Compared: Azure Load Balancer, Application Gateway, Traffic Manager

The following table summarizes the features offered by each service:

Service Azure Load Balancer Application Gateway Traffic Manager
Technology Transport level (Layer 4) Application level (Layer 7) DNS level
Application protocols supported Any HTTP, HTTPS,  HTTP/2 & WebSockets Any (An HTTP endpoint is required for endpoint monitoring)
Endpoints Azure VMs and Cloud Services role instances Any Azure Internal IP address or public internet IP address Azure VMs, Cloud Services, Azure Web Apps, and external endpoints
Vnet support Can be used for both Internet facing and internal (Vnet) applications Can be used for both Internet facing and internal (Vnet) applications Only supports Internet-facing applications
Endpoint Monitoring Supported via probes Supported via probes Supported via HTTP/HTTPS GET
Health Monitoring TCP probe
HTTP probe		 HTTP probe
HTTPS probe		 TCP probe
HTTP probe
HTTPS probe
Source IP/Sticky session Supported, 2- or 3-tuple source affinity Supported, cookie-based affinity Not Supported
Traffic controls Network Security Groups Network Security Groups Geo-traffic Restriction

This slide from the Ignite 2016 – Microsoft Azure Networking: New Network Services, Features And Scenarios session summarizes it well
click on image for enlarged view
Traditional load balancers operate at the transport layer (OSI layer 4 - TCP and UDP) and route traffic based on source IP address and port, to a destination IP address and port. But with the Application Gateway you can be even more specific. For example, you can route traffic based on the incoming URL. So if /images is in the incoming URL, you can route traffic to a specific set of servers (known as a pool) configured for images. If /video is in the URL, that traffic is routed to another pool optimized for videos.

Also see:
Options for Load Balancing Services in Azure
Azure Application Gateway - Highlights
What is the difference between Azure Application Gateway, Load Balancer, Front Door and Firewall?

Comments

Post a Comment

Popular posts from this blog

Maven Crash Course - Learn Power Query, Power Pivot & DAX in 15 Minutes

Image
In the Maven Crash Course " Learn Power Query, Power Pivot & DAX in 15 Minutes ", Chris Dutton walks through a hypothetical business case while showcasing the power of modern Excel tools like Power Query, Power Pivot and DAX. Power Query is used to extract, transform, and load data from external sources like SQL databases, PDF and CSV files. A relational model is created to join the tables without writing a single formula. Exploratory analysis is done using Power Pivot and Data Analysis Expressions (DAX). Data Analysis Expressions is the language that we can use to define new calculated columns and measures to enhance our Data Model instead of the traditional cell formulas that we'd typically use if our data was stored in worksheets. Pivot Charts and slicers are used to design a simple interactive report that the sales managers can use to analyze revenue trends and product performance.
Read more

"Data Prep & Exploratory Data Analysis" course by Maven Analytics

Image
The Maven Analytics course on " Data Prep & Exploratory Data Analysis " by Alice Zhao is a beginner-friendly introduction to machine learning with Python. It covers the key steps of the data science workflow, including: Gathering Data Scoping a Project Modeling Data Sharing Insights Cleaning Data Exploring Data Modeling Data  Sharing Insights The presentation deck which is available as a download crisply summarizes the essential details and is a great reference to keep going back to. The course is well-suited for aspiring data scientists looking to get hands-on experience with the data prep and EDA stages of the machine learning workflow using Python and Jupyter Notebook. 
Read more

Oracle Cloud Infrastructure 2024 Generative AI Professional Course & Certification Exam (1Z0-1127-24)

Image
I was happy to learn about the Oracle Cloud Infrastructure 2024 Generative AI Professional Course with video tutorials and the Certification Exam (1Z0-1127-24) from their newsletter. I found it extremely useful, timely, and relevant. The course, with about 6 hours of videos, provided me with a comprehensive view of what it takes to build a Generative AI application. Although some parts reference OCI services, much of the course remains vendor neutral. Rohit Rahi and his team at Oracle have done a great job of structuring the beginner-friendly yet comprehensive course so well, covering all the essentials across four modules. The curriculum strikes an excellent balance between depth and accessibility.  While Gen AI output is typically non-deterministic, I was surprised to learn that they can be made completely deterministic under certain conditions. Specifically, in the OCI Gen AI service, setting the temperature parameter to 0 produces consistent, deterministic output for a g...
Read more