I secure cloud-native pipelines, automate infrastructure at scale, and integrate AI-driven observability — delivering systems that are fast, resilient, and secure by default.
Embedding SAST, DAST, SCA, and secret scanning directly into CI/CD pipelines — catching vulnerabilities before they reach production.
Designing secure, scalable multi-cloud architectures on AWS and GCP with Terraform, Kubernetes, and GitOps-driven delivery.
Applying ML-driven anomaly detection, predictive alerting, and automated remediation to eliminate toil and reduce MTTR.
Building fully automated delivery pipelines from code commit to production — with compliance checks, rollbacks, and zero-touch deployments.
I'm Karthick DK, a DevSecOps & AIOps Engineer with 5+ years of experience building secure, intelligent infrastructure at scale. I specialise in integrating security into every layer of the software delivery lifecycle — from code commit to production deployment — while leveraging AI and ML techniques to build self-healing, proactively monitored systems.
My expertise spans cloud security architecture on AWS & GCP, container orchestration with Kubernetes, infrastructure automation using Terraform & Ansible, and applying AIOps principles — including ML-driven anomaly detection, automated root-cause analysis, and intelligent alerting — to drastically reduce operational overhead and mean time to recovery.
I've designed and maintained CI/CD pipelines that run automated SAST, DAST, container scanning, and compliance checks, enabling engineering teams to ship with confidence. I also write technical articles on Medium and maintain open-source DevOps tooling on GitHub.
I deliver secure, scalable DevSecOps solutions with proven expertise and a results-driven focus across cloud, containers, and automation.
AWS & GCP security architecture, IAM, VPC hardening, cloud-native security controls and compliance.
End-to-end secure delivery pipelines with automated security gates, code scanning, and compliance checks.
Container hardening, runtime security, pod security policies, and service mesh security with Istio.
Declarative, auditable infrastructure with security policies enforced at provisioning time via Checkov and OPA.
Automated vulnerability scanning, secret detection, dependency audits, and OWASP compliance integrated into pipelines.
Full-stack observability with metrics, logs, and distributed tracing for proactive incident detection and zero-downtime operations.
Applying ML models to IT operations — automated anomaly detection, predictive capacity planning, and intelligent incident correlation to reduce MTTR.
Building end-to-end ML lifecycle pipelines — automated training, versioning, deployment, and monitoring of models in production Kubernetes environments.
Live from GitHub — real repositories covering DevSecOps, AIOps, MLOps, and infrastructure automation.
Find my full work history, certifications, recommendations and professional endorsements.
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