In addition to the general DevOps strategies and development-focused DevOps strategies we’ve described previously, there are also several technical strategies that support the operations-aspects of DevOps:
- Solution monitoring. As the name suggests, this is the operational practice of monitoring running solutions and applications once they are in production. Technology infrastructure platforms such as operating systems, application servers, and communication services often provide monitoring capabilities that can be leveraged by monitoring tools (such as Microsoft Management Console, IBM Tivoli Monitoring, and jManage). However, for monitoring application-specific functionality, such as what user interface (UI) features are being used by given types of users, instrumentation that is compliant with your organization’s monitoring infrastructure will need to be built into the applications. Development teams need to be aware of this operational requirement or, better yet, have access to a framework that makes it straightforward to provide such instrumentation.
- Standard platforms. Software development practices, such as continuous deployment and initial architecture envisioning, are enabled by consistency within your operational infrastructure. It is much easier to deploy to a handful of standard hardware configurations than it is to a myriad of unique ones. It is easier to deploy when there are consistent versions of infrastructure software (e.g. operating systems, databases, middleware, and so on) deployed across your environment. For example, all instances of your Oracle DB are 184.108.40.206, you don’t have 220.127.116.11, 18.104.22.168, and 22.214.171.124 installed in various places. Furthermore, it is much easier to make architecture decisions when there is consistency of infrastructure software packages in the first place. For example you standardize on Linuz for your server operating system, you don’t also have Windows, z/OS and others also in production (and if you do you’re actively retiring them).
- Deployment testing. After a solution, or an update to a component of your operational infrastructure, has been deployed you should run a quick set of tests to verify that the deployment was successful. Were the right versions of the files installed where they need to be? And were they deployed to all appropriate servers? Were database transformations applied successfully? Did the appropriate announcements, if any, get sent out? Did the overall deployment process run within the desired time frame?
- Automated deployment. Deployments should be automated, not manual. This increases the consistency of your deployments and supports the practice of continuous deployment. Part of your automation effort should be to support both self-recovery and self-testing as native aspects of your deployment strategy.
- Support environments. Anyone doing solution support, even if it is the development team itself, is likely to need an environment in which they can reproduce problems that end users experience. There are several options available to you:
- Production. In some cases your production environment is sufficient, although many regulatory regimes, particularly life-critical and financial-critical ones, will not allow this.
- Pre-production test sandbox. Some support teams will find that they can use their pre-production test environment to try to simulate production problems. The advantage is that you don’t put production at risk when trying to reproduce problems, the disadvantage is that you the test environment will be different than production and as a result you may not be able to simulate all reported problems.
- Support sandbox. Some organizations choose to have a specific environment set up to enable support staff to simulate production problems. This strategy has the same tradeoffs as using a pre-production test sandbox plus the additional cost and maintenance associated with yet another environment.
In the next blog posting in this DevOps series we will explore solution support strategies.