School of Scientific Computing & Informatics · DevOps & cloud
DevOps for Scientific Software
Scientific software increasingly runs as shared services and production pipelines. This course teaches the DevOps practices that keep them reliable: automated testing and delivery, containers, orchestration and infrastructure as code.
Course overview
DevOps for Scientific Software covers the delivery pipeline from commit to production: branching strategies, automated tests and builds with GitHub Actions, container images, and deployment to cloud and on-premises servers.
The second half introduces Kubernetes for running services and batch jobs, infrastructure as code with Terraform, secrets management, monitoring and logging, with the regulatory and data-protection considerations specific to life-science organisations.
Learning outcomes
By the end of the course you will be able to:
- Design Git branching and review workflows for a team
- Build CI/CD pipelines with automated tests and releases
- Build secure, minimal container images
- Deploy services and batch jobs on Kubernetes
- Manage infrastructure as code with monitoring and secrets in place
Skills you will practise
Eligibility and prerequisites
Who can apply
- Students and graduates in any science, engineering, pharmacy, medicine, agriculture, geography or computing programme (B.Sc., B.Tech., B.E., BCA, M.Sc., M.Tech., MCA, PhD)
- Researchers, faculty and working professionals in research, healthcare, biotech, pharma or IT who want to apply computing to science
- Final-year students may apply before their results are declared
Prerequisites
- Linux command line
- Git basics and some programming
Best suited to
- Bioinformaticians and developers in research and biotech teams
- Research IT staff
- Students aiming at bio-IT and platform-engineering roles
Module-wise syllabus
6 modules. Each pairs instructor-led sessions with a hands-on lab on public data.
Topics
- Branching strategies
- Code review and protected branches
- Semantic versioning
Topics
- GitHub Actions workflows
- Test matrices and caching
- Automated releases
Topics
- Dockerfiles and layers
- Minimal and reproducible images
- Image scanning and registries
Topics
- Kubernetes objects
- Services and batch jobs
- Helm charts
Topics
- Terraform
- Secrets and access control
- Monitoring, logging and alerts
Topics
- Design
- Automation
- Runbook
Practical sessions and projects
Capstone project
Automate a scientific service
Build the CI/CD, containers, infrastructure and monitoring for a scientific service, and document how to operate it.
Assessed on the correctness of the analysis, the quality of the code and the reasoning in the write-up. A pass is required for the certificate.
- Collaborative development
Set up a repository with review rules, templates and automated changelogs.
- Continuous integration and delivery
Build a pipeline that tests, builds and publishes a scientific package on every release.
- Containers
Containerise a pipeline tool, shrink the image and scan it for vulnerabilities.
- Orchestration
Deploy a web service and a batch analysis job on a local Kubernetes cluster.
- Infrastructure and operations
Provision infrastructure with Terraform and add monitoring and alerting.
- Project: a production pipeline
Deliver an automated, monitored deployment of a scientific service with a written runbook.
Software, tools and datasets
Software and tools
All software is free and open source or free for academic use. Recommended computer: 8 GB RAM, 30 GB free disk, Linux, macOS or Windows with WSL2.
Datasets
- Open-source scientific tools: Material for CI/CD and containerisation.GitHub
Core reading
- Kim G, Humble J, Debois P, Willis J. The DevOps Handbook, 2nd edition. IT Revolution, 2021.
- Kurtzer GM, Sochat V, Bauer MW (2017). Singularity: scientific containers for mobility of compute. PLOS ONE 12:e0177459.
Duration, format and fees
- Next cohort
- Dates are sent with your admission offer
- Timetable
- Three evening or weekend sessions a week (IST), plus a lab clinic; intensive and weekend-only schedules on request
- Payment
- Secure online payment link with your admission offer (UPI, cards, net banking). Instalments on request for fees above ₹15,000.
- Refunds
- See the refund and cancellation policy.
Instructor
The instructor for each cohort is named in your admission offer and on this page when the cohort is announced. Vedicgen instructors are selected for hands-on research or industry experience in the subject they teach, and every course is reviewed by a second subject expert.
Questions about who teaches a cohort? [email protected]
Certificate
Learners who complete the course and pass its capstone receive a Vedicgen certificate of completion for DevOps for Scientific Software, issued by Vivofold, stating the guided hours and skills assessed. Each certificate has a unique ID and QR code that anyone can check.
Apply for DevOps for Scientific Software
Apply
Send the form below. It takes about five minutes.
Review
An adviser confirms your fit and format within two working days.
Offer
You receive dates, timetable and a secure payment link.
Onboard
Set-up guide, pre-reading and joining links.
Frequently asked questions
In the live cohort, modules are taught in instructor-led sessions with a weekly lab clinic where you work on real public data with help at hand; every session is recorded. The self-paced format uses the same lessons, labs and datasets with mentor review of your capstone. Both formats end with an assessed project reviewed for the code and the science.
A laptop with at least 8 GB of RAM and about 30 GB of free disk space, running Linux, macOS, or Windows with WSL2. Docker Desktop or a Linux machine with Docker is needed. Installation instructions are sent before the first session, and lab clinics help with any set-up problems.
Yes. Learners who complete the course and pass its assessment receive a Vedicgen certificate of completion, issued by Vivofold. Every certificate carries a unique ID and a QR code that anyone, including an employer or admissions office, can check on the certificate verification page.
Apply with the form on this page. Live and in-person cohorts run through the year; the dates, timetable and joining details of the next cohort are sent with your admission offer and listed on this page once announced. Self-paced enrolment opens as soon as your application is accepted.
Yes. No course runs longer than four weeks, and the length is customisable: choose the standard schedule, an intensive one- to two-week schedule, weekends only, or a custom timetable. Pick your preference on the application form; colleges and teams can book their own dates.
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