Amazon Web Services introduced Amazon Simple Storage Service (S3), offering developers on-demand object storage through a web API. This launch helped define AWS’s “building block” approach: customers could rent a single infrastructure capability and combine it with others as needed. S3 also set expectations for internet-scale durability and pay-as-you-go pricing.
AWS made Amazon Simple Queue Service (SQS) generally available, offering a hosted message queue to move work between application components. This helped customers build distributed systems where parts of an application can run independently without losing messages. SQS became a key “glue” service for decoupling systems on AWS.
AWS released the public beta of Amazon Elastic Compute Cloud (EC2), letting customers rent virtual servers (“instances”) and scale them up or down. EC2 made it practical to pair compute with S3 storage, enabling full applications to run on AWS instead of only storing data there. The first EC2 region became US East (N. Virginia), later known as `us-east-1`.
AWS launched Amazon Elastic Block Store (EBS), providing persistent block storage volumes that can be attached to EC2 instances. This addressed a major early limitation: instance storage was tied to the life of the virtual machine. EBS enabled more traditional workloads—especially databases—by keeping data independent from any single instance.
AWS launched Amazon CloudFront, a content delivery network (CDN) designed to speed up delivery of websites and media by caching content closer to users. CloudFront integrated tightly with S3, helping customers serve static assets globally without building their own delivery network. This expanded AWS beyond core compute and storage into performance and edge delivery.
AWS launched the Europe (Ireland) Region (`eu-west-1`), giving European customers a closer location to run applications and store data. This was a major step in AWS’s global expansion strategy: reducing latency and supporting regional operational needs. It also marked AWS’s shift from a primarily US-based platform to a multi-region one.
AWS launched the beta of Amazon Elastic MapReduce (EMR), providing a managed way to run Apache Hadoop jobs using EC2 and S3. This lowered the setup and operations work needed for large-scale data processing. EMR helped make AWS attractive for analytics and research workloads, not just web hosting.
AWS announced CloudWatch for monitoring, Auto Scaling for automatically adjusting capacity, and Elastic Load Balancing (ELB) for spreading traffic across instances. Together, these services made it easier to run resilient applications that respond to changes in demand. They also pushed AWS toward more “managed operations” instead of customers scripting everything themselves.
AWS introduced Amazon Virtual Private Cloud (VPC), allowing customers to create logically isolated networks for AWS resources and connect them to on-premises systems using VPN. VPC helped address enterprise security and networking requirements, making AWS adoption easier for organizations with existing IT environments. This was a key step in making AWS suitable for more regulated and security-conscious use cases.
AWS launched Amazon Relational Database Service (RDS), initially supporting MySQL, to automate common database tasks like provisioning and backups. This reduced the need for customers to run and manage databases directly on EC2. RDS broadened AWS’s platform from “infrastructure components” toward managed application services.
AWS opened its first Asia Pacific Region in Singapore (`ap-southeast-1`). This reduced latency for customers serving users in Asia and expanded AWS’s footprint beyond the US and Europe. It also signaled that AWS’s region rollouts were becoming a core part of its growth plan.
AWS released a preview beta of AWS Identity and Access Management (IAM), enabling customers to create users and control permissions inside an AWS account. This reduced the need to share long-term credentials and made it easier to follow least-privilege security practices. IAM became foundational for managing access as AWS accounts and service usage grew.
AWS launched the Asia Pacific (Tokyo) Region (`ap-northeast-1`), adding another major location in Asia. Expanding to Japan supported customers needing lower latency in Northeast Asia and added geographic options for availability and disaster recovery. This continued AWS’s pattern of adding regions to meet regional performance and compliance needs.
AWS opened the US West (Oregon) Region (`us-west-2`), adding a second large-scale region in the western United States. This gave customers more options for multi-region architectures inside the US. It also supported higher availability by enabling geographically separated deployments.
AWS launched the South America (São Paulo) Region (`sa-east-1`), expanding into Latin America. This helped customers serve South American users with lower latency and offered more choices for data location. It was a notable step in AWS’s move toward a truly global region map.
AWS launched Amazon DynamoDB, a fully managed NoSQL database designed for fast, predictable performance at scale. It gave customers an alternative to relational databases when workloads need flexible schemas and very high request rates. DynamoDB further strengthened AWS’s portfolio of managed data services.
AWS launched the Asia Pacific (Sydney) Region (`ap-southeast-2`), improving service for Australia and nearby markets. With Singapore, Tokyo, and Sydney available, AWS customers in Asia Pacific gained more regional choices for latency-sensitive applications and disaster recovery planning.
AWS announced a limited preview of Amazon Redshift, a managed data warehouse designed for large-scale analytics using SQL tools. Redshift aimed to make data warehousing cheaper and easier to operate than many traditional on-premises systems. This expanded AWS’s analytics capabilities beyond Hadoop-style batch processing.
AWS opened the Europe (Frankfurt) Region (`eu-central-1`), adding a second major AWS region in Europe. This supported customers with needs around latency, resiliency, and data location within continental Europe. It also reflected increasing demand for regional choice as AWS adoption grew.
AWS announced AWS Lambda, a compute service that runs code in response to events and manages the underlying servers automatically. This introduced “serverless” computing to many AWS customers: they could deploy functions without provisioning virtual machines. Lambda represented a shift toward higher-level managed compute, complementing EC2 rather than replacing it.
AWS launched the Asia Pacific (Mumbai) Region (`ap-south-1`). This gave customers in India a local option for running applications and storing data, which can be important for both performance and governance requirements. It also continued AWS’s fast expansion of regions during the mid-2010s.
AWS launched the US East (Ohio) Region (`us-east-2`), adding capacity and geographic diversity in the eastern United States. More US regions helped customers design multi-region systems with better resilience against regional disruptions. By 2016, region rollouts had become a central way AWS scaled globally.
AWS launched the Europe (London) Region (`eu-west-2`) and the Canada (Central) Region (`ca-central-1`). These openings expanded AWS’s reach into new national markets and increased options for data residency and latency. By the end of 2016, AWS had a clearly established pattern: frequent service innovation paired with steady global region expansion.
Amazon Web Services: service launches and global region rollouts (2006–2016)