Cloud & DevOps

Cloud, DevOps & Platform Engineering

Cloud-native architecture, DevOps automation, platform engineering, and reliability practices that enable teams to ship faster, operate safely, and scale predictably.

What We Deliver

Ship Faster. Operate Safely. Scale Predictably.

Clavon delivers cloud-native architecture, DevOps automation, platform engineering, and reliability practices — without sacrificing security, compliance, or cost control.

This capability covers the full lifecycle: environment design, CI/CD, Infrastructure as Code, observability, security hardening, backup/DR, SRE practices, and FinOps-driven optimisation.

Delivered as build engagements, embedded platform support, or post-go-live operations (AMS).

Cloud and DevOps infrastructure
Who We Work With

Industry Context & Use-Case Landscape

Startups & Scale-Ups

Typical Realities

  • "Deployments" are manual, risky, and person-dependent
  • Environments drift (DEV ≠ PROD), causing surprises
  • Cost grows invisibly; outages appear at the worst time
  • No observability, only guesswork during incidents

What Matters

  • Minimal, scalable landing zone + predictable deployment pipeline
  • Fast iteration with guardrails (automated checks, rollback)
  • Observability from day one (logs, metrics, traces)
  • Cost-awareness before scale exposes inefficiencies

Enterprises

Typical Realities

  • Multiple teams share platforms and integrations
  • Release governance is heavy but still fails to prevent incidents
  • Security and audit requirements are non-negotiable
  • Complex hybrid realities (legacy + cloud + vendor systems)

What Matters

  • Standardised platform patterns and golden paths
  • Policy-as-code and traceable changes (IaC + approvals)
  • Reliable environments, clear ownership, operational readiness
  • Platform engineering to reduce friction and cognitive load

Regulated & High-Assurance Environments

Health, Pharma, Finance, Public Sector

Typical Realities

  • Strong expectations for change control, traceability, and access governance
  • Data protection requirements affect environments and logs
  • Validation/audit readiness may extend into infrastructure and release processes

What Matters

  • Segregation of environments and controlled access
  • Audit-grade change traceability (who changed what, when, why)
  • Evidence of monitoring, backups, DR tests, and security posture
  • Operational SOPs aligned with compliance expectations
How We Engage

Typical Engagement Scenarios

01

Cloud Foundation / Landing Zone Setup

Trigger

New product, cloud migration, or need for standardisation

Scope

Accounts/subscriptions, network, IAM, logging baseline, environment structure

Success Criteria

Secure, scalable baseline that teams can use repeatedly

02

CI/CD & Release Automation (Build or Rescue)

Trigger

Slow releases, manual deployments, frequent rollbacks

Scope

Build pipelines, test gates, deployment automation, approvals, rollback strategy

Success Criteria

Predictable deployments with measurable reductions in cycle time and failure rate

03

Platform Engineering / Internal Developer Platform

Trigger

Teams spend too much time on infra and inconsistent tooling

Scope

Golden paths, templates, self-service environments, standard observability, policy guardrails

Success Criteria

Faster delivery with less operational burden on product squads

04

Observability & Reliability Hardening (SRE Uplift)

Trigger

Incidents are frequent and diagnosis is slow

Scope

Monitoring/logging/tracing, alerting hygiene, SLOs/SLIs, incident playbooks

Success Criteria

Faster detection and recovery (MTTR reduction), improved uptime and confidence

05

Security Hardening + Backup/DR Readiness

Trigger

Audit pressure, security concerns, business continuity requirements

Scope

Hardening controls, secret management, vulnerability baselines, backup policies, DR testing

Success Criteria

Reduced risk exposure and verified recovery capability (RPO/RTO alignment)

06

FinOps / Cloud Cost Optimisation

Trigger

Cloud bills grow without clear drivers

Scope

Cost visibility, tagging, rightsizing, scheduling, storage lifecycle, architecture review

Success Criteria

Lower spend with maintained performance and reliability

How We Work

Delivery & Operating Model

Engagement Models

  • Foundation Build (landing zones + baseline controls)
  • Delivery Enablement (CI/CD + IaC + release governance)
  • Reliability Program (observability + SRE practices + incident readiness)
  • Platform Engineering (templates, golden paths, IDP patterns)
  • Managed Services (AMS) — post-go-live ops, continuous improvement, SLA-based support

Typical Team Composition

Cloud / Platform Architect
DevOps / Platform Engineer(s)
SRE (as needed)
Security Engineer (as needed)
QA / Test Automation support for pipeline gates (as needed)
Delivery Lead / PM for governance and stakeholder alignment

Governance & Cadence

  • Baseline assessment → target state blueprint → phased rollout
  • Sprint-based implementation with measurable operational KPIs
  • Release readiness checkpoints and operational handover gates
  • Post-incident reviews feeding continuous improvement
Reference Models

Reference Architecture

Three conceptual models that underpin how we design cloud and DevOps programmes.

Diagram A — Cloud Delivery Lifecycle

Goal: Show Cloud/DevOps as a controlled system, not "deploy scripts".

PlanCodeBuildTestDeployMonitorAdaptcontinuous feedback loopDelivery Lifecycle detail

Diagram B — Platform Engineering "Golden Path"

Goal: Show how teams self-serve safely.

DEVELOPER TEAMSTeam AlphaTeam BetaTeam GammaTeam DeltaInternal Developer Portal (IDP)Self-service · Approved patterns · Policy guardrails · IaC modulesDevSandboxed · fast iterationStagingValidated · matches prodProductionGated · change-controlledALL ENVIRONMENTS ON APPROVED INFRASTRUCTURE PATTERNSPlatform Engineering detail

Diagram C — Reliability Model (SRE View)

Goal: Make reliability measurable.

SLIs — Service Level IndicatorsResponse time · Error rate · Availability · Request throughputSLOs — Service Level Objectives99.9% uptime · p95 < 200ms · Error rate < 0.1% per serviceError BudgetRemaining 0.1% = 43.8 min/month — shared between incidents and releasesAlert Rules & Burn Rate MonitoringPage when budget burn rate exceeds threshold — protect the SLOSRE & Reliability detail
Our Approach

Tooling Philosophy

Automate the path to production, but never automate risk.

Selection Principles

  • Prefer repeatability over heroics
  • Prefer policy and guardrails over manual policing
  • Prefer observability-driven operations over assumptions
  • Prefer least privilege and secure defaults
  • Prefer simpler architectures until complexity is proven necessary

Typical Tooling (Illustrative, Vendor-Neutral)

Cloud

AWS / Azure / GCP (selected per client constraints)

CI/CD

GitHub Actions / GitLab CI (pipeline-as-code)

Containers & Orchestration

Docker, Kubernetes (when justified)

IaC

Terraform / Ansible for repeatable infrastructure

Secrets

Managed secrets vaults and rotation policies

Observability

Metrics + logs + traces with alert hygiene

Security

Baseline scanning + dependency hygiene + hardened configs

Risk Awareness

Risks & How We Mitigate Them

"DevOps" becomes a pile of scripts with no governance

Symptoms

Fragile deployments, hidden tribal knowledge

Mitigation

  • Pipeline-as-code, standard templates
  • Documented runbooks, shared ownership

Environment drift (DEV/STAGE/PROD mismatch)

Symptoms

Works in staging, fails in production

Mitigation

  • IaC, environment parity patterns
  • Configuration discipline, immutable artifacts

Over-engineering (Kubernetes everywhere, complexity without benefit)

Symptoms

Slower delivery, higher ops cost, skill bottlenecks

Mitigation

  • Architecture justification framework
  • Staged maturity model, "simplicity-first" defaults

Observability noise (alerts ignored)

Symptoms

Alert fatigue, late incident response

Mitigation

  • SLO-based alerting, severity classification
  • Alert tuning, runbook-driven response

Security gaps in pipelines and environments

Symptoms

Leaked secrets, weak access control, audit exposure

Mitigation

  • Least privilege IAM, secrets management
  • Policy-as-code, scanning gates, access reviews

Backup/DR exists on paper only

Symptoms

Recovery fails when needed

Mitigation

  • Tested backups, DR drills
  • Documented RPO/RTO, evidence logs, continuous verification

Cloud cost grows without accountability

Symptoms

Surprise bills, low ROI

Mitigation

  • Tagging standards, cost dashboards
  • Rightsizing, scheduling, lifecycle policies, FinOps cadence
Regulated Environments

Compliance Considerations

Where required, Clavon designs cloud and DevOps practices with compliance awareness, including:

  • Traceable change management (approvals, release notes, versioning, audit logs)
  • Access governance (RBAC, MFA, privileged access controls)
  • Data protection (encryption at rest/in transit, secure logging, retention rules)
  • Operational controls (incident response, monitoring evidence, backup/DR evidence)
  • Environment segregation (DEV/STAGE/PROD boundaries and permissions)

We do not provide legal certification; we build operational systems that are aligned with audit expectations and are defensible with evidence.

What You Can Expect

Example Outcomes

Deployment frequency increased without increased incident rates

MTTR reduced through clear observability and runbooks

Improved uptime and performance stability through SRE practices

Reduced cloud spend via rightsizing and FinOps governance

Verified backup/DR capability aligned to business continuity needs

Faster onboarding of new engineers through golden paths and platform templates

What We Hand Over

Artefacts & Deliverables

Architecture & Standards

  • Cloud target architecture and environment model
  • Landing zone blueprint (identity, network, logging baseline)
  • Platform patterns and reusable templates

Automation & Pipelines

  • CI/CD pipelines (as code) with quality/security gates
  • IaC modules (repeatable, versioned)
  • Deployment strategies (blue/green, canary, rollback patterns where appropriate)

Reliability & Operations

  • Observability dashboards and alerting rules
  • SLO/SLI definitions and error budget model
  • Runbooks, incident playbooks, PIR templates
  • Backup/DR policy + test evidence reports

Cost & Governance

  • Tagging standards and cost dashboards
  • FinOps optimisation backlog and cadence
  • Operational readiness checklist for go-live
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Ready to Ship Faster and Operate Safely?

If your releases are slow, your deployments are risky, or your platform is difficult to operate at scale, let's talk.