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Engineered for cloud reliability, zero-trust security, and high-velocity automated delivery pipelines. Currently building: AgentOps & AI-native infrastructure workflows |
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Google Cloud Certified Professional DevOps Engineer building infrastructure that ships fast, stays secure, and scales without breaking.
I engineer across DevOps, cloud security, platform infrastructure, and ML/AI systems — designing automated delivery pipelines, enforcing zero-trust security at every layer, orchestrating multi-cluster Kubernetes environments, and building end-to-end observability into production workloads. Currently exploring AgentOps and AI-native infrastructure patterns.
My work is driven by business outcomes: reducing deployment risk, accelerating developer velocity, hardening security posture, and eliminating operational toil across multi-cloud environments.
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Multi-Cloud Internal Developer Platform 3-cluster Kubernetes topology with Backstage, Crossplane, ArgoCD, Falco, OPA, Kyverno, and Cilium in a Shared VPC environment.
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Enterprise Cloud Network & Zero-Trust Architecture Hub-and-spoke enterprise networking with strict VPC service controls, Cloud Armor WAF, and zero-trust perimeter policy.
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Production-grade service mesh on GKE with mTLS, advanced traffic routing, GitOps delivery via FluxCD, and Kiali visual telemetry.
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Automated Observability — ELK & OpenTelemetry Unified distributed observability pipeline on GKE — aggregates logs, metrics, and traces with continuous DevSecOps monitoring.
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Chaos Engineering & Observability Platform Fault injection framework using Chaos Mesh to simulate network partitions, pod failures, and latency spikes under Istio mesh observability.
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Cloud-Native Microservices on GKE Production-grade containerized microservices with Kubernetes-native autoscaling, ingress control, and IaC delivery pipelines.
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Infrastructure as Code with Terraform on GCP Modular, environment-aware GCP infrastructure automation with multi-environment deployments and automated CI/CD validation.
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Vendor-agnostic MLOps system spanning GCP, AWS, and Azure. Automates model training, artifact tracking, and cross-cloud deployment.
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GCP Multi-Tier Application Infrastructure Highly available multi-tier architecture on GCP with HTTP load balancing, Cloud Armor security policies, and Cloud SQL backends.
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Scalable ML Inference Platform Asynchronous ML inference engine with Celery task queues, Redis broker, PostgreSQL analytics, and Prometheus observability.
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Automated MLOps Training & Deployment on GCP End-to-end Vertex AI pipeline with continuous training triggers, Cloud Build CI, and progressive delivery via Cloud Deploy to GKE endpoints.
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Go CI/CD Pipeline — GitHub Actions & Cloud Build High-throughput build-test-deploy automation for Go services, delivering containerized binaries to Google Cloud via dual CI.
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DevOps Engineer | Cloud Security Engineer | Solutions / Sales Engineer | Cloud Infrastructure
If you're building something that needs to be reliable, secure, and scalable — let's talk.Connect on LinkedIn | ayushgharat234@gmail.com