Product Engineering
Agile & DevOps Practices
Slow releases are rarely one problem. A backlog nobody grooms feeds a pipeline nobody trusts, and each makes the other worse. We measure both first - lead time, deploy frequency, change failure rate, time to restore - then fix planning and pipeline together, and retire the manual gates that no longer earn their place.
HOW IT RUNS
Four phases, from unmeasured to forecastable
Each phase ends with something you can hold: a baseline, a pipeline, an automated suite, a hand-over.
Delivery Baseline
We measure the four delivery metrics - lead time, deployment frequency, change failure rate and time to restore - alongside sprint velocity and backlog health. The slowest step gets named, with evidence.
DELIVERABLES
- Baseline on the four delivery metrics
- Velocity and backlog health report
- Map of manual gates and approvals
- Ranked list of bottlenecks
- Recommended framework and tooling
- Prerequisites needed from your side
What We Build
Planning and pipeline, run as one practice
Nine services, standalone or combined. Most engagements begin with the baseline and the pipeline, then add the rest wherever the numbers point.
Sprint Planning & Backlog Management
Estimates and cadence set from real capacity, and a backlog groomed far enough ahead that the next sprint is ready before it starts.
Scrum & Kanban Delivery Frameworks
Whichever fits how work actually arrives. Every ceremony has a defined output, or it gets dropped from the calendar.
Agile Coaching & Transformation
Coaching aimed at the blockers the baseline found, for teams leaving waterfall or ad hoc delivery behind.
Retrospectives & Continuous Improvement
Retro actions with owners, checked at the next retro, so the same blocker stops resurfacing every fortnight.
CI/CD Pipeline Design & Implementation
Build and deploy pipelines sized to your release cadence, with a rollback path that has actually been run.
Test Automation
Unit, integration and regression suites that gate the pipeline, so a broken build stops before it ships.
Infrastructure as Code
Every environment defined in code. Staging matches production, and a new environment is a pull request instead of a ticket.
Containerisation & Orchestration
Docker and Kubernetes sized from measured usage, not copied from a default cluster template.
Monitoring & Incident Response
Alerts on the signals that predict incidents, and runbooks for the incidents that happen anyway.
Our Methodology
Measure first. Then change one thing.
Arguments about process end when the timings are on the table. Fix the wrong bottleneck and the delay simply reappears one step downstream.
Baseline Before Framework
Velocity, lead time and failure rate are measured before Scrum, Kanban or a hybrid is recommended.
Bottleneck Before Tooling
The slowest step on the path to production is fixed first. A new tool comes in only if the current one is the bottleneck.
Rollback Rehearsed, Not Assumed
A rollback path that has never run is a hope. Each pipeline's rollback is exercised against a real deployment.
Gates Retired With Evidence
Manual approvals that add delay without catching anything are identified and removed, with their owners on board.
DevOps Engineering Practice
Pipelines built for a bad day, not a demo
Demo pipelines and production pipelines part ways the first time an urgent fix collides with someone else's release. What separates them is settled during the build:
These five decide which one you get.
Pipeline Architecture
Stages structured around your services and their dependencies, so a new service needs configuration, not a pipeline rewrite.
Test Automation Standards
Tests maintained alongside the pipeline. A flaky test is fixed or removed, never quietly skipped.
Compliance Readiness
Audit logs and approval gates designed in for regulated environments, so the evidence exists before anyone asks for it.
Security by Design
Secret management, dependency scanning and least-privilege access scoped during design, not after an audit finding.
Infrastructure Reliability
Version-controlled environments that rebuild the same way every time, with no manual checklist in the loop.
Technology Stack
Tools we plan and ship with
We work inside the board, the CI system and the cloud you already use. A tool changes only when the baseline shows it is the bottleneck.
Jira / Linear / Azure DevOps Boards
Sprint planning, backlog and reporting in the tool your team already lives in.
Agile PlanningGitHub Actions / Jenkins / GitLab CI
Pipelines on the repository host you already run.
CI/CDDocker / Kubernetes
Packaging and scheduling for services that grow at different rates.
Containers & OrchestrationPrometheus / Grafana / Datadog
Dashboards and alerts built on leading indicators, not a green uptime light.
Monitoring & ObservabilityTerraform / Pulumi
Reproducible, version-controlled environments, from a developer sandbox to production.
Infrastructure as CodeYour toolchain first. A change is recommended only where the current tool is the measured bottleneck, never to match a template of ours.
Agile & Project Management
JiraLinearAzure DevOps BoardsCI/CD
GitHub Actions
Jenkins
GitLab CIInfrastructure & Observability
Docker
Kubernetes
Terraform
Pulumi
Prometheus
Grafana
DatadogWhere It Breaks
Three ways Agile and DevOps change fails
Each one looks like progress from the outside:
Ceremonies Without Change
Standups and retros run on schedule, and nothing they surface reaches the next sprint. The calendar changes; delivery doesn't.
The One Manual Step
Everything is automated except one approval nobody owns. That step becomes the real bottleneck, and nobody is measuring it.
Tools Before Diagnosis
A new CI platform or board is bought before anyone measures where the time goes. The delay moves; it doesn't shrink.
Why Us
How we run Agile and DevOps work
We start by measuring where your sprints and releases lose time. Frameworks and tools come after the numbers, not before them.
01
Numbers Before Frameworks
Sprint velocity and backlog health are tracked before Scrum, Kanban or a hybrid is suggested.
02
Bottlenecks Before Tools
No tool gets proposed until the path from commit to production has been timed end to end.
03
Rollback Rehearsed
Rollback is run against a real deployment before go-live, not left as a page in a wiki.
04
Your Stack, Extended
We build on the board, the CI system and the cloud you already use.
05
An Exit Built In
Hand-over includes runbooks, dashboards and a checklist of what your team can now run on its own.
Vertical Focus
What a release puts at risk, industry by industry
In retail a slow release misses a sales window. In healthcare or banking an unaudited deploy becomes a finding. The pipeline is designed for the stakes.
Release pipelines for clinical software
- An audit trail for every deployment
- Access controls and logging on patient-data releases
- Automated tests gating patient-data code paths
- Approval and rollback records for clinical releases
Audit-ready pipelines for financial systems
- Load-tested pipelines for transaction systems
- Deployment logs and approvals kept as evidence
- Automated tests on account and payment code paths
- Release sign-offs traceable to each change
Pipelines for connected-vehicle software
- Fleet rollouts staged by region and model
- Over-the-air update pipelines
- Regression gates on safety-relevant code
- Rollout monitoring with automatic rollback
Pipelines for plant-floor systems
- Deployments staged plant by plant
- Test automation for ERP and plant integrations
- Release windows planned around production schedules
- Monitoring and alerting for plant-floor services
Pipelines for software in the field
- Rollouts staged to remote and offline sites
- Test automation for seasonal load
- Update delivery over poor connectivity
- Field outage monitoring and alerting
Pipelines built for peak trading
- Load-tested checkout deployments
- Payment-flow regression suites
- Canary releases on high-traffic channels
- Checkout monitoring through peak periods
FAQs
Agile and DevOps, answered
Whichever suits the way requests reach your team. The baseline shows how work actually flows, and the recommendation follows from that.
Not at first. We can hold the backlog with your stakeholders while you appoint one, or coach an internal candidate. Sooner or later, someone on your side has to own the word no.
Any mix of the nine services above. The baseline shows which ones your delivery path actually needs, and the rest stay out.
A first working pipeline is an early milestone in the plan the baseline produces. How quickly the rest follows depends on how much is already automated and how many teams share the path.
Usually not. We work inside your current board and CI system, and propose a replacement only where the numbers show the tool itself is slowing you down.
An executive sponsor, access to repositories and environments, a product owner with real authority, and willingness to revisit release approvals. Without that last one, a faster pipeline still waits at the same gate.
Pipeline configuration, infrastructure as code, dashboards, runbooks and a before-and-after report on the four delivery metrics, plus a checklist of what your team can run without outside help.
Measure how your team
plans and ships.
Tell us how sprints get planned, how often you release, and what went wrong last time. The first step is a baseline built from your own delivery data, and a plain account of what it shows.
Have a project in mind?
Start with a baseline of where the time actually goes.