We can organize an interview with Aldin or any of our 25,000 available candidates within 48 hours. How would you like to proceed?
Schedule Interview NowMy name is Taras S. and I have over 2 years years of experience in the tech industry. I specialize in the following technologies: Amazon Web Services, Google Cloud Platform, Microsoft Azure, Docker, Kubernetes, etc.. I hold a degree in Bachelor of Computer Science (BCompSc), Master of Computer Science (MSCS). Some of the notable projects I’ve worked on include: Full-Cycle Development From Scratch, Accelerated Environment Setup and CI/CD Implementation, DevOps Transformation for a .NET/C# Application, AWS Architecture Planning, Building CI/CD. I am based in Kremenchuk, Ukraine. I've successfully completed 4 projects while developing at Softaims.
I approach every technical challenge with a mindset geared toward engineering excellence and robust solution architecture. I thrive on translating complex business requirements into elegant, efficient, and maintainable outputs. My expertise lies in diagnosing and optimizing system performance, ensuring that the deliverables are fast, reliable, and future-proof.
The core of my work involves adopting best practices and a disciplined methodology, focusing on meticulous planning and thorough verification. I believe that sustainable solution development requires discipline and a deep commitment to quality from inception to deployment. At Softaims, I leverage these skills daily to build resilient systems that stand the test of time.
I am dedicated to making a tangible difference in client success. I prioritize clear communication and transparency throughout the development lifecycle to ensure every deliverable exceeds expectations.
Main technologies
2 years
1 Year
1 Year
1 Year
Potentially possible
To implement a full development cycle, from ideation to production, for a company's website and internal CRM system, including ongoing DevOps support.
To quickly set up new environments and CI/CD pipelines for a redesigned educational platform, enabling the client's development team to efficiently deploy and manage their application.
✅Project goal: To implement a scalable and efficient architecture solution for client, a growing FinTech company, that can effectively support the increased number of developers and projects, enabling them to meet the business demand for development. ✅Solution: I performed a thorough audit of the existing setup and drew a diagram of the planned setup. Based on my findings, I suggested a work scope that covered all the issues and challenges faced by the client. We decided to align our DevOps efforts with the development team's schedule, focusing on migrating from a monolithic to a microservices architecture. While the development team worked on migrating the stack, I prepared the infrastructure for the new setup. The application was already containerized, but since the new architecture required different recipes, I wrote custom recipes for each microservice, adhering to best practices in containerization. Since the client already had an existing infrastructure in Azure that met the new requirements, I decided to continue using Azure as the provider. With Infrastructure as Code (IaC) using Terraform, I managed the cloud resources. This made cloud-level changes transparent, traceable, and reproducible. The code described the state of Azure resources and allowed easy maintenance across multiple environments (dev, UAT, and prod). For autoscaling and reliability, I chose to orchestrate the microservices with Kubernetes. I opted for Azure's managed offering for Kubernetes (AKS), and I handled the setup of the cluster using IaC. Early on, I deployed a monitoring system to collect performance metrics and website logs. I used custom dashboards to display vital statistics and the real-time state of the cluster and applications deployed to it. This helped me set accurate autoscaling parameters. Once both infrastructure and containerization work were completed, the development team had written most of the microservices. This allowed me to write custom deployment packages for Kubernetes using Helm charts. Helm made it easier to manage and upgrade each application as a coherent package in the cluster with its own versioning. With the completion of Helm charts, I was able to create CI/CD pipelines to streamline builds and deployments. These pipelines ran builds, unit tests, and security analysis of the code, and then deployed it to the development environment. Features that reached sufficient stability were rolled out to UAT. After completing automatic end-to-end testing in UAT, I approved the deployment for rollout to production. Any failures triggered an automatic rollback to a previous version. Throughout the project, I gradually shared the documentation for all project layers (infrastructure, container recipes, Helm charts, CI/CD pipelines, security policies, and disaster recovery) with the client as I delivered milestones. I also updated the initial setup diagrams to include changes made during the implementation phase.
✅Project goal: The client's goal was to establish a scalable environment with seamless deployment on AWS, optimize the development workflow, and significantly reduce the time between code commit and deployment. ✅Solution: I started with a deep audit and provided a new architecture scheme suited to AWS services. I separated all components into independent AWS services. I chose EC2 for the main application on AWS Beanstalk, and I moved the DB to AWS RDS, keeping the data on S3. For CI, I used GitlabCI as our standard solution. And for CD, I utilized the AWS CodeDeploy service. During implementation, I conducted load tests and security checks. The main result of my work was boosting the performance of the web application. I managed to increase concurrent sessions up to ~1500 without impacting response time and functionality. I reduced the development cycle from push to deploy to ~10 minutes, ensuring zero downtime and configuring rolling updates. Besides that, I set up security policies and groups. I created a backup strategy and configured robust monitoring on AWS CloudWatch. I thoroughly documented all our activities and provided them to the customer.
Bachelor of Computer Science (BCompSc) in Computer science
2014-01-01-2018-01-01
Master of Computer Science (MSCS) in Computer science
2018-01-01-2020-01-01