Service
Cloud Infrastructure Services
Infrastructure is not the part that comes after the software. It is the part that decides whether the software can be changed safely, recovered when it breaks, and operated by somebody other than its author. We build it as product surface, with the first release rather than the third.
What ships with the first release
Backups that have been restored from at least once. An untested backup is a belief, not a capability, and the moment you discover which one you have is the worst possible moment to find out.
Alerting on conditions that mean something, routed to somebody who can act. A dashboard nobody watches is not monitoring. Neither is an alert channel so noisy that the real failure arrives in a stream of things everyone has learned to ignore.
Rate limits and resource ceilings from the start. Almost every runaway cloud bill and most availability incidents trace back to a limit that was going to be added once traffic justified it.
Deployment that is boring
A deployment should be unremarkable enough to do on a Thursday afternoon. That requires it to be automated, repeatable, and reversible: the same pipeline every time, no manual steps held in one person's memory, and a rollback that has been exercised rather than assumed.
Infrastructure is defined as code for the same reason. A cloud account configured by hand through a console is a configuration nobody can review, reproduce, or rebuild after an accident, and its actual state is knowable only by inspection.
Right-sizing, in both directions
A great deal of cloud spend is capacity bought against traffic that never arrived, and a great deal of downtime is capacity that was never bought at all. Both come from the same place: guessing instead of measuring.
We size against observed load with headroom that is stated rather than implied, and we are equally willing to conclude that a system does not need Kubernetes. Managed services and a single well-configured instance are frequently the correct architecture, and the cost of unnecessary distribution is paid every day by whoever is on call.
What an engagement includes
- Infrastructure as code, with environments reproducible from the repository
- Automated deployment pipeline with an exercised rollback path
- Backup and restore, verified by performing a restore
- Monitoring, structured logs and alerting routed to someone who can act
- Rate limits, resource ceilings and cost alerting
- TLS, secrets management and network boundaries
- Capacity assessment against observed load, with stated headroom
- Runbooks for the failures that are actually likely
Common questions
- Which cloud providers do you work with?
- Principally AWS, and the same practices carry to other major providers. The provider is usually the least consequential decision on the list. How state is managed, how deployments roll back and how failures are detected matter far more, and those questions have the same answers almost everywhere.
- Can you take over infrastructure that already exists?
- Yes. That normally begins with an assessment of what is running, what it costs, how it is deployed and where it would fail, delivered in writing. Bringing an environment that was configured by hand under version control is usually the first meaningful improvement.
- Do we need Kubernetes?
- Probably not, and we will tell you plainly when the answer is no. It solves real problems at real scale and imposes a permanent operational cost on teams that have neither. Managed services and a small number of well-configured instances run a great many production systems perfectly well.
Related practices
Let's Build Something Extraordinary.
Whether you're looking to collaborate, partner with us or simply follow our journey, we'd love to hear from you.
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