At Backblaze, we’re in the business of building a storage platform that can handle billions of operations a day—reliably, predictably, and fast. That means digging deep into low-level architecture, optimizing what most people overlook, and constantly balancing trade-offs between performance, cost, and scale.
Today, we’re kicking off a new blog series that showcases the platform-level work our Engineering team has been doing to build and run a modern cloud storage platform. The kind of work that usually stays buried in Jira tickets and internal docs, but that makes all the difference when you’re serving exabytes at scale.
What it really means to build a modern cloud storage platform
When people talk about cloud storage, they usually focus on capacity, availability, and price. This includes the systems, tools, and architectural decisions that enable our infrastructure to scale reliably while handling billions of operations per day.
We’re crafting a dynamic, evolving platform that handles exabytes of data with reliability and efficiency. We’re a platform that developers and businesses build on. That means durability, performance, uptime, and predictability aren’t just nice-to-haves—they’re fundamental requirements. As Senior Vice President of Engineering, I’m excited to pull back the curtain and offer a glimpse into the ongoing engineering efforts that power our platform.
Building for simple is more complex than it seems
One of our core engineering philosophies is this: Complexity should serve simplicity. For example, changing how we handle request headers might sound like a small thing, but when you operate a distributed system at scale, even tiny inefficiencies can multiply quickly. A 5% improvement in API response time might not sound dramatic, but at exabyte scale, that translates to millions of faster interactions per day, less CPU usage, and better customer experiences across the board.
Our Engineering team is always thinking about those compound effects. Sometimes that means rewriting parts of a system that have been stable for years. Other times it means saying no to flashy solutions and choosing battle-tested designs that will hold up under load.
What to expect from this series
If you care about performance, distributed architecture, or what it actually takes to run a reliable cloud infrastructure, this is for you. We’ve published deep dives before, such as our articles on Load Balancing (and Load Balancing 2.0!), improvements on small file uploads that gave us speeds faster than AWS, Network Stats, Reed-Solomon erasure coding, using native code in Backblaze Personal Backup, everything that lives in the Backblaze Github, and many, many more.
Our goal, in addition to talking about the individual stories, is to start talking about some of the throughlines—when one project spawns another, or how we decide which project to pursue when there are competing priorities.
These projects don’t usually make headlines on their own, but taken together, they form the backbone of what makes Backblaze perform the way it does. They’ll become part of our regularly scheduled programming, and we’ll drop them in our Tech Lab category so you can find them easily.
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See you on the next one—and let us know if you have questions
We’re proud of the work our engineers are doing, but more than that, we think it’s worth sharing. Whether you’re a fellow cloud architect, a developer using our platform, or just someone curious about what it takes to run cloud infrastructure at scale, we hope this series offers something insightful.
Technology doesn’t stand still, and neither do we. The more efficient our platform becomes, the better we can serve our customers—and the more we can invest in new ideas. So stay tuned. We’re kicking things off in this content series in the next few weeks, and we look forward to hearing your thoughts!
