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What's Slowing Down Your Cloud? (Hint: It's Not the App)

Eli Lahr
Leaseweb USA

Most teams go straight to the usual suspects when performance tanks in the cloud: app bugs, code regressions, maybe even the cloud provider itself. However, the real bottleneck is hiding in plain sight more often than not: the network.

Of course, apps are only as fast and secure as the connections between them in today's hybrid and multi-cloud environments. In other words, don't just audit your app if you're dealing with lag, downtime, or data sync issues. It's time to look under the hood at the infrastructure that's supposed to be holding it all together.

Cloud's Silent Performance Killer

Modern apps run across public cloud, private data centers, edge nodes, and even bare metal. They don't live in a single place anymore. That level of distribution demands a strong, purpose-built network strategy. Every transaction, real-time response, and secure data transfer will get bogged down without it.

Here's what happens when the network doesn't keep up:

  • Latency creeps in - which frustrates users and breaks real-time workflows
  • Data bottlenecks emerge - delaying analytics and AI pipelines
  • Security gaps appear - especially when traffic flows aren't encrypted or monitored

And yet, most cloud strategies barely mention the network until something goes wrong.

Why the Network Matters More Than You Think

The benefits are immediate and undeniable when your network is built to support the complexity of hybrid and multi-cloud:

  • Redundant paths, failover routes, and resilient infrastructure ensure business continuity and faster disaster recovery (DR) = Greater Reliability
  • Low-latency connectivity powers time-sensitive workloads, i.e., video streaming, gaming, and AI inferencing = Improved Performance
  • A modern network design can flex as you scale, whether that's across regions or providers = Increased Scalability
  • Advanced encryption, traffic segmentation, and monitoring protect data in motion, not just at rest = Enhanced Security

Real-World Impact, From AI to Gaming

Let's get a bit more specific.

One global enterprise running AI workloads needed to connect on-prem GPU clusters to cloud analytics tools without crushing performance. The solution? High-speed, direct network links that cut training times and eliminated sync delays.

A gaming company faced a different problem: players abandoning matches due to latency. Shifting to a bare metal setup with smart routing and dedicated bandwidth changed the game - literally.

These companies didn't rewrite code. They rethought their network.

The Next Wave Is Already Here

With today's AI-driven services and real-time data expectations, networks have to evolve fast. Traditional setups can't keep up. What's needed now are intelligent, adaptive, secure networks that align with how apps and users actually operate today.

Cloud isn't slowing down. But without the right network infrastructure, your ability to deliver on its promise will. If your cloud feels slow, glitchy, or unreliable, don't blame the app, or the platform. Blame the pipes. The truth is that your network could be the biggest factor holding you back.

So, before your next deployment or expansion, take a hard look at the infrastructure below the surface. Because the real difference between "it works" and "it scales beautifully" often comes down to how well your network is doing its job.

Eli Lahr is a Senior Solutions Engineer at Leaseweb USA

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Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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What's Slowing Down Your Cloud? (Hint: It's Not the App)

Eli Lahr
Leaseweb USA

Most teams go straight to the usual suspects when performance tanks in the cloud: app bugs, code regressions, maybe even the cloud provider itself. However, the real bottleneck is hiding in plain sight more often than not: the network.

Of course, apps are only as fast and secure as the connections between them in today's hybrid and multi-cloud environments. In other words, don't just audit your app if you're dealing with lag, downtime, or data sync issues. It's time to look under the hood at the infrastructure that's supposed to be holding it all together.

Cloud's Silent Performance Killer

Modern apps run across public cloud, private data centers, edge nodes, and even bare metal. They don't live in a single place anymore. That level of distribution demands a strong, purpose-built network strategy. Every transaction, real-time response, and secure data transfer will get bogged down without it.

Here's what happens when the network doesn't keep up:

  • Latency creeps in - which frustrates users and breaks real-time workflows
  • Data bottlenecks emerge - delaying analytics and AI pipelines
  • Security gaps appear - especially when traffic flows aren't encrypted or monitored

And yet, most cloud strategies barely mention the network until something goes wrong.

Why the Network Matters More Than You Think

The benefits are immediate and undeniable when your network is built to support the complexity of hybrid and multi-cloud:

  • Redundant paths, failover routes, and resilient infrastructure ensure business continuity and faster disaster recovery (DR) = Greater Reliability
  • Low-latency connectivity powers time-sensitive workloads, i.e., video streaming, gaming, and AI inferencing = Improved Performance
  • A modern network design can flex as you scale, whether that's across regions or providers = Increased Scalability
  • Advanced encryption, traffic segmentation, and monitoring protect data in motion, not just at rest = Enhanced Security

Real-World Impact, From AI to Gaming

Let's get a bit more specific.

One global enterprise running AI workloads needed to connect on-prem GPU clusters to cloud analytics tools without crushing performance. The solution? High-speed, direct network links that cut training times and eliminated sync delays.

A gaming company faced a different problem: players abandoning matches due to latency. Shifting to a bare metal setup with smart routing and dedicated bandwidth changed the game - literally.

These companies didn't rewrite code. They rethought their network.

The Next Wave Is Already Here

With today's AI-driven services and real-time data expectations, networks have to evolve fast. Traditional setups can't keep up. What's needed now are intelligent, adaptive, secure networks that align with how apps and users actually operate today.

Cloud isn't slowing down. But without the right network infrastructure, your ability to deliver on its promise will. If your cloud feels slow, glitchy, or unreliable, don't blame the app, or the platform. Blame the pipes. The truth is that your network could be the biggest factor holding you back.

So, before your next deployment or expansion, take a hard look at the infrastructure below the surface. Because the real difference between "it works" and "it scales beautifully" often comes down to how well your network is doing its job.

Eli Lahr is a Senior Solutions Engineer at Leaseweb USA

Hot Topics

The Latest

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...