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Testimonials
Good consultants execute on task and deliver as planned. Better consultants overdeliver on their tasks. Great consultants become full technology partners and provide expertise beyond their scope.
I am happy to call MeteorOps my technology partners as they overdelivered, provide high-level expertise and I recommend their services as a very happy customer.
Working with MeteorOps was exactly the solution we looked for. We met a professional, involved, problem solving DevOps team, that gave us an impact in a short term period.
I was impressed at how quickly they were able to handle new tasks at a high quality and value.
We were impressed with their commitment to the project.
From my experience, working with MeteorOps brings high value to any company at almost any stage. They are uncompromising professionals, who achieve their goal no matter what.
Thanks to MeteorOps, infrastructure changes have been completed without any errors. They provide excellent ideas, manage tasks efficiently, and deliver on time. They communicate through virtual meetings, email, and a messaging app. Overall, their experience in Kubernetes and AWS is impressive.
They are very knowledgeable in their area of expertise.
They have been great at adjusting and improving as we have worked together.
I was impressed with the amount of professionalism, communication, and speed of delivery.
We got to meet Michael from MeteorOps through one of our employees. We needed DevOps help and guidance and Michael and the team provided all of it from the very beginning. They did everything from dev support to infrastructure design and configuration to helping during Production incidents like any one of our own employees. They actually became an integral part of our organization which says a lot about their personal attitude and dedication.
You guys are really a bunch of talented geniuses and it's a pleasure and a privilege to work with you.
Nguyen is a champ. He's fast and has great communication. Well done!
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Free Project Planning: We dive into your goals and current state to prepare before a kickoff.
Pay-as-you-go: Use our capacity when you need it, none of that retainer nonsense.
Experts On-Demand: Get new experts from our team when you need specific knowledge or consultation.
We Don't Sleep: Just kidding we do sleep, but we can flexibly hop on calls when you need.
Ad-hoc Calls: When a video call works better than a chat, we hop on a call together.
How it works?
HashiCorp Packer is a tool designed to automate the creation of machine images across multiple platforms from a single configuration. It simplifies the process of image creation for cloud, virtual, and physical environments by integrating with various builders such as AWS, Azure, and Google Cloud, and provisioning tools like Chef and Ansible. This ensures consistent, repeatable builds, enhancing security and reducing potential errors. Packer supports immutable infrastructure practices by facilitating the use of disposable images, making the deployment process more efficient and manageable. Its extensive documentation and strong community support further aid in its adoption for infrastructure management and deployment tasks.
Continuous Integration is a mode of work where multiple programmers can integrate changes continuously into the same code.
The foundation of successful collaboration lies in the agreement on facts, while the key to achieving development velocity is through conducting experiments in the form of tests to validate the code's functionality.
Continuous Integration facilitates both of these processes by creating two distinct processes:
- The first process allows developers to agree on the "true" codebase, commonly called the master branch or trunk.
- The second process validates the codebase after changes are made using tests.
For startups, it is crucial to have processes in place that enable collaboration, and enhance the delivery of changes in a consistent, predictable, and safe manner. This is typically achieved by running automated tests after the introduction of a change into a Git branch or after creating a Pull-Request. If the tests fail or if the branch is not up-to-date with the latest changes from the main branch, the change to the code cannot be introduced to the main version of the code. Such measures ensure that non-working changes are not introduced into the main branch, instilling confidence in introducing changes to the system.
HashiCorp Packer automates the creation of machine images across cloud and on-prem platforms from a single, version-controlled template. It is used to standardize base images, reduce configuration drift, and make provisioning faster and more repeatable.
- Builds identical images for multiple targets from one template, improving consistency across environments and providers.
- Supports a broad set of builders including AWS AMIs, Azure images, Google Compute Engine images, VMware, and VirtualBox, making it practical for hybrid and multi-cloud estates.
- Encourages immutable infrastructure by baking OS configuration and dependencies into images instead of mutating long-lived servers.
- Integrates with common provisioners such as shell, Ansible, and Chef, enabling repeatable setup steps and fewer environment-specific discrepancies.
- Produces versioned artifacts that fit CI/CD workflows, allowing images to be tested, promoted, and rolled back predictably.
- Improves security hygiene by centralizing hardening, baseline configuration, and patching in a controlled build pipeline.
- Reduces manual effort and human error by replacing ad hoc “golden server” processes with automated, auditable builds.
- Creates an audit trail when templates and build pipelines are stored in source control, supporting compliance and change management.
- Shortens instance provisioning time by pre-installing packages and configuration during the image build rather than at boot.
- Works well for standardized node images in autoscaling groups, VM fleets, and Kubernetes worker nodes where fast, consistent scaling matters.
Packer tends to work best when paired with image testing and scheduled rebuilds so artifacts stay current with security updates. It can add build pipeline complexity compared to boot-time configuration only, but typically improves reliability and startup time for scaled workloads.
Common alternatives include AWS EC2 Image Builder, Azure Image Builder, and using configuration management alone with Ansible or Chef without image baking. For more detail on the tool’s components and workflow, see Packer documentation.
Our experience with HashiCorp Packer helped us build practical patterns, templates, and delivery checklists that make image pipelines repeatable across teams and environments. Through real implementations, we learned how to standardize base images, reduce configuration drift, and shorten the path from code change to compliant machine images.
Some of the things we did include:
- Designed reusable Packer templates and a shared “golden image” library for Linux and Windows, aligned to CIS-style hardening and internal security baselines.
- Implemented multi-cloud image builds (AWS AMIs, Azure Managed Images, and GCP images) from a single source configuration to keep environments consistent across platforms.
- Integrated Packer builds into CI/CD pipelines with GitHub Actions for automated validation, build promotion, and artifact versioning.
- Built end-to-end pipelines that publish images and metadata to internal catalogs, including changelogs, SBOM references, and deprecation timelines.
- Added automated validation steps using smoke tests and policy checks (e.g., OpenSCAP, package allowlists, and patch-level gates) before images were promoted.
- Standardized secrets handling for image builds using HashiCorp Vault to avoid embedding credentials and to support short-lived tokens.
- Optimized build times by caching dependencies, reducing provisioner churn, and splitting image layers into base + application variants for faster iteration.
- Implemented image lifecycle management (retention rules, cleanup automation, and “latest stable” channels) to reduce cloud sprawl and lower operational risk.
- Enabled Kubernetes node image pipelines for managed clusters, including consistent OS configuration for autoscaling node groups and blue/green node rollouts.
- Delivered enablement sessions and runbooks so platform and security teams could maintain templates, troubleshoot builders, and enforce standards over time.
This experience helped us accumulate significant knowledge across multiple Packer use-cases, from secure golden images to CI-driven image promotion. It enables us to deliver high-quality HashiCorp Packer implementations that are maintainable, auditable, and aligned with real operational constraints.
Some of the things we can help you do with HashiCorp Packer include:
- Assess your current image build process and deliver a findings report with risks, quick wins, and recommended standards.
- Create an adoption roadmap that defines target platforms, ownership, versioning, and rollout milestones across teams.
- Implement repeatable Packer templates and pipelines for multi-cloud and on-prem images from a single source configuration.
- Integrate image builds into CI/CD with automated validation, artifact publishing, and promotion workflows.
- Establish security and compliance guardrails (hardening baselines, secrets handling, and provenance) to support audit-ready images.
- Optimize build performance and cost by reducing provisioning time, caching dependencies, and tuning builder/provisioner strategies.
- Standardize golden images and base layers that align with your Terraform and IaC practices.
- Troubleshoot flaky builds and drift issues, improving reliability with test steps, logging, and repeatable debugging workflows.
- Enable your team with hands-on training, template patterns, and delivery checklists to scale image pipelines safely.
