.NET Core Journey

Couple of weeks ago, Microsoft announced .NET Core 3 Preview 1, which is the first public release of .NET Core 3. Let us scan the journey of .NET Core

.NET Core 1
The .NET Core journey began a few years ago, with version 1 in 2016, with the goal of building the first version of .NET that was open source and cross-platform (Windows, macOS and Linux).

Version 1 shipped with new versions of ASP.NET and Entity Framework (EF) and primarily targeted Web applications.

.NET Core 2
While version 1 got .NET running on new platforms, it supported only a limited set of .NET APIs. In order to address this, we created .NET Standard, which specified the APIs that any .NET runtime must implement so that code and binaries can be shared across .NET platforms and versions.

With .NET Standard 2.0, we added more than 20,000 APIs to the .NET Standard spec,  .NET Core 2 also continued the push to make .NET one of the fastest full-stack frameworks.
 
.NET Core 3.0
.NET Core 3.0 is the next major version of the .NET Core platform. It includes many exciting new features, such as support for Windows desktop applications with Windows Forms (WinForms), Windows Presentation Foundation (WPF) and Entity Framework 6. For Web development it adds support for building client-side Web applications with C# using Razor Components (formerly known as Blazor). And it includes support for C# 8.0 and .NET Standard 2.1.

.NET Core 3.0 will also fully support ML.NET, our open source machine learning framework built for .NET developers, along with support for Internet-of-Things (IoT) scenarios.

You can see complete details of the release in the .NET Core 3 Preview 1 release notes at https://github.com/dotnet/core/blob/master/release-notes/3.0/preview/3.0.0-preview1.md

Google Analytics working model

Google Analytics collects the date the moment that visitor navigates to one of the web pages in browser. Embedded within web page content, there is a small block of JavaScript code referred as GATC (Google Analytics Tracking Code)

When the visitor's browser loads the web page, it runs GATC which performs key analytics operations.  First, it loads the Google Analytics master JavaScript file (ga.js) by downloading from Google servers. This code collects data about the visitor (like browser type, version, resolution, page title, etc.) from the browser. 5 cookies (ref image) determine whether the visitor is a repeat to the site with tracking information. Finally, it transmits to the data collection server, in turn persisted as log file at Google.

During the day, Google performs the first pass of these log files on an hourly basis and then runs another more thorough reprocessing pass at the end of the day. Data sources are from raw click data and aggregated summary data in Google's big table database. End user can view the accessed report from Google Analytics web site. 

Microsoft Digital IDentity

Last couple of years, Microsoft has invested in incubating a set of ideas for using blockchain and other distributed ledger technologies to create new types of digital identities—identities that are designed from the ground up to enhance personal privacy, security, and control.

Digital IDentity (DID) will be a first-class citizen of the Microsoft identity stack.

Vision

• Every user needs a digital identity they own, that can securely and privately store all their personal data.
• This self-owned identity must be intuitive and convenient to manage, and provide complete control over how identity data is accessed and used.

Business Benefits

• Deeply engage with users while minimizing privacy and security risks
• Transact with customers, partners, and suppliers over a unified data protocol
• Improve transparency and auditability of your business operations

Microsoft's Whitepaper of DID is available at https://query.prod.cms.rt.microsoft.com/cms/api/am/binary/RE2DjfY

DataStax Enterprise 6.7

This week, DSE 6.7 has been launched with multi-workload support for operational analytics, geospatial search, increased data protection in the cloud, better performance insights, Docker production support, and connectivity to Apache Kafka.

Top-5 improvements of DataStax Enterprise 6.7 includes:

1. Production-ready Kafka and Docker integration
2. Easier, more scalable operational analytics for today’s cloud applications
3. Simplified enterprise search for geospatial applications
4. Improved data protection with smart cloud backup/restore support
5. Improved performance diagnostics with new insights engine and third-party integration

DSE 6.7 and updated versions of OpsCenter, Studio, and DSE Drivers are available for download, as is updated documentation to guide installation and upgrading.

Data sheet of DSE 6.7, is available at https://www.datastax.com/wp-content/uploads/resources/datasheets/DataStax-DS-DataStax-Enterprise-6-7.pdf

AWS CEO at ReInvent 2018

Keynote from Andy Jassy, AWS CEO, included 20 new announcements during this week's AWS ReInvent 2018.

Available Now:

1. Amazon FSx for Windows File Server – Fully-managed Windows file system on Windows native servers
2. Amazon FSx for Lustre – Fully-managed file servers for compute-intensive workloads
3. Amazon DynamoDB On-Demand – Flexible DynamoDB with no capacity planning necessary
4. Amazon Elastic Inference – GPU-Powered Deep Learning Inference Acceleration
5. Amazon SageMaker Ground Truth – Build accurate datasets and reduce costs at the same time
6. AWS Marketplace for Machine Learning – ML algorithms and model packages are now available in the Marketplace
7. Amazon SageMaker RL – Managed Reinforcement Learning with Amazon SageMaker
8. Amazon Forecast – Time series using Amazon’s forecast algorithms

Coming Soon:

1. Amazon S3 Glacier Deep Archive – New long-term data archival class for S3
2. AWS Control Tower – Automate setting up a well-architected multi-account AWS environment
3. Amazon Textract – Optical Character Recognition to extra data from most documents
4. Amazon Personalize – Real-time personalization and recommendation
5. AWS Outposts – Bringing AWS hardware and software on-premises
6. Amazon RDS on VMware – Fully-managed service for on-premises databases
7. Amazon Quantum Ledger Database – Fully-managed ledger databases
8. AWS Managed Blockchain – Managed blockchain service supporting Hyperledger Fabric and Ethereum
9. Amazon Timestream – Database service designed specifically for time-series data
10. AWS Lake Formation – Fully-managed service will help you to build, secure and manage a data lake
11. AWS Security Hub – Centrally view and manage security alerts and automate compliance checks
12. AWS DeepRacer – Go hands-on with Reinforcement Learning with the DeepRacer