online backups are likely to take longer the smaller the data files are, and hence the more data files there are.

Data files that are too large aggravate performance problems that are caused by inode locking, since parallel processes may become serialized on the data file inode.

On occasion, size restrictions may prevent the system from using data files that exceed a certain size (often 2GB).

 

Ques. 19): Why does the order of the online redo logs occasionally change?

Answer:

This redo log becomes the next redo log if the next online redo log is still archived and another redo log is available for overwriting. The order of the online redo logs is now altered. Because the alternative would be an archiver stuck, at least briefly, this behaviour is preferable.

Only if many archive processes run in parallel and do not run again when the redo logs are archived may this situation arise. To avoid this issue, see if the archiver's performance (I/O tuning) can be improved. You must also avoid getting an archiver stuck due to a fully operational archive file system.

This problem cannot occur if the number of archiver processes is limited to one by LOG_ARCHIVE_MAX_PROCESSES

 

 

Ques. 20): On my system, why do Oracle processes run as the sid>adm user?

Answer:

By default, the UNIX PS command displays the true user, not the actual user. As a result, having adm as the displayed user for Oracle processes is not a problem. The only thing that matters is that the Oracle executable has the appropriate permissions.  

 

 

Top 20 AWS GuardDuty Questions and Answers

            Amazon GuardDuty is a threat detection service that monitors your AWS accounts and workloads for malicious behaviour in real time and provides detailed security findings for visibility and mitigation. Threat detection is provided by Amazon GuardDuty, which allows you to monitor and defend your AWS accounts, workloads, and data stored in Amazon Simple Storage Service on a continuous basis (Amazon S3). AWS CloudTrail Events, Amazon Virtual Private Cloud (VPC) Flow Logs, and domain name system (DNS) Logs are used by GuardDuty to analyse continuous metadata streams created from your account and network activity. GuardDuty also employs integrated threat intelligence to better identify threats, such as known malicious IP addresses, anomaly detection, and machine learning (ML).

AWS(Amazon Web Services) Interview Questions and Answers

Ques. 1): Is the predicted cost on the Amazon GuardDuty payer account for all linked accounts, or just for that specific payer account?

Answer: 

Only the cost of the individual payer account is included in the projected cost. The anticipated cost for the administrator account is the only thing you'll see.

AWS Cloud Interview Questions and Answers

Ques. 2): What do Amazon GuardDuty and Amazon Macie have in common?

Answer: 

Amazon GuardDuty helps identify risks like attacker reconnaissance, instance compromise, account compromise, and bucket compromise, and protects your AWS accounts, workloads, and data. Amazon Macie classifies what data you have, its security, and the access controls associated with it, allowing you to find and safeguard sensitive data in Amazon S3.

AWS RedShift Interview Questions and Answers

Ques. 3): How can I get Amazon GuardDuty to work?

Answer: 

With a few clicks in the AWS Management dashboard, Amazon GuardDuty may be set up and deployed. GuardDuty begins monitoring continuous streams of account and network activity in near real-time and at scale as soon as it is enabled. There is no need to install or administer any extra security software, sensors, or network equipment. Threat intelligence is pre-integrated into the service and is updated and maintained on a regular basis.

AWS Cloud Practitioner Essentials Questions and Answers

Ques. 4): How soon does GuardDuty begin to work?

Answer: 

When Amazon GuardDuty is on, it immediately begins scanning for malicious or illegal behaviour. The time it takes for you to start obtaining findings is determined by the level of activity in your account. GuardDuty only looks at activity that begins once it is enabled, not historical data. You'll get a finding in the GuardDuty console if GuardDuty detects any potential risks.

AWS EC2 Interview Questions and Answers

Ques. 5): Can I use Amazon GuardDuty to manage several accounts?

Answer: 

Yes, Amazon GuardDuty supports multiple accounts, allowing you to manage numerous AWS accounts from a single administrator account. All security findings are consolidated and sent to the administrator or Amazon GuardDuty administrator account for assessment and remediation when this feature is utilised. When utilising this configuration, Amazon CloudWatch Events are additionally aggregated to the Amazon GuardDuty administrator account.

AWS Lambda Interview Questions and Answers

Ques. 6): Do I have to enable AWS CloudTrail, VPC Flow Logs, and DNS logs for Amazon GuardDuty to work?

Answer: 

No. Amazon GuardDuty pulls independent data streams directly from AWS CloudTrail, VPC Flow Logs, and AWS DNS logs. You don’t have to manage Amazon S3 bucket policies or modify the way you collect and store logs. GuardDuty permissions are managed as service-linked roles that you can disable GuardDuty to revoke at any time. This makes it easy to enable the service without complex configuration, and eliminates the risk that an AWS Identity and Access Management (IAM) permission modification or S3 bucket policy change will affect service operation. It also makes GuardDuty extremely efficient at consuming high-volumes of data in near real-time without affecting the performance or availability of your account or workloads.

AWS Cloud Security Interview Questions and Answers

Ques. 7): Is Amazon GuardDuty a domestic or international service?

Answer: 

GuardDuty is a regional service provided by Amazon. The Amazon GuardDuty security findings remain in the same areas where the underlying data was generated, even when multiple accounts are enabled and several regions are used. This ensures that the data being evaluated is geographically specific and does not cross AWS regional boundaries. Customers can use Amazon CloudWatch Events to aggregate security discoveries produced by Amazon GuardDuty across regions, pushing results to a data repository under their control, such as Amazon S3, and then aggregating findings as needed.

AWS Simple Storage Service (S3) Interview Questions and Answers

Ques. 8): Is Amazon GuardDuty capable of automating preventative actions?

Answer:

You can build up automated preventative measures based on a security finding with Amazon GuardDuty, Amazon CloudWatch Events, and AWS Lambda. For example, based on security discoveries, you can develop a Lambda function to adjust your AWS security group rules. If a GuardDuty report indicates that one of your Amazon EC2 instances is being probed by a known malicious IP, you may use a CloudWatch Events rule to automatically adjust your security group rules and limit access on that port.

AWS Fargate Interview Questions and Answers

Ques. 9): I'm a new Amazon GuardDuty user. Are my accounts protected by GuardDuty for S3 by default?

Answer: 

Yes. GuardDuty for S3 protection will be enabled by default for all new accounts that enable GuardDuty via the console or API. Unless "auto-enable for S3" is enabled, new GuardDuty accounts established using the AWS Organizations "auto-enable" functionality will not have GuardDuty for S3 protection set on by default.

AWS SageMaker Interview Questions and Answers

Ques. 10): What is Amazon GuardDuty for EKS Protection and how does it work?

Answer: 

Amazon GuardDuty for EKS Protection is a GuardDuty functionality that analyses Kubernetes audit logs to monitor Amazon Elastic Kubernetes Service (Amazon EKS) cluster control plane behaviour. GuardDuty is connected with Amazon EKS, allowing it direct access to Kubernetes audit logs without the need to enable or store them. These audit logs are chronological records that capture the sequence of actions performed on the Amazon EKS control plane and are security-relevant. GuardDuty can use these Kubernetes audit logs to conduct continuous monitoring of Amazon EKS API activity and apply proven threat intelligence and anomaly detection to discover malicious behaviour or configuration changes that could expose your Amazon EKS cluster to unauthorised access.

AWS DynamoDB Interview Questions and Answers

Ques. 11): Is GuardDuty for EKS Protection available for a free trial?

Answer: 

There is a 30-day free trial available. Each new Amazon GuardDuty account in each region gets a free 30-day trial of GuardDuty, which includes GuardDuty for EKS Protection. Existing GuardDuty accounts are eligible for a free 30-day trial of GuardDuty for EKS Protection. The post-trial expenditures estimate can be seen on the GuardDuty console use page during the trial period. You will be able to see the expected fees for your member accounts if you are a GuardDuty administrator. The AWS Billing dashboard will show you the true expenses of this functionality after 30 days.

AWS Cloudwatch interview Questions and Answers

Ques. 12): What are Amazon GuardDuty's main advantages?

Answer: 

Amazon GuardDuty makes it simple to keep track of your AWS accounts, workloads, and Amazon S3 data in real time. GuardDuty is fully independent of your resources, so your workloads will not be impacted in terms of performance or availability. Threat intelligence, anomaly detection, and machine learning are all integrated into the service. Amazon GuardDuty generates actionable warnings that are simple to connect with current event management and workflow systems. There are no upfront expenses, and you only pay for the events that are examined; there is no need to install additional software or pay for threat intelligence stream subscriptions.

AWS Elastic Block Store (EBS) Interview Questions and Answers

Ques. 13): Is there a free trial available?

Answer: 

Yes, any new Amazon GuardDuty account can try the service for free for 30 days. During the free trial, you get access to the full feature set and detections. The amount of data handled and the expected daily average service charges for your account will be displayed by GuardDuty. This allows you to try Amazon GuardDuty for free and estimate service costs beyond the free trial period.

AWS Amplify Interview Questions and Answers

Ques. 14): Does Amazon GuardDuty assist with some of the PCI DSS (Payment Card Industry Data Security Standard) requirements?

Answer: 

GuardDuty examines events from a variety of AWS data sources, including AWS CloudTrail, Amazon VPC Flow Logs, and DNS logs. Threat intelligence feeds from AWS and other providers, such as CrowdStrike, are also used to detect unusual activities. Foregenix produced a white paper evaluating Amazon GuardDuty's effectiveness in meeting compliance standards, such as PCI DSS requirement 11.4, which mandates intrusion detection solutions at crucial network points.

AWS Django Interview Questions and Answers

Ques. 15): What types of data does Amazon GuardDuty look at?

Answer: 

AWS CloudTrail, VPC Flow Logs, and AWS DNS logs are analysed by Amazon GuardDuty. The service is designed to consume massive amounts of data in order to process security alerts in near real time. GuardDuty gives you access to built-in cloud detection algorithms that are maintained and continuously upgraded by AWS Security.

AWS Glue Interview Questions and Answers

Ques. 16): Is Amazon GuardDuty in charge of my logs?

Answer: 

No, your logs are not managed or stored by Amazon GuardDuty. GuardDuty analyses and discards any data it consumes in near real time. GuardDuty is able to be highly efficient, cost-effective, and lower the danger of data remanence as a result of this. You should use AWS logging and monitoring services directly for log delivery and retention, as they provide full-featured delivery and retention options.

AWS VPC Interview Questions and Answers

Ques. 17): What is Amazon GuardDuty threat intelligence?

Answer: 

Amazon GuardDuty threat intelligence consists of known attacker IP addresses and domain names. GuardDuty threat intelligence is provided by AWS Security as well as third-party providers like Proofpoint and CrowdStrike. These threat intelligence streams are pre-integrated and updated on a regular basis in GuardDuty at no additional charge.

AWS Aurora Interview Questions and Answers

Ques. 18): Is there any impact on my account's performance or availability if I enable Amazon GuardDuty?

Answer: 

No, Amazon GuardDuty is fully separate from your AWS resources, and there is no chance of your accounts or workloads being affected. GuardDuty can now work across several accounts in an organisation without disrupting existing processes.

AWS DevOps Cloud Interview Questions and Answers

Ques. 19): What is Amazon GuardDuty capable of detecting?

Answer: 

Built-in detection techniques created and optimised for the cloud are available with Amazon GuardDuty. AWS Security is in charge of maintaining and improving the detection algorithms. The following are the key detection categories:

Peculiar API activity, intra-VPC port scanning, unusual patterns of failed login requests, or unblocked port probing from a known rogue IP are all examples of reconnaissance by an attacker.

Cryptocurrency mining, malware using domain generation algorithms (DGAs), outbound denial of service activity, unusually high network traffic, unusual network protocols, outbound instance communication with a known malicious IP, temporary Amazon EC2 credentials used by an external IP address, and data exfiltration using DNS are all signs of an instance compromise.

AWS CloudFormation Interview Questions ans Answers

Ques. 20): How do security discoveries get communicated?

Answer: 

When a threat is detected, Amazon GuardDuty notifies the GuardDuty console and Amazon CloudWatch Events with a thorough security finding. As a result, alerts are actionable and simple to integrate into existing event management or workflow systems. The category, resource affected, and metadata linked with the resource, such as a severity rating, are all included in the findings.

AWS GuardDuty Questions and Answers