Serverless development
We build event-driven, scale-to-zero functions where serverless genuinely fits — and we are equally clear about where it does not, from cold starts to work that has no business being a function.
Serverless is at its best on a specific shape of problem: work that is bursty or event-driven, where paying nothing while idle and scaling out instantly under a spike is exactly right. Image processing on upload, webhook handlers, scheduled jobs, the glue between systems — these fit the model cleanly, and provisioning a server to wait around for them is waste.
It is also over-recommended, so we name the trade-offs plainly. Cold starts add latency where a request path is sensitive to it; a steady, predictable load is often cheaper on a container than on per-invocation billing; long-running or stateful work fights the model rather than fitting it; and heavy use couples you to one cloud's primitives. We reach for serverless where the workload genuinely suits it and put the rest on infrastructure we run on containers — the choice made per workload, not as a fashion.
Where serverless fits
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Event-driven and scale-to-zero
Functions triggered by uploads, queues, schedules, and webhooks — nothing running or billed while idle, scaling out on their own when the events arrive.
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The right jobs for it
Bursty, spiky, and glue workloads where per-invocation billing and instant scale are a genuine win — not a steady service dressed up as functions.
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Honest about the limits
Cold-start latency, long-running and stateful work, and cloud lock-in named up front — so the choice is made on the workload's shape, not on hype.
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Wondering if serverless fits?
Describe the workload and its load pattern. We will tell you honestly whether serverless is the right shape for it, and build it whichever way genuinely serves the work.