As technology stacks become increasingly difficult to manage and scale, engineering teams are turning to Kubernetes. But seeing where to optimize versus where to save can be murky.
Kubernetes has changed the way IT teams manage their resources. It keeps them updated on resource usage and automatically allocates assets between appliances to ensure continuous system uptime. But while the emphasis is often placed on making systems observable, making them cost transparent to finance teams is essential.
As technology stacks become increasingly difficult to manage and scale, many IT and engineering teams are turning to Kubernetes platforms. Kubernetes — a.k.a. K8s — is an open-source container system for managing and scaling business applications. The open-source orchestration software allows technology teams to deploy and manage the microservices that make up a business’ technology stack.
In 2014, Google was the company to open-source its Kubernetes initiative and gave the platform its name. Besides Google, many other tech giants — such as Microsoft Azure, SAP and Dell — have started to provide Kubernetes in recent years. The Linux Foundation, an initiative focused on open source software development, is the organization behind the resource site Kubernetes.io, which now includes a list of more than 140 certified solution providers.
Today, Kubernetes has become the leading container curve orchestration tool. Since migrating to the Kubernetes platform, nearly 10,000 companies have improved several aspects of their analytics stack and data reporting capabilities. That is why many companies are turning to Kubernetes despite its steep learning curve. Luckily, many cloud providers provide support and help organizations of any size to leverage Kubernetes.
Unlocking the potential of Kubernetes
In order to determine whether the use of the system provides true benefits, a company should consider three crucial questions:
- Is my technology stack outdated and difficult to manage?
- Is the technology scaleable?
- Is there a mix of technology — both on-premise software applications and cloud solutions?
If all those questions are answered affirmatively, enterprises have one more thing to do before they can take advantage of the benefits that come with well-architected Kubernetes environments. They first need to set up and configure these environments and figure out how to manage and operate them. This allows for portability and scalability when applications are deployed across on-premise or cloud environments. It takes less time to manage, decreases downtime, reduces IT costs and improves “time to market” speed.
A groundbreaking feature of Kubernetes is the fact that it applies to a company’s entire technology stack across multiple business units, making all of those services easier and faster to deploy as well as scale. Many companies are now transitioning their production environment onto Kubernetes with cloud or on-premise infrastructure.
One challenge they encounter early on is how to allocate Kubernetes resources accurately to the different applications, services, teams and departments in the organization. This challenge can be overcome by orchestrating a cluster of virtual machines (Kubernetes nodes) and scheduling containers to run on those nodes based on their available computing resources and the resource requirements of each container.
Transparency is often lacking
Despite its numerous benefits, implementing Kubernetes introduces some additional challenges. By default, there is a lack of transparency as companies have little insight into workloads in specific container clusters, thus making it impossible to determine which applications to optimize versus where to save resources.
Various optimizations can reduce the Kubernetes resource costs. One of these ways is monitoring and analyzing. By working with a specialized analytics provider, companies can reduce costs by up to 70 percent. One such company is replex.io, which can help finance teams showback and chargeback Kubernetes costs to teams, applications, business functions or departments.
The main goal is to get visibility into key cost parameters like CPU, memory, network and storage. Decision-makers can then report resource consumption and costs across developer and DevOps teams and chargeback teams based on efficiency and cost benchmarks. They can also correlate overall spend with realized business value, making it easy to make informed decisions about budgetary allocations while keeping teams accountable for costs without affecting agility and freedom.
Kubernetes has certainly delivered application mobility, with the orchestration of an application from one cluster to another now being possible. But it is essential to reduce costs and increase cloud infrastructure efficiency through continuous insights and proactive optimization.