Why Companies in Noida Choose Uncodemy for DevOps

# Rate a team's current level (1-5) against the target for each skill.
skills = {
    "Linux and bash":       (3, 4),
    "Git workflows":        (3, 4),
    "CI/CD pipelines":      (2, 4),
    "Docker":               (2, 4),
    "Kubernetes":           (1, 3),
    "Terraform":            (1, 3),
    "Monitoring":           (2, 3),
}
# Example values only; fill in your own team's ratings.

for skill, (now, target) in sorted(skills.items(), key=lambda s: s[1][0] - s[1][1]):
    gap = target - now
    if gap > 0:
        print(f"{skill:20} gap {gap}")

Team training goals (example template):

1. Every developer can create a CI pipeline that tests and builds.
2. The team containerises its main service with Docker.
3. Two engineers can deploy and debug on Kubernetes.
4. Infrastructure for one environment is managed with Terraform.
5. Dashboards and alerts exist for the main service.

Measure: completed labs, project review and use at work.

# .github/workflows/ci.yml: the kind of pipeline learners build
name: ci
on: [push, pull_request]
jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with: { python-version: "3.12" }
      - run: pip install -r requirements.txt pytest
      - run: pytest -q
      - run: docker build -t app:${{ github.sha }} .

#!/usr/bin/env bash
# Local Kubernetes practice with kind
set -euo pipefail
kind create cluster --name lab
kubectl create deployment web --image=nginx:1.27 --replicas=2
kubectl expose deployment web --port=80
kubectl rollout status deployment/web
kubectl get pods -o wide
kubectl set image deployment/web nginx=nginx:1.27-alpine
kubectl rollout status deployment/web
kubectl rollout undo deployment/web   # practise rollback
kind delete cluster --name lab

weights = {"labs": 0.3, "syllabus": 0.2, "projects": 0.2,
           "trainer demo": 0.15, "flexibility": 0.1, "terms clarity": 0.05}

def weighted(scores):
    return sum(weights[k] * scores[k] for k in weights)

# Placeholder scores (1-5) to fill in after demos
providers = {
    "Provider A": {"labs": 4, "syllabus": 4, "projects": 4, "trainer demo": 4, "flexibility": 3, "terms clarity": 5},
    "Provider B": {"labs": 3, "syllabus": 4, "projects": 2, "trainer demo": 3, "flexibility": 4, "terms clarity": 3},
}
for name, s in providers.items():
    print(f"{name}: {weighted(s):.2f} / 5")

1. Can you share the current DevOps syllabus in writing?
2. What share of training time is hands-on labs?
3. Which tools and cloud are used in labs?
4. What capstone project will learners complete?
5. How is progress tracked and reported?
6. Can training use examples close to our stack?
7. What are the current fees and terms for our batch size?

Company / team: ______________
Team size: ____   Current tools: ______________
Skills gap (top 3): ______________
Preferred mode: classroom / online / mixed
Preferred timing: weekday / weekend
Target outcome: ______________
How we will measure success: labs completed, project reviewed, used at work

Criteria            Uncodemy     Provider 2   Provider 3
Lab share           ______       ______       ______
Syllabus match      ______       ______       ______
Capstone project    ______       ______       ______
Trainer demo        ______       ______       ______
Progress reports    ______       ______       ______
Batch flexibility   ______       ______       ______
Fees in writing     ______       ______       ______

Review 4-6 weeks after training:

- Pipelines created or improved: ____
- Services containerised: ____
- Kubernetes or IaC used in a real task: yes / no
- Remaining gaps: ______________
- Follow-up learning needed: ______________