Your release calendar is a business constraint. It doesn't have to be.

Teceze builds and runs the pipelines, infrastructure code and release automation that let your teams ship daily instead of quarterly with every deployment tested, scanned, approved and reversible. You get faster delivery and a lower change failure rate, evidenced in DORA metrics rather than claimed in a status report.

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Six things that decide whether you ship weekly or quarterly

Most delivery slowdowns aren’t a developer productivity problem, they’re a pipeline, environment and approval problem. We engineer those out, then hand you a platform your own team can run without us.

CI/CD pipeline engineering

Build, test, scan, artefact and deploy stages as code, in GitHub Actions, GitLab CI, Azure DevOps, Jenkins or Argo CD. Standard templates per application type, so a new service inherits a production-grade pipeline on day one.

Reusable pipeline templates

Infrastructure as code

Terraform and Bicep modules with remote state, policy checks and drift detection across AWS, Azure and GCP. Environments are rebuilt from source in minutes, not reconstructed from memory during an incident.

Reproducible environments

Containers & Kubernetes platform

EKS, AKS and GKE clusters built with GitOps, autoscaling, network policy and cost guardrails. Developers get a self-service path to production; platform standards stay enforced in code, not in a wiki page.

GitOps-managed clusters

Release & rollback automation

Blue-green, canary and feature-flagged releases with automated health gates. If error rate or latency breaches threshold, the release rolls back on its own, before your users raise a ticket.

Automated rollback gates

DevSecOps built into the pipeline

SAST, SCA, secrets scanning, container image and IaC policy checks run on every commit, with severity thresholds that block a merge instead of generating a report nobody reads. Audit evidence is produced automatically.

Shift-left, audit-ready

DORA metrics & observability

Deployment frequency, lead time for change, change failure rate and MTTR instrumented per team and per service, alongside cloud cost per release. The engineering conversation with your CFO stops being anecdotal.

Board-ready delivery metrics

Faster delivery only counts if failure rate goes down with it

These are the ranges our enterprise clients typically reach within two to three delivery quarters. We baseline your current DORA position in the assessment, then commit to target movement in the statement of work.

5–10x
Deployment frequency

From monthly or fortnightly release windows to on-demand deployment per service.

70–85%
Shorter lead time

Commit to production, measured end to end including test and approval stages.

<5%
Change failure rate

Sustained, through automated gates, canary releases and tested rollback paths.

20–30%
Lower cloud spend

From right-sized environments, autoscaling and shutting down idle non-production estate.

First production-grade pipeline live in three weeks: current-state and DORA baseline, reference pipeline on one real service, platform hardening, then rollout with your engineers co-building each stage.

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Contractors are bought by the head and paid by the hour, so the incentive is to stay. We are engaged against a delivery outcome, pipelines live, DORA metrics moved, platform documented and handed over, with your engineers co-building alongside ours from week one. Knowledge transfer is a deliverable, not a courtesy. Every pipeline, module and runbook lives in your repositories under your ownership. If you choose to run it yourself at the end of the engagement, nothing breaks.

No. We work with what you already run, GitHub, GitLab, Bitbucket or Azure Repos; GitHub Actions, GitLab CI, Azure Pipelines, Jenkins or Argo CD; AWS, Azure, GCP or hybrid. Migration is a recommendation we make only where the current tool is genuinely the constraint. Where you’re mid-consolidation, we’ll build so that pipeline logic sits in reusable templates rather than tool-specific glue, which keeps a future move from becoming a rewrite.

Three weeks to a first production-grade pipeline on a real service, not a proof of concept on a sample app. Weeks one to three cover baseline, reference pipeline and hardening; rollout to further services then runs in parallel tracks. We deliberately pick a service that matters, because a pipeline built around a trivial workload never surfaces the approval, data and dependency problems that actually slow your releases down.

Yes, and this is where the fastest wins usually sit. Automating build, test, environment provisioning and release for a monolith typically removes days of manual effort per release before any refactoring is discussed. We don’t lead with a rewrite. Where decomposition is genuinely warranted, we’ll say so with a cost and sequence attached, after the pipeline is in place, not instead of it.

Speed and control fail together or hold together. Security checks, SAST, dependency and secrets scanning, container image scanning, IaC policy, run on every commit with agreed severity thresholds that block promotion automatically. Segregation of duties, approval records and change evidence are generated by the pipeline itself, which is usually stronger audit evidence than a manual change advisory process. We’ll map controls to your framework, ISO 27001, SOC 2, PCI DSS, GDPR, before the first gate goes live.

Optionally. Many clients take a managed model, 24/7 pipeline and platform operations, on-call for build and release incidents, continuous improvement backlog, delivered from our India, US and UK centres. Others take a build-and-transfer, with a fixed advisory retainer afterwards. Both are priced separately from the build, so you’re never buying a run contract to get the engineering.

The build phase is fixed-scope, fixed-price against defined deliverables, pipelines, IaC modules, platform, documentation, handover. Ongoing platform operations are priced per environment or per squad supported, monthly. We’ll model both against your estate in the assessment, including the cloud cost change, so you’re comparing total cost of delivery rather than day rates.

Four numbers, baselined before we start and reported throughout: deployment frequency, lead time for change, change failure rate and time to restore service. Targets for each are agreed in the statement of work. Ask every vendor you shortlist to commit to movement on those four. It’s the clearest way to separate DevOps engineering from resource supply.

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Let’s Find What’s Slowing Your Releases

Schedule a 45-minute assessment with our DevOps and cloud engineering leads. You’ll leave with your current DORA position and the specific bottlenecks between a commit and production.

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