DEV Community: Giriraj Roy

Cloud Computing #Day5

Giriraj Roy — Sun, 14 Aug 2022 11:10:14 +0000

In this module I will throw light on the AWS Global Infastructure, that is built by availibity zones or regions followed by the edge locations that serve as cached copies for faster delivery.

Availibility Zones

An Availability Zone is a single data center or a group of data centers within a Region. Availability Zones are located tens of miles apart from each other. This is close enough to have low latency (the time between when content requested and received) between Availability Zones. However, if a disaster occurs in one part of the Region, they are distant enough to reduce the chance that multiple Availability Zones are affected. This particular advantage serves as the main purpose of the defined infastructure.

The above diagram clearly explains the infastructure of availibility zones (like us-west-1a) within regions (say, N.California) and how they are related within a small distance to maintain low latency.

Planning for failure and deploying applications across multiple Availability Zones is an important part of building a resilient and highly available architecture.

Amazon CloudFront and Edge locations

An edge location is a site that Amazon CloudFront uses to store cached copies of your content closer to your customers for faster delivery. Hence along with the discussion of these caching locations comes Amazon CloudFront, a web service that speeds up distribution of static and dynamic web content, such as .html, .css, .js, and image files, to the users. When a user requests content that you're serving with CloudFront, the request is routed to the edge location that provides the lowest latency (time delay), so that content is delivered with the best possible performance.

I won't dive deep into the CloudFront business instead I will attach a diagram related to it.

Interacting with AWS Services

In AWS, everything is an API call (an API is an application programming interface). And what that means is, there are pre determined ways for you to interact with AWS services. And you can invoke or call these APIs to provision, configure, and manage your AWS resources.
For example, you can launch an EC2 instance or you can create an AWS Lambda function. Each of those would be different requests and different API calls to AWS. You can use the AWS Management Console, the AWS Command Line Interface, the AWS Software Development Kits, or various other tools like AWS CloudFormation, to create requests to send to AWS APIs to create and manage AWS resources.

The AWS Management Console

The AWS Management Console is a web-based interface for accessing and managing AWS services.
You can quickly access recently used services and search for other services by name, keyword, or acronym.
The console includes wizards and automated workflows that can simplify the process of completing tasks.

The AWS Command Line Interface

To save time when making API requests, you can use the AWS Command Line Interface (AWS CLI).
AWS CLI enables you to control multiple AWS services directly from the command line within one tool.
By using AWS CLI, you can automate the actions that your services and applications perform through scripts.

Software Development Kits (SDKs)

SDKs make it easier for you to use AWS services through an API designed for your programming language or platform.
SDKs enable you to use AWS services with your existing applications or create entirely new applications that will run on AWS.

Amazon Elastic BeanStalk

AWS Elastic Beanstalk is a service that helps you provision Amazon EC2-based environments. With AWS Elastic Beanstalk, you provide code and configuration settings, and Elastic Beanstalk deploys the resources necessary to perform the following tasks:

Adjust capacity
Load balancing
Automatic scaling
Application health monitoring

Using IAAS as AWS CloudFormation

AWS CloudFormation provisions your resources in a safe, repeatable manner, enabling you to frequently build your infrastructure and applications without having to perform manual actions. It determines the right operations to perform when managing your stack and rolls back changes automatically if it detects errors.

The next day will be describing how amazing the networking is carried out in AWS, the Subnets and Security groups oh its just awesome !!!

Happy Coding ☕☕

Cloud Computing #Day4

Giriraj Roy — Mon, 08 Aug 2022 05:58:10 +0000

In this article I will try to quickly cover the Amazon Messaging and Queuing services, and explore the lands of a few more additional services.

The Flaw:

In the process of accepting instructions or requirements to passing the requirements to the server both the systems will have to be on sync. At some point of time if the synchronisation is affected due to any unavoidable reason, such as the server is down the whole process stops and cannot proceed further. A much better process would be to introduce some sort of buffer or queue into the system. Hence the server or instance instead of handing the instructions directly would follow some sort of buffer, like an order board in a restaurant and the chef being the instance.

The idea of placing messages into a buffer is called messaging and queuing.

This is where AWS introduced a message queue. Messages are sent into the queue by Application A and they are processed by Application B. If Application B fails, Application A doesn't experience any disruption. Messages being sent can still be sent to the queue and will remain there until they are eventually processed. They are loosely coupled. This is what AWS aims to achieve with its architectures. And eventually brings me to two AWS services that can assist in this regard:

Amazon Simple Queue Service or SQS
Amazon Simple Notification Service or SNS.

Monolithic Application And Microservices

Applications are made of multiple components. The components communicate with each other to transmit data, fulfill requests, and keep the application running.

Now we have two approaches to combine the elements. The Monolithic Architecture where the components including databases, servers, the user interface, business logic, all are tightly coupled. In this approach to application architecture, if a single component fails, other components fail, and possibly the entire application fails.

The second approach aims to help maintain application availability when a single component fails, that is you can design your application through a microservices. In a microservices approach, application components are loosely coupled. The loose coupling prevents the entire application from failing.

When designing applications on AWS, it is advisable to take a microservices approach with services and components that fulfill different functions. Two services facilitate application integration i.e. Applicatoin A and Application B in the previous example are: Amazon Simple Notification Service (Amazon SNS) and Amazon Simple Queue Service (Amazon SQS) approach.

Amazon Simple Notification Service (Amazon SNS)

Amazon Simple Notification Service (Amazon SNS) is a publish/subscribe service. Using Amazon SNS topics, a publisher publishes messages to subscribers.

In Amazon SNS, subscribers can be web servers, email addresses, AWS Lambda functions, or several other options.

Amazon Simple Queue Service (Amazon SQS)

Amazon Simple Queue Service (Amazon SQS) is a message queuing service.

Using Amazon SQS, you can send, store, and receive messages between software components, without losing messages or requiring other services to be available. In Amazon SQS, an application sends messages into a queue. A user or service retrieves a message from the queue, processes it, and then deletes it from the queue.

Serverless Computing

I would like to revisit the topic of serverless computing, which is a service that lets you run virtual servers in the cloud. The term “serverless” means that your code runs on servers, but you do not need to provision or manage these servers. With serverless computing, you can focus more on innovating new products and features instead of maintaining servers. Another benefit of serverless computing is the flexibility to scale serverless applications automatically. Serverless computing can adjust the applications' capacity by modifying the units of consumptions, such as throughput and memory.

An AWS service for serverless computing is AWS Lambda.

AWS Lambda

AWS Lambda is a serverless compute service that runs the code in response to events and automatically manages the underlying compute resources for the client. These events may include changes in state or an update, multiple events, such as HTTP requests via Amazon API Gateway, modifications to objects in Amazon Simple Storage Service (Amazon S3) buckets, table updates in Amazon DynamoDB, and state transitions in AWS Step Functions. AWS Lambda can be used to extend other AWS services with custom logic, or create your own backend services that operate at AWS scale, performance, and security.

Lambda has its key highlights including server and operating system maintenance, capacity provisioning and automatic scaling, code and security patch deployment, and code monitoring and logging.

How Lambda Works

Another additional service is Containerization of applications.

Containers

Containers provide you with a standard way to package your application's code and dependencies into a single object. It is the orchestration service that helps you to deploy, manage, and scale your containerized applications. They smoothen the workflow with security, reliability and scalability.

Amazon provides two containerized services :

Amazon Elastic Container Service (Amazon ECS) : This is a highly scalable, high-performance container management system that enables you to run and scale containerized applications on AWS. Amazon ECS supports Docker containers.
Amazon Elastic Kubernetes Service (Amazon ECS) : This is a fully managed service that you can use to run Kubernetes on AWS.

There is also another service AWS Fargate.

AWS Fargate is a serverless compute engine for containers. It works with both Amazon ECS and Amazon EKS.
When using AWS Fargate, you do not need to provision or manage servers. AWS Fargate manages your server infrastructure for you. You can focus more on innovating and developing your applications, and you pay only for the resources that are required to run your containers.

Cloud Computing #Day 3

Giriraj Roy — Thu, 04 Aug 2022 06:45:02 +0000

We are here on the third day of the exciting cloud voyage where waves of Scaling and Elastic Load Balancing will be clashing so beautifully. So what is scaling or scalability?

Scalability

Scalability involves beginning with only the resources you need and designing your architecture to automatically respond to changing demand by scaling out or in. That is to say it will monitor the application and automatically adjust capacity to maintain steady, predictable performance at the lowest possible cost which is infact Amazon EC2 Auto Scaling.

Amazon EC2 Auto Scaling

Amazon EC2 Auto Scaling enables you to automatically add or remove Amazon EC2 instances in response to changing application demand. By automatically scaling instances in and out as needed, a greater sense of application availability can be maintained.

This gets even more exciting when we can use two approaches: dynamic scaling and predictive scaling.

Dynamic scaling responds to changing demand.
Predictive scaling automatically schedules the right number of Amazon EC2 instances based on predicted demand.

Pro Tip: Dynamic Scaling and Predictive Scaling can be used together for faster scaling

Diving Deeper

In the cloud, computing power is a programmatic resource, by adding Amazon EC2 Auto Scaling to an application, new EC2 instances can be added to the application when necessary and terminate them when no longer needed.

Working Principle >>

When preparing to launch an application on Amazon EC2 instance and configuring the size of the Auto Scaling group, you might set the minimum number of Amazon EC2 instances at one. This means that at all times, there must be at least one Amazon EC2 instance running. This is the minimum capacity, the number of Amazon EC2 instances that launch immediately after you have created the Auto Scaling group.

The second configuration that can be set is Desired Capacity, which is set to minimum capacity by default if it is not explicitly set.

There is also the configuration of setting the maximum capacity to configure the Auto Scaling Group in response to increased demand.

Chalking out the Benefits

Setup scaling quickly

AWS Auto Scaling lets you set target utilization levels for multiple resources in a single, intuitive interface. You can quickly see the average utilization of all of your scalable resources without having to navigate to other consoles.

Make smart scaling decisions

AWS Auto Scaling monitors your application and automatically adds or removes capacity from your resource groups in real-time as demands change.

Automatically maintain performance

Using AWS Auto Scaling, you maintain optimal application performance and availability, even when workloads are periodic, unpredictable, or continuously changing.

Cost Effective

AWS Auto Scaling can help you optimize your utilization and cost efficiencies when consuming AWS services so you only pay for the resources you actually need

Elastic Load Balancing

This is the AWS service that automatically distributes the incoming application traffic to multiple resources like Amazon EC2 instances. It monitors the health of its registered targets, and routes traffic only to the healthy targets.

The load balancer acts as a single point of contact betwwen the incoming traffic and the Auto Scaling Group. Although Elastic Load Balancing and Amazon EC2 Auto Scaling are separate services, they work together to help ensure that applications running in Amazon EC2 can provide high performance and availability.

The way Elastic Load Balancer toggles the number of instances between High Demand Period and Low Demand Period is essential. Whenever there is a new instance in the network it will only have to send the signal to the load balancer instead of all the sources.

There are three different types of Load balancers:

Application Load Balancer
Gateway Load Balancer
Network Load Balancer

Use Cases

Modernize applications with serverless and containers : Scale modern applications to meet demand without complex configurations or API gateways.
Improve hybrid cloud network scalability : Load balance across AWS and on-premises resources using a single load balancer.
Retain your existing network appliances : Deploy network appliances from your preferred vendor while taking advantage of the scale and flexibility of the cloud.

Cloud Computing #Day 2

Giriraj Roy — Sun, 24 Jul 2022 13:05:25 +0000

Good Wishes to the second day of my Cloud Computing aka AWS journey, I came across the architechtural insights of virtual servers, which are not only reliable and secure but also scalable and elastic which is why the name Amazon Elastic Cloud Compute (Amazon EC2)

What is Amazon EC2 ?

Amazon EC2 eliminates the need to invest in hardware up front hence can be used to launch as many or as few virtual servers as needed; configure security and networking and manage storage.

Amazon EC2 enables a user to scale up or down to handle changes in requirements or spikes in popularity, reducing the need to forecast traffic. Now this can be a lot of keywords altogether, allow me to introduce the features of Amazon EC2 :

Features of Amazon EC2 :

Virtual Computing Environments : a virtual machine or server (cloud based or physical) known as instances
Amazon Machine Images(AMIs) : preconfigured templates that contains the software configuration
Virtual Private Clouds
Secure login information in form of key pairs( public and private)
And others like, instance types, metadata, firewall, instance store volumes, Elastic IP addresses etc.

Here comes the Virtual Computing Environments into discussion, What is an Instance ?

An EC2 instance is a virtual machine (VM) that runs in the AWS Cloud. When you launch an instance, you decide the virtual hardware configuration by choosing an instance type.

Keynotes:

An instance is a VM.
An instance type is the combination of virtual hardware components, such as CPU and memory, that make up the instance.
Instance names are a combination of the instance family, generation, and size. We will look into this discussion later.

Instance Families :

As we can understand from the image there are five different instance families :

General Purpose

General-purpose instances provide a balance of compute, memory, and networking resources and can be used for a wide range of workloads.
Use cases:
These instances are ideal for applications that use these resources in equal proportions: such as web servers and code repositories.

Compute Optimized

Compute-optimized instances are ideal for compute-bound applications that benefit from high-performance processors. Instances belonging to this family are well suited for compute-intensive operations.

Use cases:

Batch processing workloads
Media transcoding
High-performance web servers
High performance computing (HPC)
Scientific modeling
Dedicated gaming servers and ad server engines
Machine learning (ML) inference
Memory Optimized

Memory-optimized instances are designed to deliver fast performance for workloads that process large data sets in memory.

Use cases:

High-performance, relational (MySQL) and NoSQL (MongoDB, Cassandra) databases.
Distributed web scale cache stores that provide in-memory caching of key-value type data (Memcached and Redis).
Storage Optimized

Storage-optimized instances are designed for workloads that require high, sequential read and write access to very large data sets on local storage. They are optimized to deliver tens of thousands of low-latency, random I/O operations per second (IOPS) to applications.

Accelerated Computing

If you require high processing capability, you will benefit from using accelerated computing instances, which provide access to hardware-based compute accelerators such as graphics processing units (GPUs), field-programmable gate arrays (FPGAs), or AWS Inferentia.
Use cases:

Video rendering
Analytics (big data)

Decoding nomenclature:

Analysing the picture , we can easily decipher the instance naming hence I am refraining for elaboration.

Amazon EC2 Pricing

Amazon EC2 offers a variety of pricing options for different use cases and definitely you pay only for the compute time.
Below are the categories :

On Demand Instances

On-Demand Instances are ideal for short-term, irregular workloads that cannot be interrupted. Use cases for On-Demand Instances include developing and testing applications and running applications that have unpredictable usage patterns.

Reserved Instances

Reserved Instances are a billing discount applied to the use of On-Demand Instances in the account. At the end of a Reserved Instance term, one can continue using the Amazon EC2 instance without interruption. However, they charge On-Demand rates until any action is taken.

Savings Plan

Amazon EC2 Savings Plans are ideal for workloads that involve a consistent amount of compute usage over a 1-year or 3-year term. With Amazon EC2 Savings Plans, you can reduce your compute costs by up to 72% over On-Demand costs.

Spot Instances

Spot Instances are ideal for workloads with flexible start and end times, or that can withstand interruptions. With Spot Instances, you can reduce your compute costs by up to 90% over On-Demand costs. Unlike Amazon EC2 Savings Plans, Spot Instances do not require contracts or a commitment to a consistent amount of compute usage.

Dedicated Hosts

Dedicated Hosts are physical servers with Amazon EC2 instance capacity that is fully dedicated to your use. On-Demand Dedicated Hosts and Dedicated Hosts Reservations can be purchased. Of all the Amazon EC2 options that were covered, Dedicated Hosts are the most expensive. I will highlight on the diffference between Dedicated Hosts and Dedicated Instances later.

That's it for today!! Next day I will be discussing on Scaling and Elastic Load Balancing. And I am extremely excited for this.

Cloud Computing #Day 1

Giriraj Roy — Mon, 18 Jul 2022 13:33:32 +0000

Introduction

Client - Server Model

Modern cloud computing follow the Client-Server model where a client can be a web browser or desktop application that a person interacts with to make requests to computer servers. A server can be services such as Amazon Elastic Compute Cloud (Amazon EC2), a type of virtual server.

What is Cloud Computing ?

The term cloud computing refers to the technology that makes cloud work.

Cloud computing is on-demand access, via the internet, to computing resources—applications, servers (physical servers and virtual servers), data storage, development tools, networking capabilities, and more—hosted at a remote data center managed by a cloud services provider (or CSP) for a monthly subscription fee or bills them according to usage.

Cloud Computing Services

IaaS (Infrastructure-as-a-Service), PaaS (Platform-as-a-Service) , and SaaS (Software-as-a-Service) are the three most common models of cloud services, Apart from Serverless Computing and Faas ( Function as a Service).

The Chart Below will distinguish between them :

Serverless Computing

Serverless computing (also called simply serverless) is a cloud computing model that offloads all the backend infrastructure management tasks–provisioning, scaling, scheduling, patching—to the cloud provider, freeing developers to focus all their time and effort on the code and business logic specific to their applications.

Serverless runs application code on a per-request basis only and scales the supporting infrastructure up and down automatically in response to the number of requests.

FaaS, or Function-as-a-Service, is often confused with serverless computing when, in fact, it's a subset of serverless. FaaS allows developers to execute portions of application code (called functions) in response to specific events.

Types Of Cloud Computing

Cloud Computing can be broadly classified into two categories:

Public Cloud
Private Cloud

Public Cloud

Public cloud is a type of cloud computing in which a cloud service provider makes computing resources—anything from SaaS applications, to individual virtual machines (VMs), to bare metal computing hardware, to complete enterprise-grade infrastructures and development platforms—available to users over the public internet accessible for free, or access might be sold according to subscription-based or pay-per-usage pricing models.

Public cloud is a multi-tenant environment—the cloud provider's data center infrastructure is shared by all public cloud customers. In the leading public clouds—Amazon Web Services (AWS), Google Cloud, IBM Cloud, Microsoft Azure, and Oracle Cloud—those customers can number in the millions.

Private Cloud

Private cloud is a cloud environment in which all cloud infrastructure and computing resources are dedicated to, and accessible by, one customer only. Private cloud combines many of the benefits of cloud computing—including elasticity, scalability, and ease of service delivery—with the access control, security, and resource customization of on-premises infrastructure.

After understanding the structures on how both private cloud and public cloud works, a conclusion can be derived by building private cloud architecture according to cloud native principles, an organization gives itself the flexibility to easily move workloads to public cloud or run them within a hybrid cloud environment whenever they’re ready.

Hybrid Cloud

The goal of hybrid cloud is to establish a mix of public and private cloud resources—and with a level of orchestration between them—that gives an organization the flexibility to choose the optimal cloud for each application or workload and to move workloads freely between the two clouds as circumstances change. This enables the organization to meet its technical and business objectives more effectively and cost-efficiently than it could with public or private cloud alone.

Cloud Security

Nevertheless, maintaining cloud security demands different procedures and employee skillsets than in legacy IT environments. Some cloud security best practices include the following:

Shared responsibility for security
User identity and access management
Security and compliance monitoring

DEV Community: Giriraj Roy

Cloud Computing #Day5

Availibility Zones

Amazon CloudFront and Edge locations

Interacting with AWS Services

The AWS Management Console

The AWS Command Line Interface

Software Development Kits (SDKs)

Amazon Elastic BeanStalk

Using IAAS as AWS CloudFormation

Happy Coding ☕☕

Cloud Computing #Day4

The Flaw:

Monolithic Application And Microservices

Amazon Simple Notification Service (Amazon SNS)

Amazon Simple Queue Service (Amazon SQS)

Serverless Computing

AWS Lambda

How Lambda Works

Containers

Cloud Computing #Day 3

Scalability

Amazon EC2 Auto Scaling

Diving Deeper

Working Principle >>

Chalking out the Benefits

Elastic Load Balancing

Use Cases

Cloud Computing #Day 2

What is Amazon EC2 ?

Features of Amazon EC2 :

Here comes the Virtual Computing Environments into discussion, What is an Instance ?

Keynotes:

Instance Families :

General Purpose

Compute Optimized

Memory Optimized

Storage Optimized

Accelerated Computing

Decoding nomenclature:

Amazon EC2 Pricing

On Demand Instances

Reserved Instances

Savings Plan

Spot Instances

Dedicated Hosts

Cloud Computing #Day 1

Introduction

Client - Server Model

What is Cloud Computing ?

Cloud Computing Services

Serverless Computing

Types Of Cloud Computing

Cloud Computing can be broadly classified into two categories:

Public Cloud

Private Cloud

Hybrid Cloud

Cloud Security