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How beehiiv saved $15K+ per month on AWS without lifting a finger using Pump Save
$15K+
Saved per month on autopilot
< 1 month
From onboarding to real savings
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Overview
"Pump showed us all our options side by side. One-year plan at 80% coverage, three-year plan at 70%, and exactly how much each one would save. The decision made itself. We locked it in, and the savings we're seeing now are probably just the start."
Eric Abis
VP of Data and Infrastructure
Beehiiv is a newsletter platform built by the team behind Morning Brew, powering creators, publishers, and brands to build, grow, and monetize their audiences at scale. The ~110-person company, now an AI-first platform with recent major product releases including an MCP server, runs its growing infrastructure on AWS with Kubernetes, MSK, ECS, and ClickHouse, while actively migrating workloads from legacy hosting platforms. As the platform expands into data science, security, and AI-native features, cloud spend is scaling quickly and becoming a larger line item each quarter.
Use Case 1
Seeing Every Option Side by Side, Then Picking the Obvious One
AWS Savings Plan documentation is dense, and modeling the right commitment level for a company whose compute needs change every month is the kind of analysis that sits in the backlog for weeks, then months. The person who should be doing it is already underwater with infrastructure work. Every day the analysis sits is another day the team pays on-demand prices for compute, which could be getting at a discount.
That's where Pump changed things for beehiiv. "The Pump platform is very useful because it really shows you your options," Eric said. "Like, if you do 80% on the one-year plan versus 70% on the three-year plan, how much would you save?" Instead of building a spreadsheet or scheduling a meeting with AWS, Eric's team could see projected savings across every combination in one view. The decision that had been stuck in the backlog for months suddenly took minutes.
The math spoke for itself. Beehiiv is invested heavily in AWS and was committed to the platform for the long haul. "I just thought, you know what? Let's just lock this in and save the most money for now," Eric said. They reviewed the options, committed to a long-term Savings Plan, and then scaled up coverage within two weeks, all coordinated asynchronously over Slack. No procurement committee. No weeks of internal debate. Just clear data that made the right choice obvious.
Within the first partial month, beehiiv was already saving thousands. By April, the first full month with savings plans active, Pump had saved them over $15,000, entirely on autopilot. Eric didn't change any code, move any workloads, or manage any reservations himself. The savings just showed up.
"The demand for compute is ever growing. I don't see us ever not needing the compute that we reserved." - Eric Abis, Head of Data and Infrastructure
Use Case 2
Savings That Grow With the Migration
Most cloud cost optimization stories end after the first commitment. The team locks in a Savings Plan, celebrates the number, and moves on. But for companies in the middle of a major infrastructure shift, the first commitment is just the starting point. The real value compounds as the footprint grows.
Beehiiv is living that exact moment. The migration from legacy hosting platforms to AWS is still underway, and their compute footprint grows every month as new workloads come online. Instead of treating that uncertainty as a reason to hold off, Pump gave Eric the confidence to commit early and scale up as the picture became clearer. "The savings that we have now are probably just the start," Eric said. "We expect to see a lot more savings as we continue to move over compute."
That's not wishful thinking. It's infrastructure reality. "ECS will be the big thing that we'll probably initially grow cost on," Eric explained, noting the team is also evaluating a transition from ECS to EKS for cost efficiency as workloads scale. On top of that, beehiiv's AI ambitions are accelerating fast. Eric described the company as "an AI-first platform" with major recent product releases, an MCP server that drew a huge response, and growing usage of AI services across the organization. "It's definitely growing as a major part of our platform and our product offering," he said.
Every one of those investments means more compute. And every dollar of new compute is another dollar that Pump can optimize. The $15K+ saved in April is what savings look like when beehiiv is still early in the migration. The real number will be much larger.
Use Case 3
Cost Visibility the CFO Can Actually Use
At most fast-growing companies, cloud cost knowledge lives inside the engineering team's head. The CFO asks how much the company is spending on cloud, and the answer is a best guess, a stale spreadsheet, or a 20-minute walkthrough of the AWS console that raises more questions than it answers. Engineers are building product, not building finance dashboards. But the gap between what engineering knows and what finance can see creates friction every month.
Beehiiv is closing that gap with Pump View. Eric described the value simply: "It's definitely helpful to go into View and see where our spend is and what we could potentially save." But the bigger win is that Dan Bae, beehiiv's CFO, can monitor cloud spend through the platform directly, without needing to schedule time with the engineering team or learn to navigate the AWS billing console.
As beehiiv's infrastructure grows more complex, spanning AWS compute, ClickHouse for data warehousing, and increasing AI service costs for their product features, having a single place to see all of it becomes essential. Beehiiv plans to connect its ClickHouse and AI costs into Pump View, giving both finance and engineering a unified dashboard across every cloud and AI vendor. No custom tooling. No monthly export rituals. Just one place where the numbers live.
Pump’s impact
The hardest part of cloud cost optimization isn't the math. It's finding the time. Engineering teams at fast-growing companies are always choosing between building the next feature and optimizing the bill for the last one. That tradeoff is why so many teams know they're overspending and do nothing about it for months.
Beehiiv broke that pattern. In their first full month on Pump Save, they saved over $15,000 on AWS without any manual optimization work, any code changes, or any engineering time diverted from product. Eric's team went from having no Savings Plan strategy at all to full coverage in under two weeks. The savings showed up immediately, and nobody had to stop what they were doing to make it happen.
That matters because beehiiv's engineering team was focused where it should have been: scaling an AI-first platform and shipping product for a rapidly growing user base. Cloud cost optimization was important, but it wasn't the team's core job. Pump filled that gap so Eric and his team could stay focused on building without leaving money on the table.
The trajectory is only going up. Beehiiv's migration is still underway, with compute demand growing as new workloads come online. "The savings that we have now are probably just the start," Eric said. "We expect to see a lot more savings as we continue to move over compute." The team is also planning to connect their ClickHouse and AI costs into Pump View, giving their CFO a unified dashboard across every cloud and AI vendor. As beehiiv evolves from a newsletter platform into a full AI-first operating system for the content economy, the infrastructure will keep scaling, and Pump will keep making sure the bill doesn't scale with it.