Ship Faster. Break Less. Scale Intelligently.
What We Do
Six core capabilities. Each solving real problems for engineering teams at scale.
The Problem
Your engineering teams are bottlenecked by infrastructure requests, inconsistent pipelines, and tribal knowledge.
Who It's For
Engineering orgs with 50+ developers struggling to scale delivery without scaling headcount.
What We Deliver
- CI/CD standardization across 100+ microservices
- GitOps with ArgoCD / Flux
- Internal developer platforms (IDP)
- Golden path templates
DevOps & Platform Engineering
Expected Outcomes
- Self-service infrastructure provisioning
- 10x faster onboarding for new services
- Standardized CI/CD across all teams
How We Help
Concrete examples from real engagements. Not hypotheticals—actual problems we've solved.
DevOps & Platform Engineering
CI/CD Standardization
We've unified pipelines across 100+ microservices for a travel-tech platform—reducing build times from 45 minutes to 8 minutes and eliminating "works on my machine" failures.
GitOps Implementation
ArgoCD and Flux deployments with proper RBAC, drift detection, and rollback automation. No more kubectl apply in production.
Internal Developer Platforms
Backstage-based portals with golden path templates. Developers scaffold new services in minutes with security, observability, and CI/CD pre-configured.
Platform Team Bootstrap
We've taken organizations from "the DevOps guy" to fully staffed platform teams with clear product ownership and self-service capabilities.
Cloud & Kubernetes
Production Cluster Design
AKS, EKS, GKE—we've built production clusters handling 50K+ RPS with proper node pools, autoscaling, and resource quotas.
Ingress & Service Mesh
From NGINX to Gateway API to Istio—we select and implement the right ingress strategy based on your actual traffic patterns.
Multi-Region DR
Active-active and active-passive architectures with automated failover. We've executed live DR tests for financial institutions with zero customer impact.
Zero-Downtime Migrations
We've migrated monoliths to microservices, on-prem to cloud, and cloud-to-cloud without a single maintenance window.
AI & Automation
AI DevOps Copilots
Custom LLM agents that answer infrastructure questions, generate Terraform, and explain production incidents using your actual runbooks.
Incident Root-Cause Analysis
LLM-powered analysis of logs, metrics, and traces that surfaces probable causes in minutes—not hours of war-room debugging.
AI-Powered Test Generation
Automated generation of integration tests, edge cases, and load test scenarios based on production traffic patterns.
Intelligent Release Validation
ML models trained on your deployment history that predict release risk and recommend rollback before customers notice.
Case Studies
Real results from real engagements. Every metric is from production—not projections.
Global Airline — Platform Engineering at Scale
A major airline operating 200+ microservices across booking, loyalty, and operations. 400 engineers across 12 countries. Deploying to production 3x per week with frequent rollbacks.
The Problem
- •Inconsistent CI/CD pipelines across teams
- •4-hour average deployment time
- •30% of deployments required rollback
- •New service onboarding took 6 weeks
Our Approach
- •Audited existing pipelines and identified 47 unique CI/CD patterns
- •Designed golden path templates covering 90% of use cases
- •Implemented ArgoCD-based GitOps with automated canary deployments
- •Built Backstage-based IDP with self-service scaffolding
Technologies Used
Results
Deployment frequency
Deployment time
Rollback rate
New service onboarding
“KubeMatrix transformed how we think about platform engineering. Our developers now ship features, not fight infrastructure.”
VP of Engineering
Global Airline
Products & Accelerators
Internal tools we've built and refined across dozens of consulting engagements. Now available to accelerate your projects.
KubeMatrix DevOps AI Assist
Your AI-powered infrastructure copilot
An LLM-powered copilot deployable in your environment (Azure OpenAI, Ollama, or private cloud). Answers infrastructure questions, generates IaC, and explains incidents using your documentation.
- Context-aware infrastructure Q&A
- Terraform and Helm generation with guardrails
- Incident explanation using your runbooks
- Deploys in your environment—no data leaves your network
“Average 40% reduction in L1 ticket volume across 15 enterprise deployments”
KubeMatrix Cost Intelligence
Real-time Kubernetes cost visibility
Real-time Kubernetes cost attribution dashboard with anomaly detection, waste identification, and optimization recommendations. Integrates with Kubecost, CloudHealth, and native cloud billing.
- Team and service-level cost attribution
- Anomaly detection and alerting
- Waste identification and recommendations
- Multi-cloud support
“Deployed at organizations with $10M+ annual cloud spend. Typical ROI: 10x in year one”
KubeMatrix Release Gates
Intelligent release quality validation
Automated release quality validation combining test results, security scans, performance benchmarks, and ML-based risk prediction. Integrates with GitHub, GitLab, and Azure DevOps.
- Unified quality gate across all signals
- ML-based release risk prediction
- Automated rollback recommendations
- CI/CD native integration
“Reduced production incidents by 65% at a fintech client within 90 days”
KubeMatrix Observability Layer
Production-ready observability in hours
Pre-configured observability stack (Prometheus, Grafana, OpenTelemetry, Loki) with opinionated dashboards, alerting rules, and SLO tracking. Deploys via Helm in hours, not weeks.
- Opinionated dashboards for common patterns
- SLO tracking and error budget alerts
- Distributed tracing with OpenTelemetry
- Log aggregation with Loki
“Standard deployment for all KubeMatrix consulting engagements. Battle-tested across 100+ clusters”
Why KubeMatrix
We're not another consulting firm with generic platitudes. Here's what actually makes us different.
DevOps Maturity-Driven
We don't just implement tools. We assess where you are, define where you need to be, and build a realistic path to get there. Every engagement starts with understanding your actual constraints—not selling you our favorite stack.
AI-First, Reliability-Focused
We've been deploying AI in production since before the ChatGPT hype. We know what works (RAG with proper guardrails) and what doesn't (throwing GPT-4 at every problem). AI should reduce toil, not create new failure modes.
Opinionated Architecture
We have strong opinions formed from operating systems at scale. We'll tell you when your architecture won't work—and show you what will. We're not here to validate bad decisions.
Not Tool Sellers, Problem Solvers
We're not reselling Datadog or pushing Kubernetes because we're certified. We select tools based on your constraints: team size, budget, compliance requirements, and existing investments.
We've Operated at Scale—and Seen Failures
Our team has been on-call for systems handling millions of requests per second. We've debugged 3 AM outages, led incident responses, and written the postmortems. We build systems assuming they will fail.
What We're Not
Tool vendors disguised as consultants
Slide deck architects who don't ship
AI hype merchants chasing trends
Engagement Models
Flexible engagement options designed to match your needs—from quick assessments to embedded teams.
Architecture Review
A deep-dive into your current architecture, pipelines, and operations. We identify risks, inefficiencies, and quick wins. Ideal starting point for organizations unsure where to begin.
Ideal for: Organizations wanting expert validation of their current approach
Fixed-Scope Delivery
Well-defined projects with clear outcomes: "Implement GitOps," "Build internal developer platform," "Deploy LLM infrastructure." Fixed price, fixed timeline, production handoff.
Ideal for: Teams with clear requirements and defined outcomes
Retainer Model
Fractional platform engineering support. We attend your architecture reviews, answer Slack questions, review PRs, and help with production incidents. Ideal for teams that need expertise without full-time headcount.
Ideal for: Scaling teams needing ongoing expert guidance
Embedded Platform Team
We embed engineers with your team to build platform capabilities while training your staff. Goal: self-sufficiency. We work ourselves out of a job.
Ideal for: Organizations building internal platform teams
AI PoC → Production
We build a working AI prototype against your actual data and systems—not a demo on sample data. If it works, we provide a production roadmap. If it doesn't, we tell you honestly.
Ideal for: Teams ready to move AI from slides to production
Not sure which engagement is right for you?
Let's Discuss Your NeedsTech Stack & Expertise
Deep expertise across the modern cloud-native stack. We don't just know these tools—we've operated them at scale.
Container Orchestration
Infrastructure as Code
Cloud Platforms
CI/CD & GitOps
AI & ML
Observability
Security
Service Mesh & Networking
Certified Across All Major Platforms
Ready to Talk Architecture?
Skip the sales call. Talk directly to an engineer who's built systems like yours.
What Happens Next
Discovery Call
30 minutes to understand your challenges
Architecture Review
We dig into your systems (complimentary)
Recommendations
Written assessment with prioritized actions
Engagement Proposal
If there's a fit, we scope the work together