Amazon Web Services

Cost remains one of the primary attractions of Amazon Web Services (AWS), but the way pricing works has matured significantly. AWS still operates on a pay-as-you-go model with no upfront costs, but newer pricing models provide more flexibility and optimisation opportunities.

For example, businesses can now take advantage of:

• Savings Plans – refined since their introduction in 2019, these allow companies to commit to usage over one or three years for significant discounts while still offering flexibility across instance families and services.
• Spot Instances with AI-driven optimisation – advanced bidding strategies and tools such as AWS Cost Explorer and third-party FinOps platforms automatically identify and manage the most cost-efficient compute resources.
• Serverless billing granularity – services like AWS Lambda now bill in per-millisecond increments, making pricing far more precise and efficient, especially for workloads that scale dynamically.

Traditional hosting models (such as shared hosting and bare-metal providers) have also adapted, but the lines between “cloud” and “on-premises” are increasingly blurred. Hybrid and multi-cloud solutions like AWS Outposts and Azure Arc extend cloud capabilities into local data centres, while edge computing offerings like AWS Local Zones and CloudFront Functions reduce reliance on centralised resources, bringing compute power closer to end users and latency-sensitive applications.

This combination of scale, flexibility, and pricing innovation makes AWS particularly attractive for both small businesses and large enterprises. Startups can experiment and grow without prohibitive upfront costs, while established companies can fine-tune costs at scale through automation and optimisation. Ultimately, AWS’s pricing model encourages innovation—when customers succeed and scale, AWS benefits as well, creating a mutually reinforcing cycle of growth.

All business services experience fluctuations in demand, especially when new ventures are being launched or scaling rapidly. Cloud-based platforms provide the flexibility to handle these peaks and troughs far more effectively than older hosting models ever could.

In the past, traditional hosting packages required businesses to pay for a fixed amount of storage, bandwidth, and server capacity—regardless of actual usage. This “one size fits all” approach often meant paying for unused resources during quiet periods, while leaving companies scrambling to upgrade infrastructure during unexpected traffic spikes. Even when upgrades were possible, they were typically slow, manual, and disruptive.

The cloud market is no longer just about AWS versus traditional hosting. While Amazon Web Services remains a dominant provider, Microsoft Azure, Google Cloud, and newer players like Oracle Cloud, regional hyperscalers, and even decentralised cloud solutions now compete vigorously for enterprise workloads. At the same time, many legacy hosting providers have adopted cloud-like features, offering pay-as-you-go billing, elastic scalability, and Kubernetes-based orchestration that blur the line between “cloud” and “non-cloud.”

Cloud platforms themselves have become far more advanced. Features once requiring manual configuration—such as load balancing or auto scaling—are now powered by AI-driven predictive scaling and autonomous resource allocation, available in services like AWS Auto Scaling, Azure Autoscale, and Google Cloud’s predictive autoscaler. Fully managed Kubernetes offerings such as Amazon EKS, Azure AKS, and Google GKE allow developers to scale applications seamlessly without managing infrastructure directly.

Cost efficiency remains a central benefit, but the conversation has matured. Thanks to innovations like cheaper SSDs, optimised object storage, and AI-driven data compression, raw storage costs are less of a concern than they once were. Instead, businesses now focus on intelligent workload distribution, multi-cloud resilience, and carbon-aware scaling strategies to balance performance, cost, and sustainability.

In short, cloud storage and compute are no longer just about scaling up and down on demand—they are about building adaptive, distributed, and environmentally responsible systems that keep pace with both customer demand and global sustainability goals.

AWS allows developers to choose freely between the technologies available for delivering your systems.

You can build applications using multiple languages and frameworks, communicating with other services as necessary – letting you choose the right implementation tools for each of your services.

The fact that services are loosely coupled means that you can change approaches without significant maintenance issues in most cases. If your business undergoes major structural change, having your services deployed over the cloud puts you in a far better position to adapt.

Reliability is one of the central goals for anyone using, creating, or supplying a cloud service. Achieving near-continuous availability is difficult—the closer you get to 100% uptime, the harder (and more expensive) it becomes. Even a “four nines” promise (99.99% uptime) still allows for nearly an hour of downtime each year, which can be costly for businesses that depend on always-on services.

Amazon’s approach to this challenge has always been to provide customers with the tools to design resilient systems, rather than guarantee absolute reliability. By 2025, that toolkit has matured considerably:

• Global Resilience – You can deploy workloads across multiple Availability Zones and regions, ensuring redundancy if a server—or even an entire region—fails.
• Load Balancing – The older “Elastic Load Balancer (ELB)” term is now used mainly as an umbrella. AWS instead offers Application Load Balancer (ALB), Network Load Balancer (NLB), and Gateway Load Balancer (GWLB), each optimised for different traffic patterns and use cases. These services, combined with multi-cloud service meshes (e.g., AWS App Mesh, Istio), enable seamless traffic distribution across services and environments.
• Auto Scaling & Predictive Scaling – AWS Auto Scaling now incorporates machine learning–driven forecasting, which allows applications to scale proactively based on predicted demand rather than simply reacting to spikes.
• Monitoring & Observability – Amazon CloudWatch has expanded well beyond basic metrics. It now includes CloudWatch Logs Insights for advanced log analytics, CloudWatch Synthetics for canary testing, CloudWatch RUM (Real User Monitoring) for end-user experience tracking, and AI-powered anomaly detection to identify issues before they cause outages.
• Backup & Recovery – While manual EBS snapshots are still possible, AWS now emphasises Amazon Data Lifecycle Manager (DLM) for automated, policy-driven snapshot management. Additionally, EBS Snapshots Archive provides a low-cost storage tier for long-term retention of backups.
• Infrastructure as Code – AWS CloudFormation and newer tools like the AWS CDK (Cloud Development Kit) allow teams to define, provision, and update infrastructure in a consistent, automated way, reducing human error and operational overhead.
• Best Practices & Security – AWS Trusted Advisor continues to provide recommendations on reliability, performance, and security, now enhanced with AI-driven insights for proactive risk mitigation.

In short, AWS doesn’t promise perfection—but it gives developers the building blocks to design systems that are self-healing, distributed, and fault-tolerant. By leveraging redundancy, automation, and intelligent scaling, organisations can achieve levels of reliability that far exceed what was possible with traditional hosting models.

Amazon Simple Storage Service (S3) is often compared to a digital cloakroom: when you put data into S3 using secure access credentials, you receive a kind of “ticket” (commonly in the form of a pre-signed URL or temporary IAM role credentials). When you want your data back, you present that ticket, and S3 retrieves it for you.

Behind the scenes, S3 has evolved well beyond simply copying data onto “multiple computers.” Today, it uses advanced erasure coding, distributed storage systems, and automatic replication across multiple Availability Zones to ensure durability and resilience. For organisations that need even higher levels of availability and geographic reach, S3 Multi-Region Access Points (MRAP) provide intelligent routing across regions for low-latency access and built-in failover.

S3 remains a cornerstone of scalability for cloud applications. You can store and retrieve virtually unlimited amounts of data, from a single byte to petabyte-scale datasets, with new options like S3 Glacier Deep Archive for long-term retention and EBS Snapshots Archive for cost-efficient backups.

Security has also advanced significantly. While the “ticket” concept still applies, AWS now emphasises short-lived IAM role credentials instead of long-term developer keys. Block Public Access is enabled by default in most cases, reducing the risk of accidental exposure. Additionally, new features like S3 Object Lambda allow developers to transform and filter data as it is retrieved, enabling more flexible, secure, and efficient data delivery.

S3 is not just a storage service—it is a globally distributed, highly resilient data platform, seamlessly integrated with analytics, machine learning, and edge computing, making it one of the most reliable foundations for modern cloud applications.

Amazon Elastic Block Store (EBS) is designed to provide the persistent storage that servers need while they are running. This makes it especially relevant for workloads such as databases, enterprise applications, and file systems that require low-latency, high-performance block storage.

Over the years, EBS has expanded well beyond its original capabilities. Today, AWS offers multiple performance tiers, including:

• io2 Block Express volumes, supporting up to 256,000 IOPS and 4,000 MB/s throughput per volume, designed for the most demanding transactional workloads.
• gp3 volumes, a cost-effective option with adjustable performance, giving developers flexibility to scale IOPS and throughput independently of storage size.

EBS now also supports Multi-Attach for certain volume types, allowing a single volume to be attached to multiple EC2 instances at once—a feature especially useful for clustered applications and distributed file systems.

Snapshots remain a cornerstone of EBS, but they are no longer stored directly as visible S3 objects. Instead, they are kept in a proprietary, AWS-managed S3-backed system, designed for durability and security. Features like Fast Snapshot Restore (FSR) mean that snapshots can now be restored instantly, without the “warm-up” delays that once slowed down recovery times.

While snapshotting and backups were once a differentiator compared to traditional hosting companies, most major providers—including Azure, Google Cloud, and even evolved legacy hosts—offer robust snapshot and replication services. What still sets EBS apart is its tight integration with the AWS ecosystem, advanced automation tools, and unmatched performance tiers for mission-critical workloads.

Another feature of AWS worth highlighting is Amazon CloudWatch. Because developers and administrators do not have physical access to the hardware delivering their applications, AWS provides a powerful suite of interfaces for monitoring, managing, and optimising resources—and CloudWatch is central to that.

CloudWatch provides comprehensive monitoring, metrics, and observability tools for AWS workloads, often eliminating the need to build custom monitoring systems. It collects and analyses performance data, helping teams maximise their use of the platform while detecting and addressing issues before they impact users.

Over time, CloudWatch has grown into a much richer service:

• CloudWatch Metrics & Alarms remain core, but now include cross-account observability, enhanced custom metrics, and tighter integration with third-party observability platforms.
• AI-driven anomaly detection automatically identifies unusual patterns in metrics and logs, reducing the need for manual tuning.
• Predictive scaling leverages machine learning to forecast traffic patterns, allowing systems to scale ahead of demand rather than react to spikes.
• Auto Scaling policies have been enhanced with features like instance refresh (for rolling updates without downtime) and warm pools (pre-initialised instances that reduce scaling latency).

Together, these features make CloudWatch not just a monitoring service but a centralised observability and automation hub, giving businesses the tools to run systems that are both resilient and efficient at scale.

Amazon’s AWS Lambda, launched in 2014, is a mature, foundational service at the heart of modern cloud computing. Lambda pioneered the serverless model, where developers run code without managing servers, with compute automatically provisioned in response to events. This reduced operational overhead and allowed teams to focus on writing business logic instead of managing infrastructure.

Lambda has grown into a powerful ecosystem. Beyond its original “zero administration” promise, Lambda now integrates with a wide range of advanced tools and services:

• Workflow Orchestration – Services like AWS Step Functions and EventBridge Pipes make it easy to connect event-driven components into complex, reliable workflows.
• Enhanced Performance – Innovations such as Graviton4-powered Lambda functions deliver improved price-performance, while Lambda SnapStart significantly reduces cold-start times for Java workloads.
• Observability & Extensions – Developers can use AWS X-Ray and Lambda extensions to gain deeper insights into performance, security, and logging.
• Serverless Databases – Services like Aurora Serverless v2 and DynamoDB On-Demand provide backend storage that scales seamlessly alongside Lambda-powered applications.
• AI/ML & Emerging Tech – Lambda integrates with services like Amazon SageMaker and AWS Bedrock, enabling serverless AI/ML applications. Support for WebAssembly (WASM) broadens the languages and runtimes available, while multi-region deployment options expand use cases in resilience and compliance.

AWS Lambda has become one of the most popular services for building scalable, event-driven, low-cost applications, and remains a key tool for organisations looking to modernise workloads without heavy infrastructure management.