The Problem Most Teams Face
Engineering teams today are moving faster than ever — but they're also drowning in complexity. Cloud bills nobody can explain. Pipelines that break on Friday afternoon. Alerts at 2am that turn out to be noise. Kubernetes clusters nobody fully understands.
I've spent 15+ years inside this problem. Here's what I actually do about it.
AI-Powered Operations
Traditional monitoring generates thousands of alerts. Most of them are noise. AIOps changes that by applying machine learning to your telemetry — correlating related events, suppressing duplicates, and surfacing the signal that actually matters.
Tools I work with:
- Dynatrace — AI-driven full-stack observability, automatic anomaly detection, and root cause analysis in seconds
- Datadog — unified metrics, traces, and logs with ML-based anomaly detection and watchdog alerts
- Grafana + Prometheus — open-source observability stack with alerting rules, SLO tracking, and Loki for logs
- OpenTelemetry — vendor-neutral instrumentation for distributed tracing across microservices
- PagerDuty / OpsGenie — intelligent alert routing with escalation policies and on-call scheduling
What this gives your team:
- 60–70% reduction in alert noise
- Predictive capacity warnings before incidents happen
- Automated root cause suggestions that cut MTTR by 40%
DevOps Transformation
DevOps isn't a tool — it's a practice. I help teams build the pipelines, the processes, and the cultural habits that make continuous delivery actually work.
Tools I work with:
- GitHub Actions / GitLab CI — fast, flexible CI/CD pipelines with matrix builds and environment gates
- ArgoCD / Flux — GitOps for Kubernetes, declarative delivery with automatic drift detection
- Terraform / Pulumi — infrastructure as code, version-controlled, peer-reviewed, reproducible
- Vault / AWS Secrets Manager — secrets management that keeps credentials out of your codebase
- Snyk / Trivy / Semgrep — security scanning baked into every pull request, not bolted on at the end
What this gives your team:
- Deployment frequency up 10–50x
- Lead time for changes from weeks to hours
- Engineers who own their pipeline, not just their code
Cloud Platform Engineering
Platform engineering gives your developers a self-service path to production — without them needing to become infrastructure experts.
Tools I work with:
- AWS (EKS, RDS, S3, Lambda, CloudFront) — designing Well-Architected environments that scale and stay within budget
- Kubernetes (EKS / GKE / AKS) — multi-tenant clusters with RBAC, Karpenter autoscaling, and service mesh
- Backstage — internal developer portal for service catalogues, golden path templates, and self-service environments
- Crossplane — Kubernetes-native cloud infrastructure provisioning
- Helm / Kustomize — parameterised Kubernetes deployments across dev, staging, and production
What this gives your team:
- New environments provisioned in 15 minutes, not 3 days
- Platform team becomes a force multiplier, not a bottleneck
- 30–40% cluster cost reduction with proper autoscaling
Software Consultation
Sometimes you don't need someone to build — you need someone to tell you what to build, what to stop building, and what's quietly on fire.
I offer architecture reviews, technology stack assessments, and honest second opinions for teams at all stages — early-stage startups picking their first cloud provider to enterprises untangling years of technical debt.
Recent Work
- Designed and deployed a multi-region AWS platform for a FinTech company handling 50M+ transactions/month
- Reduced a SaaS company's AWS bill by 38% through right-sizing and Reserved Instance strategy
- Implemented AIOps with Dynatrace for a 200-person engineering org, reducing incident resolution time from 4 hours to 45 minutes
- Built an Internal Developer Platform on Backstage for a 300+ engineer organisation
Let's Talk
If your team is dealing with platform complexity, rising cloud costs, alert fatigue, or slow delivery — I'd like to help.
Every engagement starts with a conversation. No sales deck, no long proposal. Just an honest discussion about what's broken and what's possible.