Throughout the week, I read a lot of blog-posts, articles, and so forth, that has to do with things that interest me:
- data science
- data in general
- distributed computing
- SQL Server
- transactions (both db as well as non db)
- and other “stuff”
This blog-post is the “roundup” of the things that have been most interesting to me, for the week just ending.
Distributed Computing
- O’Reilly Publishes “The State of Microservices Maturity” Report. This is an InfoQ article discussing a report by O’Reilly about microservices. In the report, O’Reilly concludes that microservices are evolving into a trend and that DevOps and microservices feed off each other.
- Point-to-Point Messaging Architecture - The Reactive Endgame. This is an InfoQ presentation where the presenters explore the current state of messaging architecture and provide an R&D perspective on the future of distributed systems.
.NET
- C# Futures: Lambda Attributes. In this article InfoQ looks at a proposal for adding attributes to lambdas and anonymous functions.
Azure
- Solving a common corporate conundrum: Making sense of all that data. This post discusses the newly announced Azure Data Explorer and its capabilities of analyzing 1 billion records of streaming data per second, as well as data stored in Azure Data Lake Storage.
- High-Performance Modern Data Warehousing with Azure Databricks and Azure SQL Data Warehouse. This blog post discusses how we can use Azure Data Factory, Azure Data Lake Storage together with Azure Databricks to load data into Azure SQL Data Warehouse for analysis, etc.
Data Science
- Announcing ML.NET 0.10 – Machine Learning for .NET. This post does what the title says; it announces the release of ML.NET 0.10. Read the post to see what new features are part of this release.
- Machine Learning with Python, Jupyter, KSQL and TensorFlow. As it says in this post: “This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers.”.
Streaming
- Processing trillions of events per day with Apache Kafka on Azure. This is cool; the post talks about the optimal setup to run one of the largest Kafka deployments in the world, and achieve a throughput of trillion events per day.
- A Beginner’s Perspective on Kafka Streams: Building Real-Time Walkthrough Detection. In retail, it is essential to detect when a customer walks in or out of a store. This blog post discusses how a company used Kafka and KSQL to be able to react quicker and with more accuracy.
SQL Server 2019
- SQL Server Big Data Clusters Workshop at SQL Bits. UK’s leading SQL Server conference SQLBits takes place in Manchester at the end of February. If you are attending, don’t miss Buck Woody’s one day SQL Server 2019 Big Data Cluster workshop. Buck knows what he talks about and he also has members of the SQL Server 2019 Big Data Cluster team on-site. I wish I could be there!
Azure Force Recon
Speaking about conferences and SQL Server Big Data Clusters; February 23 the first of many Azure tactical bootcamps is being held here in Durban, and I have the privilege to do a presentation: Live and Die with your Data, where I talk about SQL Server 2019 Big Data Clusters. So, if you do not have anything else to do, sign up and learn about Azure!
~ Finally
That’s all for this week. I hope you enjoy what I did put together. If you have ideas for what to cover, please comment on this post or ping me.
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