What is AWS?
Amazon Web Services (AWS), launched in 2006, is the world’s most comprehensive and widely adopted cloud platform.
It offers more than 245 fully featured services across global data centers, providing scalable, secure, and innovative cloud solutions.
AWS powers millions of companies worldwide — from startups to enterprises — enabling them to innovate faster and grow sustainably.
Core AWS Services (as of 2026)
| Category | Services | Description |
|---|---|---|
| Compute | EC2, Lambda, Elastic Beanstalk | Virtual servers and serverless applications |
| Storage | S3, Glacier, EBS | Scalable and reliable data storage |
| Databases | RDS, DynamoDB, Aurora | Fully managed SQL and NoSQL databases |
| Networking | VPC, Route 53, CloudFront | Fast, secure, and global networking |
| AI & ML | SageMaker, Bedrock, Rekognition | AI model development and deployment |
| Security | IAM, GuardDuty, WAF | Encryption, compliance, and threat detection |
| Data Analytics | Redshift, Athena, QuickSight | Scalable analytics and BI |
| Developer Tools | CodeBuild, Cloud9 | CI/CD pipelines and DevOps tools |
For an in-depth understanding, check Architecting on AWS.
AWS vs Competitors
| Competitor | Strength | AWS Comparison |
|---|---|---|
| Microsoft Azure | Microsoft integration | Strong but less global |
| Google Cloud | AI services | Excellent AI tools, smaller service range |
| IBM Cloud | Data security | Less agile in innovation |
| Alibaba Cloud | Asia coverage | Limited international presence |
AWS continues to dominate through scale, reliability, and constant innovation.
Benefits of AWS for Businesses
Reduced operational costs
Scalability and flexibility
Strong security and compliance
High availability
Sustainability with renewable energy
AWS also drives growth in Data Engineering
and Cloud Computing.
AWS and Artificial Intelligence
In 2026, AWS leads AI innovation.
Using Amazon SageMaker, companies can build and train machine learning models without deep AI expertise.
AWS Bedrock provides access to foundation models similar to OpenAI’s GPT or Google’s Gemini.
Recommended courses:
AWS Career Paths
| Role | Description | Course |
|---|---|---|
| AWS Cloud Architect | Designs scalable cloud infrastructure | Architecting on AWS |
| AWS Developer / DevOps Engineer | Builds and automates CI/CD pipelines | Developing on AWS |
| AWS Data Scientist | Leverages data analytics and ML | Data Analytics on AWS |
| AI Specialist | Develops intelligent solutions | Machine Learning Pipelines on AWS |
| Security Engineer | Protects cloud infrastructure | AWS Security Essentials |
AWS Certifications: Why They Matter and How to Get One
AWS certifications are globally recognized credentials that validate your technical expertise in cloud computing.
They demonstrate your ability to design, implement, and manage AWS-based systems.
Certification Categories:
Foundational: Cloud Practitioner
Associate: Solutions Architect, Developer, SysOps Administrator
Professional: Solutions Architect, DevOps Engineer
Specialty: Machine Learning, Security, Data Analytics, Networking
How to Get Certified:
Take a course from Bilginc.com (e.g. Architecting on AWS)
Practice with AWS Free Tier
Register via Pearson VUE or online
Earn a certification valid for three years
AWS is not just a technology platform—it’s the foundation of digital transformation in 2026.
From AI to data science, from DevOps to security, AWS skills will future-proof your career.