Cloud articles

Looking for something else? Check the categories of Cloud:

Data engineering on AWS Data engineering on Azure Data engineering on GCP Data engineering on the cloud

If not, below you can find all articles belonging to Cloud.

Data Loss Prevention on the cloud

When I was writing my previous blog post about losing data on the cloud, I wanted to call it "data loss prevention". It happens that this term is currently reserved for a different problem. The problem that I will cover just below.

Continue Reading →

Not losing data on the cloud - strategies

Data is a valuable asset and nobody wants to lose it. Unfortunately, it's possible - even with the cloud services. Hopefully, thanks to their features, we can reduce this risk!

Continue Reading →

Less known data services on the cloud

You all certainly heard about EMR, Dabricks, Dataflow, DynamoDB, BigQuery or Cosmos DB. Those are well known data services of AWS, Azure and GCP, but besides them, cloud providers offer some - often lesser known - services to consider in data projects. Let's see some of them in this blog post!

Continue Reading →

Azure Durable Functions

When I first heard about Durable Functions, my reaction was: "So cool! We can now build fully serverless streaming stateful pipelines!". Indeed, we can but it's not their single feature!

Continue Reading →

What's new on the cloud for data engineers - part 4 (05-08.2021)

It's time for the 4th part of the "What's new on the cloud for data engineers" series. This time I will cover the changes between May and August.

Continue Reading →

Cloud networking aspects for data engineers

Guess what topic I was afraid of at the beginning of my cloud journey as a data engineer? Networking! VPC, VPN, firewalls, ... I thought I would be able to live without the network lessons from school, but how wrong I was! IMO, as a data engineer, you should know a bit about networking since it's often related to the security part of the architectures you'll design. And in this article, I'll share with you some networking points I would like to know before starting to work on the cloud.

Continue Reading →

Data pipeline patterns with Azure Data Factory

Almost 2 years ago (already!), I wrote a blog post about data pipeline patterns in Apache Airflow (link in the "Read also" section). Since then I have worked with other data orchestrators. That's why I would like to repeat the same exercise but for Azure Data Factory.

Continue Reading →

Costs management on the cloud

The easiest way to learn is by doing but what if it involves leaving your credit card number beforehand? I've never been comfortable with that but there is no other choice to get some hands-on experience on the cloud. Hopefully, it doesn't mean you can't control your expenses. In this article, we'll see how.

Continue Reading →

Serverless streaming processing on the cloud: Azure Stream Analytics vs AWS Kinesis Data Analytics

I was writing this blog post while preparing for Azure's DP-200 and DP-201 certification. Why? To make some cleaning in my head and organize what I learned about Azure Stream Analytics and compare it with what I knew about AWS Kinesis Analytics.

Continue Reading →

Data architectures on the cloud

I haven't fully understood it yet, why the story of data architectures is the story of Greek letters. With time, they changed the context and had to adapt from an on-premise environment, often sharing the same main services, to the cloud. In this blog post, I will shortly present data architectures and try to fit them to cloud data services on AWS, Azure and GCP. Spoiler alert, there will be more pictures than usual!

Continue Reading →

Windows to the clouds

Guess what? My time-consuming learning mode based on reading the documentation paid again! This time on Azure because while reading about Stream Analytics windows I discovered that I missed some of them in the past. And since today is the day of the cloud, I will see if the same types of windows exist on AWS and GCP streaming services. And if no, what are the differences.

Continue Reading →

AWS Redshift vs Azure Synapse Analytics

You know me already. I like to compare things to spot some differences and similarities. This time, I will do this exercise for cloud data warehouses, AWS Redshift, and Azure Synapse Analytics.

Continue Reading →

Small data processing on the cloud

Believe it or not, but data processing is not only about Big Data. Even though data is one of the most important assets for modern data-driven companies, there is still a need to process small data. And to do that, you will not necessarily use the same tools as for bigger datasets.

Continue Reading →

Object stores on the cloud

The next step of my multi-cloud exploration will be object stores. In the article I will try to find similarities between S3, Storage Account and GCS.

Continue Reading →

Dead-letter pattern on the cloud

Data is not always as clean as we would like it to be. The statement is even more true for semi-structured formats like JSON, where we feel working with a structure, but unfortunately, it's not enforced. Hence, from time to time, our code can unexpectedly fail. To handle this problem - as for many others - there is a pattern. It's called dead-letter qnd I will describe it below in the context of cloud services.

Continue Reading →

Azure Data Factory control flows in Apache Airflow

How to orchestrate your data pipelines on the cloud? Often, you will have a possibility to use managed Open Source tools like Cloud Composer on GCP or Amazon Managed Workflows for Apache Airflow on AWS. Sometimes, you will need to use cloud services like for Azure and its Data Factory orchestrator. Is it complicated to create Data Factory pipelines with the Apache Airflow knowledge? We'll see that in this blog post.

Continue Reading →

Streaming data sources on the cloud

Streaming broker is one of very common entry points for modern data systems. Since they're running on the cloud, and that one of my goals for this year is to acquire a multi-cloud vision, it's a moment to see what AWS, Azure and GCP propose in this field!

Continue Reading →

My journey to Azure Data Engineer Associate

I'm happy to complete my quest for data engineering certification on top of 3 major cloud providers. Last year I became AWS Big Data certified, in January a GCP Data Engineer, and more recently, I passed DP-200 and DP-201 and became an Azure Data Engineer Associate. Although DP-203 will soon replace the 2 exams, I hope this article will help you prepare for it!

Continue Reading →

Serverless streaming on AWS - an overview

If you already worked on AWS and tried to implement streaming applications, you certainly noticed one thing. There is no single way to do it! And if you didn't notice that, I hope that this blog post will convince you, and by the way, help you to get a better understanding of the available solutions.

Continue Reading →

What's new on the cloud for data engineers - part 3 (02-04.2021)

It's time for the 3rd part of "What's new on the cloud for data engineers" series. This time I will cover the changes between February and April.

Continue Reading →