Hospitality app creator
Streamlined AWS Deployment Solution Accelerates Success
The customer had a killer idea for an application to sell hotel reservations and required expert help to containerize it and deploy it in Amazon Web Services (AWS) following best practices.
outcomes
tools & technology
The Challenge
Taking the burden off IT
To enable their developers to prioritize business logic development and meet market demands during peak seasons, they sought to alleviate the challenges of IT operations by implementing a seamless AWS deployment solution.
The Solution
Transforming Concepts into Scalable Architectures
Enter Allata. Our specialists took the application concept and designed a highly-available, elastic, and cost-effective architecture based on the Amazon Elastic Kubernetes Service (EKS). All the AWS
infrastructure derived from this architectural design and subsequent changes there of were described and managed as code using Terraform. Our team also brought in their expertise in Docker to build efficient and secure container images for the application components and devised clever ways to orchestrate these containers with Kubernetes allowing for auto scaling and Canary releases with zero downtime. We set up CI/CD pipelines on Azure DevOps that let the developers effortlessly build, analyze,
test and deploy their code to multiple environments at the push of a button. Last but not least, we enabled the mechanisms through which logs, metrics and traces were collected and sent to Datadog for
detailed monitoring of the application and underlying infrastructure.
THE RESULTS
Accelerating Success with Streamlined Efficiency
The implementation of containers introduced a consistent operations model by simplifying the management of application components and leveraging familiar processes and tools. Following best practices from Kubernetes and AWS, the system achieved resilience, high availability, and self-healing capabilities. Edge caches and auto-scaling ensured optimal performance even during peak traffic. Operations and infrastructure management automation allowed developers to focus solely on application development, resulting in improved productivity and faster delivery. The system mitigated risks with automated canary deployments and CI/CD pipelines by enabling early bug detection and confident production rollouts. Auto-scaling optimized resource allocation, enhancing cost efficiency by provisioning compute resources based on demand. The system provided continuous observability through logging, monitoring, and distributed tracing via Datadog, allowing for proactive monitoring, performance analysis, and efficient issue resolution.
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