As the lead solutions architect at a mid-sized OVNS (Open vSwitch Network Service) vendor, I field this question at least three times a week from enterprise IT teams, cloud architects, and even small DevOps teams looking to stitch together their on-prem and cloud infrastructure. For the uninitiated, OVNS is the open-source, extensible network management plane that sits on top of Open vSwitch (OVS), letting you build distributed virtual networks, overlay tunnels, and advanced layer 2/layer 3 routing across any number of hosts. For years, it’s been the go-to for teams building private clouds, bare-metal datacenter fabrics, and edge networks, locked firmly to on-prem hardware and custom private cloud stacks. So the answer to “Can OVNS be integrated with cloud platforms?” isn’t just “yes”—it’s a “yes, and here’s how we’re proving it works for real-world enterprise use cases today, not just whitepapers.” OVNS
First, let’s cut through the confusion: integrating OVNS with public or hybrid cloud platforms isn’t about running OVNS as a replacement for AWS VPC or Azure Virtual Network. It’s about building a unified network fabric that spans on-prem, public cloud regions, and edge locations—something legacy public cloud networks were never designed to do, especially for teams handling regulated data, multi-cloud workloads, or custom application architectures. Let’s start with the technical foundations that make this integration possible, because OVNS was built with cloud-native interoperability in mind, even if many users forgot that. OVNS’s core components—its central OVN Northbound/Southbound databases (OVN NB/SB), the chassis agents on each host, and the gateways that connect networks to external environments—are all stateless, API-driven, and container-friendly. That means they can be deployed almost anywhere, including inside public cloud VMs or Kubernetes clusters, without tight coupling to a specific cloud’s proprietary network stack.
Let’s break down the most common integration patterns we’ve implemented for clients over the last two years, because these aren’t theoretical: they’re production deployments serving e-commerce, healthcare, and fintech clients handling 100k+ transactions per second across hybrid environments. The first, and most straightforward, is OVNS as a distributed underlay for cloud VPCs. Wait, you’re probably thinking: “Cloud providers have their own underlays, why would I use OVNS here?” The answer is workload portability. Suppose you have a Java microservices suite running in an on-prem private cloud, and you need to move half the workloads to AWS during a peak sale to avoid latency and capacity constraints. If both your on-prem and AWS-hosted VMs are connected to an OVNS fabric, moving a virtual machine (VM) or Kubernetes pod from on-prem to AWS Region A doesn’t require reassigning IP addresses, reconfiguring firewalls, or updating routing tables across your entire application ecosystem. That’s a huge win for teams handling event-driven workloads where downtime during migration costs six figures per minute.
We did this for a large healthcare payer last year, for example. They needed to move a portion of their patient portal microservices to AWS during annual open enrollment, to handle a 4x spike in user traffic, without reconfiguring access controls or exposing PHI (protected health information) to unvetted cloud network changes. We deployed OVNS gateway VMs in two AWS Availability Zones (AZs), configured OVN’s layer 3 gateways to peer with AWS’s Direct Connect private connection, and synced OVN’s security group rules with AWS’s IAM and security services. When their DevOps team migrated a pod from an on-prem host to an AWS VM, the OVN chassis agent updated the local flow rules in 100ms, and the pod retained its static IP address, its network security policies, and its ability to communicate with on-prem EHR systems. No re-IPing, no firewall re-rules, no service interruption. That’s not a hack—it’s leveraging OVNS’s built-in support for external logical routers, which can peer with BGP speakers in cloud networks, eliminating the need for manual route entry.
The second integration pattern is OVNS overlay networks within Kubernetes clusters hosted on cloud platforms. A lot of Kubernetes users default to a cloud’s native CNI (Container Network Interface) plugin, like AWS VPC CNI or Azure CNI, because they’re easy to set up. But when you have multi-cloud Kubernetes clusters, or clusters running on both bare metal and cloud, using different CNIs creates network silos: a pod in your on-prem Kubernetes can’t natively communicate with a pod in a cloud-hosted Kubernetes, because each CNI assigns IPs in separate ranges and uses different overlay protocols. OVNS solves this here by providing a single CNI that works across all cluster environments, with OVNS’s overlay tunnel (Geneve, the standard now, instead of the older VXLAN) creating a unified layer 2 network across nodes, regardless of whether those nodes are in a bare-metal datacenter, an AWS EC2 VM, or an Azure AKS node. We recently worked with a global fintech that runs a Kubernetes cluster on-prem for core banking workloads, and an AKS cluster in Azure for customer-facing apps. They were losing 15-20ms of latency on inter-cluster pod traffic because of NAT between the two cloud-native CNIs, and they couldn’t enforce consistent network policies for banking transactions across both clusters. By replacing their native CNI with OVNS across all nodes (we ran the OVN chassis agent on every single AKS node and on-prem bare metal node, with the OVN NB/SB database replicated across three Azure VMs for high availability), they cut inter-cluster pod latency by 70% and were able to enforce a single set of network policies that blocked unencrypted traffic between banking pods, regardless of where the pods ran.
The third pattern, and one we’re seeing grow rapidly, is OVNS for multi-cloud network policy enforcement. Public clouds each have their own network policy tools: AWS has Security Groups and Network ACLs, Azure has NSGs, GCP has Firewall Rules. But these tools are siloed, so you end up with separate policy sets for each cloud, no way to enforce consistent zero-trust access across all workloads, and a lot of manual overhead when a new workload is spun up. OVNS’s distributed firewall, which is built into every chassis agent, works across all these cloud environments. You define a single set of logical firewall rules in the central OVN NB database, and those rules are pushed automatically to every OVN chassis agent—whether that agent is on-prem, in AWS, or in Azure. We implemented this for a SaaS startup that operates across AWS, GCP, and their own on-prem datacenter, with hundreds of microservices across all environments. Before OVNS, their security team spent 10+ hours a week updating firewall rules across three separate cloud consoles, and they had a critical gap: a Kubernetes pod running in GCP that was able to reach a sensitive database pod in AWS because no one had updated the cross-cloud firewall rule. With OVNS, they defined a single rule that only allowed database workloads to accept traffic from app workloads tagged as “prod”, regardless of the cloud provider. The rule was pushed to every OVN chassis agent in all three environments within 2 seconds, and the security team now spends less than an hour a week on cross-cloud policy updates.
Now, let’s talk about the common roadblocks teams hit when trying to integrate OVNS with cloud platforms, and how we mitigate them—because this is where a lot of half-baked integration attempts fall apart. The first roadblock is IP address management (IPAM). OVNS has a built-in IPAM, but many teams want to use their cloud’s native IPAM (like AWS VPC IPAM) to avoid overlapping address ranges. We’ve solved this with OVNS’s external IPAM plugin, which is compatible with AWS VPC IPAM, Azure Virtual Network IPAM, and even open-source tools like Infoblox. This means you can assign IP addresses from your existing cloud address ranges to OVNS logical networks, so there’s no overlap between OVNS and cloud network IPs, and you don’t have to manage a separate IPAM instance.
The second roadblock is cloud-specific network restrictions. Public clouds often block or throttle certain overlay protocols, or require specific permissions for custom network components. For example, AWS restricts the use of Geneve tunnels by default in most AWS accounts, because it’s a newer protocol, and Azure requires specific network security group rules to allow OVN chassis agents to communicate with each other. Our team maintains a set of pre-tested deployment guides for all major cloud platforms, which include the exact IAM permissions, security group rules, and VPC configurations needed to run OVNS without any restrictions. For AWS, that includes a CloudFormation template that enables Geneve tunnels for the relevant subnets and creates the necessary IAM roles for OVN chassis agents. For Azure, we provide an ARM template that opens the required ports for OVN’s control plane and data plane traffic, so users don’t have to manually dig through cloud documentation.
The third roadblock is high availability (HA). When you run OVNS components in a cloud environment, you can’t rely on on-prem hardware redundancy. The OVN NB/SB database, which is the single source of truth for all OVNS logical networks, needs to be replicated across multiple availability zones to avoid downtime. We’ve standardized on a multi-AZ, highly available deployment model for OVNS in cloud environments: we deploy three instances of the OVN NB/SB database, each in a separate AZ, using cloud-managed database services where possible (like AWS RDS or Azure SQL Managed Instance) for the database layer, plus a load balancer in front of the database instances for high availability. This means if one AZ goes down, the database remains available, and OVNS logical networks continue to operate without interruption. We tested this with a client during an AWS us-east-1 AZ outage last year: their OVNS database was in three AZs, and the failure of one AZ didn’t impact any of their workloads, even though they were running 200+ pods across OVNS logical networks.
Wait, but what about the big cloud providers’ proprietary networks? Some will argue that integrating OVNS adds unnecessary complexity, and that using cloud-native tools is simpler. That’s true for teams that only run workloads in a single public cloud region, with no need for portability or unified network policies. But for teams with hybrid or multi-cloud architectures, OVNS doesn’t add complexity—it reduces it. Let’s do the math: if you have two on-prem sites, two AWS regions, and one Azure region, using cloud-native network tools would mean managing six separate network stacks, six different policy sets, and six different teams to maintain them. With OVNS, you have one network stack, one policy set, and one team to maintain it. That complexity reduction translates directly to cost: our clients that switch to OVNS for hybrid integration reduce their network management costs by 30-40% on average, according to our 2023 customer survey.
Another common question we get: Is OVNS integration with cloud platforms certified? The short answer is that while OVNS is open-source, our vendor has completed compatibility certifications with AWS, Azure, and GCP, so our enterprise customers can get support for OVNS running on cloud infrastructure, without having to debug compatibility issues on their own. We’ve also contributed code back to the OVNS upstream project to improve cloud interoperability, including adding support for Azure’s Managed Identity for OVN gateway authentication, and AWS Direct Connect peer routing for OVNS logical routers. This means the improvements we make for our cloud-integrated deployments benefit the entire OVNS community, not just our customers.
Now, let’s talk about real-world limitations, because we’re not here to sell a perfect product. OVNS isn’t the right fit for every use case. If you’re a small business running a single application in a single AWS region, using AWS VPC CNI is going to be simpler and cheaper than deploying OVNS. OVNS also has higher resource overhead than some cloud-native CNIs: each OVN chassis agent uses about 50-100MB of memory per host, which is a small cost for enterprise deployments, but something to consider for very resource-constrained edge devices. Also, while OVNS works well with all major cloud platforms, it’s not a direct replacement for cloud-native managed services like Elastic Load Balancing (ELB) or Azure App Gateway—though we do integrate OVNS logical load balancers with these managed services, so you can route traffic between OVNS workloads and cloud load balancers as needed.
So where do we go from here? As a vendor, we’re working to expand OVNS’s integration with cloud-specific managed services, like adding support for AWS VPC Lattice and Azure Front Door to our OVNS logical load balancers, so teams can have a single load balancing layer across on-prem and cloud workloads. We’re also working on a serverless OVN chassis agent, which can run as an AWS Lambda or Azure Function, for teams that want to use OVNS for temporary workloads without provisioning long-running VM instances.
At the end of the day, the question of whether OVNS can be integrated with cloud platforms isn’t a technical one anymore—it’s a strategic one. For teams that need to build flexible, portable, unified networks across hybrid or multi-cloud environments, the answer is a resounding yes. We’ve helped over 50 clients do it in the last two years, from healthcare payers to SaaS startups to global fintechs, and the only limitations are the use cases where cloud-native tools are already sufficient.
If you’re evaluating network solutions for a hybrid or multi-cloud architecture, and you’re looking to reduce network management complexity while improving workload portability, our team is here to help. We work with clients to tailor OVNS deployments to their specific cloud environments, from small single-cloud deployments to large multi-region, multi-cloud enterprise networks, with end-to-end support and custom integration services. Reach out to our sales team to discuss your specific use case and get a tailored architecture recommendation.
SAVAGE References
Open vSwitch. (n.d.). OVN Architecture. Retrieved from upstream open-source project documentation.
Cloud Native Computing Foundation. (2023). CNIs for Hybrid Cloud: A Survey of Interoperability Patterns.
Gartner. (2023). Market Guide for Hybrid Cloud Network Services, Vendor Analysis Report.
OVNS Upstream Community. (2022). “Cloud Integration Plugins for OVN: A Case Study from Enterprise Deployments.” Proceedings of the Open Networking Summit.
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