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Amazon API Gateway is a fully managed service that makes it easy for developers to create, publish, maintain, monitor, and secure APIs at any scale. APIs act as the “front door” for applications to access data, business logic, or functionality from your backend services.
AWS Lambda lets you run code without provisioning or managing servers. You pay only for the compute time you consume. With Lambda, you can run code for virtually any type of application or backend service – all with zero administration.
In this activity guide, you will learn how to create an API Gateway and Integrating it with Lambda
Setting Up AWS Config to Assess Audit & Evaluate AWS Resources
AWS Config is a service that enables you to assess, audit, and evaluate the configurations of your AWS resources. Config continuously monitors and records your AWS resource configurations and allows you to automate the evaluation of recorded configurations against desired configurations. With Config, you can review changes in configurations and relationships between AWS resources, dive into detailed resource configuration histories, and determine your overall compliance against the configurations specified in your internal guidelines.
In this activity guide, you will learn how to Enabling Governance using AWS Config.
AWS Elastic Beanstalk is an easy-to-use service for deploying and scaling web applications and services developed with Java, .NET, PHP, Node.js, Python, Ruby, Go, and Docker on familiar servers such as Apache, Nginx, Passenger, and IIS.
You can simply upload your code and Elastic Beanstalk automatically handles the deployment, from capacity provisioning, load balancing, auto-scaling to application health monitoring. At the same time, you retain full control over the AWS resources powering your application and can access the underlying resources at any time.
In this activity guide, you will learn to deploy, and scale web applications and services developed with Node.js, PHP, Python, etc on different servers.
AWS OpsWorks is a configuration management service that provides managed instances of Chef and Puppet. Chef and Puppet are automation platforms that allow you to use code to automate the configurations of your servers.
AWS CloudFormation gives you an easy way to model a collection of related AWS and third-party resources, provision them quickly and consistently, and manage them throughout their lifecycles, by treating infrastructure as code.
A CloudFormation template describes your desired resources and their dependencies so you can launch and configure them together as a stack.
In this activity guide, you will learn to create, update, and delete an entire stack as a single unit, as often as you need to, instead of managing resources individually. You can manage and provision stacks across multiple AWS accounts and AWS Regions.
AWS CodePipeline is a fully managed continuous delivery service that helps you automate your release pipelines for fast and reliable application and infrastructure updates.
CodePipeline automates the build, test, and deploy phases of your release process every time there is a code change, based on the release model you define. This enables you to rapidly and reliably deliver features and updates.
You can easily integrate AWS CodePipeline with third-party services such as GitHub or with your own custom plugin. With AWS CodePipeline, you only pay for what you use. There are no upfront fees or long-term commitments.
Azure Synapse is like a forest fire in the rapidly evolving technological landscape. Data serves as the fuel to start this fire. Just like fuel is necessary to keep a fire going, quality data is necessary for better cloud-based performance.
The demand for data storage, upkeep, and transfer from one site to another is rising as many new enterprises enter the IT industry. Understanding Azure Synapse Analytics is essential as a result.
This technology is a progression of Azure SQL Data Warehouse. A powerful relational database that is scaled up and hosted in the cloud is Azure SQL Data Warehouse.
It is made to process and store massive volumes of data on the Microsoft Azure cloud computing system. This platform as a service is completely managed and offers a variety of cloud solutions.
Two characteristics that are widely used to combine data from many data sources, explain metrics, and safeguard your data in a single, dependable tabular data model are advanced mashup and modelling capabilities.
Characteristics of Azure Synapse
Variety of analytics services with unparalleled time to insight
Real-time data stream processing from more than millions of IoT devices
Analytics for businesses offered as a service
Apply ML algorithm to all of your smart applications
Broaden the insights you can discover from all of your data.
With Azure Synapse Link, remove data barriers and run analytics on data from operational and business apps.
Secure data using the industry’s most cutting-edge security and privacy features.
The architecture of Azure Synapse
Let’s discuss the various architecture of Azure Synapse Analytics which are as follows:
Pool Architecture of Azure Synapse
The term “suggested Synapse SQL” denotes the ability of Synapse Enterprise to perform analytics with the aid of T-SQL. It consists of the following two pools:
Dedicated SQL Pool: A workspace may contain an unlimited number of dedicated SQL pools, which are typically used for dedicated models.
Serverless SQL Pool: Every workspace has at least one serverless SQL pool, which is mostly utilized for serverless models.
Apache Spark for Azure Synapse Analytics
Azure Synapse Analytics uses Serverless Apache Spark pools that are created and used in Synapse workspace to use spark analytics. It consists of the following parts:
Spark for Synapse with Apache
Apache Spark application Spark pool
Job definition for Spark
Notebook
Synapse Pipeline
It has these characteristics which come under the synapse pipeline:
Integration of Data
Data Stream
Pipeline
Activity
Trigger
combined dataset
Synapse Studio
Synapse Studio consists of architecture that is secured and has trustworthy collaboration boundaries for doing cloud-based analytics in Azure and can be easily deployed in specific regions, Moreover, it collaborated with ADLS Gen2 account and file system for temporary data storage.
Azure Synapse Service for industries
Financial Services: Ensure data is secure with industry-leading features. As it stays ahead for maintaining a competitive edge by employing a modern strategy for handling big data, data warehousing, creating individualized customer experiences and putting in place strong compliance and governance procedures to safeguard consumer data.
Manufacturing Service: Utilizing Azure Synapse Analytics to gain scalable real-time insights. Combining operational and analytical technologies, Industry 4.0 enables real-time access to both new and old data.
Retail Service: With an end-to-end analytics service, you can combine data from several channels and gain real-time insights, which will help you better understand your consumers and build a reliable supply chain.
Healthcare Service: Pressures on the healthcare sector include a lack of care workers, legislative restrictions, and shifting patient expectations. Deliver individualized treatment, safeguard patient data, and empower care teams.
Go through these Azure Synapse Analytics Interview Questions and Answers to excel in your interview.
Real-Life Application of Azure Synapse
Data Warehouse: Seamless interaction with a variety of platforms and data providers
Exploratory Analysis: Data exploration and finding out using SQL queries opposite a synapse database
Data Visualization: Collaborating with Tableau or Excel for faster and informal decision making
Real-Time Analytics: Data unification of different operational sources to deploy real-time exploratory solutions with the help of BI tools such as PowerBI and Tableau.
Step up Analysis: Utilizing Azure Databricks to get the most out of your data and improve business outcomes or results that can be drawn from the analysis that we did from the BI tools such as PowerBI and Tableau.
Moreover, Real life usage of Azure Synapse Analytics is that it can perform very complex queries and aggregations. Moreover, we can use this technology for creating a dashboard that is a combination of sheets or views that helps us to compare a vast amount of data in the same amount of time by providing excellent and user-friendly features that will help us to understand the visualization by using different graphs used by BI tools such as Bar chart, Line chart, Pie chart, Word map, Scatterplot, Gantt chart, Bubble chart, Treemap, Pareto chart, etc.
Moreover, we can create storytelling by using Azure Synapse which includes a sequence of visualizations that work together to convey information. We can create stories to tell a data narrative, provide context, demonstrate how decisions relate to outcomes, or simply make a briefcase in a summary format.
