When choosing to go down the Kubernetes route, think about what database you will be running, and how well it will work given the trade-offs previously discussed. Tips for running your database on Kubernetes Also, some of the more database-specific administrative tasks-backups, scaling, tuning, etc.-are different due to the added abstractions that come with containerization. That said, it is important to remember that pods (the database application containers) are transient, so the likelihood of database application restarts or failovers is higher. Running a database on Kubernetes is closer to the full-ops option, but you do get some benefits in terms of the automation Kubernetes provides to keep the database application running. All of that can be a lot of work, but you have all the features and database flavors at your disposal.
#Metabase kubernetes full
This might best be described as the full-ops option, where you take full responsibility for building your database, scaling it, managing reliability, setting up backups, and more.
This also means you might not have access to the exact version of a database, extension, or the exact flavor of database that you want.ĭo-it-yourself on a VM. You just create a database, build your app, and let Google Cloud scale it for you. As a developer or operator, you don’t need to mess with them. This is the low-ops choice, since Google Cloud handles many of the maintenance tasks, like backups, patching and scaling. This includes Cloud Spanner, Cloud Bigtable and Cloud SQL, among others. In this blog, we’ll explore when and what types of databases can be effectively run on Kubernetes.īefore we dive into the considerations for running a database on Kubernetes, let’s briefly review our options for running databases on Google Cloud Platform (GCP) and what they’re best used for.įully managed databases. Operators want to use the same tools for databases and applications, and get the same benefits as the application layer in the data layer: rapid spin-up and repeatability across environments. However, the data layer is getting more attention, since many developers want to treat data infrastructure the same as application stacks. That makes it challenging to run a database in a distributed environment. So handling things like state (the database), availability to other layers of the application, and redundancy for a database can have very specific requirements. That’s not surprising, since containerized workloads inherently have to be resilient to restarts, scale-out, virtualization, and other constraints. Despite all that growth on the application layer, the data layer hasn’t gotten as much traction with containerization. You simultaneously improve time to market and digital transformation in your organization while keeping your teams productive and happy.Today, more and more applications are being deployed in containers on Kubernetes-so much so that we’ve heard Kubernetes called the Linux of the cloud. Your non-DevOps teams feel empowered and are finally comfortable with handling your infrastructure, automation, and deployments. With this, your DevOps have to deal with fewer tickets and can instead focus on evangelization, automation, and industrialization. It’s a very simple solution: Your DevOps engineers create a self-service portal via Cycloid which provides modules such as governance, deployment, FinOps, and operations management. We want to move away from buzzwords like NoOps or “everyone is a DevOps”. We offer a collaboration platform dedicated to DevOps and hybrid cloud adoption, allowing you to optimize how DevOps and non-DevOps use technologies and clouds while working in alignment on common projects. We can be a pillar for your organizational transformation by empowering and upskilling your existing teams, as well as improving DevX, the developer experience.
Cycloid is an hybrid cloud DevOps collaboration platform.
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