DevOps & Release Engineering

Ship faster. Break less.

We build CI/CD pipelines, implement Infrastructure-as-Code, and establish the observability foundations that let engineering teams deploy with confidence. Release day should be boring.

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2 days → 30 min release time (health tech)55% fewer production bugs (e-commerce)

What We Cover

End-to-end DevOps practice

From the first commit to the production incident postmortem, we work across the full software delivery lifecycle.

CI/CD Pipelines

End-to-end automation from commit to production. GitHub Actions, GitLab CI, Jenkins, Fastlane, and Codemagic for mobile. Every pipeline includes build caching, parallelization, and failure notifications.

Infrastructure-as-Code

Reproducible infrastructure defined in code. Terraform and Pulumi for cloud resources, Ansible for configuration management, Helm charts for Kubernetes workloads.

Observability & SRE

You cannot fix what you cannot see. We implement logging, metrics, and tracing with Prometheus, Grafana, Datadog, and Sentry—then define SLOs and error budgets so on-call has clear targets.

Incident Response

Runbooks, on-call rotation design, postmortem templates, and alerting thresholds calibrated to reduce false pages. We help you build an incident culture that learns rather than reacts.

Cost Optimization

Cloud bills grow silently. We audit resource utilization, right-size instances, implement auto-scaling, and move appropriate workloads to spot or reserved pricing.

Quality Engineering

Test automation that runs in CI. Playwright for e2e, contract tests for APIs, Flutter integration tests, and performance regression baselines. We cut QA cycle time in half for a 500,000-user e-commerce platform.

Pipeline Architecture

A typical CI/CD flow we implement

Every pipeline is adapted to your stack and team workflow—this illustrates the key stages.

Toolchain

Tools we use in production

We are not tied to a particular vendor stack. These are the tools we have operated in production across real engagements.

GitHub ActionsGitLab CIJenkinsFastlaneCodemagicCircleCI

Case Study

Health-tech DevOps overhaul

Series A Health Tech Startup

From two-day releases to 30 minutes

The client was a Series A startup with iOS, Android, and a backend API. Releases required a full-team effort over two days: manual binary builds, ad-hoc environment configuration, and QA running test suites by hand. We replaced the entire release process in three months.

GitHub Actions workflows for backend API
Fastlane lanes for iOS builds and TestFlight distribution
Codemagic for Android with Google Play internal track promotion
Monitoring dashboards with incident alerting
Full runbook documentation for the on-call rotation

GitHub ActionsFastlaneCodemagicDockerPrometheusGrafana

Release time

2 days28 minutes

Release frequency

Once per sprintMultiple times per week

QA cycle

Manual, 2–3 daysAutomated in CI, ~45 min

On-call incidents

Discovered by usersAlerted in under 2 minutes

Why FalcoFlow

What makes the work different

We have cut release time from two days to 30 minutes in production

For a Series A health-tech startup, we replaced a fragile manual release process with GitHub Actions workflows and Fastlane lanes. Releases went from a full-team, two-day event to a 28-minute automated pipeline. The same engineers now ship multiple times per week instead of once per sprint.

We design for the team that has to operate it at 2am

Every pipeline, dashboard, and alert we build assumes the person on call is tired and does not have context. Runbooks are written for that scenario. Alert thresholds are tuned to signal real problems, not just noise. On-call should be boring.

Production bugs dropped 55% after our quality engineering framework

For an e-commerce platform serving 500,000 monthly users, we designed end-to-end Playwright test suites, API contract tests, and Flutter integration tests. The result: 55% fewer production bugs and QA cycle time cut by nearly half—without adding headcount.

“Release day went from an all-hands fire drill to something our juniors can trigger with a button push. The improvement was immediate and has held for six months.”

— CTO, Health Tech Startup

Series A, mobile + backend

FAQ

Common questions

A well-structured CI/CD pipeline for a monorepo with web and mobile targets typically takes two to four weeks to implement properly—including build caching, environment management, secrets handling, staging and production promotion gates, and runbook documentation. Rushed pipelines create maintenance debt. We scope carefully and deliver something your team can actually operate without our continued help.

Both. For existing infrastructure, we start with an audit to understand what is running, how it is provisioned, and what the biggest reliability or cost risks are. We then incrementally introduce IaC and CI/CD without taking things offline. For greenfield projects, we design the full stack from the start—which lets us make better architectural decisions without the constraints of legacy choices.

For most teams, Prometheus and Grafana cover metrics and dashboards, Sentry handles error tracking, and structured logging via the ELK stack or Loki covers log aggregation. If your budget allows a managed solution, Datadog integrates all three layers cleanly. We help you define SLOs before buying any tooling—alerting without SLOs just generates noise.

Yes. We have experience migrating stateful and stateless services to Kubernetes, writing Helm charts, setting up ArgoCD for GitOps-based deployment, and configuring cluster autoscaling and pod disruption budgets for production workloads. We also help teams decide when Kubernetes is and is not the right tool—it adds real operational complexity that smaller teams often do not need.

Security is integrated into the pipeline rather than bolted on. This means secret scanning with gitleaks or truffleHog, dependency vulnerability scanning via Dependabot or Snyk, SAST tooling for critical codebases, container image scanning, and least-privilege IAM policies for every pipeline role. We also help configure branch protection rules and signed commits where appropriate.

Yes. We run postmortem facilitation using blameless methodology, document contributing factors, and identify systemic improvements—not just individual mistakes. We also build the runbooks and playbooks that make the next incident faster to resolve. The goal is that your on-call rotation has clear, tested procedures rather than relying on institutional memory.

Stop releasing by hand

Tell us about your current release process. We will identify the biggest pain points and show you what a modern pipeline looks like for your stack.

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