As someone who has worked with AWS for over a decade and holds multiple AWS certifications, I often get asked to demystify fundamental terminology and concepts. AWS now offers over 200 services with all kinds of technical vocabulary. So I put together this comprehensive reference to explain core AWS terminology in plain terms from an expert perspective.
Whether you‘re beginning your cloud journey or an experienced practitioner, clear communication requires a shared language. This guide aims to build fluency around frequently used AWS services, features, architectures and more.
I‘ll also provide insider tips and best practices gathered from many years of hands-on experience. Let‘s dive in!
Core Services
AWS continually expands its service portfolio far beyond the original offerings like EC2 and S3. Let‘s level-set some common services and decode the terminology behind them.
Amazon EC2
The EC2 acronym stands for Elastic Compute Cloud – quite a mouthful! As one of the first AWS infrastructure services, EC2 provides resizable virtual machine capacity in the cloud. Spinning EC2 instances on-demand enabled companies to scale computing power up and down based on needs.
Over 15 years later, EC2 remains a cornerstone of cloud architecture. Whether you need a single Linux server or a thousand Windows machines, EC2 delivers flexible, cost-efficient access to compute.
Tip: EC2 offers over 400 instance types optimized on various dimensions like CPU, memory, storage, GPU, etc. The "right sizing" of instance types continues to be an art and science as workload requirements evolve.
Amazon S3
Amazon Simple Storage Service (S3) has emerged as the undisputed leader in cloud object storage. The native AWS service offers unmatched durability, scalability, security and ease-of-use for unstructured data.
S3 buckets can scale to exabytes of storage and handle over 5500 requests per second per prefix. You can stream uploads directly from web applications, schedule batch data transfers, or even ship AWS Snowball appliances for petabyte-scale datasets. Integrations like S3 event notifications and Lambda triggers provide serverless processing whenever new objects arrive.
With over 30% of newly created S3 buckets protected using encryption, Amazon S3 ranks as one of the most secure cloud storage services according to recent studies. Pay-as-you-go and infrequently accessed tiers drive costs lower while still ensuring extreme data durability.
In 2022, IDC forecasts that nearly 60% of data stored in the cloud will rely on S3 infrastructure. Simply put, any modern cloud architecture leans heavily on this ubiquitous object storage fabric.
Expert Tip: Architectures like data lakes almost always build upon Amazon S3 storage foundations before enabling advanced analytics via AWS data services.
| Year | New S3 Buckets Created |
|---|---|
| 2021 | Over 250 million |
| 2022 | Projected 300+ million |
Table showing explosive annual growth in new S3 bucket creation [Source: AWS re:Invent 2021 Keynote]
AWS Lambda
AWS Lambda provides serverless compute via short-lived function containers rather than always-on virtual machines. This enables event-driven execution with near-instant scaling.
Lambda disruptively changed cloud architecture by removing capacity planning challenges. For intermittent workloads, functions spin up upon triggering events like HTTP requests, new database records or file uploads. Containers hibernate when idle so you only pay for milliseconds of usage rather than overflow capacity.
Architectures built on Lambda functions seamlessly handle volatile traffic from zero to peak levels without intervention. Auto-Scaling rules become unnecessary since Lambda intrinsically scales to demand behind the scenes.
As compute requirements intensify from streaming data pipelines to machine learning pipelines, Lambda usage continues gaining momentum:
| Year | Total Monthly Lambda Invocations |
|---|---|
| 2019 | 75 billion |
| 2022 | 200+ billion |
Table showing massive growth in AWS Lambda monthly invocations over 3 years [Source: AWS re:Invent 2022 Keynote]
Lambda functions shine for rapidly prototyping capabilities, gluing services together and augmenting traditional applications. Companies like Netflix, Expedia and McDonald’s process over 100 million Lambda invocations daily across business functions like personalized content delivery, real-time stream manipulation and order management.
Expert Note: One tradeoff around serverless functions involves stateless designs without persistent storage attached to code containers between invocations.
Amazon CloudFront
A content delivery network (CDN) like Amazon CloudFront strategically caches content across geographically dispersed edge locations to reduce latency. End users retrieve data from nearby edge caches rather than transoceanic round trips back to origin infrastructure.
CloudFront currently spans 300+ global edge sites to ensure speedy delivery measuring tens of milliseconds. The network continues evolving to handle live/streaming workloads via new capabilities like Lambda@Edge functions. This allows execution of custom logic alongside edge caches to personalize and secure content.
I‘ve used CloudFront across commercial media properties and government entities to absorb traffic spikes beyond 10 times average levels. DDoS resiliency represents another key rationale for routing ingress through CloudFront. Widespread AWS Shield protections shield applications from common malicious attacks like SYN floods at the edge. This avoids direct bombardment of origins.
Advanced features like geo-restriction, signed URLs/cookies and field-level encryption help address emerging privacy/compliance needs around regulated data and copyrighted media streams. Expect CloudFront to play an even more prominent role in future architectures as more immersive, real-time experiences dominate business models.
AWS CloudFormation
Migrating business applications to the cloud posed all kinds of new challenges around consistency, compliance and agility during scale. AWS addressed this by introducing CloudFormation to enable Infrastructure as Code (IaC) starting in 2011.
CloudFormation allows engineers to define reusable templates for configuring AWS resources using declarative YAML/JSON. For example, instead of clicking through the AWS Management Console to assemble a 3-tier architecture, engineers construct the entire topology as code.
Teams utilize these version-controlled templates as the single source of truth for building out templatized stacks. Want to recreate a production-grade stack in another AWS account or region? Simply deploy the same template to stamp out a clone rapidly.
This IaC approach facilitates rapid experimentation and standardization using infrastructure building blocks. CloudFormation templates abstract away the underlying resource APIs and handles provisioning details automatically.
In larger enterprises, IT organizations depend on CloudFormation to enforce policies, cost controls and security baselines through template governance. Central administrators restrict certain resource types while equipping developers with approved stacks for staging environments.
Expert Tip: Many teams now prefer even higher-level abstractions using the AWS CDK, Terraform or Pulumi over raw CloudFormation syntax for improved productivity.
Architectural Concepts
Now let‘s explore key terminology involved with core AWS architectural concepts.
AWS Region
An AWS Region represents a discrete geographic area containing multiple, isolated locations known as Availability Zones. AWS directly invests in massive data centers across 26 Regions based on customer density and emerging demand.
When provisioning resources, you intentionally choose a Region for governance, proximity or compliance reasons. Data tends to remain housed within the resident Region by default. Advanced replication features like cross-region snapshots or multi-master databases enable tighter global synchronization across Regions when necessary.
Expert Note: AWS offers cost-optimized methods for data transfer between Regions like Snowball devices and Direct Connect links.
Availability Zone
An AWS Availability Zone (AZ) constitutes an individual data center or zone within a Region. Each AZ runs on its own physically distinct infrastructure including power, cooling and networking. This isolating allows for much higher fault tolerance.
If technicians need to repair AZ hardware, hosted applications remain available by redistributing load to alternate zones. Large enterprises architect critical systems across minimum of three zones to eliminate individual points of failure. More budget-conscious teams often start with resources spread across two zones for moderate resilience requirements.
| Tier | Multi-AZ Architecture |
|---|---|
| Entry | Single AZ |
| Mid-Range | Dual AZ |
| Enterprise | Multi (3+) AZ |
Table showing Availability Zone configurations by architecture scale/complexity
VPC
The Virtual Private Cloud option arose from customers wanting to extend internal network topologies seamlessly into AWS. VPC fabric indeed makes it seem like EC2 instances run within corporate data centers rather than the public cloud!
Each VPC logically isolates a user-defined virtual network running on shared AWS infrastructure. This gives teams complete control to design subnet architecture, IP addressing, route tables, network gateways and security controls.
Common use cases involve Mimicking production network designs in the cloud for disaster recovery, piloting isolated dev/test labs, or accessing on-premises servers privately via VPN connections.
Architecturally, VPCs often utilize a hub-spoke model with shared gateways, security controls and peering relationships across central “hubs” under common governance. Groups can then build isolated application stacks called “spokes” within their allocated subnets.
Pro Tip: VPC flow logs, transit gateways and cloud NAT gateways help securely connect infrastructure despite complex mesh networking.
| Year | VPC Adoption Rate |
|---|---|
| 2020 | 76% |
| 2022 | 88% |
Table showing increasing default use of VPC networking over default EC2 classic [Source: Flexera 2022 State of the Cloud Report]
Clearly, VPCs represent the future of cloud-hosted infrastructure for their enhanced control, security posture and native integrations.
Identity & Access Management
As cloud usage exploded, AWS customers needed more sophisticated tools for managing user identities and resource permissions. The Identity and Access Management (IAM) service filled this gap by providing centralized authentication, authorization and auditing capabilities.
Via IAM, administrators employ identity federation to hook in enterprise directories like Microsoft Active Directory. Single sign-on capabilities allow users to securely access AWS dashboards and services without an additional login.
Granular policies attach to IAM identities to grant carefully scoped access permissions like allowing certain developer groups to start/stop production EC2 instances. Predefined IAM roles serve temporary credentials to AWS services that need privileged security powers.
Robust activity logs capture management events for auditing and anomaly detection purposes. Tools like IAM Access Analyzer spot potential credibility escalation risks across roles and policies.
According to recent research, over 85% of companies now leverage AWS IAM extensively to govern human and machine access at scale. The versatile tooling continues maturing to address emerging authentication methods like multi-factor authorization and Web Federated Identity support.
Storage Principles
Now that we‘ve surveyed major service categories, I‘ll drill deeper into storage – one of the most prolific areas of AWS.
In particular, Amazon‘s S3 underlies a multitude of modern workloads from cloud-native apps to big data analytics. Let‘s unpack what sets S3 apart.
S3 Buckets
An Amazon S3 bucket serves as a container for storing files as objects. Buckets form the foundation for virtually unlimited storage capacity across a global namespace.
AWS administers this namespace by assigning bucket names uniquely across S3. Once created in a given AWS Region, no other customer can leverage that same bucket name. You can configure buckets in different Regions to synchronize changes or serve distinct purpose.
Enforcing logical separations through targeted buckets assists greatly with access controls, lifecycle management, analytics and overall governance. Istructs often dictate storage patterns like…
- Per service or application (s3://app1_bucket)
- Per environment (s3://prod_db_backups)
- Per classification (s3://financial_data)
- Per customer (s3://cust5003_exports)
This flexible hierarchy allows both centralized and distributedProduce teams to organize expansive storage their way.
S3 Storage Classes
Amazon S3 revolutionized cloud storage with the introduction of the first low-cost, archival storage tier in the form of S3 Glacier back in 2013. This gave companies affordable options to shift backups, compliance archives and cold datasets to the cloud economically.
AWS has continued augmenting additional storage classes optimized on unique combinations of latency, frequency and durability factors:
- S3 Standard – High performance for frequently accessed data
- S3 Intelligent Tiering – Automated tiering based on changing access patterns
- S3 Standard-Infrequent Access (S3 Standard-IA) – Long-lived but less frequently accessed data tier
- S3 One Zone-Infrequent Access (S3 One Zone-IA) – Lower-redundancy option for secondary data
- S3 Glacier (Archive) – Archival tier focused on extreme data durability
Juggling multiple storage classes unlocks sizable cost savings, especially when data usage constantly evolves. S3 Lifecycle management automation now makes this even easier by transitioning objects across tiers as they age.
For example, operational databases constantly ingest new event logs that require rapid analysis. But over weeks, the value of certain log data diminishes to where archiving makes more economic sense. S3 Lifecycle policies can handle this by shifting 30-day old logs from Standard to Glacier access without any application changes.
Expert Tip: Take advantage of S3 Intelligent Tiering when access patterns seem unpredictable. The machine learning-based tiering engine closely monitors usage and moves objects accordingly.
According to 2022 research statistics, over 50% of companies now leverage multiple S3 Storage Classes aligned to use case requirements beyond one-size-fits all standard. More cost-conscious teams stand to save upwards of 68% over previous single storage class postures.
| Storage Class | Use Cases |
|---|---|
| S3 Standard | Hot analytics, content distribution, etc |
| S3 Standard-IA | Warm analytics, secondary backups |
| S3 Glacier | Archives, disaster recovery |
Table showing target use cases by S3 Storage Class
Prioritizing S3 deployment by storage class and use case stands to save enterprises anywhere from 25-68% over non-tiered approaches.
Final Thoughts
I hope this AWS terminology guide has shed light on key services and concepts from an expert perspective. Feel free to bookmark this reference to level-set language around current capabilities. AWS continues innovating at a remarkable pace so expect exciting new terminology on the horizon!
