AWS Networking and Latency Optimisation

AWS Networking and Latency Optimisation

Latency is a reliability problem wearing a different hat. A system that is technically up but slow is, to the user trying to use it, broken. And because latency hides in the network paths that rarely appear on the architecture diagram, it is often the last thing teams look at and the first thing customers notice.

This guide covers how to think about AWS network latency: where it comes from, how to diagnose it, and the levers that actually move it, from routing and edge delivery through to service-to-service communication and cross-region transfer. We run latency-sensitive workloads in production, so the focus is on finding the real bottleneck rather than guessing at it.

Diagnose before you optimise

The most common mistake with latency is optimising the wrong thing. A team assumes the database is slow, spends a week tuning it, and the real culprit was a chatty service making fifty sequential calls across availability zones. Latency is cumulative and it hides in the gaps between components, so you have to measure the whole path before you touch anything.

The causes cluster into a few categories: distance (the physical reality that data takes time to travel), the network path (cross-zone and cross-region hops, each adding milliseconds), the application (sequential calls that should be parallel, payloads larger than they need to be), and saturation (a component near capacity queues requests). Working through the common causes and fixes systematically beats guessing, and the broader network latency optimisation practices give you the checklist to run through.

Route intelligently

Where you send traffic, and how, is the first lever. Amazon Route 53 is more than DNS, it is a traffic-management layer. Weighted routing lets you split traffic across endpoints by proportion, which is useful for gradual rollouts and for balancing across regions. Latency-based routing sends each user to the endpoint that is fastest for them, which directly attacks the distance problem by serving people from the nearest healthy location. We explain the mechanics in weighted routing in Route 53. The principle across all of it: route on health and proximity, not on a static assumption about where your users are.

Serve from the edge

For anything served to end users, distance is the enemy, and the fix is to not travel the distance. Amazon CloudFront is the content delivery network that caches your content at edge locations close to users, so a request is served from a nearby point of presence rather than making the full round trip to your origin every time. This cuts latency for static assets dramatically, and with the right cache strategy it offloads a large share of traffic from your origin entirely, which improves both speed and cost. CloudFront helps most for applications with a geographically distributed user base, where the latency saving compounds across every request.

Fix service-to-service communication

In a microservices or distributed architecture, much of your latency is internal: services calling services. As the number of services grows, the communication between them becomes both a performance factor and an operational blind spot. AWS App Mesh provides a service mesh that standardises how services discover and talk to each other, with consistent routing, retries, and visibility into the traffic between services. Setting up App Mesh for service communication gives you control over the internal network behaviour that otherwise emerges by accident, and, just as importantly, visibility into where the time goes between services. You cannot fix inter-service latency you cannot see.

Control cross-region and cross-zone transfer

Moving data around your own infrastructure costs both time and money. Cross-zone traffic adds latency in small increments that accumulate, and cross-region traffic adds it in larger ones. As you add redundancy or expand geographically, the transfer paths multiply, and so does the latency and the bill. AWS Transit Gateway centralises and simplifies the connectivity between your VPCs, accounts, and regions, and getting the cross-region data transfer with Transit Gateway pattern right keeps both the latency and the cost under control. The architectural principle: keep chatty components close together, and be deliberate about what genuinely needs to cross a region boundary.

Make latency visible

Every lever above depends on seeing the latency in the first place. You cannot optimise a path you cannot measure, and aggregate latency numbers hide the problem. A p50 that looks fine can sit on top of a p99 that is destroying the experience for one in a hundred requests. Real latency optimisation needs distributed tracing that follows a request across every hop and shows you exactly which span is slow, percentile-based metrics rather than averages, and synthetic monitoring that measures the experience from where your users actually are. Without that, you are optimising in the dark.

Where Critical Cloud comes in

Finding and fixing latency across a distributed AWS environment, then keeping it fixed as the system grows, is ongoing work that depends entirely on visibility. That is what we bring.

Critical Cloud runs AWS environments with full distributed tracing and synthetic monitoring through Datadog, so latency is measured end to end, by percentile, from the user's perspective. When something slows down, we see which hop, which service, and which span is responsible, and we fix the real bottleneck rather than the assumed one. As the world's first Powered by Datadog accredited partner, that latency visibility is built into how we operate.

If slow is starting to mean broken for your users, see how Critical Support works.