Packer Advanced Training
Run a tested golden image pipeline with manifests, HCP Packer channels and Terraform consumption under clear governance. Learn Packer through a clear Foundation to Advanced path, with hands-on labs, live cohort options, certification support and full LMS access.
Last updated
Self-paced video subscription
Billed yearly at ₹9,996. This includes all four levels, complete LMS access for one year, plus 20+ additional courses and 50+ tools access.
- All four Packer levels in one price.
- 20+ additional courses and 50+ tools included, even when subscribing to one course.
- Best fit for learners who want full-library access and flexible progress.
Live & Interactive session
Instructor-led cohort, max 8 to 10 hours, with demos, labs, Q&A, assignments and practical review.
- Live small-batch cohort from soon.
- Interactive discussion and lab troubleshooting.
- Recommended for teams that need guided implementation.
1:1 Live training
The same agenda, taught one-to-one by the trainer. Start immediately, without waiting for the next batch. Max 8 to 10 hours, one-to-one.
About Packer Advanced Training.
Understand where Packer fits in modern software delivery, what this level covers, and how the program builds practical confidence step by step.
Program overview
Packer is taught as a practical technical skill for modern engineering, operations and platform teams. The course explains where the tool fits, how it is used in real delivery environments, and how learners can apply it through guided practice.
This DevOpsSchool Packer program is built for working professionals who want usable skills instead of only conceptual exposure. The training emphasizes live examples, workflow clarity, operational controls and progressive skill depth from Foundation to Advanced.
Private Packer training for delivery teams, platform groups and engineering organizations.
DevOpsSchool provides corporate Packer training for teams that need faster adoption, workflow standardization, administrative control, integration guidance and governance-ready rollout. Private batches can be aligned to development practice, release workflow, access model, maturity level and internal tooling.
- Private online or classroom delivery for engineering teams
- Aligned to Packer usage maturity, admin depth and collaboration patterns
- Useful for rollout, migration, governance and workflow consistency goals
- Can be tailored for developers, administrators, DevOps teams and leadership stakeholders
Why teams use DevOpsSchool
DevOpsSchool combines live demonstration, practical workflow discussion, implementation-oriented examples, and strong post-session learning support. That makes the training more usable for real teams than generic slide-led courses.
Choose any level. The page still shows the full progression.
Foundation, Essential, Intermediate and Advanced are presented as one linked training flow. Self-paced buyers get all levels by default, even if they start from only one course page.
Instructor-led, self-paced and corporate delivery options.
Compare delivery format, duration, level access and batch style. Fees are shown only in the top decision panel and once again after the agenda.
| Duration | Mode | Level access | Batch |
|---|---|---|---|
| 8 to 10 Hrs. max | Live & Interactive | Advanced | Public batch |
| 8 to 10 Hrs. max | 1:1 Live training | Advanced | Starts immediately |
| 1 year LMS access | Self-paced video | All 4 levels | Anytime access |
| 5 Days | Corporate | Packer Advanced Training | Private team batch |
What learners should be able to do after Packer training.
The outcomes are written for practical delivery teams: developers, DevOps engineers, release engineers, administrators and technical leads.
Build machine images as code
Write HCL2 Packer configurations that produce repeatable images for clouds and containers.
Bake hardened, ready images
Provision secure application images with shell and Ansible and debug builds quickly.
Automate image delivery
Run tested, governed image pipelines that feed Terraform and auto scaling deployments.
Why this skill, what you will achieve, and who should attend.
Use this section to decide whether the course matches your role, current experience and expected Packer responsibilities before reviewing the detailed agenda.
Why Packer matters
- Packer helps teams standardize a critical part of their software delivery, infrastructure, automation or operations workflow.
- It gives learners a repeatable way to move from basic usage to confident execution in team and enterprise environments.
- For DevOps and platform teams, Packer becomes more valuable when connected with automation, governance, monitoring and delivery practices.
- Teams using Packer effectively reduce ad-hoc execution and move toward consistent engineering standards.
Objectives
- Understand Packer concepts, architecture, terminology and operational usage patterns.
- Learn practical configuration, workflow design, access controls, team usage and quality practices.
- Apply Packer in real delivery workflows using automation, integrations, traceability and governance patterns.
- Build practical confidence to use Packer for individual, team and organizational use cases.
Pre-requisites
- Basic computer literacy and familiarity with software development workflows.
- Helpful but not mandatory: introductory DevOps, cloud, automation or software delivery awareness.
- No deep programming background is required for the Foundation and Essential levels.
Who this course is for
- Developers, administrators and engineers who need practical Packer usage skills.
- DevOps engineers, release engineers, SREs and platform teams managing delivery standards.
- Engineering leads and technical managers responsible for workflow quality, access controls and governance.
- Corporate teams migrating to or standardizing on Packer.
Small-batch live training starts every month.
Weekday batches start on the 1st and weekend batches on the first Saturday of every month. One-to-one (1:1) training can start immediately; corporate sessions are scheduled on demand.
Weekend live batch
Starts on the first Saturday of every month. Weekend sessions with demos, labs and Q&A; max 10 learners.
Weekday live batch
Starts on the 1st of every month. Weekday sessions for working professionals and distributed teams; max 10 learners.
Ask advisorAgenda depth up to the selected level.
This page shows the learning flow from Foundation through Advanced. Each level adds to the previous one, and the agenda stops at the current page level. Day counts are for corporate (day-wise) delivery; live online batches cover the same agenda in max 8 to 10 hours.
Foundation Level: Packer concepts, installation, workflow and CLIDay 1
- Getting to know Packer: what Packer is, machine images as code and immutable infrastructure
- Installing Packer: package managers or binary install, packer version and plugins via packer init
- The Packer workflow and components: sources, builders, provisioners, post-processors and plugins
- HCL2 configuration basics: the packer block, required_plugins, source and build blocks in .pkr.hcl files
- The Packer CLI: init, fmt, validate, inspect, build and console
- Builders overview: amazon-ebs, azure-arm, googlecompute, vsphere-iso, docker and qemu
- Where Packer fits: Packer versus Dockerfiles and Terraform in an image and infrastructure toolchain
- AWS access for builds: IAM permissions, named profiles and environment variables
- First image: build a Docker image with a shell provisioner and inspect the result
- Image lifecycle basics: build, test, publish, deprecate and delete
- Licensing and ecosystem: HashiCorp BSL licensing, HCP Packer and community plugins
Essential Level = Foundation + baking AWS AMIs with variables and provisionersDay 2 · 2 days cumulative
- Baking a website image for EC2: the end-to-end flow from base AMI to a ready web server image
- Selecting an AWS AMI base: the amazon-ami data source and source_ami_filter with owners and most_recent
- Automating the AWS AMI base build: amazon-ebs settings, instance type, ssh_username and timestamped ami_name
- Using build variables: variable blocks, types, defaults, .pkrvars.hcl files, environment variables and locals
- Provision Hello World: shell provisioner with inline commands and scripts
- Provisioning a basic site: installing NGINX, file provisioner for web content and enabling the service
- Multiple builds: several sources or regions in one build, only and except filters and parallel builds
- Post-processors: manifest, shell-local, docker-tag and docker-push
- Windows images: WinRM communicator, PowerShell provisioner and windows-restart
- Sharing AMIs: ami_users, ami_regions copies, tags and KMS encryption
- Team workflow: Packer configurations in Git, peer review and naming and tagging conventions
Intermediate Level = Essential + configuration management, debugging and hardened imagesDay 3 · 3 days cumulative
- Customization with a configuration management tool: simplifying provisioning with Ansible
- Using Ansible to install the web server: ansible and ansible-local provisioners, playbooks and roles
- Debugging: PACKER_LOG=1, the -debug step mode, -on-error=ask and the breakpoint provisioner
- Building hardened images: using Ansible modules to harden SSH, users, sysctl and auditd
- CIS benchmark alignment: applying CIS hardening roles and checking with OpenSCAP or Lynis
- Baking a Jenkins image: Java, Jenkins packages, plugins and configuration as code baked in
- Secrets during builds: never baking secrets and reading them from Vault or AWS Secrets Manager data sources
- Other provisioners: Chef, Puppet and Salt options and the file provisioner for configuration
- Image cleanup: removing SSH host keys, resetting cloud-init, clearing caches, history and logs
- Multi-cloud builds: Azure managed images and Compute Gallery and Google Cloud images from one configuration
- Local images: building Vagrant boxes with VirtualBox or QEMU for developer machines
- Plugin management: packer plugins install, version pinning and upgrading JSON configs with hcl2_upgrade
Advanced Level = Intermediate + image pipelines, testing, HCP Packer and governanceDays 4-5 · 5 days cumulative
- Building a pipeline for Packer images: validating Packer configurations with packer validate and fmt -check
- Creating a manifest profile: manifest post-processor output, artifact IDs and metadata for later steps
- Testing images: Goss, InSpec or Testinfra checks during the build and after launch
- CI pipeline: Jenkins, GitHub Actions or GitLab CI building images on commit and on a schedule
- HCP Packer: artifact registry, buckets, channels, ancestry tracking and revocation
- Consuming images in Terraform: HCP Packer data sources or AMI lookups and rolling Auto Scaling group updates
- Golden image strategy: base, hardened and application layers and a regular patch cadence
- Security scanning: Amazon Inspector or Trivy scans and SBOM generation for images
- Governance: approved base images, tagging policies, deprecation and cleanup of old AMIs
- Performance and cost: smaller build instances, spot instances, parallel builds and caching
- Multi-account distribution: sharing images across AWS Organizations accounts and regions securely
- Capstone: an automated golden image factory with hardening, tests, registry and Terraform consumption
Choose live training or a full year of self-paced access.
If someone buys Foundation, Essential, Intermediate or Advanced as self-paced video, the price stays the same and access is granted to all four levels by default.
Self-paced video subscription
Billed yearly at ₹9,996. This includes all four levels, complete LMS access for one year, plus 20+ additional courses and 50+ tools access.
- All four Packer levels in one price.
- 20+ additional courses and 50+ tools included, even when subscribing to one course.
- Best fit for learners who want full-library access and flexible progress.
Live & Interactive session
Instructor-led cohort, max 8 to 10 hours, with demos, labs, Q&A, assignments and practical review.
- Live small-batch cohort from soon.
- Interactive discussion and lab troubleshooting.
- Recommended for teams that need guided implementation.
1:1 Live training
The same agenda, taught one-to-one by the trainer. Start immediately, without waiting for the next batch. Max 8 to 10 hours, one-to-one.
- Start immediately: no waiting for the monthly batch.
- One learner, one trainer: full attention on your questions.
- Sessions planned around your working hours.
- Your pace, with examples from your own projects and tools.
Method of training and assessment.
The course emphasizes practical demonstration, hands-on labs and assignment-based validation instead of passive lecture-only learning.
| SL | Method of training and assessment | Weightage |
|---|---|---|
| 1 | Understanding the problem space | 5% |
| 2 | Concept discussion | 10% |
| 3 | Live demo and walkthrough | 25% |
| 4 | Lab and hands-on exercises | 50% |
| 5 | Assignments and evaluation | 10% |
Labs, exercises and real workflow practice.
Every level moves from explanation to hands-on practice, review and troubleshooting.
Build your first image with Packer
Install Packer, initialise the Docker plugin and build a container image with a shell provisioner using HCL2.
Bake a website AMI for EC2
Select an Ubuntu base AMI with a data source, provision NGINX and site content with variables, and launch an EC2 instance from the new AMI.
Bake a hardened Jenkins image
Use Ansible inside Packer to build a CIS-hardened Jenkins AMI, debug a failing step with breakpoints and verify the hardening score.
Run a golden image factory
Build a CI pipeline that validates, builds, tests and scans images, publishes them to HCP Packer channels and rolls them out with Terraform.
Packer is taught as part of a working delivery ecosystem.
You learn where the tool sits in the wider engineering workflow, not in isolation.
Core foundations
Terminology, concepts, architecture and the operating model behind the tool.
Workflow traceability
Map practical work to tasks, approvals, documentation and delivery visibility.
Automation and integration
Use Packer with validation checks, automation hooks and delivery workflows.
Governance controls
Operate with permissions, approvals, policy checks and production-safe workflows.
How your practical work is assessed.
Your certificate is backed by labs, assignments, capstone thinking and completion evidence.
Assignments
Level-specific assignments verify setup, configuration, workflow quality and operating discipline.
Hands-on validation
Learners are expected to complete practical usage, automation and troubleshooting exercises.
Completion record
Certificate issuance is tied to demonstrated participation, practical completion and course-level coverage.
Led by Rajesh Kumar and the DevOpsSchool practitioner network.
Training is grounded in practical DevOps, SRE, security, release and platform engineering experience with real enterprise delivery context.
Earn a DevOpsSchool Packer certificate.
Completion includes a digital certificate with credential details, practical assignments and a learning record aligned to the selected Packer level.
Certificate verificationCertificate of Completion
Packer Advanced Training
Unique credential ID, verifiable online
What learners say about training with Rajesh Kumar.
“Rajesh is very good trainer. Rajesh was able to resolve our queries and question effectively. We really liked the hands-on examples covered during this training program.”
“Very well organized training, helped a lot to understand the AWS concept and detailed related to various tools. Very helpful”
“The training was very useful and interactive. Rajesh helped develop the confidence of all.”
Rated 4.6 on Google · All testimonials · Video reviews on YouTube
Quoted as published, from learners in Rajesh Kumar's live trainings across DevOpsSchool courses.
Used by developers, DevOps engineers, release leads and engineering managers.
Private batches are available for teams that want the same agenda aligned to their own tools and workflows.
Why this Packer path is different.
The value is not only one course. The subscription unlocks the full learning ecosystem for one year.
| Feature | DevOpsSchool Packer Training | Typical short course |
|---|---|---|
| Levels | Foundation, Essential, Intermediate, Advanced | Single generic syllabus |
| Self-paced access | All four levels plus 20+ courses and 50+ tools | Usually one course only |
| Live training | Demos, labs, Q&A and assignment review | Often lecture-heavy |
| Certificate | DevOpsSchool completion certificate | Varies by provider |
Questions learners ask before joining.
Does Foundation cost less than Advanced?
No. Self-paced pricing is intentionally the same because access includes all four levels by default.
What is included in the yearly subscription?
One year of complete LMS access, all four levels for the selected course, plus 20+ additional courses and 50+ tools access.
Can corporate teams request customization?
Yes. The live format can be aligned to team tools, governance requirements, workflows and internal delivery standards.
What is the recommended sequence?
Foundation → Essential → Intermediate → Advanced. The agenda is designed so each level builds on the previous one.
Talk to DevOpsSchool before choosing the batch.
Use this support section for batch questions, corporate planning, LMS access clarifications, or guidance on which Packer level fits your team.
India / Worldwide: +91 99057 40781
USA: +1 (469) 756-6329
Email: contact@DevOpsSchool.com
Chat on WhatsAppExtend the course with articles, explainers and workflow guidance.
Continue learning with supporting articles that connect Packer practices to DevOps, automation, governance and delivery workflows.
Training snapshots and certificate preview.
A look at the completion certificate and the course.
Certificate preview
See what course completion evidence looks like.
Tool-focused training
Course visuals reinforce the Packer workflow and subject area.
Live batch experience
Training supports live online, private team and workshop-style delivery.
Start Packer Advanced training.
Next weekday batch starts on the 1st; weekend batch on the first Saturday. Batches are capped at 10 learners. Send your details and DevOpsSchool will share the syllabus and batch options.