Sergey Grebenshchikov, Software Developer in Munich, Bavaria, Germany
Sergey Grebenshchikov

Software Developer in Munich, Bavaria, Germany

Member since July 15, 2019
Since 2017, Sergey has been working as a consultant and engineer on DevOps projects for clients like Adidas, Siemens, Audi, and Tesla. He's acquired high-level design skills as well as hands-on development experience with major cloud platforms, containerized deployment targets (Docker/Kubernetes/ECS), and a variety of CI/CD infrastructures. He communicates clearly, efficiently, and proactively—ensuring the transparency and relevance of each task.
Sergey is now available for hire




Munich, Bavaria, Germany



Preferred Environment

Zsh, Git, VS Code, MacOS

The most amazing...

...project I've designed and developed was a symbolic execution based fuzzer/test generator and specification language for industrial control software.


  • DevOps Engineer

    2019 - 2020
    Tesla, Inc.
    • Designed and developed a greenfield CI/CD infrastructure, and migrated applications to it.
    • Built extensions for upstream tools to adapt them to client-specific workflows.
    • Set up logging and monitoring for infrastructure and applications, both via configuration of existing software as well as via custom tooling.
    Technologies: Shell, Continuous Delivery (CD), Linux, DevOps, Continuous Deployment, Helm, Kubernetes, Docker, Terraform, Go
  • Consultant | Product Engineer

    2019 - 2019
    Syncier GmbH (via Codecentric AG)
    • Developed back-end services and front-end applications for compliance-aware cloud resource management.
    Technologies: Shell, RxJS, Vuex, Vue, Jenkins, Kubernetes, Docker, Go
  • DevOps Consultant

    2018 - 2019
    Siemens AG (via Codecentric AG)
    • Ensured compliance with InfoSec requirements for an existing cloud-based CI/CD stack.
    • Simplified and modularized Terraform codebase, and defined module interfaces, enabling multiple teams to share and collaborate on infrastructure code with minimal overhead.
    • Developed various infrastructure tools in Go to support integrations with Terraform, Docker, AWS ECR, AWS Secrets Manager, Jenkins, and SonarQube.
    • Simplified and refactored Ansible-based provisioning of EC2 instances.
    • Replaced most dynamic provisioning operations with static images (Docker images and EC2 AMIs).
    Technologies: Bash Script, Shell, Amazon EC2, Continuous Delivery (CD), Amazon Web Services (AWS), Linux, DevOps, Continuous Deployment, Ansible, Jenkins, GitLab, Packer, Terraform, Docker, Go
  • Consultant

    2018 - 2018
    Audi Business Innovation GmbH (via Codecentric AG)
    • Defined the technical SLIs and outlined the SLAs for an existing centralized CI/CD platform, together with a role/responsibility allocation minimizing organizational friction.
    • Performed a quantitative technical analysis of CI/CD performance and availability issues, and a qualitative analysis of organizational constraints and bottlenecks.
    Technologies: Continuous Delivery (CD), DevOps, Continuous Deployment, Kubernetes, Docker, Jenkins, Go, R
  • Software Engineer

    2017 - 2018
    MX1 (via Codecentric AG)
    • Migrated an existing video-streaming app to Kubernetes; was responsible for the design, implementation, and task prioritization.
    • Conducted a performance analysis and developed the monitoring hooks and metrics.
    • Implemented extensions and refactored the app’s video processing pipeline.
    Technologies: Bash Script, Shell, Google Cloud Platform (GCP), Continuous Delivery (CD), Linux, DevOps, Continuous Deployment, Grafana, Prometheus, Kubernetes, Docker, FFmpeg, C, Go
  • DevOps Consultant

    2017 - 2017
    Adidas AG (via Codecentric AG)
    • Worked extensively on Kubernetes cluster infrastructure, built cluster-level/application-level monitoring using Prometheus, Grafana, cAdvisor, as well as application-specific custom metric collectors.
    • Taught courses on Docker and Kubernetes for developers and assisted teams with their transition to a DevOps workflow.
    • Developed project starter templates for Java (Spring Boot) and Node.js (Express.js) to facilitate recommended testing practices and provide immediate integration with the CI/CD environment and monitoring components.
    Technologies: Bash Script, Shell, Amazon EC2, Continuous Delivery (CD), Amazon Web Services (AWS), Linux, DevOps, Continuous Deployment, Elasticsearch, Kibana, Prometheus, Grafana, Express.js, Spring Boot, Jenkins, JavaScript, Java, Go, Kubernetes, Docker


  • JP

    A tool that generates terminal plots from JSON data (line plot, bar chart, scatter plot, heatmap, and histogram).

  • Piecewiselinear

    A tiny linear interpolation library for Go.

  • Terraform-module-versions

    This is a tool that checks for updates of external terraform modules referenced in the given Terraform source. It enables semantic versioning of Git-sourced Terraform modules, a feature otherwise only available when using modules from Terraform registries.

  • Flagvar

    Rich argument types for the Go standard library "flag" package.

  • Watchfs

    A self-contained, Docker-aware filesystem event reactor.

  • Versions

    Semantic versioning CLI—retrieval, querying, and an MVS constraint graph solver.

  • TCP-time

    A TCP connection latency analysis tool.

  • Synthesizing Software Verifiers from Proof Rules

    This paper was published in Proceedings of the 33rd ACM SIGPLAN Conference on Programming Language Design and Implementation.

    In this paper, we presented a method for the automatic synthesis of software verification tools. Our synthesis procedure takes input (a description of the employed proof rule, e.g., program safety checking via inductive invariants) and produces a tool. This tool then automatically discovers the auxiliary assertions required by the proof rule, e.g., inductive loop invariants and procedure summaries.

    We rely on a (standard) representation of proof rules using recursive equations over the auxiliary assertions. The discovery of auxiliary assertions—i.e., solving the equations—is based on an iterative process that extrapolates solutions obtained for the finitary unrollings of equations. We show how our method synthesizes automatic safety and liveness verifiers for programs with procedures, multi-threaded programs, and functional programs.

    Our experimental comparison of the resulting verifiers with existing state-of-the-art verification tools confirms the practicality of the approach.


  • Languages

    Bash Script, Go, Java, OCaml, SQL, F#, C, JavaScript, R, Python
  • Tools

    Terraform, Shell, Jenkins, Amazon ECS (Amazon Elastic Container Service), Docker Compose, Grafana, AWS CodeBuild, Packer, Helm, NGINX, VS Code, Git, Zsh, GitLab, AWS Fargate, GitLab CI/CD, Google Kubernetes Engine (GKE), Kibana, Amazon CloudFront CDN, Ansible
  • Paradigms

    Iterative Development, Continuous Deployment, Continuous Integration (CI), DevOps, Agile Software Development, Functional Programming, Continuous Delivery (CD)
  • Platforms

    Drone CI, Amazon Web Services (AWS), Docker, Kubernetes, Amazon EC2, Linux, MacOS, Google Cloud Platform (GCP), JVM
  • Other

    Site Reliability Engineering (SRE), CI/CD Pipelines, Prometheus, Simplicity, Presentations, Foreign Function Interfaces (FFI), Amazon Route 53, Domain Name System (DNS), Transport Layer Security (TLS), PKI
  • Frameworks

    Tachyons CSS, Spring Boot, Express.js
  • Libraries/APIs

    Vue, D3.js, FFmpeg, Libav, Amazon EC2 API, Atomic CSS, Vuex, RxJS, JMX
  • Storage

    Redis, PostgreSQL, SQLite, Elasticsearch, Amazon S3 (AWS S3), Google Cloud Storage


  • Master of Science (MSc) Degree in Informatik (Computer Science)
    2012 - 2015
    Technische Universität München - München, Germany
  • Bachelor of Science (BSc) Degree in Informatik (Computer Science)
    2008 - 2012
    Technische Universität München - München, Germany

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