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What does the Great Resignation Have to Do with Kubernetes?

In the spring of 2021, the number of workers who quit their jobs in a single month broke an all-time US record. Economists studying the situation called it the “Great Resignation” and soon realized it was only getting worse. By summer, even more professionals, in all sorts of different industries, had quit their jobs to seek greener pastures. 

The Great Resignation is affecting the world of technology. A recent study conducted by TalentLMS, a leading learning management system and hiring platform, projected that businesses may lose seven out of 10 tech employees over the next year. In other words, 72% of tech workers in the US are currently thinking of quitting their jobs within the next 12 months. In practical terms, this potential upset in employment means organizations in the process of establishing, managing and scaling their Kubernetes ownership are going to need to hone in on one critical thing—namely, consistency.

What’s the value of consistency?

By design, modern cloud native applications are made up of many smaller applications services aptly called microservices. In this way, Kubernetes is essentially a platform for building platforms. 

Kubernetes can be set up, configured and managed differently at every organization. What one engineer configures at one organization one way, another does differently elsewhere. And while it benefits the industry as a whole as there is some standardization and consistency, there can also be many Kubernetes unknowns within an organization. 

While this process is effective, it can make consistency a challenge across Kubernetes. When considering the Great Resignation and the real real possibility that several practitioners may be leaving your organization in the next 12 months, how are you preparing? 

Establishing Kubernetes Guardrails 

One of the first steps in achieving consistency is establishing your Kubernetes guardrails or policies.  Unfortunately, what often happens is policy is put down on paper with no way of enforcing it. When using Kubernetes, that translates to misconfigured clusters, and when misconfigured, you can open yourself up to security risks, downtime or wasted resources. This is a hard enough problem to solve when your team has been around for a while, now throw in staff turnover, training and manual enforcement and you’ve got yourself a headache.  

DevOp leaders must set up guardrails for their teams that can be automated and enforced. In this way, policy can be established, guardrails set up and negative consequences of misconfiguration avoided. 

Maintaining Kubernetes Consistently

One of the main motivations behind the Great Resignation appears to be a general lack of support in the work being done. In the case of technology (and more specifically, Kubernetes), the lack of proper IT tools is hurting the morale of high level professionals. Many workers in the industry say digital transformation priorities should focus less on monetary success and more on how to empower workers and developers to build and deploy secure, high-quality software. 

When policies and workflows are well established within microservices and guardrails set up, developers are empowered to develop faster with more ownership. Operators can know for certain with visibility into clusters that their teams are consistent and complying with established business requirements. 

And when considering the Great Resignation, if one developer leaves suddenly, there is a clear foundation in place for how multiple clusters, workloads and teams can be effectively managed. 

The Path to Consistency

Fairwinds offers its Insights platform for DevOps leaders and platform engineers to help apply Kubernetes guardrails at every point in the development lifecycle - during CI/CD, at the time of admission, and in production. Fairwinds Insights offers leaders the ability to gain visibility into and consistency with enforced guardrails across Kubernetes. 

Teams using Fairwinds Insights can empower developers by enabling them to develop quickly with consistent guardrails. It helps teams ship applications faster without having to manually check clusters to see how they’ve been configured and if fixes have been made.

Teams no longer find  themselves wondering if their Kubernetes clusters are safe, scalable, reliable or cost-effective. Instead, they have the visibility to Kubernetes needed to achieve the benefits of cloud native development. 

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