AI Log Analyzer
Analyze logs, detect failures, and get clear explanations, root causes, and actionable insights.
View on GitHubDevOps Engineer building automation
and AI-powered systems
I build and maintain reliable infrastructure, automate operational workflows, and implement AI-powered solutions for practical business automation.
Six years of experience across infrastructure, DevOps, automation, Linux systems, CI/CD, and production support. That covers both cloud and on-prem environments — building and maintaining deployment pipelines, managing servers and containers, writing operational automation, and keeping things running under real conditions.
I'm currently focused on expanding toward AI-powered workflow automation. The interest is practical: using LLM APIs to handle repetitive operational tasks — classification, data extraction, structured output from unstructured inputs — and integrating those capabilities into existing tools rather than building isolated demos.
I work well with small teams and independent businesses that need infrastructure that holds up, deployments that don't require manual intervention, and a clear direction toward automating more of the operational layer. Also exploring automated systems in trading and crypto.
Cloud and on-prem infrastructure design, provisioning, and maintenance. Terraform-managed, reproducible environments across all stages — no snowflake servers.
End-to-end deployment pipelines with testing, security scanning, and environment promotion. Workflows that ship code reliably, without manual steps or hero deployments.
An active direction: using LLM APIs to automate repetitive workflow tasks — classification, data extraction, and structured output from unstructured inputs. Focused on integration into existing tools, not standalone prototypes.
Custom systems that eliminate repetitive manual work — data processing pipelines, operational dashboards, reporting automation, and alert handling that actually closes the loop.
Observability stacks, alerting tuned to reduce noise, performance profiling, and runbooks. Systems that fail predictably, surface the right information, and recover fast.
A selection of tools focused on DevOps automation, incident analysis, and infrastructure understanding.
Analyze logs, detect failures, and get clear explanations, root causes, and actionable insights.
View on GitHubGenerate architecture documentation from Terraform, Kubernetes, and config files — including services, dependencies, risks, and runbook insights.
View on GitHubAnalyze any public GitHub repository and get a structured technical review — architecture, tech stack, risks, and improvement suggestions.
View on GitHubOwned reliability across cloud infrastructure, containerized services, and CI/CD pipelines. Handled on-call rotations and incident response, and set up monitoring and alerting to reduce noise and surface real issues early.
Executed repository migrations from Bitbucket to GitHub, preserving commit history, access controls, and CI workflows. Managed OS upgrades from Ubuntu Focal to Noble on production systems, handling dependency compatibility to keep services stable throughout.
Built and maintained CI/CD pipelines and deployment workflows across multiple services, focusing on repeatability and reducing manual operations. Worked with infrastructure-as-code and cloud provisioning to standardize environments across teams.
Participated in on-call rotations and incident response, contributing to production stability and improving deployment reliability over time.
Managed Linux-based systems across on-prem and cloud environments, handling provisioning, configuration, and operational scripting. Supported application deployments and troubleshooting, building the foundation for transitioning into full-time DevOps work.
Most of my non-work time is spent outside or doing things that require full attention.
Open to collaborations, freelance work, and interesting projects.