The reasoning seems obvious. Kubernetes adds another layer of complexity, requires dedicated infrastructure and introduces concepts like autoscaling, worker nodes and container orchestration.

But after looking at enough production environments, a different picture emerges.

Most expensive Kubernetes clusters aren't expensive because of Kubernetes.

They're expensive because of how they're operated.

Oversized resource requests, inefficient scheduling, low node utilization and fragmented cluster architectures quietly increase infrastructure costs long before anyone notices.

Resource Requests Matter More Than Most Teams Realize

Kubernetes schedules workloads according to the resources applications request—not according to what they actually consume.

That's an important distinction.

Developers often configure conservative values to avoid performance problems during peak traffic.

The application may request four CPU cores while rarely using even one.

The same happens with memory.

Individually, these decisions seem harmless.

Across hundreds of workloads, they leave large portions of the cluster reserved but unused.

Infrastructure appears fully allocated despite having significant spare capacity.

Bigger Clusters Don't Always Solve Bigger Problems

When utilization appears high, many organizations simply add more worker nodes.

This temporarily removes scheduling pressure but doesn't improve efficiency.

The underlying issue remains unchanged.

Adding infrastructure should be the last step—not the first.

Before expanding a cluster, platform teams should verify whether workloads are correctly sized, whether nodes are balanced efficiently and whether idle capacity already exists.

In many environments, better resource management delivers greater savings than additional hardware.

Metrics Should Drive Every Infrastructure Decision

Successful Kubernetes operations rely on data rather than assumptions.

Engineering teams should always know:

• Which services consume the most resources?

• Which deployments rarely use their requested CPU?

• Which nodes consistently remain underutilized?

• Where is CPU throttling affecting application performance?

• Which workloads restart unexpectedly?

Without comprehensive monitoring, optimization becomes little more than educated guessing.

Platforms such as Prometheus and Grafana have therefore become essential parts of every production Kubernetes environment.

Autoscaling Is Only Part of the Picture

Autoscaling is incredibly useful—but only when the underlying platform is already efficient.

Horizontal Pod Autoscaler adjusts replica counts.

Vertical Pod Autoscaler improves resource recommendations.

Cluster Autoscaler manages worker nodes.

None of them correct inaccurate workload configurations.

If applications request significantly more CPU or memory than necessary, autoscaling simply increases the cost of an already inefficient environment.

Simplifying Kubernetes Operations

As Kubernetes adoption grows, another challenge often appears.

Operational complexity.

Additional clusters are created for different environments, customers or business units until platform engineers spend more time maintaining infrastructure than supporting development teams.

Many organizations are now moving toward consolidated Kubernetes platforms with strong namespace isolation, RBAC policies and centralized operations.

This reduces maintenance effort while preserving security and flexibility.

The Value of Managed Kubernetes

Operating Kubernetes successfully requires far more than deploying a cluster.

Control plane maintenance, upgrades, monitoring, security, networking and backup strategies all require ongoing operational expertise.

Managed Kubernetes allows engineering teams to continue using the same Kubernetes ecosystem—Helm, kubectl, GitOps and modern CI/CD workflows—while leaving platform operations to experienced specialists.

Organizations looking for enterprise-ready Kubernetes hosted within European data centres can learn more about vshosting Managed Kubernetes here:

Managed Kubernetes: Skalierbare & Sichere Orchestrierung - vshosting~ 

Don't Forget the Infrastructure Beneath Kubernetes

Container orchestration is only one layer of the stack.

Reliable enterprise infrastructure remains equally important.

Fast NVMe storage, resilient networking, enterprise hardware and predictable performance directly influence how Kubernetes workloads behave in production.

Businesses requiring dedicated infrastructure for Kubernetes and other critical workloads can find more information about vshosting Private Cloud at:

Private Cloud: Höchste Sicherheit & Kontrolle - vshosting~ 

Conclusion

Kubernetes isn't inherently expensive.

Poor operational decisions are.

Companies that continuously monitor workloads, right-size resource requests and simplify platform management frequently reduce costs without reducing performance.

In many cases, the goal isn't building larger Kubernetes clusters.

It's operating smarter ones.

Discover more about managed infrastructure, enterprise cloud services and Kubernetes hosting at:

https://www.vshosting.de

For years, web security teams have focused on a familiar set of threats: DDoS attacks, credential stuffing, scraping bots, and malicious automation.

But a new category of traffic is emerging — one that doesn't necessarily look malicious, yet can have many of the same operational consequences.

AI agents.

Powered by large language models and autonomous workflows, these systems increasingly browse websites, compare products, retrieve information, query APIs, and gather context on behalf of users. Every prompt submitted to an AI assistant can trigger dozens of requests across multiple websites, databases, and services.

What makes this shift significant is scale.

A single human visitor may view five or ten pages before leaving a website. An AI agent can easily request hundreds of pages, API endpoints, product records, or documentation entries within seconds.

Multiply that behavior across millions of users and the result is a new infrastructure challenge that many organizations are only beginning to notice.

The hidden cost of AI-driven traffic

At vshosting, we analyzed traffic patterns across customer environments and observed a trend that is becoming increasingly difficult to ignore.

In some deployments, automated systems account for nearly half of all incoming requests.

The issue is not necessarily malicious intent.

Most AI crawlers, data collectors, and autonomous agents are simply doing what they were designed to do: collecting information as efficiently as possible.

The problem is that infrastructure must still process every request.

Servers allocate resources.

Applications execute queries.

Databases consume I/O.

APIs generate responses.

Whether the request comes from a customer or an AI agent, the computational cost remains largely the same.

For organizations operating ecommerce platforms, SaaS applications, media services, financial portals, or high-volume APIs, this additional load can quickly become expensive.

The impact usually appears in three areas:

• Increased infrastructure costs

• Higher server utilization

• Reduced performance for legitimate users

Many companies initially discover the issue through cloud invoices rather than security alerts.

When bots become your largest users

One of the most surprising observations is how quickly automated traffic can dominate system resources.

In a recent deployment protected by vshosting's Web Security Pack, more than 96 million requests were processed over a relatively short period.

The protection layer identified over 30 million challenge events and blocked more than 21 million unwanted requests before they reached the customer's infrastructure.

These numbers reveal an important reality:

Organizations often spend substantial resources serving requests that provide little or no business value.

Without filtering mechanisms, all of this traffic would reach application servers, databases, and backend systems.

The result is wasted compute capacity, higher operational costs, and increased performance risks.

AI agents behave differently than traditional bots

Traditional malicious bots tend to exhibit predictable patterns.

• They scrape aggressively.

• They perform credential attacks.

• They generate obvious anomalies.

Modern AI agents are different.

• Their traffic often resembles legitimate user behavior.

• They navigate websites naturally.

• They follow links.

• They request product pages.

• They access documentation.

• They interact with APIs.

From a security perspective, distinguishing valuable automation from wasteful automation is becoming increasingly difficult.

The challenge is no longer simply identifying bad traffic.

The challenge is determining which automated traffic deserves infrastructure resources.

This represents a fundamental shift in how organizations think about web security.

Infrastructure metrics tell the story

Looking at server-level metrics provides a clear picture of the operational impact.

During periods of elevated automated traffic, infrastructure teams frequently observe:

• Increased worker process utilization

• Higher request concurrency

• Significant spikes in load averages

• Greater variability in application response times

What makes the problem particularly challenging is that these patterns do not always indicate an attack.

Many organizations see infrastructure stress without obvious security incidents.

The traffic is technically legitimate. The resource consumption is real. And traditional security controls often allow it through.

The rise of traffic optimization as a competitive advantage

Historically, organizations measured success by traffic growth.

More visitors meant more opportunities.

Today, the equation is changing.

As AI-generated traffic continues to expand, successful organizations will increasingly focus on traffic quality rather than traffic volume.

The goal is not to block automation entirely.

Automation creates value.

Search engines create value.

AI systems create value.

Partners and integrations create value.

The objective is to ensure that infrastructure resources are allocated to traffic that supports business outcomes.

Organizations that can intelligently distinguish between valuable and non-valuable automated requests will gain measurable advantages in:

• Infrastructure efficiency

• Application performance

• Operational costs

• Customer experience

The next era of web security

The future of web security is not simply about stopping attacks. It is about managing automation. AI agents are rapidly becoming a permanent part of the internet ecosystem. Their numbers will continue to grow. Their sophistication will increase. And their impact on infrastructure will become more significant.For businesses, the question is no longer whether AI agents are visiting their websites.

The question is whether they understand how much infrastructure those agents are consuming - and whether they are prepared to manage it.

The organizations that solve this challenge early will not only improve security.

They will build faster, more resilient, and more cost-efficient digital platforms for the AI-driven web.

One such outage lasted almost five hours and became a practical demonstration of how the vshosting data center responds during a prolonged grid failure. Throughout the entire incident, the data center remained fully operational, with no interruption to customer services.

No impact on data center operations

Despite the duration of the outage, the data center infrastructure continued to operate as expected. Customer servers remained online, and no service limitations occurred.

For vshosting, the situation confirmed that the backup power architecture was designed correctly. While a number of services outside the data center were affected by the blackout, vshosting customers remained protected from its impact.

Backup power architecture

The vshosting data center uses several layers of power redundancy. The architecture is designed so that a single failure does not threaten service availability.

The backup power system includes:

• UPS systems: Vertiv APM modular units

• Diesel generators: CAT and Visa units

• Redundant power distribution: each power supply has two PDU branches, with each branch backed by double redundancy

UPS systems continuously stabilize the power supply and protect the infrastructure from voltage fluctuations. In the event of a public grid failure, diesel generators are kept in hot standby mode and start within approximately 30 seconds.

This setup ensures that servers and other critical systems do not experience interruptions during the transition from the public grid to backup power.

Why regular testing matters

A backup system is only as reliable as its most recent successful test. That is why vshosting performs controlled backup power tests four times a year.

These tests are not limited to basic functionality checks. During the process, the technical team deliberately disconnects the power supply and verifies whether all automatic procedures work according to defined scenarios. The entire process is carefully coordinated across the data center.

During testing, specialists are present in individual technical rooms, monitoring the process in real time and communicating with the control room. This allows the team to validate the behavior of all critical systems under controlled but realistic conditions.

It also confirms that the technical team knows exactly which procedures to follow during an actual outage.

During the blackout itself, the systems behaved as expected. The generators started as designed, the backup infrastructure was continuously monitored, and internal systems ran at full capacity without restrictions.

Fail-safe mechanisms and operational readiness

The power infrastructure is designed with several fail-safe mechanisms. If one of the primary backup components becomes unavailable, additional systems and procedures can take over.

These include:

• backup diesel generators in case the main units fail

• automated procedures for different failure scenarios

• escalation processes, including manual intervention by trained technical staff

• 24/7 availability of data center personnel

Automation plays a key role, but it is not the only layer of protection. A reliable operating model for critical infrastructure is created by combining automated response, redundant hardware, and an experienced team.

What happens during an outage

From an operational perspective, the response to an outage follows a clearly defined process. As soon as an outage is detected, the team immediately checks whether the automatic systems have responded correctly and whether the backup infrastructure is running as expected.

The team then monitors the situation, identifies the cause of the outage, and assesses its expected duration.

In this case, the scale of the blackout was unusual, but the response inside the data center was controlled and routine. The alarm system worked as expected, backup power took over, and the operation of the server room remained completely unaffected throughout the outage.

Customer services remained fully available

For customers, the most important result was simple: their servers kept running.

During the blackout, vshosting customer support received only two inquiries related to the autonomy of backup power sources and service availability. The company also received positive feedback from clients on social media, who appreciated that their websites, applications, and e-shops remained available while other services were affected by the outage.

Based on client feedback on social media, the situation was significant in a broader context as well. While some services, such as payment terminals, mobile networks, healthcare facilities operating on backup power, and industrial operations, were affected by the outage, websites, applications, and e-shops running at vshosting remained available.

Thanks to long-term investment in redundancy, maintenance and preparedness, vshosting services remained fully operational throughout the incident.

Lessons confirmed by real-world operation

The blackout did not reveal the need for any fundamental change in the backup power strategy. On the contrary, it confirmed that long-term investments in redundancy, automation, maintenance and operational readiness are essential.

In the past, the vshosting data center has also experienced very short power fluctuations lasting fractions of a second. In all such cases, the systems responded according to specification. This blackout was exceptional mainly because of its duration, not because of its technical complexity from the data center’s perspective.

100% power availability since the data center opened

Since opening in 2015, the vshosting data center has maintained 100% power availability without outages. This real-world large-scale blackout scenario became another confirmation that the infrastructure, processes and team readiness meet the demands of critical IT operations.

For organizations running business-critical websites, applications, e-shops or internal systems, this situation is a clear reminder of the importance of resilient infrastructure. Redundant power systems, regular stress tests, disaster recovery planning and a trained team are not optional extras. They are the foundation of service continuity when a real incident occurs.

To learn more about the technical infrastructure behind vshosting services, visit our Technology page.

A blackout shows whether backup power systems work only on paper, or whether they can protect real businesses in real time. In this case, the answer was clear: the systems worked exactly as they were designed to.