How to select the right strategy to satisfy your application needs. There is a point when every application will be deployed. We can delegate this activity to an automated task or do it manually, but we need to have a deploy strategy behind the scenes. I read many guides about deployments, most of them where good explanations about how you can implement a given solution.
There is a point when every application will be deployed. We can delegate this activity to an automated task or do it manually, but we need to have a deploy strategy behind the scenes. I read many guides about deployments, most of them where good explanations about how you can implement a given solution. The missing link with the real world is matching the implementation with the needs. In simple words, you must understand your requirement before applying a solution. That’s why I want to focus on the scenarios as well as the strategies.
You will discover in the next paragraph that each deployment strategy satisfies different needs. Recognize your use-case is essential for selecting the right tool. Each solution must be compatible with the application requirements, and this also includes the budget variable into the list.
You are right; it scents of trade-off threat. But that’s what it is. You cannot shoot a fly with a bazooka.
Ask your customer if he prefers a deployment strategy that doesn’t bring offline its service or not. I think it’s easy to guess its answer.
When it is possible, we need to keep the service alive during the deployment process. For a simple application, with few users, this may seem overkill, but it’s often possible to implement a zero-downtime DevOps process with the same effort. So, probably, the zero-downtime is something we should always put into account.
In many scenarios, we need to maintain two versions at the same time (old and new, with and without the new feature,etc.). This solution is relatively easy to implement if you think of your automated deployment services, maybe with an infrastructure creation stage. The significant matter is the cost. Not often, running two instances of the same application is link running two simple virtual machines. For a vast system, the cost of doubling the infrastructure to run two parallel versions of an application may be prohibitive. So, probably, keeping multiple systems available at the same time will be an issue.
I can continue with other examples, but the question is simple. We need to tune our solution on the real need of the application.
Simplifying too much leads to something that works today, but will stop working tomorrow. Being too much far-sighted let you sleep soundly but may impact on your budget.
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