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सर्व कौशल्ये

Cloud Platforms (AWS / GCP / Azure)

⬢ श्रेणी 1तांत्रिक
+$15–30k
पगारावरील परिणाम
8 महिने
शिकण्यास लागणारा वेळ
मध्यम
काठिण्य
8
करिअर्स
एका दृष्टिक्षेपात

Cloud platforms (AWS, Google Cloud, Azure) are essential for modern engineers: deploy scalable apps, manage infrastructure, earn $100k-$200k+ depending on expertise. AWS dominates (most jobs), GCP excels at ML, Azure for enterprise. Career: Practitioner (basic services, EC2/S3, $90-120k) → Architect (multi-tier apps, IaC, $140-180k) → Expert (multi-region, disaster recovery, $180-250k). Pricing: pay-per-usage (AWS starts free).

Cloud Platforms (AWS / GCP / Azure) म्हणजे काय

Cloud platforms (AWS, Google Cloud, Azure) are on-demand computing infrastructure accessible globally via the internet: compute (virtual machines, serverless functions), storage (object, block, databases), networking (load balancers, CDNs), and analytics. AWS is the largest provider by market share, GCP excels in ML/data (BigQuery, Vertex AI), and Azure is strong in the enterprise (tight Office 365 integration). In 2026, choosing one cloud is the baseline; multi-cloud architecture (AWS primary, GCP for ML pipelines, Azure for Windows workloads) is emerging at scale. Cloud expertise has compressed 10 years of on-premises sysadmin skills into 6–8 months of learning. A junior cloud engineer deploying EC2 + S3 + RDS commands $105–120k; a solutions architect designing multi-region disaster recovery with Infrastructure as Code commands $150–210k. The skill is democratized (AWS Free Tier, GCP $300 free credit) but depth differentiates, most engineers stay at basics; architects and SREs who master multi-region, FinOps, and chaos engineering earn principal roles.

🔧 साधने आणि परिसंस्था
AWSGCPAzureDigitalOceanCloudflareVercelRenderFly.ioIBM CloudOracle Cloud

💰 प्रदेशानुसार पगार

प्रदेशज्युनियरमध्यमसीनियर
USA$105k$150k$200k
UK£65k£90k£130k
EU€70k€95k€135k
CANADAC$110kC$160kC$210k

⚖ यांच्याशी तुलना करा

Aws LambdaAzure FunctionsKubernetes Docker

❓ FAQ

AWS vs GCP vs Azure, which should I learn first?
AWS has the largest market share, has the richest ecosystem, and Free Tier is generous. Start with AWS if unsure. GCP is best for ML/data pipelines and has simpler UX. Azure wins in enterprise roles. Most senior engineers know all three, master one first, then multi-cloud skills become 2-3 weeks per platform.
How long does it take to go from zero to cloud-ready?
6-9 months: Phase 1 (3-6m) pick one cloud and get certified (SAA-C03 for AWS); Phase 2 (3-6m) master IaC, multi-region, and disaster recovery. Accelerate with hands-on projects (deploy 5+ real apps). Bootcamp grads: 4 months if daily practice.
On-prem vs cloud, isn't cloud more expensive?
Myth. Startup/scale-up: cloud wins (no CapEx, auto-scaling, pay-per-use). Enterprise (1M+ monthly costs): hybrid or on-prem can be cheaper after 2-3 year breakeven. Real answer: cloud = operational cost, on-prem = capital risk. Most startups stay cloud 5-10 years.
Multi-cloud strategy, how many should I know?
Learn 1 deep (AWS, 6-9m), then 1 broad (GCP or Azure, 2-3 weeks per platform to grasp terminology and deployment flow). Hybrid/multi-cloud is 10% of jobs; focus depth first. Senior architects often know 2-3, but depth in 1 > breadth in 3.
Certification worth it? Which one matters most?
AWS Solutions Architect Associate (SAA-C03) = highest ROI: $130-$200 exam, +$15-30k salary boost, most recognized by recruiters. Professional cert (+$20-40k boost) requires 2+ years experience. Azure certs valuable in enterprise. GCP certs less common in job postings but growing.
IaC (Infrastructure as Code), Terraform, CloudFormation, or CDK?
Terraform (multi-cloud, declarative, #1 hiring demand). AWS CloudFormation (native, YAML, couples you to AWS). CDK (TypeScript/Python, reusable constructs, complex orgs). Master Terraform first (40% of IaC jobs), then CDK for AWS-only shops.
How do I avoid massive cloud bills?
Set billing alerts day 1 ($50/month threshold). Delete stopped resources (EC2, RDS). Use Free Tier aggressively (1M Lambda invocations/month, 1TB S3, 750 EC2 hours). Spot/reserved instances for sustained workloads. Monitor per-service cost (Lambda/DynamoDB creep). Most startups spend $200-500/month if disciplined.

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