Cloud & DevOps,
built as a product.
Landing zones, Kubernetes, IaC, CI/CD, SRE and internal platforms, engineered for reliability, cost and speed, and delivered as products your engineers actually want to ship on.
A complete cloud & DevOps practice, engineered end to end.
From landing zones through Kubernetes, delivery pipelines, SRE, observability, security and FinOps, our practice covers the full delivery surface of modern cloud platforms.
Cloud strategy & landing zones
Target-state cloud architecture, multi-account/subscription landing zones, guardrails and reference patterns, designed against your operating model, not lifted from a vendor deck.
Infrastructure as code
Terraform, OpenTofu and Pulumi codebases treated like software, modular, reviewed, tested, versioned, so infrastructure changes are proposed, discussed and rolled back like any other change.
Kubernetes & container platforms
Production Kubernetes on EKS, AKS, GKE and self-managed, with sensible base images, secure defaults, cost-aware autoscaling and the platform APIs your teams actually enjoy shipping on.
CI/CD & delivery pipelines
GitHub Actions, GitLab, Jenkins, ArgoCD and Flux pipelines that are fast, testable and honest, with progressive delivery, canary and rollback as first-class concerns.
Platform engineering
Internal developer platforms, golden paths, service catalogues, self-service environments and paved-road frameworks, designed so shipping is faster than reinventing.
SRE & reliability
SLOs, error budgets, incident response, chaos and load testing, treated as a shared engineering discipline, not a page in a runbook that no one has opened since onboarding.
Observability
Structured logs, metrics, traces and events on OpenTelemetry, Prometheus, Grafana, Datadog and equivalents, designed for the questions on-call actually asks, not the ones the tool defaults to.
Cloud security & compliance
Zero-trust identity, network and workload security aligned to CIS, NIST, ISO 27001 and sector regimes, with evidence trails engineered alongside delivery, not reconstructed before audit.
FinOps & cost engineering
Cost attribution, unit economics, right-sizing, savings plans and workload placement, measured, negotiated and defended to finance rather than blamed on the vendor.
Multi-cloud & hybrid
Multi-cloud and hybrid deployments where they genuinely earn their keep, with honest trade-offs on latency, data gravity and operational load, not multi-cloud as a slogan.
Migration & modernisation
Data-centre and cloud-to-cloud migrations run as rolling waves with parallel-run and reconciliation, never as a big-bang weekend that quietly gets rolled back.
Cloud networking & edge
Landing-zone networking, transit, service mesh, CDN and edge compute, engineered against the actual traffic profile, cost envelope and failure modes of the estate.
Land the paved road. Then move everything onto it.
A delivery model that stands up a working platform spine with a first service on it, then migrates the rest of the estate onto it in rolling waves.
Frame
Working sessions on target operating model, workloads, cost envelope, compliance and skills. Output: a phased plan with a first slice already scoped.
Foundation
Landing zone, IaC, CI/CD, observability, security baselines and a paved-road platform stood up as a working spine, with a first service running on it end-to-end.
Migrate & extend
Workloads migrated and modernised in rolling waves. New services onboard onto the paved road. Every change is IaC-driven, reviewed and observable.
Operate
SLOs, incidents, cost and security posture monitored as ongoing engineering. Enablement and runbooks are designed in, the platform is safely owned by your team on the day we hand over.
A pragmatic cloud toolchain.
Cloud, container and pipeline selection is a working decision, driven by workloads, skills and economics, not by whichever tool is trending this quarter.
AWS
Azure
GCP
Kubernetes
Docker
TerraformOOpenTofuPPulumiAAnsibleHHelmAArgoCDFFlux
GitHub ActionsGCGitLab CIJJenkinsIIstioLLinkerdCConsul
Prometheus
Grafana
DatadogOOpenTelemetry
SentryVVault
Kafka
Redis
PostgresProgrammes delivered on this practice.
What prospective clients ask us first.
If your question isn't addressed here, please reach us at hello@tekansa.com.
01AWS, Azure, GCP or multi-cloud, how do you decide?
By working backwards from workloads, existing skills, data gravity and unit economics, not from allegiances. Most organisations are best served by a primary cloud with well-chosen exceptions, rather than by trying to be equally fluent in three. We map the real workloads and constraints, and design so components can move if the economics or the compliance story shifts, that's usually more valuable than shipping identical footprints on every cloud.
02How do you approach Kubernetes without over-engineering?
Kubernetes earns its place when the workload count, team size and deployment frequency justify the operational cost, otherwise a simpler managed compute usually wins. When we do adopt it, we prefer managed control planes, opinionated defaults, a small paved-road platform layer and disciplined use of operators. The goal is a boring, safe substrate that application teams don't have to think about, not a platform that turns into a full-time hobby.
03What does 'platform engineering' actually mean in your delivery?
Building the internal developer platform as a product, with a paved road, self-service environments, golden templates, service catalogues and clear SLAs on the platform itself. The measure of success is how much application teams ship without opening a ticket, and how much the platform team spends on new capability rather than firefighting. We treat platform users like customers, not tenants.
04How do you run reliability and incidents in practice?
SLOs and error budgets on services that matter; structured incident response with roles, comms and post-mortems; chaos and load testing where the workload warrants it; on-call rotations that are humane and observable. Observability is designed for the questions on-call actually asks. The point is not zero incidents, it's a system that learns from every incident and gets steadily better.
05How do you approach cloud cost / FinOps?
As real engineering, measured and attributed. Costs are tagged, allocated to teams and workloads, and made visible in dashboards teams actually look at. Right-sizing, autoscaling, storage tiering, savings plans and workload placement are tuned against numbers, not instincts. The output is a cost curve that's understood, negotiable and defensible to finance, instead of an invoice with a surprise every quarter.
06How do you handle security, compliance and evidence?
Zero-trust identity, network and workload security are baked into the landing zone from day one. Controls are aligned to CIS, NIST, ISO 27001, SOC 2 and sector-specific regimes; evidence, configuration, policies, audit logs, IAM inventories, is generated as an engineering artefact alongside delivery. Audits become a report rather than a project because the evidence trail already exists.
Let's discuss your cloud programme.
Share a brief overview of your workloads, current estate and the outcomes you're after, we'll arrange an introductory conversation with the relevant practice leadership.