How Kubernetes Changed Deployment Process
Container-based microservices architectures have profoundly changed the way development and operations teams test and deploy modern software. Containers help companies modernize by making it easier to scale and deploy applications, but containers have also introduced new challenges and more complexity by creating an entirely new infrastructure ecosystem.
Large and small software companies alike are now deploying thousands of container instances daily, and that’s the complexity of scale they have to manage. So how do they do it?
Kubernetes is an open-source container-orchestration system for automating computer application deployment, scaling, and management. It was originally designed by Google and is now maintained by the Cloud Native Computing Foundation.
Containers have become increasingly popular since the Docker containerization project launched in 2013, but large, distributed containerized applications can become increasingly difficult to coordinate. By making containerized applications dramatically easier to manage at scale, Kubernetes has become a key part of the container revolution.
Chronology
Let’s take a look at why Kubernetes is so useful by going back in time.
Traditional deployment era: 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, the 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:
🔷 Increased ease and efficiency of container image creation compared to VM image use.
🔷Continuous development, integration, and deployment
🔷Dev and Ops separation of concerns: Create application container images at build/release time rather than deployment time, thereby decoupling applications from infrastructure.
🔷Resource isolation: predictable application performance.
🔷Resource utilization: High efficiency and density.
Need and Capability of Kubernetes
ontainers 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?
Kubernetes provides you 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 storage, 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 let 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.
Enterprises adopting Kubernetes ?
In two words: Hell Yeah!
Several data points show rapid Kubernetes adoption. Sumo Logic’s fourth annual Continuous Intelligence Report on “The State of Modern Applications and DevSecOps in the Cloud” highlights some cool adoption data on Kubernetes within enterprises. The report states that K8s is seeing increased adoption in on-premise as well as cloud-based environments. In fact, 1 in 3 enterprises in the AWS cloud today use Kubernetes as their key orchestration solution
Tinder’s Move to Kubernetes
Due to high traffic volume, Tinder’s engineering team faced challenges of scale and stability. What did they do?
The answer is, of course, Kubernetes.
Tinder’s engineering team solved interesting challenges to migrate 200 services and run a Kubernetes cluster at scale totaling 1,000 nodes, 15,000 pods, and 48,000 running containers.
Was that easy? No way. However, they had to do it for the smooth business operations going further. One of their engineering leaders said, “As we onboarded more and more services to Kubernetes, we found ourselves running a DNS service that was answering 250,000 requests per second.” Tinder’s entire engineering organization now has knowledge and experience on how to containerize and deploy their applications on Kubernetes.
Reddit’s Kubernetes Story
Reddit is one of the busiest sites in the world. Kubernetes forms the core of Reddit’s internal infrastructure.
For many years, the Reddit infrastructure team followed traditional ways of provisioning and configuring. However, this didn’t go far until they saw some huge drawbacks and failures happening while doing things the old way. Then they moved to Kubernetes.
The New York Times’s Journey to Kubernetes
Today the majority of the NYT’s customer-facing applications are running on Kubernetes. What an amazing story. The biggest impact has been an increase in the speed of deployment and productivity. Legacy deployments that took up to 45 minutes are now pushed in just a few. It’s also given developers more freedom and fewer bottlenecks. The New York Times has gone from a ticket-based system for requesting resources and weekly deploy schedules to allowing developers to push updates independently.
Spotify Using Kubernetes
Spotify is an early K8s adopter and has significant cost-saving values by adopting K8s as described in this note. Leveraging K8s, Spotify has seen 2–3x CPU utilization using the orchestration capabilities of K8s, resulting in better IT spend optimization.
Airbnb’s Kubernetes Story
Airbnb’s transition from a monolithic to a microservices architecture is pretty amazing. They needed to scale continuous delivery horizontally, and the goal was to make continuous delivery available to the company’s 1,000 or so engineers so they could add new services. Airbnb adopted Kubernetes to support over 1,000 engineers concurrently configuring and deploying over 250 critical services to Kubernetes. The net result is that AirBnb can now do over 500 deploys per day on average.
I want you to see this excellent presentation from Melanie Cebula, the infrastructure engineer at Airbnb.
Pinterest’s Kubernetes Story
With over 250 million monthly active users and serving over 10 billion recommendations every single day, the engineers at Pinterest knew these numbers are going to grow day by day, and they began to realize the pain of scalability and performance issues.
Their initial strategy was to move their workload from EC2 instances to Docker containers; they first moved their services to Docker to free up engineering time spent on Puppet and to have an immutable infrastructure.
The next strategy was to move to Kubernetes. Now they can take ideas from ideation to production in a matter of minutes, whereas earlier they used to take hours or even days. They have cut down so much overhead cost by utilizing Kubernetes and have removed a lot of manual work without making engineers worry about the underlying infrastructure.
Pokemon Go’s Kubernetes Story
How was Pokemon Go able to scale so efficiently became so successful? The answer is Kubernetes. Pokemon Go was developed and published by Niantic Inc. and grew to 500+ million downloads and 20+ million daily active users.
Pokemon Go engineers never thought their user base would increase exponentially to surpass expectations within a short time. They were not ready for it, and the servers couldn’t handle this much traffic.
Pokemon Go also faced a severe challenge when it came to vertical and horizontal scaling because of the real-time activity by millions of users worldwide. Niantic was not prepared for this.
The solution was in the magic of containers. The application logic for the game ran on Google Container Engine (GKE) powered by the open-source Kubernetes project. Niantic chose GKE for its ability to orchestrate their container cluster at a planetary-scale, freeing its team to focus on deploying live changes for their players. In this way, Niantic used Google Cloud to turn Pokémon GO into service for millions of players, continuously adapting and improving. This gave them more time to concentrate on building the game’s application logic and new features rather than worrying about the scaling part.
LendingTree Using Kubernetes
LendingTree has many microservices that make up its business apps. LendingTree uses Kubernetes and its horizontal scaling capability to deploy and run these services, and to ensure that their customers have access to service even during peak load. And to get visibility into these containerized and virtual services and monitor its Kubernetes deployment, LendingTree uses Sumo Logic.
And We have data on 18,653 companies that use Kubernetes. The companies using Kubernetes are most often found in United States and in the Computer Software industry. Kubernetes is most often used by companies with 50–200 employees and 1M-10M dollars in revenue.
Adidas Kubernetes Story
Staying true to its culture, adidas got 40% of its most impactful systems running on Kubernetes in a year
Challenge
In recent years, the adidas team was happy with its software choices from a technology perspective — but accessing all of the tools was a problem. For instance, “just to get a developer VM, you had to send a request form, give the purpose, give the title of the project, who’s responsible, give the internal cost center a call so that they can do recharges,” says Daniel Eichten, Senior Director of Platform Engineering. “The best case is you got your machine in half an hour. Worst case is half a week or sometimes even a week.”
Solution
To improve the process, “we started from the developer point of view,” and looked for ways to shorten the time it took to get a project up and running and into the adidas infrastructure, says Senior Director of Platform Engineering Fernando Cornago. They found the solution with containerization, agile development, continuous delivery, and a cloud native platform that includes Kubernetes and Prometheus.
Impact
Just six months after the project began, 100% of the adidas e-commerce site was running on Kubernetes. Load time for the e-commerce site was reduced by half. Releases went from every 4–6 weeks to 3–4 times a day. With 4,000 pods, 200 nodes, and 80,000 builds per month, adidas is now running 40% of its most critical, impactful systems on its cloud native platform.
In recent years, the adidas team was happy with its software choices from a technology perspective — but accessing all of the tools was a problem.
For engineers at adidas, says Daniel Eichten, Senior Director of Platform Engineering, “it felt like being an artist with your hands tied behind your back, and you’re supposed to paint something.”
For instance, “just to get a developer VM, you had to send a request form, give the purpose, give the title of the project, who’s responsible, give the internal cost center a call so that they can do recharges,” says Eichten. “Eventually, after a ton of approvals, then the provisioning of the machine happened within minutes, and then the best case is you got your machine in half an hour. Worst case is half a week or sometimes even a week.”
To improve the process, “we started from the developer point of view,” and looked for ways to shorten the time it took to get a project up and running and into the adidas infrastructure, says Senior Director of Platform Engineering Fernando Cornago.
In addition to being ready for Cyber Week — 100% of the adidas e-commerce site was running on Kubernetes then, just six months after the project began — the cloud native stack has had other impressive results. Load time for the e-commerce site was reduced by half. Releases went from every 4–6 weeks to 3–4 times a day. With 4,000 pods, 200 nodes, and 80,000 builds per month, adidas is now running 40% of its most critical, impactful systems on its cloud native platform.
And adoption has spread quickly among adidas’s 300-strong engineering corps. “I call our cloud native platform the field of dreams,” says Eichten. “We built it, and we never anticipated that people would come and just love it.”
For one thing, “everybody who can touch a line of code” has spent one full week onboarding and learning the platform with members of the 35-person platform engineering team, says Cornago. “We try to spend 50% of our time sitting with the teams, because this is the only way to understand how our platform is being used. And this is how the teams will feel safe that there is someone on the other side of the wall, also feeling the pain.”
Additionally, Cornago and Eichten took advantage of the fact that as a fashion athletic wear brand, adidas has sports and competition in its DNA. “Top-down mandates don’t work at adidas, but gamification works,” says Cornago. “So this year we had a DevOps Cup competition. Every team created new technical capabilities and had a hypothesis of how this affected business value. We announced the winner at a big internal tech summit with more than 600 people. It’s been really, really useful for the teams.”
BOSE Kubernetes Story(CNCF)
Bose: Supporting Rapid Development for Millions of IoT Products With Kubernetes
Challenge
A household name in high-quality audio equipment, Bose has offered connected products for more than five years, and as that demand grew, the infrastructure had to change to support it. “We needed to provide a mechanism for developers to rapidly prototype and deploy services all the way to production pretty fast,” says Lead Cloud Engineer Josh West. In 2016, the company decided to start building a platform from scratch. The primary goal: “To be one to two steps ahead of the different product groups so that we are never scrambling to catch up with their scale,” says Cloud Architecture Manager Dylan O’Mahony.
Solution
From the beginning, the team knew it wanted a microservices architecture. After evaluating and prototyping a couple of orchestration solutions, the team decided to adopt Kubernetes for its scaled IoT Platform-as-a-Service running on AWS. The platform, which also incorporated Prometheus monitoring, launched in production in 2017, serving over 3 million connected products from the get-go. Bose has since adopted a number of other CNCF technologies, including Fluted, Core DNS, Jaegar, and OpenTracing.
Impact
With about 100 engineers onboarded, the platform is now enabling 30,000 non-production deployments across dozens of microservices per year. In 2018, there were 1250+ production deployments. Just one production cluster holds 1,800 namespaces and 340 worker nodes. “We had a brand new service taken from concept through coding and deployment all the way to production, including hardening, security testing and so forth, in less than two and a half weeks,” says O’Mahony.
"At Bose we're building an IoT platform that has enabled our physical products. If it weren't for Kubernetes and the rest of the CNCF projects being free open source software with such a strong community, we would never have achieved scale, or even gotten to launch on schedule."
— JOSH WEST, LEAD CLOUD ENGINEER, BOSEA household name in high-quality audio equipment, Bose has offered connected products for more than five years, and as that demand grew, the infrastructure had to change to support it.
“We needed to provide a mechanism for developers to rapidly prototype and deploy services all the way to production pretty fast,” says Lead Cloud Engineer Josh West. “There were a lot of cloud capabilities we wanted to provide to support our audio equipment and experiences.”
In 2016, the company decided to start building an IoT platform from scratch. The primary goal: “To be one to two steps ahead of the different product groups so that we are never scrambling to catch up with their scale,” says Cloud Architecture Manager Dylan O’Mahony. “If they release a new connected product, we want to be already well ahead of being able to handle whatever scale that they’re going to throw at us.”
From the beginning, the team knew it wanted a microservices architecture and platform as a service. After evaluating and prototyping orchestration solutions, including Mesos and Docker Swarm, the team decided to adopt Kubernetes for its platform running on AWS. Kubernetes was still in 1.5, but already the technology could do much of what the team wanted and needed for the present and the future. For West, that meant having storage and network handled. O’Mahony points to Kubernetes’ portability in case Bose decides to go multi-cloud.
“Bose is a company that looks out for the long term,” says West. “Going with a quick commercial off-the-shelf solution might’ve worked for that point in time, but it would not have carried us forward, which is what we needed from Kubernetes and the CNCF.”
"Everybody on the team thinks in terms of automation, leaning out the processes, getting things done as quickly as possible. When you step back and look at what it means for a 50-plus-year-old speaker company to have that sort of culture, it really is quite incredible, and I think the tools that we use and the foundation that we've built with them is a huge piece of that." — DYLAN O'MAHONY, CLOUD ARCHITECTURE MANAGER, BOSEAround the world, many CIO’s and technologists have chosen to use Kubernetes, and it is expected to evolve much more in the years to come.
Kubernetes is a great tool for orchestrating containerized applications. It automates the very complex task of dynamically scaling an application in real-time. The world is turning to automatic so Nowadays all companies using Kubernetes.
