ULUKBEK ISAKOV

Environment: AWS, Terraform, Jenkins, GitHub Actions, Kubernetes, Docker, Prometheus, Grafana, ArgoCD, Ansible, Python, Bash, CI/CD, Agile

• Implemented GitHub Actions for continuous integration to automate code quality and formatting checks, replacing manual Jenkins pipeline steps for faster feedback and improved CI/CD workflow separation
• Led Kubernetes migration for a high-impact application, coordinating with developers and stakeholders to create a detailed migration plan, implementing testing and validation processes, and deploying the application to production, ensuring seamless performance and scalability
• Upgraded EKS clusters from version 1.27 to 1.28, using AWS CLI for control plane updates and Terraform with Jenkins pipelines for automated rollout
• Resolved node upgrade issues by troubleshooting with Spot Ocean and implementing manual node detachments to ensure smooth deployment
• Implemented AWS Load Balancer Controller to replace NGINX Ingress, optimizing Kubernetes traffic management by integrating AWS-native services (ALB, NLB, ELB) and enabling Terraform-based Infrastructure as Code for scalable, resilient deployments
• Streamlined VPC connectivity by transitioning from VPC Peering to AWS Transit Gateway, reducing network complexity, improving scalability for new AWS accounts, and centralizing VPC and on-premises connections for efficient, scalable infrastructure management
• Led AWS cost-optimization initiative by identifying inefficient compute resource usage, implementing a scheduled Lambda function for automatic EC2 shutdowns, and proposing Reserved Instances for stable production environments, resulting in 40% cost savings and streamlined resource management
• Migrated Terraform monorepo to a microservice-oriented structure, separating components into dedicated repositories, implementing data sources to maintain cross-service dependencies, and restructuring CI/CD pipelines, resulting in safer updates, improved scalability, and streamlined infrastructure management
• Improved system observability by refining Prometheus and Grafana configurations, creating targeted alerts and reducing incident response times by 20%, leading to higher service uptime and faster issue resolution
• Implemented GitLeaks-based security workflow in GitHub Actions to detect and report sensitive data exposure (e.g., API keys, usernames) in code, generating readable reports for quick issue resolution
• Created a reusable workflow to streamline implementation across repositories, ensuring enhanced code security
• Strengthened security and compliance by implementing role-based access control (RBAC) within Kubernetes clusters, limiting access based on roles and responsibilities, minimizing unauthorized access risks, and ensuring adherence to security policies
• Environment: AWS, Terraform, Jenkins, GitHub Actions, Kubernetes, Docker, Prometheus, Grafana, ArgoCD, Ansible, Python, Bash, CI/CD, Agile

Environment: AWS, Terraform, Jenkins, GitLab CI, GitHub, Kubernetes, Docker, Ansible, SumoLogic, Datadog, ELK Stack, Python, Bash, CI/CD, Agile

• Reorganized Terraform codebase into modular components (EKS clusters, RDS databases, S3 buckets) by breaking down a monolithic repo into individual modules, each stored in dedicated GitHub repositories with customized pipelines, leading to improved scalability, manageability, and faster code deployment
• Implemented a phased Terraform upgrade to bring infrastructure closer to the latest standards, addressing compatibility and security improvements step-by-step while introducing modular configurations, enhancing maintainability and aligning with best practices
• Led EKS upgrade from Kubernetes 1.23 to 1.24, coordinating Terraform and Jenkins for infrastructure updates, aligning Helm charts to new API requirements, and validating internal and third-party applications with ArgoCD and integration tests to ensure security and stability
• Optimized Hazelcast deployment across six AWS regions by transitioning from Community to Enterprise edition and leveraging Terraform and Ansible for infrastructure consistency, reducing the number of instances from 80 to 12 and achieving substantial cost savings
• Optimized AWS ElastiCache Redis infrastructure to reduce costs by analyzing CloudWatch metrics for CPU and memory utilization, proposing downsizing options, and consolidating pre-production clusters
• Led a seamless cutover using Terraform and a custom Bash script for data migration, achieving substantial savings on the AWS bill while maintaining performance
• Enhanced security configuration management by automating rule updates with a GitHub-triggered pipeline, enabling on-demand adjustments and seamless security rule enforcement, improving compliance while reducing manual intervention
• Enhanced visibility into AWS Spot instance autoscaling activities by developing a Python-based Lambda function to retrieve scale-in and scale-out logs from Spotinst and forward them to SumoLogic for centralized monitoring
• Designed and built a SumoLogic dashboard to visualize scaling activity, enabling correlation with production incidents and improving scalability insights
• Developed a robust monitoring solution for GitHub Actions self-hosted runners by integrating GitHub's API with Datadog, using a Python Lambda function deployed via Terraform
• Implemented alerts in Slack and PagerDuty for downtime or unavailable runners, ensuring high CI/CD reliability and immediate on-call response to disruptions
• Built a reusable Jenkins library of over 30 Groovy modules, eliminating redundant code and enabling consistent, streamlined updates across 50+ pipelines to enhance scalability and reliability, critical in a high-paced deployment environment
• Led 'demonolithing' initiative for Java microservices by separating components into dedicated repositories, creating CI/CD pipelines per service, and enabling automated syncs via ArgoCD, resulting in faster, independent deployments and improved scalability
• Developed an automated Jenkins pipeline for DoorDash promotions, integrating AWS, Terraform, and EKS to dynamically deploy full infrastructure stacks for each campaign, enabling seamless, non-technical initiation of promotions and reducing manual effort through automated logging and monitoring with the ELK stack
• Environment: AWS, Terraform, Jenkins, GitLab CI, GitHub, Kubernetes, Docker, Ansible, SumoLogic, Datadog, ELK Stack, Python, Bash, CI/CD, Agile

Environment: Linux, Windows, AWS (EC2, S3, VPC), Bash, VPN, Firewalls, Load Balancers, Jenkins, CI/CD, Agile

• Automated server maintenance by creating custom Bash scripts to monitor backup integrity, archive and compress old log files, and manage resource cleanup, reducing manual intervention by 30% and improving system reliability
• Led migration of critical on-premises applications to AWS, assisting in configuring VPCs, setting up EC2 instances, and securing S3 storage for backups, which improved scalability and disaster recovery options for key systems
• Established secure network configurations by deploying firewalls, setting up VPN tunnels, and configuring load balancers, strengthening the network infrastructure and ensuring reliable connectivity across multiple locations
• Created a basic CI/CD pipeline using Jenkins to automate internal tool deployments, enabling automated build, test, and deployment processes that reduced deployment time by 25% and minimized human error
• Implemented monitoring protocols for system performance, analyzing logs and metrics for CPU, memory, and disk usage, and proactively addressing performance bottlenecks to maintain stability in production environments
• Optimized server configurations for Linux and Windows systems, tuning settings to improve memory allocation, disk I/O, and CPU scheduling, which increased server efficiency and extended system uptime
• Developed documentation for new processes and workflows created during the migration to AWS and automation efforts, improving knowledge sharing across teams and aiding onboarding of new team members
• Provided technical support for network and server issues, coordinating with other IT teams to troubleshoot and resolve infrastructure problems, achieving 95% issue resolution within the first 24 hours
• Environment: Linux, Windows, AWS (EC2, S3, VPC), Bash, VPN, Firewalls, Load Balancers, Jenkins, CI/CD, Agile