Success Stories / Building a Highly Available AWS-Based Microservice Architecture

Building a Highly Available AWS-Based Microservice Architecture

A hybrid creative agency and software provider serving the event management industry partnered with Matoffo to eliminate operational bottlenecks threatening platform reliability and customer satisfaction.
Amazon ECSDevOps ConsultingGitLab CISaaS
24 min read

Executive Summary

A hybrid creative agency and software provider serving the event management industry partnered with Matoffo to eliminate operational bottlenecks threatening platform reliability and customer satisfaction.

Matoffo reengineered the infrastructure using AWS ECS, Amazon CloudFront, GitLab CI, AWS CodeDeploy, and Terraform to deliver a highly available, microservice-based architecture. 

The transformation delivered measurable business impact: deployment cycles accelerated from manual, error-prone processes to fully automated releases during peak holiday traffic, engineering productivity increased through the elimination of deployment-related incidents, and platform stability improved significantly.

Client Background

The client operates as a unique enterprise combining creative agency services with software development capabilities for the event management industry. The company enables businesses to streamline operations and gain actionable event intelligence through a unified platform that consolidates talent bookings, guest lists, event programs, task collaboration, and CRM functionality.

Serving clients across North America and Europe, the company positions itself as a “single source of truth” for event professionals, bringing together programmers, marketers, and content experts under one roof. The platform handles diverse workflows ranging from high-volume ticket sales during peak seasons to complex multi-stakeholder event coordination for corporate clients.

Client's Feedback

5.0
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"Matoffo delivered our cloud infrastructure and CI/CD pipeline transformation on time and exactly as promised. Throughout the engagement, their team maintained excellent communication through Slack and Google Meet, keeping us informed at every step. What impressed us most was their customer-oriented approach—they didn't just implement technology, they took time to understand our business challenges and designed solutions that truly fit our needs. We're extremely satisfied with the partnership and the operational foundation Matoffo built for our growth."

Founder & CEO,

Customer Challenge

As the client’s roster expanded and seasonal traffic patterns intensified, the company’s infrastructure struggled to support rapid feature deployment while maintaining platform stability. The business faced mounting pressure to deliver flawless releases during critical revenue periods, but existing manual processes created risk and operational friction.

Key Business Challenges:

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Revenue Risk from Deployment Failures:

Manual deployment processes required taking the platform offline during critical business hours, risking transaction loss during peak booking periods and damaging customer confidence. A single failed deployment during the holiday season could result in substantial revenue impact and client churn.
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Limited Release Velocity:

Engineering teams spent 40%+ of their time on deployment coordination, manual testing, and post-release monitoring rather than feature development. This operational overhead constrained the company's ability to respond to competitive pressure and customer feature requests, directly impacting growth potential.

These converging pressures threatened the company’s ability to maintain customer satisfaction, capture seasonal revenue opportunities, and scale the business profitably in an increasingly competitive market.

Goals and Requirements

To address infrastructure constraints and position the company for sustainable growth, the client established clear, measurable objectives spanning performance, financial impact, and operational resilience.

Performance Targets

  • Achieve Zero-Downtime Deployments:

    Eliminate all service interruptions during release cycles, enabling deployment during business hours and peak traffic periods without customer impact.

  • Accelerate Release Frequency:

    Reduce deployment cycle time from days to hours, enabling engineering teams to ship features and fixes multiple times per day with confidence and safety.

  • Improve Rollback Reliability:

    Implement automated rollback mechanisms capable of reverting to the last known stable version within minutes, minimizing mean time to recovery (MTTR) for any deployment issues.

Financial & Operational Targets

  • Reduce Infrastructure Costs by 30%+:

    Optimize resource utilization through containerization and auto-scaling, eliminating over-provisioning while maintaining performance headroom for growth.

  • Lower Operational Overhead by 40%:

    Automate manual deployment and configuration tasks, freeing engineering resources to focus on feature development rather than infrastructure maintenance.

Scalability & Reliability

  • Support 10x Traffic Growth:

    Design architecture to handle seasonal demand spikes and business expansion without degradation, using AWS auto-scaling and managed services to provide elastic capacity.

  • Achieve 99.9%+ Uptime SLA:

    Implement fault-tolerant microservice architecture with health monitoring, automated recovery, and multi-availability zone deployment to eliminate single points of failure.

The Solution

To transform the client’s deployment infrastructure and operational model, Matoffo implemented a comprehensive cloud-native architecture on AWS, emphasizing automation, resilience, and developer productivity. The solution was delivered through a structured approach that balanced immediate operational needs with long-term scalability requirements.

  1. 1

    Architecture Design & Technology Selection

    Matoffo conducted detailed discovery sessions with the client's technical and business stakeholders to map current pain points, traffic patterns, and growth projections. Based on this analysis, the team designed a microservice architecture using Amazon ECS with AWS Fargate for compute, avoiding the operational complexity and cost of a full Kubernetes implementation.
  2. 2

    Container Optimization & Image Standardization

    The development team containerized the client's application stack using Docker, implementing industry best practices including multi-stage builds, layer optimization, and application decoupling. These techniques reduced image sizes by 60%+, accelerated deployment times, and improved security by minimizing attack surface.
  3. 3

    CI/CD Pipeline Automation with GitLab CI

    Matoffo rebuilt the client's deployment pipeline from the ground up using GitLab CI, replacing fragile manual scripts with a fully automated workflow. The new pipeline handled code building, testing, Docker image creation, infrastructure provisioning, and application deployment without human intervention after code commits. Pipeline stages included automated testing gates, security scanning, and integration with AWS CodeDeploy for orchestrated deployments. The team implemented caching strategies and parallelization to optimize pipeline execution time, reducing build-to-deploy cycles from 45+ minutes to under 10 minutes.
  4. 4

    Blue/Green Deployment Implementation

    To achieve zero-downtime releases and safe rollback capabilities, Matoffo integrated AWS CodeDeploy into the deployment workflow. CodeDeploy orchestrated Blue/Green deployments, creating new infrastructure instances (Green), validating health, shifting traffic from old instances (Blue) to new instances, and maintaining old infrastructure for rapid rollback if issues emerged.
  5. 5

    Infrastructure as Code with Terraform

    All AWS infrastructure—including networking, compute, storage, load balancing, and security configurations—was codified using Terraform. Infrastructure definitions lived in version control, enabling peer review, change tracking, and automated provisioning of consistent environments.
  6. 6

    Monitoring, Security & Operational Excellence

    The solution included comprehensive monitoring using AWS CloudWatch for metrics, logs, and alarms. Automated alerts notified teams of performance anomalies, capacity issues, or deployment failures, enabling proactive response before customer impact.

Results and Impact

Before the solution:

The client’s deployment process required manual coordination across multiple team members, extensive testing windows, and service downtime during critical business hours. Infrastructure provisioning took days or weeks, deployments carried a significant risk of failure, and rollback procedures were unreliable and time-consuming. Engineering teams spent substantial effort on deployment coordination and firefighting, limiting their capacity for feature development and innovation. The operational model could not scale to support business growth without proportional increases in DevOps headcount.

After the solution:

Matoffo’s cloud-native architecture transformed operational capabilities and business agility. Deployments became fully automated, safe, and fast—executing in minutes rather than hours without service interruption. Engineering teams gained confidence to release updates during business hours and peak traffic periods, knowing rollback procedures were reliable and rapid. Infrastructure became elastic and cost-efficient, automatically scaling to meet demand without manual intervention or over-provisioning.

Quantitative Outcomes

  • 100% Zero-Downtime Deployment Achievement: All releases executed without service interruption, achieved through AWS CodeDeploy Blue/Green deployments and automated health validation. This eliminated revenue risk during peak booking periods and improved customer satisfaction by ensuring consistent platform availability.

  • 90%+ Reduction in Deployment Time: Deployment cycles decreased from 60+ minutes of manual coordination to under 10 minutes of automated execution, enabled by GitLab CI pipeline optimization, Docker containerization, and parallel testing strategies. Faster deployments accelerated time-to-market for features and reduced the opportunity cost of delayed releases.

  • Deployment Frequency Increased 5x: Engineering teams shifted from weekly deployment windows to multiple daily releases, enabled by automated testing, one-click deployments, and confidence in rollback safety. Higher release velocity improved competitive responsiveness and customer satisfaction through faster bug fixes and feature delivery.

  • 40% Reduction in Infrastructure Costs: AWS Fargate auto-scaling and container optimization eliminated over-provisioned capacity while maintaining performance headroom. Cost predictability improved through Infrastructure as Code and monitoring, enabling accurate budget forecasting and eliminating surprise infrastructure expenses.

  • Rollback Time Reduced from Hours to Under 5 Minutes: AWS CodeDeploy’s automated rollback eliminated manual recovery procedures, achieved by maintaining previous deployment artifacts and enabling one-click reversion. Reduced mean time to recovery (MTTR), minimized business impact of deployment issues, and improved overall platform reliability.

Qualitative Outcomes

  • Engineering Productivity and Morale: Elimination of manual deployment tasks and deployment-related incidents freed 40%+ of engineering time for feature development and innovation. Teams reported higher job satisfaction through reduced operational toil, fewer weekend incident responses, and greater focus on strategic initiatives.

  • Operational Resilience and Confidence: Automated health checks, comprehensive monitoring, and reliable rollback procedures created organizational confidence in the deployment process. Teams deployed fearlessly during business hours, knowing issues could be detected and resolved rapidly without customer impact.

Key Learnings

  • Right-Sizing Technology Choices for Business Context

    The client initially requested a Kubernetes-based solution; however, Matoffo’s consultative approach identified that Amazon ECS with AWS Fargate better aligned with the company’s operational maturity, team skills, and cost constraints. This decision reduced complexity, accelerated time-to-value, and lowered total cost of ownership while delivering all required functionality.

  • Automation as Risk Reduction, Not Just Efficiency

    While automation improved deployment speed, its greatest value emerged through risk reduction and improved reliability. GitLab CI eliminated human errors in manual deployments, AWS CodeDeploy’s Blue/Green strategy provided safe rollback mechanisms, and Infrastructure as Code prevented configuration drift. These automation investments transformed deployments from high-risk events to routine, predictable operations.

Next Steps

With a modern, automated infrastructure foundation now in place, the client is positioned to unlock additional business value through strategic platform enhancements. The following initiatives build directly on the deployed architecture to deepen operational insights and further accelerate development velocity.

  1. 1

    Intelligent Observability for Proactive Performance Management

    The next phase will implement advanced monitoring using AWS X-Ray for distributed tracing, Amazon CloudWatch Insights for log analytics, and custom business metrics dashboards. These tools will provide visibility into user journey performance, identify revenue-impacting bottlenecks before they affect customers, and enable data-driven optimization decisions.
  2. 2

    Expanded Automation and Quality Assurance

    Building on the CI/CD foundation, the client will integrate comprehensive automated testing, including API contract tests, load testing, and security scanning directly into the deployment pipeline. Additional quality gates will prevent releases that degrade performance, introduce security vulnerabilities, or fail reliability thresholds—further reducing deployment risk while enabling even higher release velocity.

Conclusion

Matoffo’s partnership with the client illustrates how strategic infrastructure modernization can create transformational business value beyond mere technical improvements. By replacing fragile manual processes with automated, resilient cloud-native architecture, the company gained the operational foundation required to scale profitably and compete effectively in a demanding market.

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