After 10+ years helping enterprises migrate critical systems to the cloud, I‘ve come to appreciate firsthand the vast and often confusing array of acronyms encompassing Amazon Web Services. For those new to cloud computing, the terminology can feel like an impenetrable maze of tech jargon. My goal here is to help decode the meaning behind some core AWS abbreviations in plain language so you can navigate cloud environments more confidently.
Given AWS offers over 200 different services that are continuously evolving, this guide just scratches the surface. My focus is explaining the most common abbreviations related to key services, architecture concepts, security, storage, networking, compute, containers, data analytics, and cost management across the AWS ecosystem. Even as an experienced cloud architect, I still reference this AWS acronym cheat sheet regularly!
Why AWS Terminology Matters
First, some context on why taking time to understand AWS abbreviations will pay dividends in your effectiveness in leveraging cloud technologies. IDC forecasts worldwide spending on public cloud services will grow at a 23% compound annual growth rate between 2020-2024, reaching over $1 trillion. AWS leads the pack with over 30% market share in the cloud infrastructure market. Given the pace of innovation on AWS, tech professionals that fail to continually educate themselves on new services risk skills becoming outdated.
Knowing the difference between ECS and Lambda for serverless compute or CloudFront versus CloudWatch for monitoring can have very real architectural and cost implications on cloud projects. Developers that take time becoming fluent in “AWS speak” will transform more smoothly from on-premises virtual machines to modern cloud development patterns.
Now let’s break down core AWS terminology by category to simplify the learning process so you can focus more on leveraging AWS rather than just learning acronyms.
AWS Service Offerings
With over 200 cloud computing services available, AWS uses acronyms to refer to its key offerings. Some essential ones include:
EC2: Elastic Compute Cloud provides resizable virtual machine capacity allowing you to launch as many or as few virtual servers as needed via API calls. Useful for horizontally scaling web apps to handle traffic spikes.
S3: Simple Storage Service offers highly durable and available object-based cloud storage for purposes like backups, big data lakes, static websites, content repositories. Over quintillion objects are stored in S3 buckets across AWS.
RDS: Relational Database Service takes care of provisioning, patching, and managing relational databases like PostgreSQL and MySQL so you can focus on your applications rather than database administration.
Lambda: Serverless functions running code in response to triggered events like incoming API requests or file uploads to S3. Essential for modern microservices architectures on AWS.
Global Infrastructure Concepts
AWS runs its infrastructure globally across geographic Regions which break down further into Availability Zones and edge locations:
Region: A discrete geographic area, like us-east-1 located in Virginia or eu-central-1 in Frankfurt Germany. A region encompasses multiple data centers equipped with redundant power, cooling and networking.
AZ: An Availability Zone represents an isolated location within an AWS Region, up to 100kms apart. Each AZ offers independent infrastructure for fault tolerance so failures don‘t impact other zones.
Edge Locations: The 200+ CloudFront edge caching locations deployed globally to reduce latency by caching content close to end users.
Networking and Connectivity
AWS offers advanced networking capabilities for connecting resources across cloud environments and hybrid data centers:
VPC: A Virtual Private Cloud represents a private, isolated section you define on AWS to run resources like EC2 instances, RDS databases, and Lambda functions. You have complete control over IP address ranges, subnets, route tables, network gateways, and security settings.
Subnet: A segment of a VPC‘s IP address range where you group resources based on security or traffic isolation requirements. Public facing web workloads may route through public subnets while databases land in private subnets.
NAT Gateway: Allow resources in private subnets to access the public internet for critical updates while preventing inbound internet traffic. NAT Gateways live in public subnets.
VPC Peering: Connect two VPCs, even across separate AWS accounts and regions, using private IP addresses without transiting the public internet. Useful for security, legacy migrations, and hybrid connectivity.
Security, Identity and Compliance
AWS bakes security capabilities into the underlying cloud infrastructure and services used to construct solutions:
IAM: Identity and Access Management enables secure authentication and granular authorization by giving users and resources unique identities and permissions.
KMS: Key Management Service handles creating and controling cryptographic keys used to encrypt critical data in services like S3, EBS, and RDS without you having to worry about key management complexity.
GuardDuty: Monitors API calls, DNS requests, and VPC Flow Logs for signs of potential cyberthreats and unauthorized behavior. Alerts security teams about suspicious activity.
PCI DSS: Payment Card Industry Data Security Standard compliance is mandatory for storing, processing, or transmitting credit card data securely.
SOC Reports: System and Organization Control reports from third-party auditors validate security, availability, and confidentiality controls across key AWS services and data centers.
Storage Options
AWS offers various storage tiers and categories optimized for different access patterns:
EBS Volumes: Elastic Block Store provisions persistent block storage volumes that attach to EC2 instances similar to local drives. Useful for databases, enterprise apps, transactional workloads requiring low latency access to storage.
S3 Standard: Highly scalable object-based cloud storage capable of handling exabytes of data while maintaining 99.999999999% durability and 99.99% availability backed by a Service Level Agreement.
S3 Glacier: Archival storage for long term data retention where minutes to hours delay in accessing data may be acceptable. Costs 1/5th as much as S3 Standard with comparable resilience and encryption but requires an explicit retrieval request to access archived objects.
EFS: Elastic File System offers simple shared file-based storage for Linux workloads using standard NFSv4 protocol accessible concurrently by thousands of EC2 instances.
Compute Options
In addition to provisioning EC2 instances, developers can leverage other AWS compute technologies:
Lambda: Event-driven serverless functions useful for processing data uploads, responding to API events, data streaming, cron jobs, and more. abstract away infrastructure complexity.
ECS: Elastic Container Service simplifies deploying and operating containerized microservices across clusters of EC2 instances using APIs and management interfaces.
Auto Scaling Groups: Automatically add or remove EC2 instances based on user-defined policies aimed at maintaining consistent performance at the lowest cost.
Elastic Beanstalk: Automates provisioning underlying resources like EC2, load balancing, auto scaling required to run applications while handling health monitoring and application version deployments.
Containers and Orchestration
AWS offers two popular container platforms:
ECS: Elastic Container Service to natively launch Docker containers by specifying images, CPU/memory parameters, network settings, environment variables and more.
EKS: Elastic Kubernetes Service creates managed Kubernetes clusters making it easy to deploy microservices using Kubernetes constructs like pods, services, replication controllers and ingresses.
Fargate: Serverless compute engine that works with ECS and EKS to run containers without having to manage the underlying EC2 instances. Useful for focusing on applications not infrastructure.
Data Analytics and Business Intelligence
Turning raw data into business insights drives better decisions. AWS analytics offerings include:
Athena: Serverless data query service allows running standard SQL to analyze data sitting in S3 buckets without needing to setup complex ETL pipelines. Works directly against common formats like CSV, JSON, ORC, and Parquet.
QuickSight: Fast cloud-powered business intelligence service for creating interactive dashboards by connecting to AWS data sources including S3 buckets, Redshift data warehouses, and AWS IoT sensors. Leverages ML Insights.
EMR: Elastic MapReduce provides a fully-managed Hadoop framework optimized for processing vast amounts of structured and unstructured data using EC2 and S3. You can run petabyte-scale analysis at less than half the cost of traditional on-premises solutions.
Migration and Data Transfer
Migrating petabyte-scale data from legacy infrastructure into AWS can pose challenges. Services to help:
Snowball: Physically ship storage devices to AWS for transferring anywhere from terabytes to exabytes of data offline as an alternative to slow internet. Useful for large dataset migrations.
DMS: Database Migration Service helps you move production databases to AWS quickly and securely. The replication engine continues replicating ongoing changes to minimize downtime.
SMS: Server Migration Service helps migrate thousands of on-premises servers to AWS via incremental replication of live server volumes along with automation around recalling applications.
Management, Monitoring and Optimization
Gaining visibility while automating manual processes is key to effectively operating in the cloud:
CloudTrail: Logs of all API calls between AWS services, users, and resources. Think cloud breadcrumbs for security analysis, resource change tracking, and troubleshooting system issues.
Config: Records configurations of AWS resources and allows you to rewind through historical snapshots to perform auditing or determine when configurations changed and by whom.
Auto Scaling: Monitor resource utilization metrics like CPU and automatically add or remove EC2 capacity to maintain steady, predictable application performance during fluctuations in traffic volume.
Reserved Instances: Reduce overall compute costs by making a 1-3 year commitment to consistent baseline capacity. Useful for steady state workloads and achieving discounts up to 75% versus on-demand instance pricing.
Conclusion
Mastering cloud computing involves learning a complex web of ambiguous tech jargon. My goal was to decode the terminology behind Amazon Web Services to help you navigate AWS more confidently, especially when conversing with other technologists.
What AWS abbreviations remain a mystery you‘d like explained? Any services or concepts not covered that trip you up? I invite you to share questions in the comments below so we can further demystify the maze of cloud computing acronyms together!
