Today we are releasing another chapter in preview for Inside Azure Management v4 book. This one is focused on automation in Azure. As I have mentioned before this will be free book with option to purchase via Amazon as well. On this blog post I would like to thank the main authors of the book Pete Zerger, Tao Yang and Kevin Greene. Additionally I would like to thank as well to Ryan Irujo, Alexandre Verkinderen and Bert Wolters who also helped with a few chapters. Download the chapter and subscribe for future book updates from by clicking on the book cover below.
These are challenging times for the whole world but to stay true to ourselves we are preparing for the release of the 4th edition of Inside Azure Management book. We expect to be ready no later than 15th of May but as you can understand many of us are busy supporting our customers from home. The book as always will be free download but of course you will be able to purchase it via Amazon as well if you want to. Return to this blog post in a few days to check for the Amazon link. We have worked hard to update the content to the latest changes inside Azure but also to give you some new scenarios.
In IT naming of resources has been around for quite some time. In some of the early days IT personal was using super hero names, constellation names, etc. to name their servers. That was when the number of servers count was equal or less than your fingers. Over the years the number of servers has went up which required using naming convention. Another need for the naming convention was also the different role each server had. Of course with the coming of the cloud the result is that even more resource started to be generated. Strangely though we haven’t changed much our guidelines for naming resources much compared to how we did it on-premises. But may be it is time to change them?
With the recent capability of setting retention period for Log Analytics data per table a lot of new possibilities of managing and retaining your data pop-up. A common scenario is that you may have a lot of performance data which may be logged every minute or even every 10 seconds. You need that data in such short intervals in your Log Analytics workspace only for the past month or so but you do not need such granularity for older data. At the same time it is good to have some summarization (aggregation) of that data for longer period due to compliance, analysis, etc but there is a cost associated when you retain a lot of data for longer period. By using serverless and the new per table retention capability now you can achieve this and save cost. In this blog I will show you how you can achieve this with simple example.
At Ignite the Azure Monitor team has announced that you can now send subscription activity logs to Log Analytics. Wait? What? Isn’t that already available? And the answer yes it was available before but if we look closer you will see that the previous implementation was not very native to Azure. With the new implementation besides making the API better there are also other improvements like faster ingestion, ability to send different categories, etc.