Building resilient, scalable systems that empower teams
I architect and automate cloud infrastructure at scale. I turn complex deployment challenges into elegant, repeatable processes. My sweet spot is the space where infrastructure meets automation.
Code → Build → Test → Deploy → Monitor → Scale
↓ ↓ ↓ ↓ ↓ ↓
Commit Quality Security GitOps Metrics Reliability
☁️ Cloud Platforms
| Platform | Services |
|---|---|
| AWS | EC2, RDS, S3, Lambda, ECS, VPC, CloudFormation, IAM |
| Azure | VMs, App Service, AKS, Azure DevOps, Container Registry |
| Google Cloud | Compute Engine, GKE, Cloud Functions, Cloud SQL |
📦 Container & Orchestration
| Tool | Expertise |
|---|---|
| Docker | Multi-stage builds, image optimization, registry management |
| Kubernetes | Helm charts, StatefulSets, DaemonSets, network policies |
| Helm | Chart templating, dependency management, releases |
🔧 Infrastructure Automation
| Tool | Usage |
|---|---|
| Terraform | Modular architecture, remote state, CI/CD integration |
| CloudFormation | Stack templates, change sets, nested stacks |
| Ansible | Configuration management, playbook orchestration |
🚀 CI/CD & Automation
| Platform | Implementation |
|---|---|
| GitHub Actions | Workflows, matrix builds, artifacts, environments |
| GitLab CI/CD | Pipelines, stages, manual gates, caching strategies |
| ArgoCD | GitOps principles, application sync, multi-cluster |
| Jenkins | Declarative pipelines, shared libraries, integration |
📊 Monitoring & Observability
| Stack | Purpose |
|---|---|
| Prometheus | Metrics collection, service discovery, alerting rules |
| Grafana | Dashboards, alerting, notification channels, SLOs |
| ELK Stack | Log aggregation, parsing, visualization, analysis |
| Loki | Log storage optimization, label strategies |
💻 Languages & Tools
| Language | Purpose |
|---|---|
| Python | Automation scripts, AWS/Azure SDK tools, utilities |
| Bash | System administration, deployment automation |
| Go | Performance-critical tools, cloud-native projects |
| YAML/HCL | Infrastructure definitions, configuration |
Code Push → GitHub Actions/GitLab CI
→ Automated Testing Suite
→ Security Scanning (SAST/DAST)
→ Terraform Plan & Review
→ ArgoCD Sync to Staging
→ Smoke Tests
→ Blue-Green Deployment
→ Production Live ✅
Designing multi-stage deployment pipelines with automated testing, security scanning, and intelligent rollback strategies. Making deployments fast and safe.
Running production-grade Kubernetes clusters with deep expertise in:
- Networking: Service meshes, ingress controllers, network policies
- Storage: PersistentVolumes, dynamic provisioning, backup strategies
- Security: RBAC, Pod Security Policies, network segmentation
- Resource Management: HPA, VPA, cost optimization
- Observability: Metrics, logs, traces integrated into operations
Writing reusable, testable Terraform modules that:
- ✅ Deploy consistent infrastructure across AWS, Azure, GCP
- ✅ Implement security best practices by default
- ✅ Support multiple environments from single codebase
- ✅ Include automated testing and validation
- ✅ Scale efficiently without manual intervention
Building comprehensive observability ecosystems:
- Prometheus for metrics collection and alerting
- Grafana for beautiful dashboards and SLOs
- ELK Stack for log aggregation and analysis
- Loki for efficient log storage and querying
- Custom metrics and intelligent alerting rules
Current Focus Areas:
- 🎯 Advanced Kubernetes patterns and operators
- 🎯 Service mesh implementations (Istio, Linkerd)
- 🎯 Infrastructure testing and validation frameworks
- 🎯 Cloud cost optimization strategies
- 🎯 GitOps maturity and scaling patterns
Proven Competencies:
- ✅ Docker containerization and optimization
- ✅ Kubernetes fundamentals and advanced patterns
- ✅ Terraform infrastructure coding
- ✅ CI/CD pipeline design and implementation
- ✅ Prometheus and Grafana monitoring setup
- ✅ AWS, Azure, and Google Cloud administration
- ✅ Infrastructure automation with Ansible
- ✅ Python and Bash scripting for DevOps
Completed:
- ✅ Azure Fundamentals
- ✅ AWS Cloud Practitioner
- ✅ Kubernetes Fundamentals
Architected and maintained Kubernetes clusters supporting production workloads. Designed CI/CD pipelines reducing deployment time and human error. Implemented comprehensive monitoring reducing incident detection time significantly.
Created reusable Terraform modules accelerating infrastructure provisioning. Developed CI/CD workflows automating testing, security scanning, and deployments. Implemented GitOps patterns enabling safer infrastructure changes at scale.
Multi-cloud infrastructure design across AWS, Azure, and GCP. Cost optimization strategies through resource right-sizing and automation. Security-hardened cloud environments with proper isolation and access control mechanisms.
Embedded security practices into infrastructure pipelines from ground up. Implemented container scanning and vulnerability management. Built secrets management and rotation strategies across environments.
| Principle | Why It Matters |
|---|---|
| Automate first | Manual processes are error-prone and don't scale. If you're doing it manually twice, automate it |
| Security always | DevSecOps from the start, not as an afterthought. Security decisions are made early |
| Monitor everything | What you can't measure, you can't optimize. Comprehensive visibility prevents surprises |
| Keep it simple | Complex infrastructure that breaks is worse than simple infrastructure that works reliably |
| Document ruthlessly | Good documentation is as valuable as good code. Clear docs prevent knowledge silos |
| Reliability > Velocity | Fast systems that break are worse than slow systems that work. Build for reliability first |
Before implementing, I understand the underlying problem, constraints, and success metrics. A perfect solution to the wrong problem is still wrong.
When things break, I dig deeper than the symptom. Understanding why systems fail prevents the same failure from happening again.
Good infrastructure serves the team. I build systems that make developers more productive, operations more reliable, and deployments more confident.
I'm genuinely interested in:
- 🏗️ Architectural Challenges → How to design systems at scale
- ⚙️ Automation Innovation → Reducing manual toil through clever solutions
- ☸️ Kubernetes Complexity → Best practices, troubleshooting, optimization
- 🚀 DevOps Evolution → Industry trends, tools, and methodologies
- 📊 Observability Patterns → Building visibility into complex systems
- 💡 Infrastructure Challenges → Real problems, creative solutions
- 📧 Email: [email protected]
- 💼 LinkedIn: linkedin.com/in/kaushalacts
- 🐙 GitHub: github.com/kaushalacts
- 🐦 Twitter: @kaushalacts
| Metric | Value |
|---|---|
| Location | Gurugram, Haryana, India 🇮🇳 |
| Experience | 2+ years (DevOps & Cloud Infrastructure) |
| Specialization | Infrastructure Automation, Cloud Native, CI/CD |
| Focus Area | Reliability, Scalability, Automation |
| Learning Style | Hands-on, practical, real-world challenges |
| Vision | Systems that scale gracefully, operate reliably |
- 💡 Passionate about DevOps, Cloud, and Automation
- 📚 Constant learner - reading about infrastructure daily
- 🔧 Love solving real problems with elegant solutions
- 🎯 Goal: Build systems that scale gracefully and serve teams well
- 🚀 Believe infrastructure is the foundation of great products
DevOps is the bridge between infrastructure and business outcomes.
- ✅ Full-time DevOps/Infrastructure roles
- ✅ Challenging technical problems requiring creative solutions
- ✅ Collaboration on open-source infrastructure projects
- ✅ Knowledge sharing and mentoring opportunities
Last Updated: December 2024
Actively building • Continuously learning • Always optimizing