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Production infrastructure online

Umesh Raut

DevOps Engineer | Cloud Infrastructure | Kubernetes | Platform Engineering

I build scalable, automated, production-grade infrastructure systems.

99.9% availability target
zero-touch CI/CD releases
Kubernetes scaling playbooks
cost-aware cloud operations

Live DevOps Dashboard

Production telemetry, topology, and events in one cockpit.

The interface now behaves like a cloud operations center: saturation, latency, error budget, rollout state, event streams, pod health, and dependency topology are visible at the same time.

Operating principle: every deployment must be observable, reversible, and capacity-aware before it reaches production.
API p95
38ms
good
latency
Cluster CPU
41%
good
6 nodes
Memory
62%
watch
request/limit
Error rate
0.03%
good
5xx
Deploy freq
7/day
good
automated
MTTR drill
11m
good
rollback
Kubernetes service topologyprod namespace
Route53 + ALB
TLS, WAF, rate limits
Ingress NGINX
blue/green traffic split
API deployment
HPA 4 -> 7 pods
Queue workers
async jobs, retry budget
Redis cache
multi-AZ failover
RDS private
encrypted, snapshots
Prometheus/Grafana
SLO alerts, dashboards
Network activityservice mesh p95
Kubernetes pods
api-gatewayrunning
workerrolling
grafanarunning
prometheusrunning
ingressrunning
redisrunning
Infrastructure event streamlive replay
12:41:03INFOargocdsync completed for portfolio-api rev 7f4c9ac
12:41:11INFOhpaapi deployment scaled from 4 to 7 replicas
12:41:18WARNprometheusmemory request pressure above 60 percent for worker pool
12:41:26INFOjenkinsimage signed and pushed to registry/prod/api:v3.8.1
12:41:39INFOterraformdrift check clean: vpc, iam, eks node group, alarms
12:41:52OKsloavailability window healthy: burn rate 0.18x

Linux Operations Console

A recruiter can inspect the platform from the shell.

The terminal simulates production operator habits: checking services, logs, filesystem pressure, Kubernetes rollout state, Terraform plans, and incident runbooks.

Current context
eks-prod / prod namespace
Useful probes
kubectl top pods, ss -tulpn, journalctl -u kubelet
Runbooks
rollback, scaling, incident response, cost optimization
Release policy
scan, canary, SLO verify, rollback ready
Suggested demo path: run `kubectl get pods`, `kubectl top pods`, `tail -f /var/log/deployments.log`, then `cat /runbooks/rollback.md`.

Immersive Projects

Infrastructure stories with design, rollout, signals, and recovery thinking.

EKS Production Infrastructure

Terraform-driven AWS EKS platform with private networking, autoscaling, IAM boundaries, and observability.

Engineering objectiveCreate a repeatable production Kubernetes base with private subnets, node groups, IAM roles, and platform add-ons.
Deployment lifecycle
plan
policy
provision
bootstrap
observe
VPC
EKS
ALB
HPA
RDS
CloudWatch
Operating signals
node pressureok
pod restartswatch
ingress p95ok
cost driftok
AWSEKSTerraformHelmPrometheus

EKS Production Infrastructure

Terraform-driven AWS EKS platform with private networking, autoscaling, IAM boundaries, and observability.

source
build
scan
deploy
AWSEKSTerraformHelmPrometheus
Designed for high availability, controlled rollouts, and measurable operating cost.

Jenkins CI/CD Automation

Pipeline-as-code system that builds containers, runs security checks, and deploys through gated environments.

source
build
scan
deploy
JenkinsDockerGitBashKubernetes
Reduced manual deployment work and made releases repeatable.

Kubernetes Monitoring Stack

Prometheus, Grafana, alert routing, pod health views, and SLO-inspired dashboards for production workloads.

source
build
scan
deploy
PrometheusGrafanaAlertmanagerLinux
Improved incident detection with clear service-level visibility.

Multi-cloud Deployment Platform

Portable deployment workflow for AWS-style and container-native infrastructure targets.

source
build
scan
deploy
TerraformDockerGitHub ActionsHelm
Created consistent deployment primitives across environments.

AI Infrastructure Deployment

GPU-ready service deployment blueprint with secrets, monitoring, rollout controls, and workload isolation.

source
build
scan
deploy
KubernetesPythonDockerNginx
Packaged AI services for safer, faster production delivery.

Highly Available Microservices

Containerized services with ingress, probes, rolling deploys, metrics, and recovery-oriented operations.

source
build
scan
deploy
KubernetesDockerHelmAWS
Built service architecture around resilience and fast rollback.

3D Skill Galaxy

Core platform skills orbit production reliability.

Hover a node to reveal usage depth, confidence, and real infrastructure context.

Platform Core
Kubernetes 88%
Deployments, services, probes, HPA, ingress
Docker 90%
Image hardening, Compose, registries
AWS 84%
VPC, EC2, IAM, S3, EKS patterns
Terraform 82%
Reusable IaC modules and plans
Jenkins 86%
Pipeline as code and release automation
Linux 89%
Shell, services, logs, networking
GitHub Actions 80%
Reusable workflows and quality gates
Prometheus 78%
Metrics, exporters, alerting rules
Grafana 80%
Dashboards, SLO panels, incidents
ArgoCD 74%
GitOps sync and rollout visibility
Helm 76%
Parameterized Kubernetes releases
Python 73%
Automation scripts and API glue
Bash 86%
Linux automation and diagnostics
Ansible 72%
Configuration automation

Experience Pipeline

From Linux operations to automated delivery.

Hissan Lab Pvt Ltd Pune

9 months internship
1Implemented Linux administration workflows and deployment automation.
2Built CI/CD pipeline foundations for containerized applications.
3Supported monitoring, log review, and infrastructure health checks.
4Practiced cloud implementation patterns with security-aware access control.

Encrypted Transmission

Send the next deployment brief.

Recruiters, SRE leads, and cloud teams can reach Umesh for DevOps, Kubernetes, AWS, Linux, CI/CD, and platform engineering roles.

secure channel established

to: hiring-team@cloud.company

subject: DevOps Engineer - Umesh Raut

signal: Kubernetes, AWS, Terraform, Jenkins, Linux

I design automated infrastructure systems that are observable, repeatable, secure, and ready for production pressure.