Description
I run Cloud Operations across 8+ AWS accounts and I'm trying to deepen into real DevOps/SRE engineering rather than stay in monitoring-and-tickets land.
Looking for an honest technical gut-check on whether my day-to-day and my side projects are pointed at the right skills, or whether I'm building shallow things that look good on paper but don't hold up.
What the day job actually involves:
CloudWatch + EventBridge/SNS alerting across 8+ client accounts, SLA-based incident triage and root-cause isolation
Python (Boto3) and Bash automation for recurring housekeeping and health checks
SSM Patch Manager patching across \~15–20 Linux/Windows servers, plus in-place Windows Server upgrades
IAM least-privilege, KMS encryption, security groups, Site-to-Site VPN setup
AMI lifecycle management and a cross-region migration (AMI replication + post-migration validation)
Side projects (all Terraform + GitHub Actions):
An AIOps incident-diagnosis agent on AWS Bedrock — reads CloudWatch alarms, runs RAG over runbooks, returns a ranked remediation plan. Read-only, human approval before anything executes. Event-driven stack (Step Functions, Lambda, Bedrock KBs, Guardrails).
A CI/CD pipeline to ECS Fargate — GitHub Actions tests/builds/scans/pushes a Spring Boot API to ECR, deploys behind an ALB. Provisioned VPC + endpoints with Terraform, debugged endpoint/S3-gateway/ALB health-check timing to get zero-downtime deploys.
A self-healing EKS platform — multi-replica Deployments, Prometheus/Grafana, HPA scaling on CPU with automatic pod recovery.
The questions I actually want answered:
Depth vs breadth — is this a coherent skill progression, or three unrelated demos? Would you rather see one of these taken much deeper (real load, chaos testing, actual SLOs) than three at surface level?
The AIOps/Bedrock project — does a GenAI ops agent read as genuinely useful, or as hype-chasing that experienced engineers roll their eyes at?
What's missing — if you were leveling someone fr
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