Software Alternatives, Accelerators & Startups

Packer VS Google Kubernetes Engine

Compare Packer VS Google Kubernetes Engine and see what are their differences

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Packer logo Packer

Packer is an open-source software for creating identical machine images from a single source configuration.

Google Kubernetes Engine logo Google Kubernetes Engine

Google Kubernetes Engine is a powerful cluster manager and orchestration system for running your Docker containers. Set up a cluster in minutes.
  • Packer Landing page
    Landing page //
    2023-09-15
  • Google Kubernetes Engine Landing page
    Landing page //
    2023-02-05

Packer features and specs

  • Multi-Provider Support
    Packer supports a wide variety of providers such as AWS, Azure, Google Cloud, VMware, and more. This allows for flexibility and the ability to create machine images across different environments.
  • Automation
    Packer automates the creation of machine images, eliminating the need for manual image configuration and reducing the potential for human error.
  • Script Reusability
    Packer allows for the reuse of scripts and configuration files, enabling a consistent and repeatable process for image creation.
  • Parallel Builds
    Packer can build multiple images in parallel, which can significantly speed up the provisioning process.
  • Idempotency
    Packer ensures that the output machine image is always an identical result given the same input configuration, reducing the risk of inconsistencies.

Possible disadvantages of Packer

  • Steep Learning Curve
    The variety of features and flexibility that Packer offers can make it complex and challenging to learn, especially for beginners.
  • Limited Debugging Tools
    Packer's debugging tools are not as mature or as integrated as those found in some other DevOps tools, making troubleshooting more difficult.
  • Configuration Complexity
    Complex configurations with multiple builders and provisioners can become hard to manage and maintain, leading to potential errors.
  • No State Management
    Unlike Terraform, Packer does not manage state, which means users need to handle state management separately if required.
  • Dependency on External Tools
    Packer often relies on external scripts and tools for provisioning, which can introduce additional dependencies and complexities.

Google Kubernetes Engine features and specs

  • Managed Service
    GKE is a fully managed service, which means Google takes care of tasks like provisioning, maintenance, and updates of the cluster, reducing the operational burden on users.
  • Scalability
    GKE offers robust scalability options, allowing you to easily scale your applications up or down based on demand. This is facilitated through auto-scaling features for both nodes and pods.
  • Integration with Google Cloud Services
    GKE integrates seamlessly with other Google Cloud services such as Cloud Storage, BigQuery, and more, providing a streamlined experience for leveraging multiple cloud tools.
  • Security
    GKE offers advanced security features like private clusters, and integrates with Google Cloud IAM, which allows for fine-grained access control, helping to secure your Kubernetes environment.
  • Ease of Use
    GKE's comprehensive dashboard, command-line interface, and supporting documentation make it easy to deploy, manage, and monitor Kubernetes clusters.
  • Global Reach
    With GKE, you can deploy clusters across multiple regions and zones, giving you the ability to build highly available, geographically dispersed applications.

Possible disadvantages of Google Kubernetes Engine

  • Cost
    While GKE offers extensive features, it can be more expensive compared to other Kubernetes solutions, especially when additional services and high-availability features are utilized.
  • Limited Customization
    As a managed service, GKE has some limitations in terms of customization and control over the underlying infrastructure compared to self-managed Kubernetes environments.
  • Complexity
    Despite its ease of use features, GKE still requires a certain level of expertise to efficiently manage Kubernetes clusters, which can be a steep learning curve for beginners.
  • Dependence on Google Cloud
    Using GKE ties you to the Google Cloud ecosystem, which may limit flexibility if you decide to migrate to a different cloud provider or adopt a multi-cloud strategy.
  • Resource Constraints
    Like all cloud services, GKE nodes can be subject to resource limits and quotas imposed by Google Cloud, which can impact performance if not properly managed.
  • SLA and Downtime
    While Google Cloud offers Service Level Agreements (SLAs), there is still a risk of downtime which could affect your applications. Additionally, relying on a third-party provider means issues may take time to resolve.

Packer videos

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Google Kubernetes Engine videos

Getting Started with Containers and Google Kubernetes Engine (Cloud Next '18)

More videos:

  • Review - Optimize cost to performance on Google Kubernetes Engine
  • Tutorial - Google Kubernetes Engine (GKE) | Coupon: UDEMYSEP20 - Kubernetes Made Easy | Kubernetes Tutorial

Category Popularity

0-100% (relative to Packer and Google Kubernetes Engine)
DevOps Tools
58 58%
42% 42
Developer Tools
21 21%
79% 79
Continuous Integration And Delivery
Cloud Computing
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Packer and Google Kubernetes Engine

Packer Reviews

Introduction to Top Open Source Virtualization Tools
Packer is notably light, high performing, and operates on every major operating system. It assembles and configures all the necessary components for a virtual machine then creates images that run on multiple platforms. Packer doesn’t replace configuration management tools like Puppet or Chef; as a matter of fact, when creating images, Packer can utilize tools like Puppet or...

Google Kubernetes Engine Reviews

Top 12 Kubernetes Alternatives to Choose From in 2023
Google Kubernetes Engine (GKE) is a prominent choice for a Kubernetes alternative. It is provided and managed by Google Cloud, which offers fully managed Kubernetes services.
Source: humalect.com
11 Best Rancher Alternatives Multi Cluster Orchestration Platform
Google Kubernetes Engine is a CaaS (container as a service) platform that lets you easily create, resize, manage, update, upgrade, and debug container clusters. Google Kubernetes Engine, aka GKE, was the first managed Kubernetes service, and therefore, it is highly regarded in the industry.
Top 10 Best Container Software in 2022
If you need a speedy creation of developer environments, working on micro services-based architecture and if you want to deploy production grade clusters then Docker and Google Kubernetes Engine would be the most suitable tools. They are very well suited for DevOps team.
7 Best Containerization Software Solutions of 2022
If you’re looking for a managed solution to help you deploy and scale containerized apps on your virtual machines quickly, Google Kubernetes Engine is a great choice.
Source: techgumb.com

Social recommendations and mentions

Based on our record, Google Kubernetes Engine should be more popular than Packer. It has been mentiond 49 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Packer mentions (9)

  • Failed to connect to the host via SSH on Ubuntu 22.04
    If you have just upgraded to Ubuntu 22.04, and you suddenly experience either errors when trying to ssh into hosts, or when running ansible or again when running the ansible provisioner building a packer image, this is probably going to be useful for you. - Source: dev.to / over 2 years ago
  • Create a minimalist OS using Docker Containers and Hashicorp Packer
    I am already using Hashicorp Packer at work and for personal projects and I wanted to test This idea out by wrapping it a single Packer Template file. This reduces the level of maintaining a lot of small scripts, Dockerfiles and configurations and the user can simply trigger a couple of Commands to get a minimalist OS at the end of the process. - Source: dev.to / over 2 years ago
  • After self-hosting my email for twenty-three years I have thrown in the towel. The oligopoly has won.
    And while it is a slight increase in complexity, it can be an overall net gain in functionality, configurability and reliability. Much like Packer is far more reliable and practical than manually making VM images sitting in front of a terminal, even though making the initial configuration takes some time. Source: over 2 years ago
  • Customized Ubuntu Images using Packer + QEMU + Cloud-Init & UEFI bootloading
    Hashicorp Packer provides a nice wrapper / abstraction over the QEMU in order to boot the image and use it to set it up on first-boot. Instead of writing really long commands in order to boot up the image using QEMU, Packer provided a nice Configuration Template in a more Readable fashion. - Source: dev.to / over 2 years ago
  • The journey of sharing a wired USB printer over the network
    Packer seemed like the perfect tool for the job. I have never used it before and wanted to get familiar with the tool. It doesn't come with ARM support out of the box, but there are two community projects to fill that niche. - Source: dev.to / about 3 years ago
View more

Google Kubernetes Engine mentions (49)

  • Google Cloud Unveils A4 VMs with NVIDIA Blackwell GPUs for AI
    Integration with Google Kubernetes Engine (GKE), which supports up to 65,000 nodes per cluster, facilitating robust AI infrastructure. - Source: dev.to / about 2 months ago
  • Deploy Gemini-powered LangChain applications on GKE
    In my previous post, we explored how LangChain simplifies the development of AI-powered applications. We saw how its modularity, flexibility, and extensibility make it a powerful tool for working with large language models (LLMs) like Gemini. Now, let's take it a step further and see how we can deploy and scale our LangChain applications using the robust infrastructure of Google Kubernetes Engine (GKE) and the... - Source: dev.to / 3 months ago
  • Securing Applications Using Keycloak's Helm Chart
    Kubernetes cluster: You need a running Kubernetes cluster that supports persistent volumes. You can use a local cluster, like kind or Minikube, or a cloud-based solution, like GKE%20orEKS or EKS. The cluster should expose ports 80 (HTTP) and 443 (HTTPS) for external access. Persistent storage should be configured to retain Keycloak data (e.g., user credentials, sessions) across restarts. - Source: dev.to / 5 months ago
  • Simplify development of AI-powered applications with LangChain
    In a later post, I will take a look at how you can use LangChain to connect to a local Gemma instance, all running in a Google Kubernetes Engine (GKE) cluster. - Source: dev.to / 7 months ago
  • 26 Top Kubernetes Tools
    Google Kubernetes Engine (GKE) is another managed Kubernetes service that lets you spin up new cloud clusters on demand. It's specifically designed to help you run Kubernetes workloads without specialist Kubernetes expertise, and it includes a range of optional features that provide more automation for admin tasks. These include powerful capabilities around governance, compliance, security, and configuration... - Source: dev.to / 11 months ago
View more

What are some alternatives?

When comparing Packer and Google Kubernetes Engine, you can also consider the following products

Terraform - Tool for building, changing, and versioning infrastructure safely and efficiently.

Kubernetes - Kubernetes is an open source orchestration system for Docker containers

Puppet Enterprise - Get started with Puppet Enterprise, or upgrade or expand.

Amazon ECS - Amazon EC2 Container Service is a highly scalable, high-performance​ container management service that supports Docker containers.

Rancher - Open Source Platform for Running a Private Container Service

Docker - Docker is an open platform that enables developers and system administrators to create distributed applications.