The combination of containers and Kubernetes has become a foundational technology stack for enterprises running workloads across multi-cloud and hybrid cloud environments. Companies across industries are leveraging the pair to move faster, reduce infrastructure costs, and gain the flexibility to run applications wherever the business requires.
What Are Containers and Why Does Kubernetes Matter?
Containers are self-contained software packages that bundle an application together with all of its dependencies — libraries, runtime, configuration — so that the application runs consistently regardless of the underlying computing environment. This makes containers ideal for moving workloads between a developer’s laptop, a test environment, an on-premises data centre, and public cloud infrastructure without environment-specific issues.
But containers introduce their own operational complexity. Running dozens or hundreds of containers in production requires automated tooling to handle deployment, health checks, scaling, networking, and rolling updates. That is the problem Kubernetes solves. Originally developed at Google and now maintained by the Cloud Native Computing Foundation (CNCF), Kubernetes is an open-source container orchestration system that automates these operational concerns at scale.
Together, containers and Kubernetes give engineering teams workload portability and the orchestration layer needed to operate that portability reliably in production. The following real-world case studies illustrate what that looks like in practice.
Expedia Group: Accelerating Travel Services with Containers and EKS
Expedia Group began adopting microservices architecture and AWS public cloud services in 2013. In 2015, the company started deploying containers via Amazon EC2 Container Service (ECS) to run microservices workloads within AWS. The primary drivers were application portability across multiple environments and faster time-to-market for new products and features.
“With containers spinning up in seconds, the amount of time that is needed to ship a new feature to our customers has significantly reduced, and we are able to accelerate our speed to market.”
— Kuldeep Chowhan, Distinguished Engineer, Vrbo (a unit of Expedia Group)
Today, thousands of applications run in production on ECS across multiple AWS regions, giving Expedia the high availability needed to serve a global customer base without disruption.
From Apache Mesos to Kubernetes
In 2015, the Vrbo brand adopted Apache Mesos to manage container workloads spanning both on-premises data centres and AWS. This hybrid approach allowed Vrbo developers to run identical workloads in both environments, accelerating the eventual migration from on-premises infrastructure to the cloud.
As Kubernetes grew in adoption across the industry, Expedia’s Hotels.com unit moved hundreds of its applications onto Kubernetes running in AWS. After Amazon launched its managed Elastic Kubernetes Service (EKS), multiple teams across Expedia Group — including data science, online experiences, and streaming — began adopting it as their standard container orchestration platform.
“Longer term, that is the direction Expedia Group is planning on heading for container runtime and orchestration needs.”
— Kuldeep Chowhan, Vrbo
Measurable Business Impact
The shift to microservices and containers produced measurable improvements in engineering velocity and infrastructure efficiency:
- Release velocity: The Vrbo brand reported a 12-times increase in release velocity over three years.
- Deployment frequency: New features that previously took months to ship can now be released multiple times per day.
- Targeted scaling: Instead of scaling an entire monolithic application to handle traffic spikes, teams can now scale only the specific microservices experiencing elevated demand, reducing infrastructure costs.
- High availability: Distributing containerised workloads across multiple AWS regions means customers worldwide can access Expedia’s travel services without service interruptions.
Operational Realities
Chowhan was candid that containers do not eliminate infrastructure management entirely. Container runtimes and orchestration platforms require their own updates, and those updates must be rolled out across the server fleet running the platform. Development tooling, practices, and engineer skill sets also had to evolve continuously — from source code toolchains to runtime operations — as the container ecosystem matured.
“We had to retool to be adapt in the new ecosystem across our travel platform, and also train our engineers with the evolving ecosystem across containers.”
— Kuldeep Chowhan, Vrbo
Primerica: Modernising Financial Services with a Hybrid Cloud Strategy
Primerica, a financial services and insurance firm, built a Kubernetes environment to scale applications on a private cloud built on IBM software running on Nutanix hardware. Docker containers provide application consistency between development, test, and production environments — a critical requirement when migrating from a traditional technology stack to a modern hybrid cloud architecture.
“This is a key strategic component in our migration from our traditional technology stack to our modern hybrid cloud.”
— Barry Pellas, CTO and Executive Vice President of Application Development and Delivery, Primerica
By standardising on containers, Primerica gains environment parity — code that behaves the same way in development behaves the same way in production. This consistency is particularly valuable in regulated industries such as financial services, where predictable, auditable application behaviour matters as much as delivery speed.
Key Takeaways for DevOps Teams
The experiences of Expedia Group and Primerica highlight several patterns that recur across successful container and Kubernetes adoptions:
- Start with portability as a goal. Containers deliver the most value when teams have a concrete multi-environment or multi-cloud problem to solve — not as a technology-first initiative.
- Plan for orchestration from the start. Running containers in development is straightforward; running them reliably at scale in production requires Kubernetes or a comparable orchestration layer from the outset.
- Invest in engineer training. Adopting containers and Kubernetes requires reskilling. The toolchain — CI/CD pipelines, observability, security scanning — changes significantly from a traditional VM or bare-metal workflow.
- Infrastructure management does not disappear. Managed services such as EKS reduce the operational burden of running Kubernetes, but platform updates, cluster upgrades, and node management remain ongoing responsibilities.
- Microservices and containers are complementary. The ability to scale, deploy, and update individual microservices independently is a primary driver of the engineering velocity gains these organisations reported.
As multi-cloud and hybrid cloud strategies become standard rather than aspirational, containers and Kubernetes are increasingly the common infrastructure layer that makes workload portability a practical reality rather than an architectural ideal.
Original source reporting: sg.channelasia.tech (2020)