For this post I am assuming you are pretty familiar with the concept of deployment strategies (if not check out this post by Etienne). Now these are typically seen from an application deployment level, where platforms (like for instance Kubernetes) typically have out-of-the box mechanisms in place to do this. Now what if you would want to do this on an “infrastructure level”, like for instance the Kubernetes version of Azure Kubernetes Service. We could do an in-place upgrade, which will carefully cordon and drain the nodes. Though what if things go bad? We could do a Canary, Blue/Green, A/B, Shadow, … on cluster level too? Though how would we tackle the infrastructure point of view of this? That is the base for today’s post!
Architecture at hand
For today’s post we’ll leverage the following high level architecture ;
This project leverages Terraform under the hood. Things like DNS, Traffic Manager, Key Vault, CosmosDB, etc are “statefull’ where its lifecycle is fully managed by Terraform. On the other hand, our kubernetes clusters are “stateless” from an Infrastructure-as-Code point-of-view. We deploy them via Terraform, though do not keep track of them… All the lifecycle management is done on operating on the associated tags afterwards.
The drawing above was not created in Visio for once. The above was made leveraging CloudSkew, which was created by Mithun Shanbhag. Always awesome to see community contributions, which we can only applaud!
Continue reading “Leveraging Azure Tags and Azure Graph for deploying to your Blue/Green environments”
At the last Ignite conference, three new additions joined the Data Box family. In today’s post we’ll take one of those out for a spin, being the “Data Box Gateway“. This one comes as a virtual appliance that you can run on top of your own physical hardware.
So where does it fit into the picture?
- Cloud archival – Copy hundreds of TBs of data to Azure storage using Data Box Gateway in a secure and efficient manner. The data can be ingested one time or an ongoing basis for archival scenarios.
- Data aggregation – Aggregate data from multiple sources into a single location in Azure Storage for data processing and analytics.
- Integration with on-premises workloads – Integrate with on-premises workloads such as backup and restore that use cloud storage and need local access for commonly used files.
Let’s take it for a spin!
So let’s make it a bit more tangible and see what the user experience is in setting it up & using it. Start by searching the Azure Marketplace for Data Box Gateway.
Continue reading “Taking the Azure Data Box Gateway (preview) out for a spin!”
The way how organizations categorize/handle classified information can vary significantly. Where it can go from about 6 categories towards a more “limited” set of 3 to 4 categories. Where you see that some government organizations have even tried to reduce this in an effort to make it more accessible.
So for today, we’ll be looking at how we can handle sensitive/classified information in Azure. And to ensure you that you Azure implementations can facilitate sensitive data.
Side Story : Security should be like a roundabout
Though I don’t remember which conference talk it was… One visual has always stuck with me when talking about security. Imagine security like road infrastructure. Having a complex situation might be needed at times, though it will increase the risk that the drivers (~users) will make mistakes.
Continue reading “Traffic Light Protocol alike Security Reference Architecture for Azure”
The “BulkUploader” module of VMchooser has existed for quite some time. It is without doubt the most loved capability by all the visitors/users. Though where many are accustomed to working with the CSV Input file, do know that you can now also use the export files of Azure Migrate! For today’s post, let’s go through the process…
Let’s take a look
Go to your Azure Migrate project
Continue reading “VMchooser now supports Azure Migrate Exports”
Pfew, it’s odd to admit that it has been a while since I’ve posted about Rancher. Though today is as good a day as any to pick up that thread… So today we’ll go through give or take the same objective as in the past, where we’ll notice that the integration has improved significantly with the arrival of AKS! Let’s get today’s post underway and deploy AKS from our Rancher control plane.
Before the below started, I already had the following things ready ;
Continue reading “Taking a glance at Rancher’s ability to manage the Azure Kubernetes Service (AKS)”
A while ago I talked about “Faas/Serverless” in relation to vendor lock-in. Today we’ll be continuing in that road, where we’ll be doing a small proof-of-concept (PoC). In this PoC, we’ll be replatforming existing Azure Functions code into an Azure Functions container!
Things to know
Since Azure Functions 2.0 (in preview at the time of writing this post), you are able to leverage containers. Though be aware that there are several known issues. Do check them out first before embarking on your journey!
So first, we’ll start off with testing the Azure Functions Core Tools! If you’re looking to follow this guide, be sure to have the Azure Functions Core Tools installed, which also depends on .NET Core 2.0 and Nodejs. Once you have those installed, do a “func –help”, and you’ll see what capabilities are at hand…
Continue reading “Replatforming Azure Functions into an Azure Functions Container”