DEV Community: Gowtham E

Java abstact class vs Interface

Gowtham E — Sat, 04 Nov 2023 15:20:26 +0000

Lets see how Abstract classes and Interfaces differs,

Abstract classes supports both abstract(methods without definition) and non-abstract methods.
Interface supports only abstract method, then multiple Default and Static methods.
Interface supports multiple inheritance by implementing multiple interfaces.
Abstract class doesn't provide support for multiple inheritance.
Interface can't provide implementation of abstract class.
Abstract class can provide implementation of interface by defining their methods.
Abstract class can extend other java class and implement multiple interfaces.
Interface only extends other interfaces only.

AWS - S3 STORAGE

Gowtham E — Sun, 29 May 2022 17:53:00 +0000

AWS - S3 (Simple Storage Service)

Stores data as an object - object storage.
Unlimited Storage.
Stores a data in the bucket(files).
Objects are stored in buckets. Each bucket size is up-to 5 TB.

-S3 is a universal namespace, that is, names of the buckets must be unique globally. When you upload a file to S3, you will receive a HTTP 200 code if your upload was successful.

You can access the s3 data from any where in the public internet, by changing the bucket policy.
We can host a static web page using S3 service.

Object Store

Amazon S3 is a simple key, value store designed to store as many objects as you want. You store these objects in one or more buckets. An object consists of the following:

Key — The name that you assign to an object. You use the object key to retrieve the object.
Version ID — Within a bucket, a key and version ID uniquely identify an object
Value — The content that we are storing
Metadata — A set of name-value pairs with which you can store information regarding the object.
Subresources — Amazon S3 uses the subresource mechanism to store object-specific additional information.
Access Control Information — We can control access to the objects in Amazon S3.

Versioning

Versioning allows us to preserve, retrieve, and restore every version of every object stored inside an Amazon S3 bucket. Once you enable Versioning for a bucket, Amazon S3 preserves existing objects anytime you perform a PUT, POST, COPY, or DELETE operation on them.
- When you make any change in the S3 bucket storage, new changes will be updated to the current bucket and old changes will be saved. If we want to restore to old state it's easy in S3.

S3 has the following features:

Tiered storage available
Life cycle management
Versioning
Encryption
Secure your data using access control lists & bucket policies.

Storage classes in S3

S3 Standard

99.99% availability
99.999999999% durability
Designed to sustain the loss of 2 facilities concurrently

S3 IA

Infrequently accessed

For data that is accessed less frequently but required rapid access when needed
Lower fee than S3, but charged a retrieval fee

S3 Onezone IA

Used when we don’t need it in multiple availability zones.
Similar to S3 IA except with respect to the availability zones

S3 Intelligent Tiering

Uses machine language.
Designated to minimize costs by automatically moving data to the most cost-effective access tier without performance impact or operational overhead.

S3 Glacier

Secure, durable, low cost for data archiving.
Usually cheaper than on-premise solutions
Retrieval times configurable from minutes to hours

S3 Glacier Deep Archive

Lowest cost storage class
Retrieval time of 12 hour

S3 Outposts

Has been introduced as a storage class to deliver object storage to on-premises AWS outpost environments.

S3 Service billing based on following :

Storage
Requests
Storage management pricing
Data transfer pricing
Transfer acceleration
Cross-region replication pricing

Transfer acceleration:

Enables fast, easy, secure transfer of your files over long distances between your end-users & an S3 bucket.

Cross-Region Replication:

Feature that replicates the data from one bucket to another bucket which could be in a different region.

AWS - DYNAMO DB

Gowtham E — Thu, 26 May 2022 18:24:36 +0000

Serverless in nature, there’s no infrastructure provisioning needed.

DynamoDB is a fully managed, Internet scalable, easily administrated and cost-effective NoSQL database.

DynamoDB offers built-in security, continuous backups, automated multi-Region replication, in-memory caching, and data export tools.
Data is organized in tables, which contains items. Each item contains a set of key-value pairs of attributes. There are two special types of attributes: the primary-key, which works similarly to an item ID, and the sort-key, which allows for ordering the items.

Dynamo supports secondary indexes. They can be used to reference and order items by different primary-key and sort-keys. It is a schema-less database, in which items can have different sets of attributes. This allows for sparse indexes: composed only of items that contain a particular attribute.

DynamoDB can handle more than 10 trillion requests per day and can support peaks of more than 20 million requests per second.

Main Concepts of DynamoDB

Data Types
DynamoDB supports different data types for attributes of an item, they can be mainly categorised into the following:

Scalar Types : Number, String, Binary, Boolean and Null.
Document Types : List and Map
Set Types : Number Set, String Set, and Binary Set.

Table: as a collection that can hold a virtually infinite number of items, it may also have secondary indexes associated

Secondary Index: duplicates table items using a different primary-key and sort-key

Item: the most basic unit in Dynamo, it holds the data attributes structured in a JSON

Attribute: a key value pair that contains informational data-points about an item in the database table

Primary Key: a special form of attribute that is used to reference items, similarly to an item ID

Sort Key: another special form of attribute that is used to organize items in a different sorting order

Streams: a constant stream of state-changing operations executed against a table

Query: operation to retrieve a particular item (or set of items)

Scan: operation to scan the entire table or a section of it

Filter: rules to apply after a query or scan has executed, but before results are returned to the requester.

Core Features of DynamoDB

Autoscaling

Probably the most important feature of Dynamodb, it delivers automatic scaling of throughput and storage based on the performance or usage of your application. In a typical database server, the sysadmin takes care of scaling when the application encounters higher than usual traffic. With DynamoDB, you can create database tables that can store and retrieve any amount of data, and the scaling is automatically managed by AWS. This includes scaling up for higher traffic and scaling down for lower traffic, so you only pay for what you use.

Data Models

DynamoDB supports both key-value and document data models. This enables you to have a flexible schema, so each row can have any number of columns at any point in time. This is crucial for growing businesses that have ever-changing requirements.

Re-defining database schema is a nightmare that many developers/database admins go through in a growing application. This data model flexibility saves offers a robust database solution for small as well as large businesses.

Replication

AWS takes care of DynamoDB tables replication automatically based on your choice of AWS regions (cross-region replication). Even distributed applications can have single-digit millisecond read and write performance using DynamoDB.

With replication in place, you don't have to worry about data availability. In the event of the primary source failure, you can easily access the data from a secondary reserve, reducing the probability of application downtime.

Backups & Recovery

DynamoDB provides On-demand backups for your tables that you can enable within the AWS console. You can also enable automatic backup and archiving of your data to other AWS solutions like S3.

DynamoDB also offers Point-in-time recovery. This protects your data from accidental write/delete operations. With Point-in-time recovery, you can restore your database to any point in time for the last 35 days. Point-in-time recovery is achieved by storing incremental backups of your database and that is managed automatically by AWS.

Security

DynamoDB encrypts data at rest by default and also in transit using the keys stored in AWS Key Management Service (or customer-provided keys). With encryption in place, you can build security-sensitive applications that meet compliance and regulatory requirements. DynamoDB also provides access control via AWS IAM roles.

Monitoring

Monitoring is crucial to any business-critical application. It helps maintain reliability and also notify personnel in case of an event or failure. AWS offers detailed monitoring tools like CloudWatch Logs, CloudWatch Events, and CloudTrail Logs that will help you to watch, notify and debug all types of events in DynamoDB. You can also set custom triggers based on metrics like system errors, capacity usage, etc.

Now let’s compare DynamoDB with two of the popular database alternatives — MySQL and MongoDB.

DynamoDB vs MySQL

Obviously, there is a big difference between MySQL and Mongo DB because MySQL is a relational database. In terms of benefits, I think MySQL is limited because of the requirement of having a schema before you can start pushing data.

MySQL is great for many use cases as well. It is often called “The world’s most popular open-source database” and it delivers a fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server.

But being a NoSQL database provides DynamoDB much more flexibility in terms of data modeling. Even though AWS provides managed services for my SQL and other relational databases DynamoDB is a database designed by AWS and not just a hosted database solution. So this offers more improvements and features that MySQL and other relational databases can’t.

DynamoDB vs MongoDB

Dynamo DB and MongoDB are closely related to each other since both are NoSQL databases. But since DynamoDB is built and maintained by AWS it offers much more features and integrations especially with other Amazon services like S3, compare to MongoDB.

If I were running a growing company I would prefer using DynamoDB solely for the purpose of its scalability and cross-region replication features. AWS does not offer a managed MongoDB service but if you are looking for one, MongoDB Atlas would be a great alternative.

Another important feature of DynamoDB over MongoDB is that MongoDB is not secure by default and you have to configure security yourself. DynamoDB is secure by default, so it might be a better option if security is a deal-breaker for you.

TLDR

AWS DynamoDB is a fully managed NoSQL database that can scale in and scale out based on demand. AWS takes care of typical functions including software patching, replication, and maintenance. DynamoDB also offers encryption at rest, point-in-time snapshots, and powerful monitoring capabilities. In a nutshell, it is a great option when you are building an application that needs a high-performance scalable NoSQL database.

Additional features

DynamoDB Streams allow you perform change-data-capture (CDC) on your DynamoDB table and respond to updates in your table using Lambda functions. You can also pipe these changes into a Kinesis data stream.
Transactions allow you to do all-or-nothing operations across different items.
DynamoDB Global Tables is a feature that allows you to create Multi-Region Multi-Master setups across the globe with minimal latency.
PartiQL is a query language designed by AWS that’s similar to SQL and can be used across different NoSQL offerings.
DAX or the DynamoDB Accelerator is an in-memory write-through cache in front of DynamoDB if you need microsecond response times.

Comparative Analysis Between Amazon DynamoDB and Other Databases

Compared to other transactional databases, like Oracle, MSSQL, or PostgreSQL, AWS DynamoDB is schemaless, meaning it does not require conformation to a rigid schema of data types, tables, etc. This, though, also comes with a tradeoff: key advantages, like consistently high performance and millisecond latency, are compromised with ACID (atomicity, consistency, isolation, and durability) properties supported by a relational database.

Compared to other NoSQL databases, AWS DynamoDB supports data models like key-value pair (see figure below), and document data structures such as JSON, XML and HTML. But DynamoDB lacks support for columnar data sets, like Cassandra and HBase, and graph models such as Orient DB.

AWS Testing Service - DEVICE FARM

Gowtham E — Wed, 25 May 2022 17:30:51 +0000

What is Device farm ?

Device Farm is a testing service from AWS.
Test native, hybrid and web applications on real Android and IOS device in the cloud.
Also test desktop browser apps using device farm.
AWS Device Farm supports native and hybrid Android, iOS, and web apps, and cross-platform apps.
Best part of AWS Device Farm is tests are run on real, non-rooted devices. The devices are a mixture of OEM and carrier-branded devices.
AWS Device Farm works on Internet Explorer 9 or later and the latest versions of Chrome, Firefox, and Safari.
Max file size is 4 GB applications will be allowed. Device Farm is only available in the us-west-2 (Oregon) region.

Test automation framework supported for mobile

Appium Java JUnit, Appium Java TestNG, Appium Python, Calabash, Instrumentation (Including JUnit, Espresso, Robotium, and any instrumentation-based tests), UI Automation, UI Automator, and XCTest (Including XCUI and KIF)

Test automation framework supported for web application

Selenium, Appium Java JUnit, Appium Java TestNG, or Appium Python.

Test in Browsers

Supports selenium scripts.
All browsers are hosted on EC2 Windows instances which run on Microsoft Windows Server.
Supports Chrome, FireFox, Microsoft - IE and Edge.

Pricing :

For desktop browsers :

charged $0.005 per browser instance minute

For Mobile device app :

Standard rate of $0.17 per device minute.
Unlimited testing and remote access starting at $250 per month for both ios and android, priced at $250 per slot per month. Device slots correspond to concurrency.

AWS Storage - Difference between OBJECT STORAGE, BLOCK STORAGE and FILE STORAGE

Gowtham E — Tue, 24 May 2022 18:15:48 +0000

Definition

These are the storage types provided by AWS services such as

S3 - Simple Storage Service for object storage
EBS - Elastic Block Store for Block storage
EFS - Elastic File Storage for object storage

OBJECT STORAGE (S3)

S3 is for object storage. Eg.. Photos, videos, files, and simple web pages.
Data storage for unstructured data.
Can be accessed from multiple instances.
Data is organized hierarchically.
More comprehensive metadata labels makes querying easier.
Great for Data lakes, archiving files for long-term, and hosting static web sites.
Lower cost as compared to EFS and EBS.
Highly available, Durable, and Flexible.

AWS S3 use cases:
1) Data lake and big data analytics.
2) Backup and restoration.
3) Reliable disaster recovery.
4) Methodical archiving.

BLOCK STORAGE (EBS)

EC2 block storage. Eg.. computer’s hard drive
System storage for Amazon EC2 VM's.
Used as per-instance storage (EC2).
Data is stored in equally-sized blocks.
EBS encryption, High availability and easy backup.

AWS EBS use cases:
1) Testing and development.
2) NoSQL databases.
3) Relational databases.
4) Business consistency.
5) Enterprise-wide applications.

FILE STORAGE (EFS)

Scalable data storage for Amazon EC2 VM's.
EFS is a file system for many EC2 instances. Eg.. Multiple EC2 instances and lots of data.
Can be mounted by multiple instances.
Highly scalable — Can grow or shrink as per demand.
Fully elastic — No need to provision new infrastructure.
Can cross AWS region boundary using VPC peering.

EFS use cases:
1)Lift-and-shift application support.
2) Analytics for big data.
3) Content management system and web server support.
4) Application development and testing.

AWS Certifications

Gowtham E — Mon, 23 May 2022 18:24:45 +0000

Foundation Level

AWS Certified Cloud Practitioner - For Beginners

Essential AWS services and features, including business use cases and AWS security and compliance fundamentals.
Questions type : MCQ's
Length: 90 minutes
Fee: $100

Associate Level

AWS Certified Solutions Architect

-Deploying, configuring, and managing compute, network, storage, and database services in AWS.
-Understanding of the AWS Well-Architected Framework, AWS networking, security services, and the AWS global infrastructure.
Questions type : MCQ's
Length: 130 minutes
Fee: $150

AWS Certified Developer

-AWS SDK to interact with and optimize the AWS services that you build into an application
-Proficiency in developing, deploying, and debugging cloud-based applications using AWS and writing code for serverless applications.
Questions type : MCQ's
Length: 130 minutes
Fee: $150

AWS Certified SysOps Administrator

-Experience deploying, managing, and operating workloads on AWS as well as implementing security controls and compliance requirements
-Understanding of the AWS Well-Architected Framework as well as AWS networking and security services
Questions type : MCQ's
Length: 180 minutes
Fee: $150

Professional Level

AWS Certified Solutions Architect - Professional

-Build and deploy distributed systems in the AWS Cloud to spec, plus understand how to deploy them at scale with fault tolerance and high availability.
-Ability to deploy multi-tier applications to the AWS Cloud, and to build enterprise-scale cloud solutions with AWS resources.
Questions type : MCQ's
Length: 180 minutes
Fee: $300

AWS Certified DevOps Engineer - Professional

Continuous integration and continuous delivery (CI/CD) methodologies and automation best practices, including best practices for automating security and compliance checks.
- Define and deploy monitoring, metrics, and logging systems on AWS. Questions type : MCQ's Length: 180 minutes Fee: $300

Specialty Level

AWS Advanced Networking

Perform complex networking tasks, architecting and implementing network solution.
Design, implementation, and optimization of the following: Routing architectures (including static and dynamic); multi-region solutions for a global enterprise; highly available connectivity solutions (e.g., AWS Direct Connect, VPN). Questions type : MCQ's Length: 170 minutes Fee: $300

AWS Data Analytics

Define AWS data analytics services and understand how they integrate with each other
Explain how AWS data analytics services fit in the data lifecycle of collection, storage, processing, and visualization. Questions type : MCQ's Length: 180 minutes Fee: $300

AWS DataBase

Expertise working with on-premises and AWS Cloud-based relational and NoSQL databases.
Analyze needs and requirements to design and recommend appropriate database solutions by using AWS services. Questions type : MCQ's Length: 180 minutes Fee: $300

AWS Machine Learning

Developing, architecting, and running ML or deep learning workloads in the AWS Cloud.
Ability to follow model-training, deployment, and operational best practices Questions type : MCQ's Length: 180 minutes Fee: $300

AWS Security

AWS security services and features of services to provide a secure production environment and an understanding of security operations and risks.
Knowledge of the AWS shared responsibility model and its application; security controls for workloads on AWS; logging and monitoring strategies; cloud security threat models; patch management and security automation. Questions type : MCQ's Length: 170 minutes Fee: $300

SAP on AWS

design an SAP solution that runs in the AWS Cloud in adherence with best practices laid out in the AWS Well-Architected Framework, and SAP certification and support requirements. Questions type : MCQ's Length: 170 minutes Fee: $300

AWS BLOG 101

Gowtham E — Sun, 22 May 2022 08:22:46 +0000

AWS Blog – 101

“It’s still day one” – Amazon

This is my first blog – from my lovable topic on AWS – Amazon Web Services overview.

Learning is not only everything, getting hands dirty ,consistency and Networking makes you path very easy and bright.

AWS – Amazon web service is a cloud service provider and market leader in cloud computing provider that offers various computing services that are accessible over the public internet.

Cloud computing models :

1.IAAS – Infrastructure as as Service.
It is the basic building block of cloud IT. Generally provides access to data storage space, networking features, and computer hardware(virtual or dedicated hardware)
Eg services : VPC ,EBS, EC2

2.PAAS – Platform as a Service.
AWS manages the underlying infrastructure (usually operating system and hardware). This helps the developer to be more efficient as they do not have to worry about undifferentiated heavy lifting required for running the applications such as capacity planning, software maintenance, resource procurement, patching, etc., and focus more on deployment and management of the applications. **Example: **RDS, RedShift, ElasticSearch

3.SASS – Software as a Service.
It is a complete product that usually runs on a browser. It primarily refers to end-user applications. It is run and managed by the service provider. The end-user only has to worry about the application of the software suitable to its needs.
*Example : * SAP, Gmail, Dropbox

AWS History :
Employee of Amazon.com (retail services) proposed an idea for shared resource model based in infrastructure,
AWS services launched
• 2004 – SQS ‘Simple Queue Service’
• 2006- Launched its cloud products (S3,EC2)
• 2010 - Amazon.com completely moved to AWS
• 2012- Holds first customer event – re:Invent conference
• 2013 – certifications launched
• 2014 – AWS Committed to achieve 100% renewable energy usage for its global footprint
• 2015- Reveals revenues achieved of $4.6 billion
• 2016- Surpassed $10 billon revenue target
• 2016- Release snowball and snowmobile
• 2019- Offers nearly 100 cloud services
• 2021- AWS comprises over 200 products and services (including private 5G Network service ).

AWS Certifications Levels:

FOUR levels of certifications available in AWS
1.Foundational
2.Associate
3.Professional
4.Speciality

Careers in AWS :

1.AWS – ML Machine learning
2.AWS – Data Analytics
3.DEVOPS Engineer
4.AWS – Solution Architect
5.Cloud Data Base Admin
6.SYS Ops Admin