Code in production. Faster and with more confidence.
Continuous delivery measured by the four DORA metrics, with infrastructure as code and tested rollback.
DevOps became a job-posting term, but what matters is measurable. AWS documents the four DORA metrics as a way to track delivery maturity: deployment frequency, lead time for changes, change failure rate and mean time to recovery. If those four do not improve, the transformation did not happen, no matter how many tools were adopted.
The first two metrics measure speed; the last two, stability. The common mistake is optimizing one pair at the expense of the other: raising deployment frequency and breaking production every week, or shielding everything with manual approvals until nothing ships. A mature pipeline improves all four indicators at once, because test automation and rollback lower the cost of being wrong.
Infrastructure as code is the foundation for that. Without IaC, every environment becomes irreproducible craftwork, the drift between development and production grows quietly, and rollback depends on someone remembering what was changed. With IaC, infrastructure goes through pull request review like any other code.
If two or more of these scenarios sound familiar, it is worth a conversation.
Initial assessment at no cost
The exact composition depends on your environment and on the requirements identified during the assessment. This is the baseline we work from for this solution.
Delivery pipeline orchestration, promoting changes across environments and accounts
On-demand build and automated test execution
Blue/green and canary deployment strategies with automatic rollback
Versioned, reviewable infrastructure as code
Container image registry with vulnerability scanning
Container orchestration for long-running workloads
Serverless execution for event-driven workloads
Operational automation, parameter management and patching
Health signals that feed the decision to promote or roll back a deploy
Recording of degradation caused by a change, input for the change failure rate metric
We measure deployment frequency, lead time, change failure rate and MTTR in the current state. Without a baseline there is no way to demonstrate progress later.
We convert the environment to CloudFormation or CDK, removing manual console changes as an accepted path to change.
We build the pipeline with tests, static analysis and security scanning as automatic gates. What is verifiable should not depend on human review.
We implement blue/green or canary with automatic rollback triggered by metrics. Lowering the cost of being wrong is what allows fewer mistakes.
We integrate dependency, image and infrastructure as code scanning into the flow, shifting security verification to before the merge.
We instrument automatic collection of the DORA metrics and review the results with the team on a defined cadence.
Number of changes delivered successfully to production per period
Time between the commit and the change running in production
Share of deployments that cause degradation and require a fix
Mean time to bring the service back after a failure caused by a change
Market references documented by AWS itself in equivalent scenarios. Each card links to the original story published on the AWS site.
Facing fast growth, the company standardized its deployment pipeline on Amazon EKS, automating much of what used to be manual.
Published result
AWS describes pipeline standardization and productivity gains for the engineers.
The automation introduced alongside the migration to AWS significantly reduced the volume of recurring operational work.
Published result
AWS published 40% operational savings and an 80% drop in IT help desk tickets.
The cases above are customer stories published by Amazon Web Services. The results cited belong to the companies mentioned and serve as a reference for what is technically achievable on AWS. They do not represent results delivered by Núvoli, nor a guarantee of equivalent performance, since every environment has its own context.
Our approach is not opinion. It follows guidance documented by AWS, and you can check the source yourself.
The first step is an assessment of your current setup, at no cost and with no commitment. You come out of it with risks mapped and priorities defined, even if you decide not to move forward with Núvoli.
