Get an in-depth explanation for every question, access them on mobile or PC; the selection is yours!
Knowledge Hut is another venue that helps you steel oneself against AWS tests with its five full-length mock tests and 300 questions. cloud computing technology
you'll undergo this test even on your smartphones and appear multiple times.
It also provides sample questions so you'll get an overall idea of what you'll expect within the real exam. The time for every practice test is 45 minutes and includes 60 questions.
If you're trying to find free practice tests to pump up your confidence before appearing for the AWS certification exam, you'll consider Testprep Training. However, you'll also upgrade to the paid version for just $14.99. It consists of two test modes – practice and exam. There are 76 videos included, alongside 23+ hours of content access.
Passing the important AWS certification exam isn't a simple nut to crack. It requires in-depth knowledge of cloud computing that you simply are able to do with consistent study and practice. Thus, practice tests mentioned above can cause you to able to combat even the foremost difficult papers and pass them with excellent scores.
An Introduction to AWS Lambda for Beginners
When you are building applications, you would like them to deliver a superb user experience. to form the magic happen, your application needs a backend code that runs in response to events.
But managing the infrastructure to host and execute backend code requires you to size, provision, and scale a bunch of servers, manage OS updates, apply security patches then monitor all this infrastructure for performance and availability.
Wouldn’t it's nice if you'll specialize in building great applications without having to stress about their infrastructure? that's where AWS Lambda comes into the image.
What is AWS Lambda?
AWS Lambda may be a serverless compute service that allows you to run your code without fear about provisioning or managing any server. you'll run your application or backend service using AWS Lambda with zero administration. Just upload your code on Lambda, and it'll run your code, even scale the infrastructure with high availability.
The code which you run on AWS Lambda is named a lambda function. Currently, it supports the subsequent programming languages:
It also provides a runtime API that will be wont to run functions written in other (native) programming languages.
To work with AWS Lambda, there's just one prerequisite; you ought to have an account on AWS from where you'll access the AWS management console.
You can call Lambda is FaaS (Function-as-a-Service) by AWS.
AWS Lambda Features
Below are a number of the important features offered by AWS Lambda:
AWS Lambda easily scales the infrastructure with none additional configuration. It reduces the operational work involved.
It offers multiple options like AWS S3, CloudWatch, DynamoDB, API Gateway, Kinesis, CodeCommit, and lots of more to trigger an occasion.
You don’t get to invest upfront. You pay just for the memory employed by the lambda function and minimal cost on the number of requests hence cost-efficient.
AWS Lambda is secure. It uses AWS IAM to define all the roles and security policies.
It offers fault tolerance for both services running the code and therefore the function. you are doing not need to worry about the application down.
AWS Lambda Pricing
AWS Lambda pricing depends on the duration and therefore the memory employed by the lambda function written by you. the utmost you'll assign is 3008 MB memory to a lambda function in 64 MB increments. Below may be a pricing table with all the memory slabs for 100 milliseconds.
First, you create a function and add basic information thereto, just like the programming language to be utilized in the function.
Then you write your code on the lambda editor or upload it during a supported programming language during a zip file.
Once the lambda code is uploaded, the service handles all the capacity scaling, patching, and administration of the infrastructure.
To run the code, you would like to trigger the lambda function with an external AWS service, which may invoke the lambda function. for instance, it is often an S3 bucket.
Within a couple of seconds, lambda is going to be able to trigger your function automatically when an occasion occurs. AWS Lambda runs your code when the trigger event is named. It provisions manages and monitors the servers for you.
If your function requires tons of processing power, it'll choose an instance type that has more processing power and RAM, alternatively if your lambda code only executes for 2 seconds, it'll select a rock bottom possible instance, which saves your money and time.
So, that's how AWS Lambda works internally. Let me show you a demo on AWS Lambda.
Creating AWS Lambda Function
I am getting to create a really simple game using the lambda function in Node.js for this text. I will be able to create a lambda function for rolling a dice, generating variety randomly between 1 to six, and printing it.
Go to AWS management console, and in search bar type Lambda, click on Lambda.
An Introduction to Infrastructure as Code
As per the Accelerate State of DevOps 2019 report survey, 80% of the respondents said that the first application or service they supported was hosted on some quiet cloud platform. 50% of the respondents said their primary application was hosted on the general public cloud.
Why Infrastructure as Code?
Traditionally, if we glance back once you wanted a server, you'd raise a ticket, and someone from the ops team would create a VM instance or order a physical server. this might be using scripts, point and click on, or maybe manual install.
And then, with every request, there would be more VMs, for DNS, mail, databases, and so on. And then, there have been continuous updates to the Operating systems, web servers, JVMs, and everything else. Over time that they had slightly different configurations from one another (configuration drift) leading to snowflake servers. And when something broke, it had been a challenge to trace what changes were made.
This was still acceptable as long as servers were few and long-lived.
A big change happened with the arrival of cloud service companies like AWS. Many companies, rather than investing in hardware and data centers, started moving their applications to the cloud. And within the cloud, you'll deploy a server in minutes, which earlier would take hours or maybe days.
To maintain optimum performance and availability, you'll need to deploy more instances to satisfy demand. then later you'll need to terminate them to save lots of on costs. call center technology
As you pay by the hour, you'll get to proportion or down a day. Doing this manually, repeatedly each day is clearly challenging.
Capturing the steps required to deploy or terminate instances and other infrastructure components in code enables automation. Automation in cloud and infrastructure provisioning can help deliver value faster and reliably.
What is Infrastructure as Code?
Infrastructure as code (IaC) is infrastructure automation using software development principles and practices.
The idea is that you simply treat your infrastructure like the software then write, test, and execute code to define, deploy, update, and destroy your infrastructure. You write code to manage your servers, databases, networks, logs, application deployment & configuration. once you want to form changes to your infrastructure, you create changes to code, test it, then apply it to your systems.
Infrastructure as code offers significant benefits over manual provisioning:
As the infrastructure is defined as code, the whole process and deployment are often automated and may be started by anyone within the DevOps team. Users of infrastructure get the resources they have once they need them.
Being idempotent means you define the specified state, and regardless of what percentage times you run the script, the result's an equivalent. It checks the present state and therefore the desired state and only applies the changes which are needed. this will be extremely difficult to realize with bash scripts.
Tools like Ansible and Terraform have built-in features to form your code idempotent.
Reduces the time and energy required for provisioning, much but manual provisioning.
Faster software delivery
Quick provisioning of infrastructure for development, testing, and production leads to your ability to deliver software much faster. Since the deployment process is automated, it's also consistent and repeatable.
The state of the infrastructure is defined in code that is definitely readable by anyone.
Traditionally changes to the assembly systems are considered risky. But then, change is inevitable. you'll get to add a replacement database once you add a replacement feature. you'll get to add new servers or storage to the cluster. Infrastructure as code reduces the trouble and risk of creating changes to infrastructure.
You can check-in your source files in version control, which suggests you'll track all the changes done to the infrastructure and revert quickly to the previous version if something breaks.
Validation and testing
Infrastructure as code enables testing and applying small changes continuously. As everything is code, you'll check for errors using static analysis and automatic tests.
The shift to infrastructure as code enables you to embed security right from the start, then you'll apply changes reliably and safely.
Infrastructure as Code tools
While many tools are available, choosing one to figure with, might not be easy. Following are a number of the considerations, you would possibly find helpful :
Configuration management vs. provisioning tools
Broadly, tools available fall into two categories –
Configuration management tools.
Configuration management tools
Configuration management tools are designed to manage users, install and manage software and tools on existing servers. Chef, Puppet, Ansible, and SaltStack are all primarily configuration tools.
An Introduction to ☁️ Cloud Service Models – PaaS, SaaS, IaaS, FaaS, and More…
There are many short names utilized in Cloud Service Models, and sometimes it's going to be confusing.
When you start with Cloud Computing, there are many things to find out. during this article, I will be able to mention a number of the favored cloud service models that are widely used and are a must-know for aspiring cloud architects.
Three cloud service models PaaS, SaaS, and IaaS are the foremost important among all, so I will be able to start with them.
PaaS stands for Platform as a Service.
Here, your cloud provider gives you the entire platform to use. once I say the entire platform to use, it means the provider takes care of all the underlying parts of the infrastructure. for instance, your servers are taken care of, and your virtual machines are taken care of, you're given some predefined tools which you'll use to create your applications.
You can use configuration management tools to put in and update the software on servers.
Terraform, CloudFormation, OpenStack Heat, on the opposite hand, are provisioning tools, i.e., wont to create servers, database servers, load balancers, queues, subnets, firewalls, and everyone another component of your infrastructure. These tools make API calls to providers to make the specified infrastructure. Mutable vs. immutable infrastructure
Mutable infrastructure is one that will be modified after it's been provisioned. Chef, Ansible, Puppet & SaltStack are designed to put in or update the software on existing servers. this might happen repeatedly over the lifetime of a server. After many updates, each server is probably going to be a touch different from others, resulting in configuration drift. for instance, some changes which work fine on test servers might not work on production servers.
Tools like Terraform and CloudFormation are designed to make a replacement server from a machine image or a container image whenever. If the servers got to be updated, you replace them with new servers. When the new servers are up, you'll terminate the old ones. Each deployment uses an immutable image to make a server, therefore avoiding configuration drift. this will be a touch slow, though.
Imperative vs. declarative tools
Imperative tools are almost like scripting. You list steps to be taken to reach the specified state. Declarative tools enable you to specify the top state, and therefore the tool works out the steps to realize that state.
While Chef is primarily an important tool, Ansible uses a hybrid approach and supports both imperative and declarative techniques.
Terraform, CloudFormation, Puppet, OpenStack Heat, and SaltStack all belong to the declarative tools category where you declare the specified end state.
Using multiple tools together
Though each of those tools is often used on its own, a standard approach is to use them together. for instance, you'll use Terraform to create VPCs, subnets, Internet gateways, load balancers, and VMs then use Ansible to configure and deploy services on these instances.
Infrastructure defined as code offers many advantages over manual provisioning – it is often version-controlled, tested, results in faster provisioning, and software delivery. Many organization has already started adopting the IaC approach to create and manage their infrastructure.
How about building your own PaaS?
Sounds exciting and therefore the excellent news is you'll create your mini PaaS for your needs.
SaaS stands for Software as a Service.
It means a cloud provider is supplying you with complete software like servers, databases, application codes within the sort of service.
For example, Gmail, where you exchange emails without fear about what's happening within the background. All you've got to try to do is type your email, and it gets delivered to the situation or to the person you would like to deliver it. you're not concerned about how the platform works, what are the safety concerns, what if the server goes down, where is that the mail getting stored, it’s none of your concern.
The service providers are providing you an entire software or an application within the sort of service, that's why this architecture is named Software as a Service.
No got to install anything
Resource managed by the seller
Ex – Freshdesk as a helpdesk and self-service solution.
IaaS stands for Infrastructure as a service.
The definition of infrastructure as a service means only the infrastructure is given to you, everything else is some things that you simply put within the way you would like it, then you employ information technology degrees
. IaaS provides computing architecture and infrastructure aside from that data storage, virtualization servers, and networking.
Let me explain it with an analogy.
For example, suppose you rent a house, now the owner gives you a house and says use it the way you would like to and pay me the rent. So, you're paying the owner for the house, and once you get inside the house, you realize that it only features a bed and a table. aside from that, you would like to place within the kitchen utensils, and you would like to line up the house the way you would like to use it, then you'll plow ahead and use that house. Basically, you're fixing your infrastructure.
Below are some important features of IaaS:
Rented / licensed / pay as you go
Several Levels of Services
100% Resource Availability
GUI or CLI based quick access
Ex – Vultr, Kamatera, AWS, GCP
API as a Service is employed to manage its own custom APIs and permit applications to attach to 3rd party APIs like Google map, voice search API, etc.
It is also utilized in generating documentation of APIs, which describes all the functionalities and dealing with the API. It is often shared with the team using that API or 3rd party APIs.
Using API services, an application can ask for the features stored within the backend.
It provides analytics software over the cloud on the subscription-based model. it's become an important option for businesses to bypass upfront new capital costs and adopt new business process requirements easily.
You can use AaaS for Predictive analytics, Data Analytics, Business Analytics, to seek out insights and trends on the info. during this age of massive Data, AaaS may be a savior. It can clean, analyze, and store insights from Big data in a scalable and cost-effective manner.
The above image is from Cloudflare.
It takes care of all the backend services of an application, and therefore the developers can focus only on writing and maintaining the frontend side of the appliance. It provides backend services like management, user authentication, cloud storage, hosting on the cloud, pushes notifications, etc.
If I take an example of amazon.com, it's one of the foremost popular e-commerce websites worldwide. What you see as a user may be a friendly website or an app, but tons of things are happening at the backend. BaaS can help Amazon with storage, user management, payment gateway, recommendation system, push notification to its user for up to date offers, and lots of more backend functionalities.
Ex – Managed Database by DigitalOcean
Data as a Service
Data as a Service (sometimes also called DaaS) may be a service model that gives pre-aggregated and pre-calculated data, which may provide better insights, and you'll make better business decisions. It uses the cloud to supply data storage, data integration processing, data analysis services using networks.
Less Setup Time
Services/tools managed automatically
Ex – MongoDB
DBaaS stands for Database as a Service.
DBaaS is managed by public and personal cloud providers. It provides database functionalities as a service to internal/external customers. Application developers don't believe database administrators for management when using Database as a Service.
Benefits of using DBaaS.
Reduces operational cost
Easier to deploy and manage
Supports all sizes of business
Pay for what you employ
Automates database operations
Clustering setup in minutes
High-availability across regions
Ex – Scalegrid for MySQL, PostgreSQL, Redis, MongoDB
DaaS stands for Desktop as a Service.
Virtual desktops hosted over the cloud on any device from anywhere. It offers a subscription-based model and is multi-tenant. It improves data security and enhances remote productivity because it provides services altogether the geographies.
Virtual Desktop Infrastructure (VDI) features a lot of similarities to DaaS. The difference between the 2 is that infrastructure on DaaS is hosted over the cloud, whereas the infrastructure of VDI is usually located on-premise.
ex – V2 Cloud
FaaS stands for Function as a Service.
It helps to get rid of the complexities of servers and provides a serverless architecture. you'll specialize in the business logic, and everything within the background is taken care of by service providers—all you've got to stress about code development.
AWS Lambda is an example of FaaS, which has been developed by Amazon. Azure and GCP also supports FaaS through Azure functions and Google Cloud functions.
Removes complexity, provides an abstraction
Billing supported usage only
Provisioning time in milliseconds
Ex – Cloudflare Workers
SECaaS stands for Security as a Service.
Cloud-based security where an application or infrastructure is secured by a cloud-based security provider (CSBP). an easy example of Security as a Service is an antivirus software provided by a corporation like Avast, Norton, McAfee, etc.
Other security services like anti-malware, firewall, penetration testing, intrusion detection, authentication, spam filtering, Identity and Access Management (IAM) are a neighborhood of SECaaS.
Ex – SUCURI for Web Application Firewall
So, these were the important cloud service models that you simply will encounter frequently while working with cloud solutions. plow ahead and check out out anybody of the cloud service models mentioned above using anybody's cloud service provider (AWS, Azure, Google Cloud) to urge a feel of it.