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Infrastructure & Reliability
Cloud Architecture, DevOps Automation & Site Reliability
Infrastructure should be boring, reproducible and cheaper next quarter than this one. We codify everything in version control, automate the path from commit to production with safety nets that actually trigger, and instrument systems so you learn about problems from an alert rather than from a customer.
Ecosystem matrix
The stack we build on
Mainstream, well-supported technology chosen so your team can hire for it. We will justify any choice on this list, and we avoid exotic tools that create a dependency on us.
AWS
Google Cloud
Azure
Terraform
Kubernetes
Docker
GitHub Actions
ArgoCD
Prometheus
Grafana
Datadog
Ansible
Pulumi
Deliverable blueprint
99.99% uptime SLA, automated rollback safety nets, immutable cloud infrastructure.
Sub-services deep dive
5 specialist capabilities
Expand any capability for its core scope, architectural blueprint and typical delivery window.
Landing zones, network topology and migration sequencing designed around your compliance, latency and cost constraints β including regional requirements across the Gulf.
Core capabilities
- Landing zone design with account and network segmentation
- Migration wave planning with rollback checkpoints
- Cost architecture: right-sizing, commitments and storage tiering
- Data residency design for GCC and EU regulatory requirements
Architectural blueprint
Assessment and dependency mapping β landing zone provisioning β wave-based migration with validation gates β cost and reliability optimisation.
Delivery timeline
8β20 weeks depending on estate
AWS, Google Cloud, Microsoft Azure
The path from commit to production, automated and safe enough that deploying on a Friday afternoon stops being a joke about recklessness.
Core capabilities
- Build, test and security scanning gates on every pull request
- Progressive delivery: canary, blue-green and feature flags
- Automated rollback triggered by service-level objective breach
- Ephemeral preview environments per branch
Architectural blueprint
Commit β CI gates (test, scan, budget) β artefact registry β GitOps reconciliation β canary rollout with automated SLO-based rollback.
Delivery timeline
4β8 weeks
GitHub Actions, GitLab CI, ArgoCD
Production Kubernetes done properly β or an honest recommendation that managed container services would serve you better at your current scale.
Core capabilities
- Cluster architecture with node pool and workload isolation
- Helm chart authoring and GitOps-driven deployment
- Horizontal, vertical and cluster autoscaling tuned to real traffic
- Service mesh, network policy and pod security standards
Architectural blueprint
Container build pipeline β registry with vulnerability scanning β GitOps reconciliation into cluster β autoscaling with pod disruption budgets.
Delivery timeline
6β12 weeks
EKS, GKE, AKS, Docker, Helm
Every resource defined in version control and reviewed like application code, so environments are reproducible and configuration drift stops being a mystery.
Core capabilities
- Reusable Terraform module library with semantic versioning
- Remote state management with locking and workspace isolation
- Policy-as-code guardrails preventing non-compliant resources
- Automated drift detection with reconciliation reporting
Architectural blueprint
Module registry β environment compositions β plan review in CI with policy checks β gated apply β scheduled drift detection.
Delivery timeline
5β10 weeks
Terraform, Ansible, Pulumi
Follow-the-sun on-call coverage from our global hubs, with observability designed so alerts mean something and runbooks resolve incidents rather than describing them.
Core capabilities
- SLO definition with error budgets that govern release pace
- Metrics, logs and distributed tracing correlated in one place
- Actionable alerting tuned to eliminate pager fatigue
- Blameless post-incident review with tracked remediation
Architectural blueprint
OpenTelemetry instrumentation β unified observability backend β SLO-based alerting β on-call rotation with runbook automation.
Delivery timeline
Ongoing, 6-week onboarding
Prometheus, Grafana, Datadog, PagerDuty
How we engineer
A four-stage accelerated lifecycle
The same sequence on every engagement, whether it runs six weeks or two years. Each stage has an exit condition, so nobody discovers a disagreement in month four.
STAGE 01
Discover
We map the business outcome, constraints and existing estate before proposing anything. Discovery ends with a costed plan, not a sales deck.
1β3 weeks
STAGE 02
Architect
Rendering strategy, data model, integration contracts and the non-functional requirements are settled and documented as decision records.
2β4 weeks
STAGE 03
Execute
Fortnightly increments against a visible backlog, with working software demonstrated every cycle rather than status reported.
6β24 weeks
STAGE 04
Scale
Load testing, observability, runbooks and knowledge transfer β then either you take it in-house or we operate it under an SLA.
Ongoing
Featured case study
European fintech infrastructure
Before → After
We deploy forty times a week now. Two years ago it was a scheduled event with a rollback plan and a prayer.
— VP Platform Engineering, European fintech infrastructure
Deploy lead time — before
9 days
after
22 min
Cloud spend — before
$147K/mo
after
$81K/mo
Change failure rate — before
18%
after
2.1%
Mean time to recovery — before
4.2 hrs
after
11 min
Engagement tiers
Indicative pricing
Published because opaque pricing wastes everyone's time. Figures are in USD and indicative; a fixed quotation follows discovery.
Cloud Assessment
$16,000
Fixed scope Β· 3 weeks
A quantified picture of your cost, reliability and security posture with a costed remediation plan.
- Architecture and security review
- Cost optimisation analysis
- Reliability and SLO gap assessment
- Prioritised remediation roadmap
- Executive findings presentation
Platform Build
$88,000
Most selected Β· 12 weeks
Infrastructure as code, automated delivery and observability implemented end to end.
- Everything in Cloud Assessment
- Full Terraform infrastructure codebase
- CI/CD with progressive delivery
- Observability and SLO alerting
- Runbooks and team enablement
- 60 days hypercare
Managed SRE
Custom
Ongoing retainer
We run it: 24/7 on-call, continuous optimisation and formal reliability targets.
- Everything in Platform Build
- 24/7 follow-the-sun on-call
- 99.99% uptime SLA
- Continuous cost optimisation
- Monthly reliability reporting
- Quarterly disaster recovery drills
Answers
Frequently asked technical questions
Usually substantially. Typical first-pass savings land between 25% and 45% through right-sizing, commitment purchasing, storage lifecycle policies and eliminating orphaned resources. We start with a fixed-fee assessment so the saving is quantified before you commit to the work.
Frequently not. Kubernetes earns its operational overhead when you run many services with genuinely different scaling profiles. Below that, managed container services like Fargate or Cloud Run deliver most of the benefit at a fraction of the complexity, and we will say so.
Follow-the-sun rotation across our Pakistan, UK and North America hubs, so every escalation reaches an engineer who is awake and on shift. Response time commitments are defined per severity in the SLA.
We keep the portable layer portable β containers, Terraform, open telemetry standards β while still using managed services where they genuinely outperform. Total provider neutrality is expensive and rarely worth it; we make the trade-off explicit rather than dogmatic.
That is common. We build the platform, document it thoroughly, then either run it on retainer or train the engineers you hire. Several clients use us as their platform team for two years before insourcing, which is a legitimate strategy.
Frequently paired with