As adtech platforms grow, so do the requests they serve and the data their systems move. Bidders and auction services need to handle that growing volume without missing response deadlines. At the same time, protecting margins hinges on keeping infrastructure costs sustainable over the long term.
For platforms running sustained, always-on workloads in the public cloud, moving to dedicated bare metal servers can reduce compute, storage, and bandwidth costs without sacrificing performance. Teams can also retain cloud services where needed, using dedicated infrastructure for predictable baseline demand.
In this guide, we’ll examine the main infrastructure cost drivers for adtech platforms, ways to reduce them, and how bare metal or hybrid infrastructure can help keep the infrastructure bill under control.
What drives infrastructure costs for adtech platforms?
Behind the scenes of the digital advertising industry are the servers, networks, and databases that receive bid requests, run auctions, and record the events used for reporting and attribution.
Keeping these systems within response-time limits while processing billions of requests takes significant resources. As traffic grows, the cost of compute, data transfer, and storage can put serious pressure on margins.
Several characteristics of adtech workloads make infrastructure costs particularly challenging to manage:
1. Always-on compute
Bidders, auction services, and supporting databases often run continuously. Unlike workloads that can scale down to zero during quiet periods, these systems need substantial compute capacity available around the clock.
Additionally, the usage-based billing model common among major cloud providers means you pay for each cloud instance for as long as it’s running, even when your workload uses only a fraction of its CPU and memory.
Combined, these factors can leave you paying around the clock for compute capacity you’re only partly using, at rates that include a premium for flexibility you rarely need. That drives up the cost of each request processed.
2. Bandwidth and data transfer
Bid requests and responses, database replication, and event pipelines move data between systems and locations.
Depending on the provider and network path, transferring data out to the internet, between availability zones, or across regions can incur usage-based charges.
These fees, including egress fees, may be modest at a small scale. But for platforms moving hundreds of terabytes — or petabytes — of billable traffic each month, these costs can become a substantial portion of the infrastructure bill.
3. Database and storage requirements
Adtech platforms store and access large amounts of data, from audience profiles and campaign settings to bid logs and performance reports. These systems need enough storage to hold the data and enough read/write performance to keep up with production traffic.
In the cloud, the bill can include separate charges for storage capacity, read/write operations, throughput, and backups. As data volumes and activity grow, teams may find themselves paying more both to store their data and to access it at the speed their applications require.
4. Redundancy and infrastructure operations
Keeping an adtech platform available requires more infrastructure than it takes to serve normal traffic. Database replicas, standby servers, and backups add costs, including capacity held ready to keep bidding and auction services running during failures or maintenance.
There’s also the ongoing cost of operating that infrastructure. Managing operating systems, monitoring performance, and responding to incidents takes engineering time, paid services, or a combination of both.
Layer these costs on top of compute, storage, and data transfer charges, and it’s easy to see how an adtech platform’s infrastructure bill can become hard to untangle.
Strategies for reducing adtech infrastructure costs
When the infrastructure bill keeps climbing, adtech teams need ways to bring costs under control without compromising performance.
Savings can come from adjusting instance sizes, reducing billable data movement, or securing better rates for sustained usage. Teams can also change the underlying cost structure by moving workloads to dedicated infrastructure.
Some strategies worth evaluating include:
Right-sizing compute: Compare instance configurations against production throughput and tail latency. A smaller instance is only a saving if it can handle its share of requests without increasing timeouts.
Reducing data transfer charges: Map the billable paths between auction services, databases, event pipelines, and external partners. Review whether placement or connectivity changes could lower charges without compromising latency or resilience.
Using committed-use discounts: Compare discounted cloud rates for capacity the platform consistently needs. Factor in existing commitments and their expiration dates when evaluating alternatives.
Moving sustained workloads to bare metal: Compare the monthly cost of dedicated servers against the cloud capacity needed to handle the same request volume, including database, storage, and bandwidth requirements.
These approaches can work together. Teams may first remove waste from their cloud environment, then find that the remaining baseline workload is still expensive to run at cloud rates. That is where dedicated infrastructure deserves a closer look.
Lowering adtech infrastructure costs with bare metal
Not just in adtech, but across industries, teams are increasingly turning to cloud repatriation when cloud costs become difficult to justify. As workloads become more consistent and resource-intensive, many find that dedicated infrastructure offers a more economical way to run them while preserving performance.
Bare metal servers leased from a provider gives an adtech platform dedicated physical hardware for a fixed price. Rather than paying separately for cloud instances, attached storage, and provisioned storage performance, teams lease a server with a defined CPU, memory, and disk configuration. Bandwidth may be included as a monthly allowance or offered on an unmetered bandwidth plan.
For adtech platforms, this model can provide favorable costs when workloads consistently use substantial resources:
Always-on compute: Bidders, auction services, and supporting systems may need a predictable baseline of capacity around the clock. Dedicated servers can lower the cost of that capacity when utilization is sufficient to justify the hardware.
High data transfer volumes: Included or unmetered bandwidth can reduce costs for platforms exchanging large amounts of data with advertising partners.
Sustained database and storage activity: Local SSD or NVMe storage provides capacity and read/write performance within the server price, potentially reducing separately billed storage costs.
At the same time, bare metal also puts more responsibility on your team for the OS, software stack, and capacity planning. But for sustained workloads, that operational work can be justified by a lower cost per request and more consistent access to dedicated compute, memory, and storage resources.
For a broader look at performance, operational tradeoffs, and provider selection, see our guide to bare metal for adtech platforms.
Cloud and bare metal costs compared
Cloud and bare metal providers package their charges differently, so comparing compute prices alone won’t give you the full picture.
A comparison considering the total cost of ownership (TCO) should include all of the resources required to run the same workload at the same performance and availability levels.
Here’s a breakdown of how the costs of cloud and bare metal infrastructure compare:
Cost component | Public cloud | Leased bare metal |
Compute | Typically usage-based billing, with discounts available through commitments | Fixed server price for a defined hardware configuration, usually billed on a monthly or hourly basis |
Storage | Depending on the service, separate charges for capacity, IOPS, throughput, and snapshots | Local drives typically included in the server price; additional storage and backups may be available at an additional cost |
Data transfer | Outbound data transfer often metered. Charges depend on destination, region, and network path | Included allowance with metered usage, or unmetered bandwidth, depending on the plan |
Redundancy | Additional instances, storage replicas, and related services | Additional servers, replicated storage, and supporting network services |
Operations | Responsibilities vary between self-managed instances and managed services | Teams typically manage the OS and software stack; the provider maintains physical hardware |
Determining which model is most economical will depend on your use case, workload profile, and the needs of your infrastructure team.
Dedicated servers can offer lower costs for sustained demand, while cloud infrastructure may remain more economical for temporary workloads or services that would require substantial engineering effort to replace.
Hybrid infrastructure: Reducing costs without a full cloud migration
An adtech platform doesn’t need to move every service to bare metal to improve its infrastructure economics. A hybrid deployment can put sustained production workloads on dedicated servers while retaining managed cloud services and tooling that would be expensive to replace.
A platform might run its baseline bidder capacity and supporting databases on dedicated servers while keeping development environments and managed services in the cloud. Cloud capacity can also support temporary demand increases, provided the application is designed to run across both environments.
The split needs careful planning. Separating an application from its database can add latency, and moving data between bare metal and cloud services can introduce transfer charges that eat into the savings. Systems that exchange large amounts of data may be better off moving together.
For a practical migration, start with a predictable workload whose dependencies are well understood. Moving it first gives your team a way to measure the savings, validate performance, and build confidence before taking on a larger migration.
Reduce adtech infrastructure costs with Rackdog
For DSPs, SSPs, and exchanges, reducing infrastructure costs means improving the economics of processing production traffic while meeting latency and availability requirements. Dedicated servers can make that possible by lowering the cost of sustained compute, database activity, and network traffic.
Rackdog provides bare metal servers for adtech workloads, with fixed monthly pricing and unmetered bandwidth plans. Global deployment locations, full root access, and API and Terraform support give your team control over where and how your infrastructure runs.
Create an account to start deploying today, or get in touch with an infrastructure expert from our team to explore a bare metal solution that’s right for you.