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14 Top Data Pipeline Key Terms Explained

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 Here are some key terms commonly used in data pipelines 1. Data Sources Definition: Points where data originates (e.g., databases, APIs, files, IoT devices). Examples: Relational databases (PostgreSQL, MySQL), APIs, cloud storage (S3), streaming data (Kafka), and on-premise systems. 2. Data Ingestion Definition: The process of importing or collecting raw data from various sources into a system for processing or storage. Methods: Batch ingestion, real-time/streaming ingestion. 3. Data Transformation Definition: Modifying, cleaning, or enriching data to make it usable for analysis or storage. Examples: Data cleaning (removing duplicates, fixing missing values). Data enrichment (joining with other data sources). ETL (Extract, Transform, Load). ELT (Extract, Load, Transform). 4. Data Storage Definition: Locations where data is stored after ingestion and transformation. Types: Data Lakes: Store raw, unstructured, or semi-structured data (e.g., S3, Azure Data Lake). Data Warehous...
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AWS Vs Azure Load Balancers Top Insights

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In AWS, you have three types of load-balancers. In the case of Azure, you have only two load balancers. This post tells you the comparison between these two.


1. AWS Load Balancers:

  • Application Load balancer
  • Network Load balancer
  • Classic Load balancers.


a. Application Load Balancer


Balancing of HTTP and HTTPS traffic and provides advanced request routing targeted at the delivery of modern application architectures, including micro-services and containers. 


Operating at the individual request level (Layer 7), Application Load Balancer routes traffic to targets within Amazon Virtual Private Cloud (Amazon VPC) based on the content of the request.


b. Network Load Balancer


Network Load Balancer is best suited for load balancing of Transmission Control Protocol (TCP), User Datagram Protocol (UDP), and Transport Layer Security (TLS) traffic where extreme performance is required.


c. Classic Load Balancer


The Classic Load Balancer provides the basic load-balancing across multiple Amazon EC2 instances. 


It operates at both the request level and connection level. Classic Load Balancer the real use is for applications that build within the EC2-Classic network.


AWS vs Azure load balancers explained in this post for your quick reference.

2. Azure Load Balancers:


In the case of Azure load balancers, it has two types. And is needs many steps to make it workable:


  • Create an Azure load balancer
  • Create a load balancer health probe
  • Create load balancer traffic rules
  • Use the Custom Script Extension to create an IIS-site
  • Create virtual machines and attach them to a load balancer
  • View a load balancer in action
  • Add and remove VMs from a load-balancer


The Azure has two types of load balancers. Those are:

  • Public Load-Balancer.
  • Private( Internal) Load-balancer.


i. Public Load Balancer


A public load-balancer can provide outbound connections for virtual machines (VMs) inside your virtual network by translating their private IP-addresses to public IP-addresses. 


Public Load-Balancer's purpose is to load balance internet traffic to your VMs.


ii. Private Load Balancer


In the case of an internal (or private) load balancer, you need private IPs for the frontend only. 


The purpose of this is to load-balance the traffic inside a virtual network. It is true that accessing of frontend from an on-premises network is a hybrid scenario.


iii. Azure Load Balancer Features


  1. Load balancing of internal and external traffic.
  2. Connectivity of Azure virtual Machines.
  3. Security.


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