DEV Community: Vivekanand Gujjeti

AWS Beanstalk

Vivekanand Gujjeti — Mon, 23 May 2022 16:17:43 +0000

What is Amazon Elastic Beanstalk?
● Beanstalk is a compute service for deploying and scaling applications developed in many popular languages.
● Developers can focus on writing code and don’t need to worry about the underlying infrastructure required to run the application.
● AWS Elastic Beanstalk is the best way to deploy your application in the fastest and simplest way.
● It provides the user interface/dashboard to monitor your application.
● It gives you the flexibility to choose AWS resources such as Amazon EC2 Instance along with the pricing options which suit your application needs.

AWS Elastic Beanstalk supports two types of Environment:
● Web Tier Environment
o This application hosted on the Web Server Environment handles the HTTP and HTTPS requests from the users.
o Beanstalk Environment: When an environment is launched, Beanstalk automatically assigns various resources to run the application successfully.
o Elastic Load Balancer: Request is received from the user via Route53 which forwards the request to ELB. Then ELB distributes the request among various EC2 Instances of the Autoscaling group.
o Auto Scaling Group: Auto Scaling will automatically add or remove EC2 Instance based on the load in the application.
o Host Manager: Software components inside every EC2 Instance
which is responsible for the following:
▪ Log files generation
▪ Monitoring
▪ Events in Instance

● Worker Environment
○ A worker is a background process that helps applications for handling heavy resource and time-intensive operations.
○ It is responsible for database clean up, report generation that helps to remain up and running.
○ In the Worker Environment, Beanstalk installs a Daemon on each EC2 Instance in the Auto Scaling Group.
○ Daemon pulls requests from the SQS queue and executes the task
based on the message received.
○ After execution, SQS will delete the message, and in case of failure, it will retry to send the message.

Platform Supported
● .Net (on Linux or Windows)
● Docker
● GlassFish
● Go
● Java
● Node.js
● Python
● Ruby
● Tomcat

Deployment Models:

All at Once: Deployment will start taking place in all the instances at the same time. It means all your EC2 Instances will be out of service for a short time. Your application will be completely down for the same duration.
Rolling : Deploy the new version in batches; unlike all at once, one group of instances will run the old version of the application. That means there will not be complete downtime just like all at once.
Rolling with additional batch : Deploy the new version in batches. But before that, provision an additional group of instances to compensate for the updating one.
*Immutable * : Deploy the new version to a separate group of instances, and the update will be immutable.
Traffic splitting : Deploy the new version to a separate group of instances and split the incoming traffic between the older and the new ones.

Pricing:
● Amazon will not charge you for AWS Elastic Beanstalk.
● Instead, you will be paying for the resources such as EC2 Instance, ELB and Auto Scaling group where your application is hosted.

Lambda@Edge

Vivekanand Gujjeti — Thu, 19 May 2022 16:35:07 +0000

● It is the feature of Amazon CloudFront which allows you to run your code
closer to the location of Users of your application.
● It improves performance and reduces latency.
● Just like lambda, you don’t have to manage and provision the infrastructure around the world.
● Lambda@Edge runs your code in response to the event created by the CDN.

Lambda Event

Vivekanand Gujjeti — Wed, 18 May 2022 19:23:04 +0000

Lambda Event
● Lambda Event is an entity that invokes the lambda function.
● Lambda supports synchronous invocation of Lambda Functions.
● Lambda supports the following sources as an event:
o AWS DynamoDB
o AWS SQS
o AWS SNS
o CloudWatch Event
o API Gateway
o AWS IoT
o Kinesis
o CloudWatch Logs

Lambda Layers

Vivekanand Gujjeti — Sun, 15 May 2022 17:30:51 +0000

●A Lambda layer is a container/archive which contains additional code such as libraries, dependencies, or custom runtimes.
● AWS Lambda allows five layers in a function.
● Layers are immutable.
● A new version will be added if you publish a new layer.
● Layers are by default private but can be shared and made public explicitly.

Lambda Functions

Vivekanand Gujjeti — Wed, 11 May 2022 21:30:23 +0000

● A function is a block of code in Lambda.
● You upload your application/code in the form of single or multiple functions.
● You can upload a zip file, or you can upload a file from the S3 bucket as well.
● After deploying the Lambda function, Lambda automatically monitors
functions on your behalf, reporting metrics through Amazon CloudWatch.

When do you use Lambda?

Vivekanand Gujjeti — Wed, 11 May 2022 15:58:52 +0000

● When using AWS Lambda, you are only responsible for your code.
● AWS Lambda manages the memory, CPU, Network, and other resources.
● It means you cannot log in to the compute instances or customize the
operating system.
● If you want to manage your own compute resources, you can use other
compute services such as EC2, Elastic Beanstalk.
● There will be a level of abstraction which means you cannot log in to the
server or customize the runtime.

AWS Lambda

Vivekanand Gujjeti — Tue, 10 May 2022 16:02:11 +0000

What is AWS Lambda?
● AWS Lambda is a serverless compute service through which you can run your code without provisioning any Servers.
● It only runs your code when needed and also scales automatically when the request count increases.
● AWS Lambda follows the Pay per use principle – it means there is no charge when your code is not running.
● Lambda allows you to run your code for any application or backend service with zero administration.
● Lambda can run code in response to the events. Example – update in DynamoDB Table or change in S3 bucket.
● You can even run your code in response to HTTP requests using Amazon API Gateway.

AWS Lambda

Vivekanand Gujjeti — Mon, 09 May 2022 12:51:32 +0000

AWS Lambda is a serverless computing service that allows users to run code as functions without provisioning or managing servers.

Lambda Functions supports the following languages:

Pricing details:
Charges are applied based on the number of requests for the functions and the time taken to execute the code.

   The memory allocated to AWS Lambda for computing is **128MB **(minimum) to **3008MB **(maximum). 
   **Additional memory** can be requested in an increment of **64MB between 128MB** **- 3008MB.**

   The **default execution time** for AWS Lambda is **3seconds**, and the maximum is **15 minutes** (**900 seconds**).

Querying Data in S3 with Amazon Athena

Vivekanand Gujjeti — Sun, 08 May 2022 20:13:18 +0000

Architecture Diagram

Task Details

Log into AWS Management Console.
1. Setup workgroup
2. Create a database in Glue.
3. Query table in Athena

Task 1:-
i. Login to AWS Console

Task 2:-
i. Make sure you are in the N.Virginia Region.
ii. Navigate to menu in the top, then click on Athena.
iii. Click on the Get started button.

iv. In the menu bar, click on Workgroup:primary.

v. To create a workgroup, Click on the Create workgroup button.

vi. Provide details to create a workgroup:
- Workgroup Name: Enter WhizWorkgroup
- Description: Enter Workgroup for Athena lab
- Query result location: Select the S3 bucket, whose name is starting with whizlabs...

- Leave other settings as default.
- Click on the Create Workgroup button.

vii. Now it will list all the Workgroups

viii. Select WhizWorkgroup by checking on the option and click on the Switch workgroup button.

ix. Now it will show the opening page, click on Get started

x. Now you can verify your workspace.

Task 3: Create a database in Glue

 1. Make sure you are in the **<u>N.Virginia</u>** Region.
 2. Navigate to   menu at the top, then click on **<u>AWS Glue</u>** in 
    the   section.
 3. By default, you will be able to see the **<u>tables </u>**present. In the left sidebar, Under Data catalog, Click on **<u>Databases</u>**.
 4. Click on the **<u>ADD DATABASE</u>**
 5. In the pop-up menu, enter the database name as 
   **<u>whizgluedatabase </u>**and click on the **<u>Create </u>**button.

6. The database is now created.

Task 4: Create a table in Glue

In the left sidebar, Under Data catalog, Click on Tables.
To create a table, click on the Add tables button and select Add table manually.

In the Set up your table's properties section, do the following: • Enter the Table name as whiz-sample-table • select the Database, select whizgluedatabase • Click on the Next button.

In the Add a data store section, do the following: • Select the type of source: S3 (default) • Data is located in: Specified path in my account (default) • Include path: Select the S3 bucket name starting with whizlabs... • Click on the Next button below to proceed further...

In the Choose a data format section, do the following: • Select Classification as CSV • Choose delimiter as Comma: , • Click on the Next button.

In the Define a schema section, we will add 2 columns. • Click on the ADD Column button. • Column name: Enter Expense_Type and Column Type: Select string • Click on the Add button below.

• Click on the ADD Column button again.
• Column name: Enter Expense_Category and Column Type: Select string
• Click on the Add button below.
• After adding both the columns, click on the Next button.

Add partition indices: Leave everything as default and click on Next button.
Review the configuration of the table and click on the Finish button.

The table is now created.

Task 5: Query table in Athena

Make sure you are in the N.Virginia Region.
Navigate to menu in the top, then click on Athena in the section.
Click on the Get started button, if asked.
In the left sidebar, under data source, Select the database as whizgluedatabase.
Then you will see our table, whiz-sample-table.
To preview the data of whiz-sample-table table, select the Preview table.

Query editor will automatically generate the SQL statement for querying the first 10 columns.

The result of the query is shown below.

To get the results of all expenses types under expense_category of food, paste the following SQL statement into the query editor. • SELECT * FROM "whizgluedatabase"."whiz-sample-table" where expense_category = 'Food'; Note: To execute the queries through the keyboard directly use the shortcut Ctrl + Enter (For windows) or Tab + Enter (For Mac)
You can play around with some of the queries like:
Getting a total number of rows present by running the following SQL statement in the query editor. • SELECT count(*) FROM "whizgluedatabase"."whiz-sample-table";

Once you execute this command you will get the result.

Thank you.

What is Amazon Athena?

Vivekanand Gujjeti — Sat, 07 May 2022 07:47:37 +0000

Amazon Athena is an interactive serverless service used to analyze data directly in Amazon Simple Storage Service using standard SQL ad-hoc queries.

Pricing Details:-

Charges are applied based on the amount of data scanned by each query at standard S3 rates for storage, requests, and data transfer.
Canceled queries are charged based on the amount of data scanned.
1. No charges are applied for Data Definition Language (DDL) statements. 4.Charges are applied for canceled queries also based on the amount of data scanned.
Additional costs can be reduced if data gets compressed, partitioned, or converted into a columnar format.

Functions of Athena:

It helps to analyze different kinds of data (unstructured, semi-structured, and structured) stored in Amazon S3.
Using Athena, ad-hoc queries can be executed using ANSI SQL without actually loading the data into Athena.
It can be integrated with Amazon Quick Sight for data visualization and helps to generate reports with business intelligence tools.
It can be integrated with the AWS Glue Data Catalog to store metadata in Amazon S3 and offers data discovery features of AWS Glue.
It helps to connect SQL clients with a JDBC or an ODBC driver.
It executes multiple queries in parallel, so no need to worry about compute resources.
It supports various standard data formats, such as CSV, JSON, ORC,Avro, and Parquet.

How to apply the AWS Community Builder Program

Vivekanand Gujjeti — Sat, 07 May 2022 07:07:02 +0000

The AWS Community Builders program offers technical resources, mentorship, and networking opportunities to AWS technical enthusiasts and emerging thought leaders who are passionate about sharing knowledge and connecting with the technical community.
Are you interested to join AWS builders Program? You should apply the program to build relationships with AWS product teams, AWS Heroes, and the AWS community.
Throughout the program, AWS subject matter experts will provide informative webinars, share insights — including information about the latest services — as well as best practices for creating technical content, increasing reach, and sharing AWS knowledge across online and in-person communities. The program will accept a limited number of members per year. All AWS builders are welcome and encouraged to apply.

We have many category for applying the AWS community builder program. There are list of categories:-
• Machine Learning
• Mobile and Web Apps
• Storage
• Containers
• Developer Tools
• Management, Governance and Migration
• Serverless
• Gravitron / Arm Development
• Data (Databases, Analytics, Blockchain)
• Security, Identity & Compliance
• Game Tech
• Networking and Content Delivery
If you want to become an AWS Community Builders application form, please join now in the cycle of Jan 2022. The application form is open until midnight PST on January 24th, so don’t wait too long to apply.
What are the benefits of joining the AWS Community Builders program?
• Access to AWS product & Services and information about new services and features
• Mentorship from AWS subject matter experts on a variety of topics
• AWS Promotional Credits and other helpful resources to support content creation
• Opportunities to connect with and learn from like-minded developers

you can check out more details here https://lnkd.in/gMt96NuQ