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How DevOps Changes Monitoring

One of the most interesting changes that I have observed in my career is Microsoft shifting from just being a development organization to truly becoming a DevOps team, in the case of the SQL Server team. The product code developers are the operations support for the cloud service hosting Azure SQL Database. Many other large development organizations have this model, but my relationships and experience with SQL Server have allowed me to observe this product much more closely. My major observation is that the major reason dev cycles turn so much faster is to fix problems that in traditional on-premises software would have possibly taken months between patches, or even years between full releases, that now get fixed in the course of a few weeks. This has really changed the way Microsoft releases SQL Server on-premises--after a major release, there is a cumulative update released every month for the first year. This means more problems get fixed faster, and if you are using the cloud service, the release cadence is even faster. I know most of us do not work for hyper-scale public cloud providers with massive development resources, but I used this example because it is a very real-world visible impact into the way a DevOps model can transform an organization. So how does this apply to running our infrastructure organizations? I think even in the most off-the-shelf traditional shop, you should be thinking about how to automate the following work:
  • Manual
  • Repetitive
  • Work with no enduring value
  • Work that doesn’t scale with your application
As a system admin, your main job task is to keep the lights (and more importantly, the servers) on in your organization. By adopting a mindset of trying to automate as many of these tasks as possible, you will enjoy your job more, and have more time to focus on tasks that are more strategic to your organization. You can take advantage of frameworks like PowerShell and Python scripting in your environments (yes, you will have to write some code) to bring this all together, but this mindset will change the way you view system administration. Where do you start with automation? Identify your most common tasks that consume the most time--for example, if you are using VM templates to deploy your operating system environments (that’s a really fancy way of saying VMs), you have already started down this path. A logical next stop might be to automate the process for keeping your templates up to date with patches, or to use scripting to ensure that any post-deployment configuration tasks happen without human intervention. To do this really well, you should adopt a developer mindset--all of your scripts should use source control, you should work to develop a unit testing process (the one negative to automation is that if you break something badly, you can break a lot of things badly, and quickly), and some aspects of a development methodology to keep the progress moving forward. Moving into this mindset is a big shift for many organizations. However, in modern IT, influences like cloud and the aforementioned rapid development cycles mean that everything just moves faster. The other benefit of this automation, which should be a major influence on what tasks you automate, is the reduction in alert pages. If you can automate away your most common pager responses, your entire team and organization will benefit. The final, largest benefit of automation is that you know a script will run the same every time it's executed, as opposed to your junior admin, who may or may not get a complex task sequence correct each time.
Joey D'Antoni
Joey D'Antoni is a principal consultant at Denny Cherry and Associates Consulting. He is recognized as a VMware vExpert and a Microsoft Data Platform MVP…
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