Kubernetes

Any system that’s going to be deployed for the enterprise needs to have at least a basic level of monitoring in place to manage it. Kubernetes is no exception to this rule. When we, as a community, underwent the shift from physical servers to virtual infrastructure, we didn’t ignore the new VMs and just keep monitoring the hardware, we had to come up with new products to monitor our infrastructure. Sysdig is building these new solutions for the Kubernetes world. ...

The Kubernetes series has now ventured into some non-native k8s discussions. Helm is a relatively common tool used in the industry and it makes sense to talk about why that is. This post covers the basics of Helm so we can make our own evaluations about its use in our Kubernetes environment. Helm - The Theory So what is Helm? In the most simplest terms its a package manager for Kubernetes. Think of Helm this way, Helm is to Kubernetes as yum/apt is to Linux. Yeah, sounds pretty neat now doesn’t it? ...

The focus of this post is on pod based backups, but this could also go for Deployments, replica sets, etc. This is not a post about how to backup your Kubernetes cluster including things like etcd, but rather the resources that have been deployed on the cluster. Pods have been used as an example to walk through how we can take backups of our applications once deployed in a Kubernetes cluster. ...

We love deployments and replica sets because they make sure that our containers are always in our desired state. If a container fails for some reason, a new one is created to replace it. But what do we do when the deployment order of our containers matters? For that, we look for help from Kubernetes StatefulSets. StatefulSets - The Theory StatefulSets work much like a Deployment does. They contain identical container specs but they ensure an order for the deployment. Instead of all the pods being deployed at the same time, StatefulSets deploy the containers in sequential order where the first pod is deployed and ready before the next pod starts. (NOTE: it is possible to deploy pods in parallel if you need them to, but this might confuse your understanding of StatefulSets for now, so ignore that.) Each of these pods has its own identity and is named with a unique ID so that it can be referenced. ...

In the previous post we covered Persistent Volumes (PV) and how we can use those volumes to store data that shouldn’t be deleted if a container is removed. The big problem with that post is that we have to manually create the volumes and persistent volume claims. It would sure be nice to have those volumes spun up automatically wouldn’t it? Well, we can do that with a storage class. For a storage class to be really useful, we’ll have to tie our Kubernetes cluster in with our infrastructure provider like AWS, Azure or vSphere for example. This coordination is done through a cloud provider. ...

Containers are often times short lived. They might scale based on need, and will redeploy when issues occur. This functionality is welcomed, but sometimes we have state to worry about and state is not meant to be short lived. Kubernetes persistent volumes can help to resolve this discrepancy. Volumes - The Theory In the Kubernetes world, persistent storage is broken down into two kinds of objects. A Persistent Volume (PV) and a Persistent Volume Claim (PVC). First, lets tackle a Persistent Volume. ...

Secret, Secret, I’ve got a secret! OK, enough of the Styx lyrics, this is serious business. In the previous post we used ConfigMaps to store a database connection string. That is probably not the best idea for something with a sensitive password in it. Luckily Kubernetes provides a way to store sensitive configuration items and its called a “secret”. Secrets - The Theory The short answer to understanding secrets would be to think of a ConfigMap, which we have discussed in a previous post in this series, but with non-clear text. ...

Sometimes you need to add additional configurations to your running containers. Kubernetes has an object to help with this and this post will cover those ConfigMaps. ConfigMaps - The Theory Not all of our applications can be as simple as the basic nginx containers we’ve deployed earlier in this series. In some cases, we need to pass configuration files, variables, or other information to our apps. The theory for this post is pretty simple, ConfigMaps store key/value pair information in an object that can be retrieved by your containers. This configuration data can make your applications more portable. ...

DNS is a critical service in any system. Kubernetes is no different, but Kubernetes will implement its own domain naming system that’s implemented within your Kubernetes cluster. This post explores the details that you need to know to operate a k8s cluster properly. Kubernetes DNS - The theory I don’t want to dive into DNS too much since it’s a core service most should be familiar with. But at a really high level, DNS translates an IP address that might be changing, with an easily remember-able name such as “theithollow.com”. Every network has a DNS server, but Kubernetes implements their own DNS within the cluster to make connecting to containers a simple task. ...

It’s time to look closer at how we access our containers from outside the Kubernetes cluster. We’ve talked about Services with NodePorts, LoadBalancers, etc., but a better way to handle ingress might be to use an ingress-controller to proxy our requests to the right backend service. This post will take us through how to integrate an ingress-controller into our Kubernetes cluster. Ingress Controllers - The Theory Lets first talk about why we’d want to use an ingress controller in the first place. Take an example web application like you might have for a retail store. That web application might have an index page at “http://store-name.com/" and a shopping cart page at “http://store-name.com/cart" and an api URI at “http://store-name.com/api". We could build all these in a single container, but perhaps each of those becomes their own set of pods so that they can all scale out independently. If the API needs more resources, we can just increase the number of pods and nodes for the api service and leave the / and the /cart services alone. It also allows for multiple groups to work on different parts simultaneously but we’re starting to drift off the point which hopefully you get now. ...