'Containers vs. Serverless: Which is Better for DevOps?' by rehemagi serverless devops
I want to tell you about the pros and cons of managing your own containers versus letting serverless do it for you. The tribal warfare needs to stop. Let's just agree on a couple of facts. Both technologies have awesome use-cases and valid pain points.
I just want to tell you when to use what. In response to this, there are several factors to take into account. The main, most prominent, is indeed development speed and time-to-market for startups. But, once you dig down there are several important factors to think about, like complex deployment scenarios and the time it takes to deploy your application. Vendor lock-in is another key point you need to think about, even though I'd argue it's not that big of an issue. The cost is though. If you're responsible for paying the infrastructure bills at the end of the month you'll care about how much you're spending.Let's be short and sweet. Containers are isolated stateless environments. A container is a lightweight, stand-alone, executable package of a piece of software that includes everything needed to run it, including code, runtime, system tools, system libraries, settings, etc. By containerizing the application and its dependencies, differences in OS distributions and underlying infrastructure are abstracted away. I like to say that it's like a tiny virtual machine, but not really. Most developers understand the concept of virtual machines. We are used to running apps in virtual machines. They simulate a real machine and have everything a real machine has. Well, running an app inside a container is the same, except for a couple of important architectural differences, mainly that containers run on the same operating system kernel. Let me show you... Here you can see a nice overview. Virtual machines use something called a hypervisor. It manages every virtual machine on a host. And as you can see every VM has its own operating system. While containers share the host operating system. Making containers significantly smaller and much faster to create and delete.may not be the same. However, I believe a set amount can be agreed upon, with keeping both camps happy. Using containers means you won't have any auto-scaling by default. It's something you need to set up yourself. Luckily, vendor-specific tools like AWS Auto Scaling make it rather painless. The advantage here is that you have full control of your resources, and you are in charge of the scaling, meaning you can theoretically have infinite scalability. Well, as close as your provider allows you.. You need to learn about the ecosystem and the various tools at your disposal. For many, it's a steep learning curve, because ultimately you're the one deploying and managing the application. In having more freedom and control, you must submit to the fact it will be complex with various moving parts. Sadly this introduces more cost. After all, you're paying for the resources all the time, no matter whether you have traffic or not.you have at your disposal. The ecosystem is so evolved you won't have any issues setting up the necessary tools. Last of all, with containers your team will have the same development environment no matter which operating system they're using. That just makes it incredibly easy for larger teams to be efficient.The use-cases for containerized applications are significantly wider than with serverless. Mainly because you can, with little to no fuss, refactor existing monolithic applications to container-based setups. But, to get maximum benefit, you should split up your monolithic application into individual microservices. They'll be deployed as individual containers which you'll configure to talk to each other. Among the usual application you'll use containers for are Web APIs, machine learning computations, and long-running processes. In short, whatever you already use traditional servers for would be a great candidate to be put into a container. When you're already paying for the servers no matter the load, make sure to really use them.Deploy a containerized Node.js app to a Kubernetes cluster on AWS There will be a couple of steps we need to focus on, first of all creating a container image and pushing it to a repository. After that, we need to create a Kubernetes cluster and write the configuration files for our containers. The last step will be deploying everything to the cluster and making sure it works.
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