AWS: Everything You Need to Know About the Amazon Cloud Computing Platform

What is AWS?

What does AWS stand for? AWS simply refers to Amazon Web Services.

What is Amazon Web Services (AWS)? AWS is a comprehensive cloud platform. The AWS market share accounts for about half of the top ten cloud providers’ market, an indication of how widely used the platform is.

While AWS web services are not open-source, they support and integrate with many open-source tools and technologies. AWS managed services work with popular open-source tools such as:

• Amazon RDS for MySQL/PostgreSQL: Managed relational databases
• Amazon Elasticsearch Service: Managed Elasticsearch clusters
• Amazon EMR: Managed Hadoop and Spark clusters for big data processing
• Amazon EKS: Managed Kubernetes service

Moreover, AWS contributes to various open-source projects and provides infrastructure for open-source software.

How Does AWS Work?

What is AWS cloud known for, overall? It is important to discuss some basic AWS services and the AWS console to understand how AWS works.

• Scalable computing power. Amazon Elastic Compute Cloud (EC2) allows users to run and manage virtual servers easily at scale.
• Storage services manage a range of data. Amazon Simple Storage Service (S3) handles scalable objects, while Amazon Elastic Block Store (EBS) offers persistent block storage. Amazon FSx provides managed a file storage service that comes in multiple types for many popular file systems (such as SMB and Lustre). 
• A variety of database options. These include Amazon relational database service (RDS) and a NoSQL option, Amazon DynamoDB.
• Networking features. AWS Direct Connect establishes a dedicated connection to AWS. Amazon VPC provides a logically isolated virtual network where customers define and control resource deployment, placement, connectivity, and security.
• Developer tools. AWS tools for development and deployment include AWS CodePipeline and AWS CodeBuild.
• Security services. AWS Identity and Access Management (AWS IAM) controls access to resources and Key Management Service (AWS KMS) manages encryption keys.
• Artificial Intelligence. Amazon Sagemaker provides a broad set of tools to build, train, and deploy machine learning models. Amazon Bedrock is a managed service for AI Foundation Models (FMs) from leading AI models providers including Anthropic, Cohere, Stability AI, and Amazon through a single API

Users deploy and manage AWS services either through the web-based management console, the AWS Command Line Interface, or using public-facing API’s provided by most AWS services. The AWS console allows users to manage AWS services visually, and easily deploy and monitor resources. Users can launch instances, configure databases, and set up networks directly through the AWS console.

There are other ways to interact with AWS services:

• Via a unified management interface using the AWS Command Line Interface (CLI) tool
• By integrating AWS services into user applications using AWS Software Development Kits (AWS SDKs), available in various programming languages
• Using AWS CloudFormation templates to define and provision infrastructure code

Learn more about the features and history of AWS here.

AWS Architecture Explained

AWS cloud architecture is made up of several core cloud services deployed and connected to support business needs:

Compute services. There are several main types of AWS compute services – virtual servers (Amazon EC2), containers (Amazon EKS and Amazon ECS), and serverless computing (AWS Lambda and AWS Fargate). Amazon EC2 provides scalable virtual servers; AWS Lambda executes code in response to events without provisioning servers; and Amazon ECS/EKS are AWS managed services that are used for running containers and Kubernetes clusters.

Storage services. AWS provides managed storage services for block, object and file system needs – Amazon S3 for object storage, Amazon EBS for block storage and Amazon EFS for managed file storage—both for use with EC2 instances—and Amazon Glacier low-cost archival storage can all help form an internal AWS Architecture.

Database services. AWS cloud architecture may also be shaped by Amazon RDS, Amazon DynamoDB, or Amazon Redshift.

Check out Amazon’s AWS reference architecture diagrams here.

AWS Infrastructure

AWS relies on a robust, scalable, global network of infrastructure to deliver its services. Key components of AWS infrastructure include:

Data centers. AWS operates numerous data centers globally, which house physical hardware (servers, storage devices, networking equipment) that runs AWS services. Each is designed for redundancy and fault tolerance.

Regions and Availability Zones (AZs). AWS is divided into geographic regions, each containing multiple AZs. AZs are isolated data centers with independent power, cooling, and networking designed for high availability that allow users to architect fault-tolerant, resilient applications and services close to home to reduce latency.

Edge locations. AWS has numerous edge locations worldwide—closer to users—to provide content delivery and caching services through Amazon Cloudfront, reducing latency. 

Networking. The AWS network connects its data centers and edge locations and supports its services with high-speed and low-latency.

Hardware. AWS employs both custom-built and industry-standard equipment, optimized for various workloads, including specialized hardware and high-performance storage systems.

What is AWS Used For?

Due to its extensive suite of services and global reach, AWS is ideal for a range of applications:

• Web hosting and content delivery
• Data storage and backup
• Big data and analytics
• Machine learning and AI
• DevOps and Continuous Integration/Continuous Deployment (CI/CD) pipelines
• Internet of Things (IoT) deployments
• Mobile and web applications

A few examples of common AWS use cases include:

• Backend services via AWS Amplify and AWS AppSync
• Push alerts using Amazon Simple Notification Service (SNS)
• E-commerce platforms hosted with EC2, using S3 for cloud storage, RDS for the backend, Amazon Cloudfront for content delivery, and AWS Lambda for serverless backend logic
• Support for streaming media on AWS with S3 storage of video files, CloudFront content delivery, AWS Elemental Media Services transcoding and packaging videos, and Amazon DynamoDB managing user data and metadata

How Much Does AWS Cost? 

Amazon Web Services pricing is flexible, based on what each user needs. However, AWS pricing can also be complex, especially as bespoke usage combines with a wide variety of services, each with its own pricing model.

There are a few basic billing models in AWS:

• Pay-as-you-go. The user pays only for what they use, without initial investments or long-term contracts.
• Per-second billing. AWS bills by the second for many services for more precise cost management.
• Free tier. AWS offers limited usage of certain services for the first 12 months to help new users get started

AWS uses different pricing models depending on the service:

• On-demand. Compute capacity in EC2 in this model is priced by the hour or second with no long-term commitments or upfront payments; storage in this model in S3 based on the amount used per month.
• Reserved instances. This is more like a contract that typically ranges from 1 to 3 years; users commit to using EC2 instances for the stated term in exchange for a significant discount compared to on-demand pricing.
• Spot instances. Users bid for unused EC2 capacity at potentially lower costs—prices vary based on supply and demand.
• Flexible savings plans. These are another type of contract, usually ranging from 1 to 3 years, that offer a significant savings relative to on-demand pricing. The user commits to consistently using a minimum amount (measured in $/hour) at the agreed lower price.
• Dedicated hosts. Physical EC2 servers set aside for a particular user can help meet compliance requirements

Core AWS Products and Services

There are a wide range of AWS cloud compute products and services that encompass storage, networking, databases, and other areas. A partial AWS services list and a brief mention of how they work follows:

AWS Lambda

AWS Lambda serverless computing allows users to run code without the administrative tasks inherent to provisioning and managing servers. Users can also respond rapidly to events such as changes in data, shifts in system state, or user actions and scales automatically.

What is AWS Lambda used for?

Common use cases for AWS Lambda include:

• Real-time file processing
• Data transformation and extract, transform, load (ETL) tasks
• Serverless microservices
• Automated backups and routine maintenance tasks
• Real-time notifications and alerts
• Compatible with multiple languages and integrates with many other AWS cloud services
• Deployment of machine learning models for real-time inference
• Implementation of custom backend logic for web or mobile applications

Amazon EC2

The Amazon Elastic Compute Cloud (EC2) web service offers resizable cloud compute capacity. Developers can rent secure, scalable virtual EC2 servers known as instances that applications can run on.

Key features of Amazon EC2 include:

• Scalability
• A wide range of instance types tailored for different workloads
• Flexible pricing options
• Multiple storage options
• Networking features
• Built-in security features
• Management tools

Common use cases for Amazon EC2 include:

• Web hosting and applications
• App deployment
• Big data and analytics
• Training and deploying machine learning models
• Running batch processing jobs for data transformation
• Setting up development and testing environments
• Setting up disaster recovery environments
• Launching, terminating, and connecting to instances
• Security configuration
• Monitoring and scaling

Amazon EC2 offers customers their choice of processor and GPU accelerators from Intel, AMD, Apple, NVIDIA, and Amazon respectfully. For compute processors, customers can choose from the following options to meet their applications requirements:

• Intel Xeon processors support general purpose as well as storage, compute, and network optimized instance families.
• AMD EPYC processors support a wide range of use cases from enterprise compute to HPC and development environments.
• Apple Mac instances are built on Apple Mac Mini  computers for building and running Apple Mac OS applications:
• AWS Graviton processors are built by Amazon based on the ARM architecture and support a wide range of compute applications with lower power and greater price-performance than comparable alternative instances.
• AWS Nitro System is the foundation of the Amazon EC2 compute environment, consisting of lightweight hypervisor, and set of custom-built offload cards to provide server-level network, security, and memory services to EC2 instances.

AWS also provides multiple options for hardware accelerators for EC2 instances including:

• NVIDIA Hopper and NVIDIA Blackwell Graphical Processing Untis (GPUs)
• Intel Habana Gaudi GPUs
• AMD Radeon GPUs
• AWS Inferentia accelerators for AI model inference
• AWS Tranium accelerators for AI model training

AWS Relational Database Service (RDS)

AWS RDS is a relational cloud database with fewer administrative and technical burdens for users that supports engines such as Amazon Aurora, MySQL, Oracle, and Microsoft SQL.

AWS RDS is well-suited for content management systems (CMS), and web and mobile, e-commerce, analytics and business intelligence, and enterprise database storage applications.

AWS offers a variety of other fully managed database services for different business use cases:

• Amazon DynamoDB. This NoSQL key-value and document database is optimized for high-performance applications, IoT, mobile applications, gaming, and real-time bidding.
• Amazon Aurora. A high availability relational option, Aurora is both compatible with standard MySQL databases such as PostgreSQL and up to 3 to 5 times faster, suiting it for enterprise, SaaS, e-commerce, and business-critical applications.
• Amazon Redshift. This petabyte-scale data warehouse service is ideal for big data analytics and business intelligence.
• Amazon DocumentDB. This scalable, highly available document database service supports MongoDB workloads, and is well-suited for content management, catalogs, user profiles, and mobile applications.
• Amazon Neptune. This service supports graph models Property Graph and RDF (Resource Description Framework) and is optimized for storing and querying highly connected data. This makes it popular for use with social networking, recommendation engines, fraud detection, and knowledge graphs.
• Amazon ElastiCache. This in-memory data store is used for real-time analytics, session storage, leaderboards, and geospatial applications.
• Amazon Quantum Ledger Database (QLDB). Along with an immutable, cryptographically verifiable transaction log and SQL-like API, this is used for financial transactions, supply chain tracking, system of record, and identity management.
• Amazon Timestream. A time series database for IoT applications, industrial telemetry, application monitoring and DevOps.
• Amazon Keyspaces. A highly available, Cassandra-compatible, NoSQL database service for Internet of Things (IoT), real-time data, personalization engines, time-series data.

Amazon S3

AWS Simple Storage Service (AWS S3) allows users to store and retrieve limitless amounts of data on demand to support a range of storage needs.

AWS S3 organizes data into storage classes based on ease and frequency of access:

• Standard. Frequently accessed data with low latency and high throughput
• Intelligent-tiering. Automatically moves data between frequent and infrequent access tiers based on changing access patterns
• One Zone-IA (Infrequent Access). For data that is infrequently accessed
• Glacier. For long-term archival storage with retrieval times ranging from minutes to hours
• Glacier deep archive. Lowest-cost storage for data that is rarely accessed and has a retrieval time of hours

Common use cases for Amazon S3 include:

• Backup and recovery, including disaster recovery
• Content storage and distribution
• Store raw big data or intermediate results in S3 and use AWS analytics services like Amazon Athena, Amazon Redshift Spectrum, or AWS Glue for querying and processing the data
• Data archiving
• Storing and accessing application data

AWS Identity and Access Management (AWS IAM)

AWS Identity and Access Management (AWS IAM) securely and selectively manages access to AWS services and resources and what actions users can perform.

Key features of AWS IAM include:

• User management
• Permissions and managed policies
• IAM roles and temporary security credentials
• Access control
• Multi-factor authentication (MFA)
• Integration with external identity providers
• Single sign-on (SSO)
• Audit and monitoring with AWS CloudTrail and IAM Access Advisor
• Least privilege and role rotation security best practices

AWS Elastic Block Storage (AWS EBS)

AWS Elastic Block Storage (AWS EBS) service can be attached to EC2 instances for a range of data storage needs. Amazon elastic volumes are persistent, durable, highly available, and scalable.

Common use cases for AWS EBS block storage service include:

• Database storage for databases running on EC2 instances
• Application data storage and snapshots for backup and recovery
• Creation and management of file systems on EC2 instances
• Hosting of the operating system and application software for EC2 instances for easy restarts and reconfiguration
• Setting up development and testing environments with customizable storage configurations
• Using EBS snapshots as part of integrated AWS backup service and disaster recovery strategy

AWS Elastic File System (AWS EFS)

AWS Elastic File System (AWS EFS) is a fully managed, scalable storage service for Amazon instances and on-premises servers.

Common use cases for the AWS EFS include:

• Storing and managing website content or digital assets for content management systems (CMS) and web applications
• Storing and processing large datasets for big data processing frameworks, data lakes, and analytics applications
• Developing and testing applications to ensure consistent shared access to files
• Managing home directories for multiple users in environments such as development clusters or research labs
• Backup and disaster recovery
• Content distribution

AWS Cloudfront

AWS CloudFront is a global Content Delivery Network (CDN). It accelerates content between origin servers such as S3 buckets, EC2 instances, or on-premises servers and a network of edge locations to improve performance.

AWS CloudFront supports encryption and HTTPS for secure data transmission. Users can restrict access to content with SSL/TLS certificates, AWS Certificate Manager (ACM) certificates, or signed URLs and signed cookies.

AWS CloudFront also integrates with Web Application Firewall (AWS WAF) to prevent common web exploits and attacks.

Common use cases for AWS CloudFront include:

• Website acceleration. AWS CloudFront can cache and deliver static and dynamic content such as HTML, CSS, JavaScript, and images from edge locations.
• Enhanced content delivery with high throughput. This is especially important for applications with large media files, such as videos or software downloads.
• API acceleration. Cache responses at edge locations and optimize request handling to speed access and reduce load on backend servers.
• Live stream with low latency and high availability worldwide
• Ensuring security and compliance. This is critical for web applications and content with AWS WAF, the use of HTTPS, and other access control mechanisms.
• Global reach. Achieve improved access speeds and reduced latency

AWS SNS

AWS Simple Notification Service (AWS SNS) is a fully managed tool that allows users to contact a large number of recipients across distributed systems using various messaging protocols.

Common use cases for AWS SNS include:

• Application events and system failure or performance alerts via email, SMS, or mobile push notifications when specific events occur
• Event-driven architectures that trigger actions in response to events
• User notifications about updates, promotions, or activity
• Send system integration messages and information
• Transactional notifications such as order confirmations or password resets
• Monitoring system health and alerts on performance based on specific conditions in CloudWatch alarms or application event

AWS SQS

Amazon Simple Queue Service (SQS) is a fully managed service that enables users to decouple and scale distributed systems and applications. This way, they can use SQS to send, store, and receive messages reliably even when components fail or are not available.

Common use cases for AWS SQS include:

• Decoupling microservices that must communicate asynchronously so they can integrate, operate independently, and handle varying loads
• Message buffering during high traffic periods to smooth out workload spikes, prevent system overload, and ensure reliable message processing
• Task queuing and distribution to worker processes or services for background processing, improved efficiency, and optimal responsiveness
• Event-driven architectures use SQS to respond to events and messages, and integrate with AWS Lambda or other services to process and act upon triggering events
• Asynchronous order processing for e-commerce applications.
• Disparate application integration and data exchange

AWS VPC

AWS Virtual Private Cloud (AWS VPC) allows users to logically isolate AWS cloud networks. A virtual network is similar in many ways to a traditional onsite data center version, but it has virtual infrastructure that can scale on demand.

Common use cases for AWS VPC include:

• Isolate networks for applications
• Create hybrid AWS cloud architectures
• Use VPCs with public subnets for web servers, private subnets for application servers, and isolated subnets for databases to segment and secure network
• Secure development and testing environments with VPCs to control access and ensure they do not interfere with production resources
• Features like security groups, NACLs, and VPNs help users meet regulatory requirements surrounding data protection, network isolation, and secure access
• Use AWS VPC with an auto-scaling group and load balancer to deploy scalable web applications with high availability and fault tolerance

AWS Email Services

AWS offers Amazon Simple Email Service (Amazon SES) and Amazon Pinpoint. Each is designed for different email use cases and has its own unique suite of delivery, tracking, and analytics features.

Amazon SES is a scalable, cost-effective service commonly used for more basic, transactional emails. These might include password resets, marketing campaigns such as promotional newsletters, and notifications such as system statuses.

In contrast, Amazon Pinpoint offers much more powerful marketing features for more personalized marketing campaigns, including user engagement, behavioral messaging, and performance monitoring. It is a flexible marketing communications service that offers email, SMS, push notifications, and voice messages as well as advanced targeting and analytics features.

AWS API Gateway

This service handles AWS API management. AWS API Gateway has a number of functions:

• Allows developers to create, publish, maintain, monitor, and secure APIs at any scale
• Acts as a gateway for accessing backend services, such as AWS Lambda functions, Amazon EC2 instances, or any web application
• Handles tasks such as request routing, authorization, and API monitoring
• Builds applications that interact with AWS Lambda functions, exposing them as RESTful or WebSocket APIs, enabling serverless development
• Routes requests between microservices and handle API management tasks in a distributed application
• Use WebSocket APIs in API Gateway to enable real-time, two-way communication features such as chat or live notifications between clients and servers

AWS Migration Services

AWS offers a comprehensive suite of migration services:

• AWS Migration Hub. This centralized dashboard tracks and manages AWS cloud migration progress across multiple tools.
• AWS Application Migration Service (AWS MGN). This tool automates testing and simplifies lift-and-shifts with continuous replication and minimal downtime.
• AWS Server Migration Service (AWS SMS). This service automates scheduling and replicates data incrementally—a cost-efficient strategy that facilitates the migration of on-premises virtual machines to AWS.
• AWS Database Migration Service (AWS DMS). This replicates data continuously, offers schema conversion, and supports many database engines with minimal downtime.
• AWS DataSync. This tool delivers more efficient data transfer, improved security, and optimized performance that automates data transfer between on-premises storage and AWS.
• AWS Snowball & Snowcone. These tools offer data transfer, edge computing (Snowcone), and encryption, making it possible to securely move large volumes of data to and from AWS.AWS Transfer Family. This offers SFTP, FTPS, FTP support, security features, and integrates with S3 to deliver managed file transfer directly into and out of that platform

AWS Security Services

AWS security services protect data, applications, and infrastructure across various AWS environments. They address identity and access management, threat detection, compliance, and related issues.

Key AWS security services include:

• AWS Identity and Access Management (AWS IAM). This controls access to AWS resources and services through AWS users and groups, defined roles, and assignment of permissions and policies linked to roles and users. It also connects multi-factor authentication (MFA) to user accounts.
• AWS Key Management Service (KMS). This service creates, rotates, and manages keys for encryption of data at rest and in transit. Users decide whether to use AWS-managed or customer-managed keys.
• AWS CloudHSM. Regulatory requirements for data protection include dedicated hardware security modules (HSMs) for encryption and decryption operations. AWS CloudHSM integrates with AWS services and custom secure key management applications.
• AWS Secrets Manager. This tool manages database credentials and API keys securely and automatically rotates them to reduce the risk of exposure. It also controls access using IAM policies.
• AWS Shield. This offers both basic and advanced protection against Distributed Denial of Service (DDoS) attacks for all AWS services, depending on which level the user selects.
• AWS Web Application Firewall (AWS WAF). This critical service protects against common web exploits with custom rules that block or allow traffic. It also offers web traffic logs that help users identify and respond to threats.
• AWS Security Hub. As the name suggests, this service offers a centralized view of security alerts and compliance status with aggregated, prioritized security findings from AWS and partner services.
• Amazon GuardDuty. This offers continuous threat detection and monitoring for malicious or unauthorized activity in AWS environments. It generates findings based on anomaly detection, threat intelligence, and machine learning and delivers integrated alerts with AWS CloudWatch and AWS Security Hub for incident response.

AWS Artificial Intelligence Services

AWS provides managed services, developer tools, foundation models, data services, and infrastructure options that support a wide range of use cases for artificial intelligence.

• AWS Sagemaker: Amazon Sagemaker provides a broad set of tools to build, train, and deploy machine learning models.
• AWS Bedrock: Amazon Bedrock is a managed service for AI Foundation Models (FMs) from leading AI models providers including Anthropic, Cohere, Stability AI, and Amazon through a single API.
• Amazon Q: Amazon Q is a generative-AI assistant that customers can use for a incresingly broad range of use cases including chat, code debugging, call center automation, and data analytics

Learn more about AWS services using the AWS Service Catalog, found here.

AWS vs Azure vs Google Cloud (GCP)

An AWS vs Azure vs GCP comparison shows that each of these major cloud computing platforms has a few key advantages:

AWS vs Azure

Amazon Web Services (AWS)

• The Amazon cloud computing platform provides the greatest range of services.
• AWS has the largest number of data centers and availability zones worldwide, a large ecosystem of partners and third-party integrations, and a vast user community.
• AWS is known for rapid innovation and frequent releases of new services and features.
• However, the AWS cloud computing platform can be complex and presents a steep learning curve.
• The pay-as-you-go pricing model can increase costs without careful management.

Microsoft Azure

• Seamless integration with Microsoft products
• Strong hybrid cloud solutions with services like Azure Arc and Azure Stack, which allow for integration between on-premises and cloud environments
• A strong focus on enterprise needs, including extensive compliance and regulatory certifications
• Robust tools for developers and DevOps, including Azure DevOps and Visual Studio integration
• Fewer services than AWSPricing can be complex, and difficult to navigate and predict

AWS vs GCP

In terms of AWS vs Google Cloud, we’ve discussed the basics of AWS above.

Google Cloud Platform (GCP)

• GCP offers BigQuery, Dataflow, and Dataproc tools for big data processing and analytics.
• Google offers TensorFlow and AutoML for advanced AI and machine learning.
• GCP benefits from a global infrastructure network.
• GCP boasts a user-friendly interface.
• Compared to both AWS and Azure, GCP has a smaller market share, which can impact the availability of third-party integrations and support.
• GCP may have more limited capabilities in some areas, especially in enterprise-focused solutions.

Advantages and Disadvantages of AWS

AWS offers many advantages, although it also presents with some disadvantages to consider. Here is a balanced view of the main advantages and disadvantages of AWS:

AWS Advantages

There are numerous advantages of AWS, including:

• An extensive portfolio of services covering compute, storage, databases, networking, machine learning, and analytics, that allow for diverse use cases and comprehensive solutions
• On-demand resources that can scale up or down based on user needs that handle varying workloads and avoid over-provisioning
• A vast network of data centers across multiple regions and availability zones worldwide
• Pay-as-you-go pricing that avoids upfront investments
• Robust security features, including encryption, IAM, and compliance certifications to meet various regulatory requirements
• A large ecosystem of partners, third-party integrations, and a vibrant community of user tools, support, and resources
• Frequent new services, features, and updates
• Fully managed services simplify deployment, management, and maintenance of applications and infrastructureCost management tools and services help users monitor, manage, and optimize their spending

Disadvantages of AWS

Disadvantages of AWS include:

• Vast array of services and features can be complex and overwhelming
• The pay-as-you-go model is flexible, but can lead to unexpected costs without optimization
• Variable pricing can be difficult to manage, especially for fluctuating or unpredictable workloads
• Premium support plans can be costly, and basic support might not meet all user needs
• AWS imposes service limits and quotas on various resources, which can require users to request increases or work around limitations for large-scale deployments
• Heavy reliance on AWS services can lead to vendor lock-in
• AWS offers high availability, but service disruptions or outages can occurUsers are responsible for managing security within their environments

About AWS Certifications

What is AWS certification? A process is offered to formally validate users’ AWS cloud services skills and knowledge. This helps both users and the AWS community, because it allows professionals to demonstrate their expertise in support of their career development while nurturing a broader community of users with knowledge to share.

The certification process starts with preparation. AWS offers online courses, face-to-face training, study guides, sample questions, and practice exams to help candidates prepare.

Practical background with AWS services is highly recommended, and many certification exams require hands-on experience with AWS environments.

Candidates register for exams through the AWS certification website or through Pearson VUE, a testing partner. Exams are typically multiple-choice and may include scenario-based questions. Some specialty exams may have additional question formats.

Depending on the specific certification, exams range in length from 90 to 180 minutes. They can be taken at authorized testing centers or remotely with proctoring.

AWS certifications are organized into levels:

There is one foundational level certification:

• AWS Certified Cloud Practitioner. This is someone who can demonstrate a basic understanding of AWS cloud services and concepts and is an appropriate certification for people with a non-technical background or those new to cloud computing.

Associate level certifications are as follows:

• AWS Certified Solutions Architect. This focuses on designing distributed AWS systems and applications.
• AWS Certified Developer. This emphasizes developing and maintaining AWS-based applications.
• AWS Certified SysOps Administrator. This centers on operational management, deployment, and administration of AWS systems.

Professional level certifications are as follows:

• AWS Certified Solutions Architect. This demands advanced expertise in designing complex AWS architectures and solutions.
• AWS Certified DevOps Engineer. This requires advanced skills in DevOps, continuous integration, and AWS deployment.

Specialty level certifications are as follows:

• AWS Certified Security. This demands deep knowledge in securing AWS environments.
• AWS Certified Big Data. This requires expertise in handling big data and analytics on AWS.
• AWS Certified Advanced Networking. This emphasizes proficiency in advanced networking concepts and AWS networking services.
• AWS Certified Machine Learning. This demands skills in building, training, and deploying machine learning models on AWS.
• AWS Certified Database. This requires in-depth understanding of AWS database services and solutions.

AWS certifications are valid for three years. Recertification requires passing the latest version of the exam or a higher-level certification.

Fees vary based on certification level. For example, associate-level exams typically cost around $150, while professional and specialty exams may cost around $300.

Benefits of AWS certification include career advancement, formal recognition, access to exclusive AWS Certified communities and resources, and professional growth.

WEKA for AWS

Data intensive workloads on AWS like generative AI, drug discovery, visual effect rendering, electronic design automation, AI inference, and many more require low latency and high throughput combined with the flexibility of the cloud. With WEKA, you get the following features for your AWS workloads:

• Cloud-native integration (WEKA software deploys within the customer VPC on a cluster of Amazon EC2 instances with extended namespace to Amazon S3
• Bi-directional autoscaling (through integration with AWS Autoscaling)
• Auto-tier NVMe to Blob in single namespace
• Multi-protocol support for all applications (POSIX, NFS, SMB, S3)
• Data portability from on-premises to AWS and between AWS and other cloud providers (Azure and Google Cloud)

Contact WEKA today to learn more about how we can power your cloud workloads.