Advascale

The Advascale Team audited the entire infrastructure and proposed to implement the DevOps practice of modeling developer workflow for operational tasks. We proposed to improve continuous integration and layer them into the cloud process.The disposable development environments are implemented in Kubernetes and separated by namespaces. DNS and Kubernetes namespace naming is taken from short-lived feature branches, as an id of the linked task. For each opened Merge Request a separate deployment was created and will be destroyed on closure.GCP resources like VPC, GKE cluster, Container registry, and others were created using Terraform.CI/CD is implemented using GitHub workflow and actions. Unit, status, and e2e tests are reused from the existing workflows.The new workflow is triggered by pull request actions and executes tests as steps. After the passed test is built an application docker image and the application is deployed to the Kubernetes cluster.The GKE Autopilot reduces the operational cost of managing clusters, optimizes clusters, and yields higher workload availability. There is no necessity in monitoring the health of your nodes or calculating the amount of compute capacity that your workloads require.With a disposable development environment, Advascale facilitated the Axle development team to accelerate innovation, security, and compliance.

We created a dynamic environment for working with test branches and a staging environment. The production version of the application is isolated and runs in a separate cluster; we implemented monitoring and logging. The application is deployed in a Kubernetes cluster, and an unlimited number of test environments and staging were provided, along with a separate cluster for production.By setting up the scalability we make the cloud more efficient: ensuring the maximum available power with an increased load, and more economical even at minimum traffic. Ultimately, the client received the most flexible development environment and fault-tolerant production.Boiler finance is launched and allows to compare finance simply get a boiler quote online now in under 20 seconds.

The result of the project is:Cost decreased six times;Real-time visibility into cloud spending achieved;High availability and scalable architecture performed;All unused instances, EIPs, and other resources optimized;​New architecture allowed to invest less time in managing services.The new infrastructure is now deployed in three accounts within the Ireland region. All services for every account were analyzed to reduce costs and plan appropriately for resource resizing, resource sizes, and reservations.The total cost has been reduced to $5800 per month, down from $17000 per month.Therefore, Enra’s IT infrastructure has become more scalable, cost-efficient, and reliable due to the AWS features implemented by Advascale.

Advascale successfully migrated the company’s system to the new infrastructure, ensuring scalability, optimized costs, and ensure high availability across multiple Availability Zones.Advascale needed to calculate the AWS cost of one tenant (stage/prod) and the implementation part cost for proofing of values and cost efficiency, which the Client can obtain with this transition. Other essential metrics were the performance of the new cloud infrastructure and the opportunity to manage its web app environment efficiently.Advascale calculated with AWS Pricing Calculator and found several tips on decreasing costs compared with Heroku prices. For example, some services like CloudFront have a Free Tier - the first 1TB per month of data transfer out to the internet, and 10 million HTTP/HTTPS requests from all Edge locations will be free (excludes CloudFront China). Estimates for production and stage were about 388,48 $/Mo without cost-saving and about 332,03 $/Mo with the cost-saving option “1 year no upfront”.With Advascale’s solution, RoR stack does not have any limitation in scalability during load activity peaks. Advascale also adopted the advantageous cloud cost model ensured by EKS scaling. The Client also achieved lower network latency.