Kubernetes vs Virtualization
This is the final part of the three-part blog series on "Leaving AWS and rolling your own servers with Kubernetes". Previously, we have covered:
Now, let's take a look at why Kubernetes is a better choice than virtualization to enable a more "cloudy" mode of operations on your new cluster.
Virtualization vs Kubernetes
"How should I think about virtualization vs containers?" comes up quite often, but it is hard to answer without further qualification. The original appeal of virtualization technology was to consolidate workloads to fewer servers, i.e. to increase infrastructure utilization and reduce infrastructure-related CAPEX. Containers do the same thing, only better. Therefore, they should replace virtual machines, right? Well, yes and no.
The meaning of "virtualization" has been expanded in recent years. It’s not just servers that are virtualized, we now have software-defined (virtual) networks, virtual storage, virtual load balancers, etc. Your entire environment can be virtualized and defined via a configuration file, sometimes as part of your application packaging. If that’s the world you live in, congratulations, you are living in a cloud-native world.
Simply deploying Kubernetes onto a dozen of bare metal servers is not going to deliver all of the typical cloud comforts. Let’s take a look at what will be missing:
- Networking. Feature-rich cloud ecosystems offer nearly unlimited software-defined virtual private networks (VPCs) that can span across server cabinets or even server rooms, etc. They do this by implementing sophisticated network flow controllers paired with expensive, specialized (often made in-house) network hardware. As I mentioned earlier, there are some native integrations for leading SDN tech for Kubernetes but they are not as mature. A couple of interesting companies in this space are Cumulus Networks and BigSwitch. However, if your environment is as simple as the setup we're using here, Kubernetes contains everything you need to have floating IPs and load balancers.
- Storage. Fortunes have been made by selling storage solutions for virtualization. Enterprise storage vendors have built impressive products that not only allow users to scale storage independently from compute but also offer impressive snapshotting, backup and disaster recovery capabilities that make live VM migrations a breeze. The lack of maturity of Kubernetes-native virtual storage offerings is one of the top obstacles towards Kubernetes adoption right now. Although, the situation is rapidly improving with next-generation vendors like Portworx filling the void and well-known, production-tested projects like Ceph enjoying first-class Kubernetes support.
- Tenant isolation. If your goal is to execute untrusted 3rd party code on your infrastructure, proper tenant isolation is essential. The most secure (and least flexible) tenant isolation technique is to place each one onto the dedicated hardware hosts, network, etc. However, in nearly all cases, virtualization solves this issue well enough. While vulnerabilities in hypervisors are discovered every once in a while, a successful real-world attack on a “cloud neighbor” is very rare. Containers by themselves are still not recommended for sharing a physical host with untrusted 3rd parties but with recent innovations like Kata containers, Kubernetes is closing this gap.
- Support for legacy applications. Modern cloud ecosystems benefit from the large investments that have been previously made into running legacy, cloud-unaware applications on them. Features like robust virtualized storage and live migrations make it relatively trivial to take an application and turn it into a highly available appliance without any modifications to its source code. Once again, the container ecosystem is rapidly catching up with projects like CRIU promising to close these gaps. However, Kubernetes is still best suited for cloud-native applications that don't take local storage for granted.
So should you be running Kubernetes on top of OpenStack or VMWare vCloud? The answer is, again, it depends on your use case but, in our opinion, you should at least try to eliminate virtualization. Here's why:
- Simplicity. Private clouds are complex pieces of software. OpenStack, despite years of polishing, remains excruciatingly complex. There are various management tools but the tools are often not free and, more importantly, require expertise to manage. There will always be vulnerabilities to patch, newer versions to upgrade to, and so on. Reducing this complexity means increased reliability. Having a single stack to operate means cutting the frequency of updates in half and reducing the probability of a critical misconfiguration taking all of your applications down. Remember, part of the reason AWS was heavily promoting the usage of availability zones (AZ) from the start, was to make it easier for themselves to manage the underlying virtualization platform. Virtualization failures/maintenance can be more impactful than hardware failures!
- Performance. Modern virtualized stacks are quite good at approaching bare metal levels of performance but running Kubernetes on top of virtualized servers is going to require more resources than running it on bare metal because virtualization still carries some tax and private cloud software itself consumes resources.
- Cost. Private cloud solutions are not always free. Some of them are free open source software and others can be quite expensive - but none are free to operate. Employing experts and/or paying for software licenses is unavoidable if you are going to run mission-critical workloads on top of private cloud software.
Going back to the original question of whether you should be running Kubernetes on bare metal, let’s qualify the answer by saying you should try it if the following applies:
- You do not have pre-existing investments in private cloud solutions and you lack the expertise to operate them.
- You are not running untrusted 3rd party code in your cluster.
- Your network scale is modest and fits into the simple design as described above.
- Your applications do not depend on features only a virtualized storage can provide and do not depend on hardware-assisted HA (like live migration).
For most of the readers, the last bullet point will be the hardest to answer, so let’s dive into it a bit deeper.
Managing State with Containerizing Applications
Despite what some people may say, Kubernetes is actually surprisingly good at emulating a boring Linux host for a legacy application that was written with legacy expectations. Modern, cloud-native features of Kubernetes like configuration management, secrets management, and service discovery are all accessible by old-school applications through widely accepted legacy APIs such as environment variables or files.
In other words, if an application can be configured to change its behavior (e.g. to use a different database connection string, by updating an environment variable or a configuration file somewhere in /etc), Kubernetes supports this quite well. There is no need to update the application code and teach it to interface with the Kubernetes API to accomplish this.
Usually, Kubernetes users struggle to migrate their applications when it comes to managing state, i.e. the more dependencies exist between an application and the local storage of its host, the more challenging the migration becomes.
Kubernetes’ initial design has favored applications that can be described as stateless network services - processes that consume only CPU, network and memory and do not need any storage. Unfortunately, the world we live in is very much stateful and most applications deliver value by manipulating data that must be stored somewhere.
Why has Kubernetes developed a reputation as being problematic for stateful applications like databases? Because in order to deliver the highest possible infrastructure utilization, Kubernetes needs to move the applications across servers. If a database is “chained” to a local storage array, it can’t be moved away from it.
Consider several strategies to address this problem. Do not treat them all as a panacea, but choose what best fits your situation:
- Do not run databases under Kubernetes. In fact, most distributed databases like Cassandra, HDFS or MongoDB, predate Kubernetes and have similar clustering capabilities built-in. They are perfectly capable of managing their own cluster state, replication, load-balancing, and auto-scaling. Allocate some nodes in your rack to them and these databases will be quite happy. That’s their native environment, after all. Kubernetes has the concept of external services which should be used to make such “external” databases visible to applications running inside the cluster. You will not have a “100% pure” Kubernetes environment but who said you must have one?...Especially if you have already invested in tooling and automation for your database of choice. Sometimes not fixing what’s not broken is a valid strategy.
- Use network-attached storage. Generally speaking, not relying on locally attached storage is always preferable because it allows you to scale storage resources independently from compute. This strategy does not work universally for all access patterns but Kubernetes is now well-equipped to handle cases when it does. Features like persistent volumes, stateful sets, and database-aware operators make it possible to run stateful applications inside Kubernetes.
- Choose storage solutions aligned with microservices architecture principles and adhere to the requirements of container-native data services. This new generation of storage products is closely aligned with the scaling model of Kubernetes. Such storage solutions can be directly integrated with the application layer for portability, scaling and data protection. In other words, consider adopting container-optimized storage and data management systems such as Portworx.
Deployments and Configuration
Managing configuration across large server fleets used to be a problem until modern configuration management tools like Ansible, Chef, and Puppet appeared on the market. The core capability of these tools is to keep the critical parts of a server’s filesystem (configuration files) in a well-known state across the entire fleet, usually via a declarative style of languages like YAML.
Over time, users have grown to like their configuration management tools so much, that the demand for additional functionality has appeared. It is not uncommon now to meet engineers who use Ansible not only to manage configuration but also to provision AWS resources and deploy their applications. If you have a tendency of using Ansible as a Swiss army knife for everything, it will probably break at some point and you will want to supplement it with a specialized tool for other tasks. For example, Terraform or CloudFormation for provisioning infrastructure resources and Jenkins or CircleCI for continuous integration and delivery (CI/CD).
How will your Kubernetes migration change your existing tooling for these tasks?
You will still need a configuration management tool. Kubernetes needs an operating system to run and the OS needs to be configured, updated and kept secure. Whatever your weapon of choice is to manage fleets of Linux server, you'll probably be happiest to continue using it with Kubernetes.
Your CI/CD tool is probably inadequate. Popular CI/CD solutions were designed for the pre-Kubernetes world. They will continue to work, but most are engineered with a world view incompatible with Kubernetes design principles, which forces their users to get creative and come up with “upside down” solutions. This blog post, for example, teaches you to "Run Kubernetes on Travis CI" which is a tutorial for how to spread bread on top of the butter.
Every time you read "Run Kubernetes on top of X" type of article, most likely that would be a piece about something you should not be doing. Kubernetes wasn't meant to run on top of CI/CD. Instead, a Kubernetes-native CI/CD must use a service account to connect to K8s API and take advantage of built-in primitives like labels, deployments, and jobs. We took a quick look at Gitlab’s Kubernetes integration and on the surface, they appear to be doing it the right way. There are also some new projects emerging in the space that are designed specifically for Kubernetes.
As any successful new technology, Kubernetes is disruptive, and certain "old ways" become obsolete. Just as the benefits of virtualization are starting to fade in the face of Kubernetes proliferation, today’s CI/CD market will be transformed as well.
To implement your CI/CD strategy, take a look at the Kubernetes native approach to deploy code into a cluster and build on top of that. For most users, it will come across as too low level but knowing it is essential. The next stop would be to take a look at Helm or Kustomize, (both are higher level tools for packaging software for Kubernetes deployments) and also at its possible future successor, the Application API. The universe of application deployment solutions for Kubernetes is a fast expanding one. Whatever we write about here will probably become obsolete in just a few months.
True application portability
Assuming you have Kubernetes up and running in your cabinet, let's not forget another benefit of K8s which we haven’t mentioned yet here - your applications are now much more portable.
Back in the day, a piece of software could fit into a single VM and software distribution between two parties could be implemented simply by sharing a VM image or building a relatively simple installation package. Today, modern, cloud-native applications are too complex and fragile to be distributed this way. For SaaS companies, this does not present a problem because their software is delivered as a service and such software is often “chained” to one or two deployments. But if deploying cloud-native software into someone else’s public or private cloud is a requirement, the challenge is enormous.
Kubernetes changes that. In theory, if an application can run on a Kubernetes cluster, it can be moved anywhere where a standards-conforming cluster is present. Hopefully, with Kubernetes gaining momentum, it will become the norm to quickly move an application across all major cloud providers and pick the one with best performance or price. As cloud hosting continues to be consolidated by the top two or three providers, the world desperately needs a technology that will commoditize cloud providers.
What's even more exciting is that Kubernetes allows applications to be downloaded, shared and installed using a simple, single-file installation method. Our own open source Kubernetes packaging solution called Gravity allows developers to build “cluster images” that are identical in principle to VM images but they can contain an entire Kubernetes cluster, pre-loaded with multiple applications. Statements like, "I have snapshotted my AWS account and emailed it to you, so you can get it up in your colo," will not seem so crazy.
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While setting up a privately hosted colocation environment -- and freeing yourself from the cloud overlords -- may sounds feasible, there are still many devil-in-the-detail level considerations: costs, networking, and the physical environment build-out are just a few.
Kubernetes can be considered as a valid (and superior) alternative to virtualization, as long as you do not require securely separating cluster tenants, because containers cannot yet securely sandbox a rogue application.
It's possible to dive much deeper into a permutation of each topic, but I hope this provided a big picture view the areas your team should be debating.
Lastly, however you choose to host your applications and infrastructure, we hope you consider bringing Teleport along for the ride.
Gravity allows you to package and deploy your Kubernetes clusters (along with the apps inside) across multiple clouds and for securely deploying your SaaS on premises of your enterprise customers.
Teleport offers a modern SSH gateway for secure access to your infrastructure, and it doesn't get in the way, helping your engineers to stay productive.
Both projects are open source and offer tremendous flexibility to run applications and manage infrastructure across multiple clouds and on-premise environments. If you have questions on anything in this series, please ping me on Twitter at @kontsevoyThanks to Aaron Sullivan and Erik Carlin for reading the draft of this post and providing valuable suggestions.
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