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Sercan Topcu
Verified Expert in Engineering
DevOps Engineer and Developer
Austin, TX, United States
Toptal member since March 28, 2024
Bio
Sercan is a DevOps/site reliability engineer with hands-on experience across AWS, Google Cloud Platform (GCP), and Kubernetes. At 2K Games, he improved observability with Datadog and Argo CD, built proactive alerts, and cut AWS and GCP costs by 20%. At Apple, Sercan implemented GitOps deployments using Argo CD, Flux, and Terraform, reducing errors and accelerating releases. Skilled in CI/CD, infrastructure as code, and cloud monitoring, he will be a great addition to any team.
Portfolio
2K Games
Amazon Web Services (AWS), Google Cloud Platform (GCP), Argo CD, Amazon EKS...
Apple (Advantis Global)
Cloud, Containerization, Orchestration, GitOps, Scripting...
Delta Airlines
Containerization, Cloud, Infrastructure as Code (IaC), CI/CD Pipelines, GitOps...
Experience
- Linux - 7 years
- Cloud Platforms - 6 years
- CI/CD Pipelines - 5 years
- Kubernetes - 5 years
- Terraform - 5 years
- Monitoring - 4 years
- GitOps - 4 years
- Kustomize - 3 years
Work Experience
DevOps / Site Reliability Engineer
2024 - PRESENT
2K Games
- Leveraged cloud platform expertise in AWS and Google Cloud Platform (GCP), along with Kubernetes, specifically Amazon EKS and Google Kubernetes Engine (GKE), to ensure high availability and scalability of infrastructure.
- Automated infrastructure provisioning and product deployment using Terraform, Helm, and Argo CD.
- Enhanced deployment strategies by optimizing CI/CD pipelines with GitHub Actions.
- Monitored and troubleshooted production environments, improving system availability and reducing downtime through proactive monitoring using Datadog, Prometheus, and Grafana.
- Contributed to cross-functional collaborations and engaged in process improvements for more effective automation.
- Analyzed and optimized costs by identifying opportunities for cloud resource efficiency.
Technologies: Amazon Web Services (AWS), Google Cloud Platform (GCP), Argo CD, Amazon EKS, Google Kubernetes Engine (GKE), Helm, Service, Cloud Platforms, Terragrunt, Terraform, GitOps, Monitoring, Linux, GitHub Actions
DevOps Engineer
2023 - 2024
Apple (Advantis Global)
- Developed and managed a robust Kubernetes ecosystem with Amazon EKS, optimized for different stages, from development to production.
- Implemented Flux CD with Kustomize for automated, environment-specific deployments and enhanced network security using Cilium network policies.
- Centralized Dockerfile management, leveraging Amazon Elastic Container Service (ECS) and Amazon Elastic Container Registry (ECR) for efficient container orchestration and registry.
- Maintained a Helm chart repository using Helm releases for precise application deployment.
- Managed a consolidated Terraform repository with Terragrunt, integrating AWS services for comprehensive infrastructure management.
- Gained experience with Bash scripting for automation and operational efficiency.
- Utilized Datadog and Prometheus for metric analysis and streamlined troubleshooting.
- Developed custom Splunk queries and dashboards for complex debugging and performance analysis.
- Handled on-call responsibilities, integrating PagerDuty for effective incident management.
Technologies: Cloud, Containerization, Orchestration, GitOps, Scripting, Infrastructure as Code (IaC), Monitoring, CI/CD Pipelines, Terraform, Linux, Helm, Service, Cloud Platforms, AWS CloudFormation, Terragrunt, Argo CD, GitHub Actions
DevOps Engineer
2021 - 2023
Delta Airlines
- Specialized in Kubernetes containerization, deploying and scaling applications using Helm charts and Docker.
- Managed Kubernetes applications across AWS and GCP services.
- Streamlined deployment with Terraform, enhancing infrastructure management and workflow efficiency.
- Managed Google Cloud SQL instances for critical application databases, ensuring high availability, and utilized Google Cloud Memorystore as a caching layer to improve application response times.
- Maintained and optimized GitHub Actions for CI/CD, automating testing and deployment processes.
- Implemented data pipelines to stream application logs into BigQuery for centralized analysis and explored the use of BigTable as a scalable NoSQL database solution for storing and querying large datasets efficiently.
- Monitored system performance with Prometheus and Grafana, creating insightful dashboards for decision-making.
- Developed basic automation tools and scripts in Python, focusing on continuous skill enhancement.
Technologies: Containerization, Cloud, Infrastructure as Code (IaC), CI/CD Pipelines, GitOps, Monitoring, Logging, Terraform, Google Cloud Platform (GCP), Google Kubernetes Engine (GKE), Linux, Memorystore, Google BigQuery, Google Cloud SQL, Google Bigtable, Helm, Cloud Platforms, AWS CloudFormation, Jenkins, GitHub Actions
DevOps Engineer
2020 - 2021
J.Crew
- Implemented and maintained AWS security best practices, managing IAM roles and policies and provisioning AWS resources.
- Designed, implemented, and maintained CI/CD pipelines using GitHub Actions and Jenkins, optimizing application and service deployment workflows.
- Automated application deployments in AWS using Terraform, focusing on efficient traffic management with AWS load-balancing solutions, including Elastic Load Balancing (ELB), Application Load Balancer (ALB), and Network Load Balancer (NLB).
- Collaborated with development teams to ensure applications are designed for scalability, reliability, and security.
- Provisioned GCP services using Terraform, managing Virtual Private Clouds (VPCs), Google Cloud Storage (GCS), auto-scaling policies and groups, and security groups.
- Experienced in using Ansible for automated configuration management and writing playbooks.
Technologies: Cloud, CI/CD Pipelines, Infrastructure as Code (IaC), Configuration Management, Terraform, Google Cloud Platform (GCP), Google Kubernetes Engine (GKE), Linux, Memorystore, Google BigQuery, Google Cloud SQL, Google Bigtable, Cloud Platforms, Jenkins, GitHub Actions
Cloud Engineer
2018 - 2020
Motorola Solutions
- Created, deployed, and maintained AWS infrastructure, including Amazon Elastic Compute Cloud (EC2), VPC, Amazon Simple Storage Service (S3), and Amazon RDS, focusing on scalability and robustness.
- Improved the reliability and performance of cloud applications and infrastructure on AWS.
- Monitored cloud infrastructure for performance, security, and cost efficiency.
- Managed AWS Auto Scaling Groups (ASG) for the high availability of applications.
- Handled AWS Identity and Access Management (IAM) roles and policies, ensuring secure access and permissions.
Technologies: Cloud, Amazon Web Services (AWS), AWS IAM, Amazon EC2, Amazon Virtual Private Cloud (VPC), Linux, Cloud Platforms, GitHub Actions
Project History
A GitOps Workflow Using Argo CD and Terraform to Reduce Deployment Errors
As a DevOps engineer at Apple, I designed and implemented a GitOps-based deployment workflow for our mobile app infrastructure using Argo CD and Kustomize, supporting development, test, stage, and production environments on Amazon EKS.
I provisioned and managed the infrastructure with Terraform using Terragrunt to eliminate code duplication across environments and ensure consistent deployments.
Applications were containerized using Docker and deployed via Kubernetes, with Argo CD ensuring continuous synchronization between Git and the live environment.
For observability, I integrated Datadog for real-time performance metrics, Prometheus for custom monitoring and alerting, and Splunk for centralized log analysis. I also configured PagerDuty for on-call management and automated incident escalations.
RESULTS
Reduced deployment errors, improved infrastructure consistency, and significantly accelerated rollout cycles through automation and GitOps best practices.
I provisioned and managed the infrastructure with Terraform using Terragrunt to eliminate code duplication across environments and ensure consistent deployments.
Applications were containerized using Docker and deployed via Kubernetes, with Argo CD ensuring continuous synchronization between Git and the live environment.
For observability, I integrated Datadog for real-time performance metrics, Prometheus for custom monitoring and alerting, and Splunk for centralized log analysis. I also configured PagerDuty for on-call management and automated incident escalations.
RESULTS
Reduced deployment errors, improved infrastructure consistency, and significantly accelerated rollout cycles through automation and GitOps best practices.
CI/CD Pipeline for Tier 3 AWS Web App
As a DevOps engineer at Delta Air Lines, I built a full CI/CD pipeline for a tier 3 AWS web app, including the front end, back end, and database. I utilized Terraform to provision infrastructure, including VPCs, Amazon EC2 instances, and Amazon RDS.
I used GitHub Actions to automate testing, build Docker images, and deploy to appropriate environments, such as development, stage, and production. I also handled secure secrets management and environment-specific variables.
RESULTS
The pipeline improved release speed by approximately 40% and reduced manual steps, providing a more secure and reliable deployment workflow.
I used GitHub Actions to automate testing, build Docker images, and deploy to appropriate environments, such as development, stage, and production. I also handled secure secrets management and environment-specific variables.
RESULTS
The pipeline improved release speed by approximately 40% and reduced manual steps, providing a more secure and reliable deployment workflow.
Datadog Monitoring and Argo CD for EKS/GKE Clusters
As a site reliability engineer at 2K Games, I established observability for Kubernetes workloads running on Amazon EKS and GKE. I deployed Datadog Agents and Operators using Argo CD by structuring them as GitOps applications:
• Agent YAML (kind: Datadog) was managed in an agent/folder.
• Operator YAMLs were in an operator/folder with values.yaml to define properties like fullnameOverride: datadog-operator.
This approach ensured consistent agent deployment and version control across clusters.
Also, I created custom Datadog dashboards and configured monitors for CPU, memory, request rates, and errors. Alerts were routed to PagerDuty for production and Slack for non-production.
Argo CD also managed app deployments, ensuring sync between Git and cluster state, reducing drift, and enabling fast rollbacks.
RESULTS
As a result, I improved visibility and enabled faster incident detection and safer deployments.
• Agent YAML (kind: Datadog) was managed in an agent/folder.
• Operator YAMLs were in an operator/folder with values.yaml to define properties like fullnameOverride: datadog-operator.
This approach ensured consistent agent deployment and version control across clusters.
Also, I created custom Datadog dashboards and configured monitors for CPU, memory, request rates, and errors. Alerts were routed to PagerDuty for production and Slack for non-production.
Argo CD also managed app deployments, ensuring sync between Git and cluster state, reducing drift, and enabling fast rollbacks.
RESULTS
As a result, I improved visibility and enabled faster incident detection and safer deployments.
Education
2011 - 2015
Bachelor's Degree in Hotel and Hospitality Management
Mugla University - Mugla, Turkiye
Certifications
MAY 2025 - MAY 2028
AWS Certified Solutions Architect
Amazon Web Services (AWS)
JANUARY 2025 - JANUARY 2027
HashiCorp Certified: Terraform Associate
HashiCorp
JANUARY 2024 - JANUARY 2027
Certified Kubernetes Application Developer
Cloud Native Computing Foundation
FEBRUARY 2023 - FEBRUARY 2026
Certified Kubernetes Administrator
Cloud Native Computing Foundation
NOVEMBER 2022 - NOVEMBER 2025
AWS Certified Cloud Practitioner
Amazon Web Services (AWS)
Skills
Libraries/APIs
Terragrunt
Tools
Terraform, Google Kubernetes Engine (GKE), Helm, AWS CloudFormation, Amazon EKS, Logging, AWS IAM, Amazon Virtual Private Cloud (VPC), Jenkins, Kustomize, GitHub, Slack, Splunk
Paradigms
DevOps, Continuous Development (CD), Continuous Integration (CI), Continuous Delivery (CD), Management
Languages
Bash Script, Python, Bash, SQL, YAML
Platforms
Kubernetes, Google Cloud Platform (GCP), Linux, Amazon Web Services (AWS), Docker, Amazon EC2, Cilium, AWS IoT, PagerDuty
Storage
Google Cloud SQL, NoSQL, Google Bigtable, Datadog
Frameworks
Flux
Other
Cloud Platforms, GitOps, CI/CD Pipelines, Rio, Complex Problem Solving, Smart Solutions, Monitoring, GitHub Actions, Infrastructure as Code (IaC), Memorystore, Service, Cloud, Containerization, Orchestration, Scripting, Configuration Management, Google BigQuery, Argo CD, Amazon RDS, Prometheus
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