- Latency and packet loss can severely degrade Cloud performance, even on high-bandwidth networks.
- Keeping data close reduces latency but increases exposure to correlated failures and resilience risks.
- Modern WAN acceleration and optimization technologies allow geographically distributed Clouds without performance trade-offs.
- Effective Cloud strategy balances distance, performance, security, and disaster recovery through tested, resilient architectures.
Cloud and Wide Area Network (WAN) latency, packet loss, and poor bandwidth utilization are challenges for every part of the Cloud ecosystem, from enterprise clients to service providers.
Latency and packet loss can reduce performance even on the highest-bandwidth network. And more bandwidth doesn’t necessarily translate into faster data transfers.
What causes latency and packet loss, and what are the solutions (and compromises) needed to deliver fast and secure data?
First let’s define some terms right now, and and we’ll look at more definitions later. TL;DR alert: just jump ahead if you know all this!
What is latency?
Latency is the delay between request and response. It’s the time it takes for data to travel from one point to another and back again. Click a link, send a command, load an app—latency is the pause before something happens.
For the Cloud ecosystem, latency matters because speed underpins everything. High latency can mean sluggish applications, choppy video, slow backups, and frustrated users, even when bandwidth looks fine on paper (or speed test). As workloads move closer to the Edge and customer expectations tighten, reducing latency isn’t just a technical concern—it’s a competitive advantage for platforms, providers, and MSPs alike.
What is packet loss?
Packet loss happens when small units of data fail to reach their destination as they move across a network. Instead of arriving intact and in order, some packets are dropped along the way, forcing systems to resend them or work with incomplete information.
In the world of the Cloud, packet loss directly impacts performance and reliability. It can show up as frozen video calls, failed file transfers, slow application responses, or unstable connections, even on high-speed networks. As Cloud services become more real-time and distributed, keeping packet loss to a minimum is essential for delivering the seamless, always-on experiences users now expect.
How to Fix Cloud latency and packet loss
Latency increases with distance. Hence the temptation to place your Clouds, disaster recovery sites, and data centers in close proximity to each other—particularly as there is an increasing emphasis on data sovereignty and legislation that supports (or requires) keeping data local.
Denis Stanarevic, Solution Portfolio Lead for Data Services Platforms at Hewlett Packard Enterprise (HPE), advises caution: “Proximity simplifies network design and accelerates backup and recovery. However, this approach exposes the environment to the risk of correlated failures: floods, earthquakes, power outages, or coordinated cyber-attacks. They can simultaneously impact both production and disaster recovery environments.”
Putting all your data into the same circles of disruption therefore carries risks that must be balanced against data speeds.
David Trossell, CEO and CTO of Bridgeworks, explains why a centralized approach puts service continuity and uptime in jeopardy during a power outage:
“Hosting within the same data center, or shadow center, is still an issue. Sometimes failover zones are created by splitting the data center in half, but it’s only fine if you don’t lose power to both sides. If you really want to have a secure disaster recovery system, you need a 3-2-1-1-0 approach.”
Time for another quick explainer…
What is the 3-2-1-1-0 approach to data protection?
The 3-2-1-1-0 approach is a best-practice framework for data protection and backup resilience. It means keeping three copies of data, stored on two different types of media, with one copy kept offsite, one copy offline or immutable, and zero errors verified through regular testing and monitoring.
For the Cloud ecosystem, 3-2-1-1-0 reflects how backup strategies have evolved to meet modern threats like ransomware and system failure. As data becomes more distributed and business continuity expectations rise, this approach helps MSPs and platform providers move beyond basic backup toward proven, auditable resilience that customers can trust.
Trossell advises that data should not be situated close together, even when using the 3-2-1-1-0 approach. This will help to minimize downtime and mitigate any potential risk of data loss.
The data location and latency dilemma
Regulations such as GDPR and the EU’s Cloud Sovereignty Framework may require data to be stored within national or regional boundaries. Beyond these restrictions, where should you locate the data?
Distance has its advantages, as we have seen. The issue is that latency becomes more problematic the farther away you transfer data.
One approach to mitigating latency and packet loss is WAN Acceleration, which relies upon artificial intelligence, machine learning, and data parallelization. WAN Acceleration can send and receive voluminous amounts of encrypted data. It is also data agnostic, and it can’t be seen by those, such as Bridgeworks, providing the service.
There are other technologies that reduce or neutralize the downsides of geographically dispersed deployments.
Stanarevic explains that collectively these capabilities empower customers to embrace multiple Clouds situated thousands of miles apart without negative impacts on backup windows, recovery time objectives (RTO), or recovery point objectives (RPO).
He cites some of HPE’s solutions:
Predictive Data Path Optimization: This monitors network conditions to predict latency spikes or packet loss episodes to enable real-time data flow optimization, rerouting traffic dynamically over least-congested or lowest-latency paths.
Intelligent Data Deduplication and Compression: By minimizing redundant data transmission through on-the-fly deduplication and adaptive compression, you can dramatically reduce bandwidth consumption. This is especially important for encrypted data transfers where payload sizes can inflate network loads.
WAN Acceleration and Protocol Optimization: Proprietary WAN acceleration techniques combined with protocol enhancements reduce round-trip times, and in HPE’s case retransmissions are frequently encountered in conventional TCP/IP communication over long distances.
Edge Computing and Data Locality: Through Edge-to-Cloud platforms, organizations can process critical workloads close to their point of origin while seamlessly synchronizing with distant DR repositories. This hybrid architecture ensures zero compromise on latency-sensitive applications.
Ensuring security and WAN performance
With multiple approaches available, enterprises must find the right balance between geographically diverse data centers and investment in technologies that mitigate latency, packet loss, and improve bandwidth utilization.
Trossell agrees, explaining that latency will always exist, but by using AI to control a level of parallelization you can mitigate the effects of latency and packet loss.
Stanarevic’s key piece of advice is to regularly test disaster recovery plans across sites to validate actual latency and packet loss, and their impact in simulated disaster scenarios.
He cautions that whether multi-Cloud or hybrid Cloud strategies are adopted, in an era defined by digital transformation, data proliferation, and complex regulatory landscapes, nobody can afford to compromise on backup and disaster recovery strategies for the sake of geographic proximity.
