Building Resilient Cloud Workloads with AWS Well-Architected Reviews

Cloud Outages Are Inevitable. Is Your Business Prepared?

Earlier this week, AWS experienced a limited-service disruption in one of the eastern regions of the United States. Social media feeds filled with commentary. Some expressed outrage, others found opportunities to criticize, and the uninitiated were simply surprised. The truth is that while these events are rare, they do occur from time to time. Every service provider is susceptible. As a consumer of services directly or indirectly affected, your options are limited. But as a business, you should be prepared. The financial, reputational, and operational costs of an outage can be substantial. While the internet’s foundation is resilience, it’s a choice you must actively make for your solutions. The same goes for services deployed on AWS, Azure, or any cloud or data center provider.

Well-Architected as a Choice

AWS, as well as all of the leading cloud providers, provide a well-architected framework that guides you to building the right solutions in the cloud. Reliability is a foundational pillar of the AWS Well-Architected Framework, and at the core provides this guidance:

Resiliency is a shared responsibility between AWS and you […]
AWS is responsible for resiliency of the infrastructure that runs all of the services offered in the AWS Cloud. This infrastructure comprises the hardware, software, networking, and facilities that run AWS Cloud services. AWS uses commercially reasonable efforts to make these AWS Cloud services available, ensuring service availability meets or exceeds AWS Service Level Agreements (SLAs) […]
Your responsibility is determined by the AWS Cloud services that you select. This determines the amount of configuration work you must perform as part of your resiliency responsibilities. […] DR strategies may also make use of multiple AWS Regions. For example, in an active/passive configuration, service for the workload fails over from its active Region to its DR Region if the active Region can no longer serve requests.

Businesses continuously face trade-offs. In this case, the trade-off between investing in a sufficient DR strategy vs. the cost of a low-probability outage causing harm to your business. The good news is that the cost of doing something is not as high as many fear.

Resilience and Reliability on a Spectrum

Putting a DR strategy in place does not require breaking the bank. The path to resilience maturity can start with small steps.

For most organizations, the reliability and resilience roadmap can be broken down into four stages:

• Stage 0 – Hope & Heroics: No documented playbooks. The plan is Slack, smart people, and luck. Downtime is chaotic and customer updates lag.
• Stage 1 – At Least We Have a Plan: Runbooks exist, stakeholders know who is on point, but failover steps are mostly manual. Teams coordinate faster and communication remains consistent.
• Stage 2 – Assisted Automation: Core scenarios trigger scripted responses, observability drives action, and chaos tests happen regularly. Mean time to recover shortens as toil drops.
• Stage 3 – Self-Healing: Multi-region or multi-account patterns, automated runbooks, and human involvement is exception management, not firefighting. Incidents often resolve before customers notice.

Each step up the maturity curve unlocks a tangible outcome for founders and operators: improved customer confidence at Stage 1, measurable MTTR reduction (and fewer all-hands-on-deck nights) at Stage 2, and brand differentiation plus easier due diligence conversations at Stage 3.

Process and Planning to Stage 1

Reaching Stage 1 is about putting intentionality behind what has been tacit knowledge. The goal is to capture how your teams respond to disruption so that the next incident is faster, calmer, and easier to coordinate.

Key considerations when formalizing that first plan:

• Align on ownership: define who leads incident response, who communicates externally, and who has decision authority.
• Document playbooks: capture the manual steps operators already take, with links to dashboards, credentials, and escalation paths.
• Inventory dependencies: list critical third-party services, internal platforms, and data flows so you know what a failure could impact.
• Establish communications rhythm: predefine which channels to use (Slack, status pages, SMS) and when to escalate to leadership or customers.
• Rehearse the basics: schedule tabletop exercises or dry runs to walk through the documented plan before a real event forces the test.

Scripting your way to Stage 2

Stage 2 builds on the documented plan with lightweight automation and richer observability. The objective is not full autonomy yet—it is about reducing toil and shrinking the time to mitigation when people are already under pressure.

To bridge the gap between manual runbooks and assisted automation:

• Automate recurring tasks: script common mitigation steps such as scaling a service, draining queues, or toggling feature flags.
• Codify backups and restores: ensure snapshots, point-in-time restores, and data replication jobs are scheduled, monitored, and tested regularly.
• Instrument meaningful alerts: feed metrics, traces, and synthetics into alerting pipelines that point to action—not just noise.
• Centralize incident tooling: provide responders with a single pane (e.g., Chatbot, CloudWatch, etc.) to trigger scripts and view status.
• Validate with chaos experiments: run small, scoped failure injection tests to confirm the scripts work and teams trust the automation.

Introduce Self-healing to Stage 3

Stage 3 is where the workload can self-stabilize. Humans still play a role, but automation detects, responds, and often resolves incidents before a pager fires. The mindset shifts from response optimization to resilience engineering.

Guidance for progressing toward self-healing:

• Design for failure domains: adopt multi-AZ and, where justified, multi-region patterns with automated failover and data replication.
• Embed policy-driven remediation: use infrastructure-as-code and event-driven workflows (Step Functions, EventBridge, Lambda) to trigger corrective actions.
• Guardrail with immutable configurations: enforce deployment and configuration consistency through GitOps, preventing drift from reintroducing fragility.
• Close the feedback loop: feed incident learnings into resilience objectives, service-level indicators, and automated canaries.
• Measure what matters: track mean time to recover, error budgets, and automation coverage to sustain investment in self-healing capabilities.

Bottom Line

Most teams don’t know where to start. Getting started might be simpler than you think, you don’t need to boil the ocean. Start with an assessment of where you are, then build a pragmatic roadmap. Having a resilience strategy in place is not important until it is. And for some, the costs of failure may far exceed the investment in such a strategy.

Our team has helped many organizations, from startups, to small-to-medium businesses get started. It may be as simple as doing a well-architected review, something that may take a few days to complete, but would help you establish that starting point in your organization’s journey. We determine eligibility for a complimentary review based on workload readiness and scope, ensuring the engagement creates immediate value.

As part of the well-architected review assessment offering, Polymath Services performs a current state assessment of the six pillars of the well-architected framework:

• Operational Excellence: streamline operations with runbooks, observability, and continuous improvement loops.
• Security: protect data and workloads through least-privilege access, detective controls, and automated guardrails.
• Reliability: architect for fault isolation, recovery strategies, and change management that prevent cascading failures.
• Performance & Efficiency: match resources to workload demand, optimize architecture patterns, and monitor to avoid bottlenecks.
• Cost optimization: balance capability with spend by rightsizing, adopting managed services, and leveraging pricing models.
• Sustainability: reduce environmental impact with efficient architectures, scaling policies, and workload observability.

If you are either not on AWS or are partially on AWS and would like to discuss how migrating to AWS could help you build better resilience, our migration and modernization services are specifically designed for that. We typically start with an AWS Migration Readiness Discovery to validate scope, surface risks, and prioritize the first wave of workloads. For certain scenarios and/or workloads, AWS funding may be able to offset the cost of migration. Funding decisions and disbursement are handled by AWS; we support you in preparing the strongest possible case.

References

• Polymath Services Migration & Modernization Services
• AWS Well-Architected Framework: Shared Responsibility Model for Resiliency
• AWS Chatbot