KUBERNETES : The Container Orchestration TOOL !!!
Since , the past few years , Kubernetes has reached heights in the field of Micro Services as well as is ruling the world of cotainerization deployment and orchestrating that particular part …
This Particular Article will take you through the insights of what KUBERNETES actually is and how top MNC’s have eventually benefitted their requirement and use case by shifting their workload to Kubernetes .
In the end , there is a Detailed CASE STUDY , as to how SPOTIFY has used Kubernetes , to run its more than 150 micro services over Kubernetes and has scaled to heights .
SO Let’s get Started !!!
What is KUBERNETES ???
Kubernetes is a portable, extensible, open-source platform for managing containerized workloads and services, that facilitates both declarative configuration and automation. It has a large, rapidly growing ecosystem. Kubernetes services, support, and tools are widely available.
The name Kubernetes originates from Greek, meaning helmsman or pilot. Google open-sourced the Kubernetes project in 2014. Kubernetes combines over 15 years of Google’s experience running production workloads at scale with best-of-breed ideas and practices from the community .
Let’s Have a Flash Back of Time First !!!
Let’s take a look at why Kubernetes is so useful by going back in time.
Traditional deployment era: Early on, organizations ran applications on physical servers. There was no way to define resource boundaries for applications in a physical server, and this caused resource allocation issues. For example, if multiple applications run on a physical server, there can be instances where one application would take up most of the resources, and as a result, the other applications would underperform. A solution for this would be to run each application on a different physical server. But this did not scale as resources were underutilized, and it was expensive for organizations to maintain many physical servers.
Virtualized deployment era: As a solution, virtualization was introduced. It allows you to run multiple Virtual Machines (VMs) on a single physical server’s CPU. Virtualization allows applications to be isolated between VMs and provides a level of security as the information of one application cannot be freely accessed by another application.
Virtualization allows better utilization of resources in a physical server and allows better scalability because an application can be added or updated easily, reduces hardware costs, and much more. With virtualization you can present a set of physical resources as a cluster of disposable virtual machines.
Each VM is a full machine running all the components, including its own operating system, on top of the virtualized hardware.
Container deployment era: Containers are similar to VMs, but they have relaxed isolation properties to share the Operating System (OS) among the applications. Therefore, containers are considered lightweight. Similar to a VM, a container has its own filesystem, share of CPU, memory, process space, and more. As they are decoupled from the underlying infrastructure, they are portable across clouds and OS distributions.
Containers have become popular because they provide extra benefits, such as:
- Agile application creation and deployment: increased ease and efficiency of container image creation compared to VM image use.
- Continuous development, integration, and deployment: provides for reliable and frequent container image build and deployment with quick and easy rollbacks (due to image immutability).
- Dev and Ops separation of concerns: create application container images at build/release time rather than deployment time, thereby decoupling applications from infrastructure.
- Observability not only surfaces OS-level information and metrics, but also application health and other signals.
- Environmental consistency across development, testing, and production: Runs the same on a laptop as it does in the cloud.
- Cloud and OS distribution portability: Runs on Ubuntu, RHEL, CoreOS, on-premises, on major public clouds, and anywhere else.
- Application-centric management: Raises the level of abstraction from running an OS on virtual hardware to running an application on an OS using logical resources.
- Loosely coupled, distributed, elastic, liberated micro-services: applications are broken into smaller, independent pieces and can be deployed and managed dynamically — not a monolithic stack running on one big single-purpose machine.
- Resource isolation: predictable application performance.
- Resource utilization: high efficiency and density.
Why you need Kubernetes and what it can do
Containers are a good way to bundle and run your applications. In a production environment, you need to manage the containers that run the applications and ensure that there is no downtime. For example, if a container goes down, another container needs to start. Wouldn’t it be easier if this behavior was handled by a system?
That’s how Kubernetes comes to the rescue! Kubernetes provides you with a framework to run distributed systems resiliently. It takes care of scaling and failover for your application, provides deployment patterns, and more. For example, Kubernetes can easily manage a canary deployment for your system.
Kubernetes provides us with:
- Service discovery and load balancing Kubernetes can expose a container using the DNS name or using their own IP address. If traffic to a container is high, Kubernetes is able to load balance and distribute the network traffic so that the deployment is stable.
- Storage orchestration Kubernetes allows you to automatically mount a storage system of your choice, such as local storages, public cloud providers, and more.
- Automated rollouts and rollbacks You can describe the desired state for your deployed containers using Kubernetes, and it can change the actual state to the desired state at a controlled rate. For example, you can automate Kubernetes to create new containers for your deployment, remove existing containers and adopt all their resources to the new container.
- Automatic bin packing You provide Kubernetes with a cluster of nodes that it can use to run containerized tasks. You tell Kubernetes how much CPU and memory (RAM) each container needs. Kubernetes can fit containers onto your nodes to make the best use of your resources.
- Self-healing Kubernetes restarts containers that fail, replaces containers, kills containers that don’t respond to your user-defined health check, and doesn’t advertise them to clients until they are ready to serve.
- Secret and configuration management Kubernetes lets you store and manage sensitive information, such as passwords, OAuth tokens, and SSH keys. You can deploy and update secrets and application configuration without rebuilding your container images, and without exposing secrets in your stack configuration
What Kubernetes is not
Kubernetes is not a traditional, all-inclusive PaaS (Platform as a Service) system. Since Kubernetes operates at the container level rather than at the hardware level, it provides some generally applicable features common to PaaS offerings, such as deployment, scaling, load balancing, and lets users integrate their logging, monitoring, and alerting solutions. However, Kubernetes is not monolithic, and these default solutions are optional and pluggable. Kubernetes provides the building blocks for building developer platforms, but preserves user choice and flexibility where it is important.
- Does not limit the types of applications supported. Kubernetes aims to support an extremely diverse variety of workloads, including stateless, stateful , and data-processing workloads. If an application can run in a container, it should run great on Kubernetes.
- Does not deploy source code and does not build your application. Continuous Integration, Delivery, and Deployment (CI/CD) workflows are determined by organization cultures and preferences as well as technical requirements.
- Does not provide application-level services, such as middleware (for example, message buses), data-processing frameworks (for example, Spark), databases (for example, MySQL), caches, nor cluster storage systems (for example, Ceph) as built-in services. Such components can run on Kubernetes, and/or can be accessed by applications running on Kubernetes through portable mechanisms, such as the Open Service Broker.
- Does not dictate logging, monitoring, or alerting solutions. It provides some integrations as proof of concept, and mechanisms to collect and export metrics.
- Does not provide nor mandate a configuration language/system (for example, Jsonnet). It provides a declarative API that may be targeted by arbitrary forms of declarative specifications.
- Does not provide nor adopt any comprehensive machine configuration, maintenance, management, or self-healing systems.
- Additionally, Kubernetes is not a mere orchestration system. In fact, it eliminates the need for orchestration. The technical definition of orchestration is execution of a defined workflow: first do A, then B, then C. In contrast, Kubernetes comprises a set of independent, composable control processes that continuously drive the current state towards the provided desired state. It shouldn’t matter how you get from A to C. Centralized control is also not required. This results in a system that is easier to use and more powerful, robust, resilient, and extensible
Now let’s move to the case study part , where we discuss hoe Spotify is benefitting itself from Kubernetes …
Launched in 2008, the audio-streaming platform has grown to over 200 million monthly active users across the world. “Our goal is to empower creators and enable a really immersive listening experience for all of the consumers that we have today — and hopefully the consumers we’ll have in the future,” says Jai Chakrabarti, Director of Engineering, Infrastructure and Operations. An early adopter of microservices and Docker, Spotify had containerized microservices running across its fleet of VMs with a homegrown container orchestration system called Helios. By late 2017, it became clear that “having a small team working on the features was just not as efficient as adopting something that was supported by a much bigger community,” he says.
“We saw the amazing community that had grown up around Kubernetes, and we wanted to be part of that,” says Chakrabarti. Kubernetes was more feature-rich than Helios. Plus, “we wanted to benefit from added velocity and reduced cost, and also align with the rest of the industry on best practices and tools.” At the same time, the team wanted to contribute its expertise and influence in the flourishing Kubernetes community. The migration, which would happen in parallel with Helios running, could go smoothly because “Kubernetes fit very nicely as a complement and now as a replacement to Helios,” says Chakrabarti.
The team spent much of 2018 addressing the core technology issues required for a migration, which started late that year and is a big focus for 2019. “A small percentage of our fleet has been migrated to Kubernetes, and some of the things that we’ve heard from our internal teams are that they have less of a need to focus on manual capacity provisioning and more time to focus on delivering features for Spotify,” says Chakrabarti. The biggest service currently running on Kubernetes takes about 10 million requests per second as an aggregate service and benefits greatly from autoscaling, says Site Reliability Engineer James Wen. Plus, he adds, “Before, teams would have to wait for an hour to create a new service and get an operational host to run it in production, but with Kubernetes, they can do that on the order of seconds and minutes.” In addition, with Kubernetes’s bin-packing and multi-tenancy capabilities, CPU utilization has improved on average two- to threefold.
An early adopter of microservices and Docker, Spotify had containerized microservices running across its fleet of VMs since 2014. The company used an open source, homegrown container orchestration system called Helios, and in 2016–17 completed a migration from on premise data centers to Google Cloud. Underpinning these decisions, “We have a culture around autonomous teams, over 200 autonomous engineering squads who are working on different pieces of the pie, and they need to be able to iterate quickly,” Chakrabarti says. “So for us to have developer velocity tools that allow squads to move quickly is really important.”
But by late 2017, it became clear that “having a small team working on the Helios features was just not as efficient as adopting something that was supported by a much bigger community,” says Chakrabarti. “We saw the amazing community that had grown up around Kubernetes, and we wanted to be part of that. We wanted to benefit from added velocity and reduced cost, and also align with the rest of the industry on best practices and tools.” At the same time, the team wanted to contribute its expertise and influence in the flourishing Kubernetes community.
Another plus: “Kubernetes fit very nicely as a complement and now as a replacement to Helios, so we could have it running alongside Helios to mitigate the risks,” says Chakrabarti. “During the migration, the services run on both, so we’re not having to put all of our eggs in one basket until we can validate Kubernetes under a variety of load circumstances and stress circumstances.”
The team spent much of 2018 addressing the core technology issues required for the migration. “We were able to use a lot of the Kubernetes APIs and extensibility features of Kubernetes to support and interface with our legacy infrastructure, so the integration was straightforward and easy,” says Site Reliability Engineer James Wen.
Migration started late that year and has accelerated in 2019. “Our focus is really on stateless services, and once we address our last remaining technology blocker, that’s where we hope that the uptick will come from,” says Chakrabarti. “For stateful services there’s more work that we need to do.”
A small percentage of Spotify’s fleet, containing over 150 services, has been migrated to Kubernetes so far. “We’ve heard from our customers that they have less of a need to focus on manual capacity provisioning and more time to focus on delivering features for Spotify,” says Chakrabarti. The biggest service currently running on Kubernetes takes over 10 million requests per second as an aggregate service and benefits greatly from autoscaling, says Wen. Plus, Wen adds, “Before, teams would have to wait for an hour to create a new service and get an operational host to run it in production, but with Kubernetes, they can do that on the order of seconds and minutes.” In addition, with Kubernetes’s bin-packing and multi-tenancy capabilities, CPU utilization has improved on average two- to threefold.