By Brian Bauman, Solutions Architect
Learn what causes high multicloud latency, and how you can reduce it with a few simple methods – no hardware deployment required.
Latency is usually one of those problems that shows up before anyone has time to go looking for it – and troubleshooting it can feel like you’re aiming for a moving target.
In this guide we’ll explain what actually causes latency between cloud environments, how to reduce it, and what other companies have achieved by making the right changes to their architecture.
Network latency refers to the time it takes for a data packet to travel from source to destination and back. This round trip is typically measured in milliseconds and commonly referred to as the Round-Trip Time (RTT).
Latency in multicloud environments is affected by two main contributors: the physical distance a data packet must travel, and the level of network congestion.
As a data packet traverses a network, it passes through multiple “hops,” with each hop representing a handoff between network devices. The further these hops are from one another, the higher the latency will be.
These network devices also have specific bandwidth allocations which can become overrun during periods of high traffic. This causes data packets to be queued for processing or rerouted along a different path, resulting in a longer RTT.
High latency is common when sending traffic over the public internet, where data packets have to pass through various peering partners, compete with other traffic, and take multiple hops between cloud provider regions.
For IT teams, high latency usually manifests as intermittent performance complaints, inflated webpage loading times, trouble maintaining predictable service behavior between clouds, and of course, increased RTT measurements.
One misconception shows up over and over: the belief that adding bandwidth lowers latency. It doesn’t. A larger pipe helps with throughput, but not travel time.
The only reliable fixes for tackling latency are placing your multicloud resources strategically, reducing the physical distance between environments, then using private connectivity to avoid congested paths and optimize performance.
Since distance is the biggest factor impacting latency, closing the gap is the most effective fix for reducing latency. If, for example, your workloads live in AWS us-east-1 (Northern Virginia) and Azure SouthCentral (San Antonio), you could place AWS resources into a Local Zone in Dallas. This functions as an additional Availability Zone within the us-east-1 VPC, enabling you to place your AWS workloads physically closer to your Azure environment and drastically reducing RTT.
This method doesn’t require an overhaul of your architecture; you just have to be intentional about placement.
Interconnecting a multicloud environment with a private network is like putting an expressway between your disparate cloud resources.
Running traffic over private connectivity reduces the number of hops between clouds and avoids congestion, significantly reducing RTT and avoiding the inconsistent latency caused by the fluctuations of internet routing. And when you connect two cloud environments directly, giving applications direct access to one another’s data and services, you’ll get predictable high performance with added reliability and security.
There’s also a financial benefit to this method: Public cloud egress over the internet averages around $0.09/GB, which stacks up quickly at scale. Private connectivity typically cuts these egress fees by 60-70% every month.
For the right architecture, edge connectivity minimizes the physical distance between your applications and the networks they depend on. Instead of sending traffic across long-haul routes with multiple public hops, edge connectivity is an effective way to keep workloads close to users, partners, or other cloud environments.
Companies should consider edge designs when latency directly impacts the business – think customer-facing applications, real-time compute, or transactional workloads. You’ll want to deploy your edge networking resources at the on-ramps of your multicloud environments to see the benefits.
Megaport makes it easier to control your multicloud latency by moving your private traffic onto a global private network underlay.
With Megaport Cloud Router (MCR) for cloud interconnection and Megaport Virtual Edge (MVE) for edge connectivity, you can deploy virtual appliances on demand and place them in data centers close to your public cloud environments for direct, predictable paths.
Using Megaport not only lowers latency but also provides:
This leading travel platform connected its multicloud environments using MCR to reduce latency and jitter, making its network far more resilient during heavy booking periods.
Real-time scalability meant the business could handle demand spikes without degradation.
The Warehouse Group operated across geographically separated cloud regions in Auckland and Sydney. By using MCR to peer between these environments, they significantly lowered latency and improved the experience for both internal teams and end customers.
Options used Megaport’s SDN to deliver reliable, low-latency connectivity to clients in the financial sector. The flexibility and on-demand provisioning helped them support a broad digital transformation program without sacrificing performance.
For Flexify.IO, private connectivity reduced their high cloud egress fees and enabled a more efficient multicloud storage strategy. Lower and more predictable latency made it feasible to move and replicate data across clouds.
Low-latency multicloud is all down to physics, paths, and control.
Megaport helps with this by providing on-demand, fixed-bandwidth private connectivity through services like MCR and MVE, letting you build a multicloud architecture that’s fast, predictable, and easy to adjust as your environment evolves.
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