Things I learnt at the Windows Azure Camp in Hyderabad

Here are some of the new things I learnt at the Windows Azure Camp that was held yesterday at the Microsoft campus in Hyderabad -

* Windows Azure Service Management API is a REST API for managing your services and deployments programmatically to do many of the things that you can do through the Azure portal. Usage of the API is free

* Can the Service Management API be used to replicate a new portal that's like the Silverlight-based Azure portal?
- Not exactly, some info like Billing cannot be fetched through API

* csmanage.exe is a tool to manage your deployments and services, using the Windows Azure Service Management API

* What you can do with Windows Azure Service Management API -
- Integrate with Tools/Dashboards
- Integrate with Build & Deployment - Nightly builds
- Monitoring systems
- Specialized scenarios - Auto scaling

* Azure cannot (currently) auto scale dynamically. Options to implement auto scaling -
- use publically available command-line tools or cmdlets
- third party commercial tools like AzureWatch
- do it yourself using APIs - related link

* Why do Azure APIs use REST?
- REST APIs make Azure access language independent

* The Windows Azure SDK 1.3 adds the ability to use Remote Desktop Services to access Windows Azure roles and supports Full IIS, allowing your web roles to access the full range of web server features available in an on-premise IIS installation.

* Domino’s Pizza is a public site that uses Azure

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