Shipping should be the least dramatic part of the week.
Deployment frequency is not a vanity metric. It is the clearest available proxy for how much fear is in your system.
JANNEX provides DevOps and platform engineering: CI/CD pipeline design, infrastructure as code, container and serverless platforms, environment provisioning, secrets management, observability, alerting, on-call practice and incident review.
The symptoms of a delivery problem
They are cultural before they are technical, but they always have a technical cause you can fix.
- Releases batched into a monthly window because each one is risky
- An environment that only resembles production in the parts nobody checks
- Secrets in a repository, or in a message thread
- Alerts that fire so often nobody reads them
- Incident reviews that identify a person rather than a missing control
How we build delivery
Small changes, released often, observed properly, reversed quickly.
Reproducible environments
Defined in code and rebuilt from scratch routinely, so drift has nowhere to accumulate.
A pipeline with teeth
Build, test, security scan, deploy. Quality gates that fail the build rather than emailing a report.
Progressive delivery
Staged rollout with automated rollback on the signals that matter.
Observability before scale
Metrics, logs and traces correlated, with alerts tied to service-level objectives.
What this covers
Delivery
- CI/CD pipeline design
- Trunk-based workflow
- Automated testing gates
- Artifact and registry management
- Progressive rollout and rollback
Platform
- Infrastructure as code
- Container orchestration
- Environment provisioning
- Secrets and configuration management
- Internal developer tooling
Operate
- Metrics, logs and distributed tracing
- Service-level objectives and error budgets
- Alert design and routing
- On-call rotation and runbooks
- Blameless incident review
Technology
The working set for this capability. Choices are made per engagement, against your constraints and your team's skills.
Where it is typically applied
Patterns we see repeatedly, described generically. Your version will differ in the details, and the details are the work.
From monthly to on-demand releases
Pipeline, tests and rollback built so that deploying is a decision rather than an event.
Environments on request
Provisioned from code per branch, torn down automatically, with a cost ceiling.
Observability that answers questions
Traces linked to logs and metrics, so the first question in an incident is answerable in minutes.
An on-call rotation people can live with
Alerts tuned to user-visible symptoms, runbooks written, and noise removed deliberately.
How the engagement runs
The same seven stages, scoped to the size of the problem.
Understand
We start with the constraint, not the feature list. What breaks today, who it affects, what it costs.
Define
A written scope with the trade-offs made explicit — what is in, what is deferred, what we will measure.
Design
Interfaces, data models and system boundaries designed together, because they constrain each other.
Build
Short cycles against a working environment. Reviewed code, tests where they earn their keep.
Launch
Staged rollout with monitoring in place before traffic, not after the first incident.
Learn
Instrumented usage read against the thing we said we would measure at Define.
Scale
Performance, cost and operations tuned once real load has told us where the pressure is.
Questions we are asked
Do we need Kubernetes?
Most organisations do not. Managed containers or serverless carry far less operational weight for the same outcome. Kubernetes earns its cost at genuine scale, with real multi-tenancy, or where a platform team already exists.
Can you improve delivery without rebuilding everything?
Usually yes. Pipeline, environments, secrets handling and observability can be fixed around an existing application, and that is often where the fastest improvement is.
How do you measure improvement?
Deployment frequency, lead time from merge to production, change failure rate and time to restore. Measured before, so the after means something.
Related reading
Monolith vs microservices: what actually makes sense?
Service boundaries are an organisational decision with a technical bill attached. Most teams pay the bill before they need the benefit.
Read AWS · 7 min readHow to build a cost-efficient AWS architecture from day one
The decisions taken in the first fortnight determine most of what you will pay in year two.
ReadHave something worth building?
Tell us the constraint you are working against. If we are not the right people for it, we will say so.
Or write to connect@jannex.in