Kapstan: A Streamlined Ansible Alternative for Infrastructure Configuration

Configuration management is the key component for stability and efficiency in dynamic infrastructure today. Ansible addresses this challenge with agentless server management, a simple YAML-based approach, and a strong community, making hard-to-configure deployments easy.

In this blog post, we will cover Ansible, the core problems it faces in terms of user interface, ramp-up time, state management, and general maintainability, and how they compare with traditional tools and newer Internal Developer Platforms. By the end of this post, you'll have a clearer picture of where Ansible fits into modern IT operations and in which circumstances alternatives might offer you a better way forward. ‍

What is Ansible?

Ansible, first launched in 2012, is an agentless automation tool and uses SSH. It is contrary to Chef or Puppet, which requires installed agents. It allows for the use of simple automation using its YAML-based playbooks, which makes it accessible for provisioning, configuration management, and application deployment. Some common use cases include server management across on-premises and cloud environments, automated application deployments, and routine administrative tasks. Thanks to its modular design and agentless architecture, it's a reasonable choice for teams in pursuit of standardization in infrastructure automation. 

Challenges with Ansible & Traditional Configuration Management Tools

Performance in Large-Scale Environments

Ansible's agentless architecture and stateless model are highly popular but degrade deployment velocity when dealing with hundreds or thousands of nodes. Each node's state needs to be ascertained before changes are applied, ensuring accuracy but causing delay. In some cases, the less frequently used pull-based model can make synchronization difficult, especially when network connectivity is poor. These aspects cause difficulties for teams attempting to deal with large infrastructures with tight time requirements.

Challenges of YAML

YAML is at the heart of Ansible, and opinions range far and wide on whether it is usable for larger codebases. The format does not have inherent validation, so errors only reveal themselves when playbooks are run. This delays feedback and makes it harder to identify issues. Additionally, nested sections quickly become messy, particularly when specifying conditions or dependencies. Some engineers use YAML as they would a programming language, which makes playbooks harder to read and maintain. In accordance with the "Zen of Ansible," it is best to keep task-based automation in mind and reserve complex logic for Python scripts. Do not underestimate the extensive array of available plugins. At first glance, it appears advantageous—there exists a plugin for almost every issue. Yet, the intricacies accumulate, and soon enough, you may discover yourself dedicating hours to perfecting playbooks. Numerous teams in search of Ansible alternatives gravitate towards tools that strike a balance between simplicity and functionality.

User Interface: AWX and Tower

Ansible Tower and AWX, the open-source alternative, provide an inviting graphical interface to manage playbooks, credentials, and logs. AWX has been around for a few years and is continuing to grow. The installation process for it by default, however, is to run with Kubernetes, taking away from essential infrastructure work to execute another platform. Groups of users less at ease with Kubernetes might be working on issues outside of typical automation responsibilities, and that consequently equals more maintenance and learning requirements.

Steep Learning Curve

As with most infrastructure-as-code offerings, Ansible requires an up-front investment of time and effort. There are numerous ways a user can declare a single workflow, and new users will tend to try and use YAML to declare complex or deeply nested logic, which becomes convoluted. Since Ansible is an action-oriented automation system and not a general-purpose programming language, for complex business logic, Python is usually a safer bet—a point that Ansible's own documentation makes very explicitly. The enormous number of plugins available is both blessing and curse: while there's likely a module for almost every requirement, large playbooks are an exercise in large-scale optimization.

State Management Failures

Idempotency Without State Tracking in Reality

Ansible playbooks are required to be idempotent, i.e., running a task repeatedly won't change an already properly configured system. But this idempotency is not enforced by an external state-tracking mechanism like Puppet or Terraform. Ansible instead uses the refreshed inventory data and real-time facts furnished by the nodes. Therefore, each run involves on-the-fly checking of the current state, at the expense of performance in large environments.

Overhead of Performance during State Checks

Ansible, without a persistent state file, needs a full verification of the state of every managed node before applying any changes with every run of a playbook. Although this rigor guarantees correctness, it can make deployments very slow when dealing with hundreds or thousands of nodes at once. In contrast to Terraform's state file, which enables fast comparisons and applying changes, Ansible needs to verify state in real-time, so it is not as efficient for fast infrastructure updates.

Sequenced Change Management

Ansible's built-in logging is fairly rudimentary and relies on callback plugins, which tends to encourage organizations to look for alternatives for better change tracking. Large teams prefer to use Ansible with AWX/Tower, internal logging libraries, or third-party databases to keep audit trails to track configuration changes. These, of course, have an additional layer of overhead, which would be less ideal for smaller teams who require optimal automation with zero overhead.

Ansible Scalability & Maintenance Overhead

When infrastructure grows, maintaining Ansible playbooks is increasingly challenging. An enterprise might struggle with hundreds of interconnected playbooks and plugins that each deal with varying portions of the environment. The next example illustrates creating an AWS VPC and security group configuration for HTTP and HTTPS traffic in a simplified manner:

# Network configuration playbook
- hosts: network_infrastructure
 gather_facts: no
 vars:
   aws_region: us-west-2
 tasks:
   - name: Configure VPC
     amazon.aws.ec2_vpc_net:
       name: my-vpc
       state: present
       cidr_block: "10.0.0.0/16"
       region: "{{ aws_region }}"

- hosts: security_groups
 gather_facts: no
 vars:
   aws_region: us-west-2
 tasks:
   - name: Create application security group
     amazon.aws.ec2_security_group:
       name: app_security_group
       description: Security group for application servers
       region: "{{ aws_region }}"
       rules:
         - proto: tcp
           ports:
             - 80
             - 443
           cidr_ip: 0.0.0.0/0

Now unless until you have read the following Ansible module guides, there’s no possible way you could have come up with the above config right?

• amazon.aws.ec2_vpc_net module – Configure AWS Virtual Private Clouds
• amazon.aws.ec2_security_group module – Maintain an EC2 security group

It would be difficult to create this configuration from scratch without looking at the amazon.aws.ec2_vpc_net and amazon.aws.ec2_security_group module documentation. It is a classic issue presented by the extensive module library of Ansible: while it offers great flexibility, groups must spend time learning the parameters and operations of every module.

But both novices and professionals can reduce mistakes by adhering to linting practices that identify frequent errors. Such problems tend not to be discovered in big teams, especially where there are many people working on the same codebase. Among the frequent problems are the usage of generic shell commands instead of custom modules, lack of potential errors, and lack of transparent retry logic or helpful error messages.

Here is a "bad" example of a playbook to ensure the running of a systemd service, followed by a better version using modules for greater clarity and reliability:

- hosts: all
  tasks:
    - shell: "systemctl status myservice"
      register: service_check

    - shell: "systemctl restart myservice"
      when: service_check.rc != 0
  
    - shell: "sleep 5"

    - shell: "systemctl status myservice"
      register: final_check
 
    - debug: 
        msg: "Service probably running now"
      when: final_check.rc == 0
                

- name: Ensure service is running
  hosts: all
  become: true
  gather_facts: true

  tasks:
    - name: Get service facts
      service_facts:

    - name: Restart service if not running
      systemd:
        name: myservice
        state: restarted
        daemon_reload: true
      when: >
        ansible_facts.services['myservice.service'] is not defined or
        ansible_facts.services['myservice.service'].state != 'running'

    - name: Verify service is running
      systemd:
        name: myservice
      register: service_status
      until: service_status.status.ActiveState == "active"
      retries: 3
      delay: 5
                

The enhanced iteration is simpler to navigate, but the presence of a less efficient one implies that there is a requirement for a group of specialists to ensure that large Ansible deployments are smooth. This arrangement can be suitable for companies heavily committed to Ansible, but small teams can use a less complex one. An Internal Developer Platform such as Kapstan solves this issue by eliminating the requirement for writing and managing multiple playbooks so that all engineers can manage platform tasks without requiring specialist knowledge of several Ansible modules.

What Are IDPs & Why are they a viable modern Ansible Alternative?

An Internal Developer Platform (IDP) is a self-service platform that conceals the underlying complexity. It usually relies on building blocks such as Kubernetes, Terraform, and Ansible, but presents them in a single interface so that developers can deploy applications without having to struggle with low-level configuration subtleties.

Kapstan is a viable alternative to Ansible. It offers a solution for on-demand provisioning of environments and creating customized workflows. It can easily integrate into DevOps workflows and allow teams to easily automate deployment and monitoring of resources. Kapstan abstracts away the toil of managing kubernetes, allowing developers to deploy applications without needing to understand the nuances of container orchestration, This enables teams to standardize deployments and simplify resource provisioning, thus ensuring faster iterations, lower operational overhead, and greater developer productivity and thereby making it a viable Ansible alternative.

IDPs can come a considerable way in lightening the load on application developers, as they eliminate the requirement to learn lots of tools per layer of the stack. Still, the burden of constructing and maintaining the platform itself falls to someone, and that could add extra overhead. Furthermore, there is the threat of vendor lock-in if an IDP makes use of proprietary components. Yet, for the majority of teams, the possibility of streamlining onboarding processes and minimizing manual effort is an attractive reason to use an IDP, either as a complete solution or as an add-on to tools like Ansible.

How Kapstan aims to simplify development and operations

1. Provide an intuitive, web-based interface for infrastructure management.
2. It empowers developers to provision and manage resources without requiring in-depth operational expertise, while also promoting consistent deployment processes across different environments
3. By reducing configuration overhead with abstracted, reusable components, Kapstan helps teams focus on building and delivering applications more efficiently.

With IDPs, and in this case with Kapstan, developers can:

• Spin-Up Environments on Demand: Instead of waiting for the operations team to create a development, staging, or production environment, developers can set them up themselves in a matter of minutes. This is especially useful when working on microservices that require isolated environments for testing.
• Easily Roll Back Deployments: If something goes wrong with a deployment, developers can quickly revert to the previous stable version. No more waiting for operations to handle rollbacks—developers can fix things fast.
• Built-in Monitoring: Rather than hunting down system admins or DevOps to understand infrastructure costs or system metrics, IDPs provide built-in tools to monitor application performance, track resource usage, and keep tabs on costs directly from the platform. This allows developers to stay on top of their apps’ health and avoid surprises.

• Role-based access controls: Fine-grained access controls allow teams to define who can provision, modify, or deploy resources. For example, junior developers may only access staging environments, while senior engineers have production access.

How Kapstan Provides an Ansible Alternative

Kapstan is a complete replacement for your Ansible playbooks, we employ approaches born from the frustrations of developers with managing cloud resources.

Enhanced Developer Autonomy

An Internal Developer Platform (IDP) gives developers independence to self-serve. They are able to provision environments, roll back changes, and view logs without depending on operations teams to approve them. Not only does this make repetitive work less cumbersome, but it also supports better collaboration between development and operations.

As an example, if a group of developers wants to experiment with a new database for a feature prototype, they can use Kapstan to boot up an ad-hoc instance, apply the schema modifications, and publish the result for feedback all without needing to open a ticket with the DBA team. Not only does this simplify the process, but it also instills ownership and speeds up delivery.

No silver bullet

While IDPs offer significant advantages, they aren't universal solutions. Organizations must carefully evaluate their specific infrastructure needs and gradually transition existing systems.

IDPs eliminate the need for using complex infrastructure provisioning & configuration management tools like Ansible & Terraform, replacing them with declarative, user-friendly interfaces that require minimal technical overhead. However, teams often require more controllable environments, in those cases vendor lock-in is a crucial factor to judge tools on, Kapstan doesn’t lock you to the platform, you can export helm charts, and terraform plans whenever needed.

The primary value proposition is reducing operational overhead. Instead of hiring specialized Ansible experts or extensive training programs, teams can leverage intuitive platforms that democratize infrastructure management.

• Legacy systems or highly customized environments may require hybrid approaches, where traditional tools like Ansible complement IDPs.
• Cultural shifts in how teams collaborate and manage infrastructure must be planned carefully to avoid disruptions.

Conclusion: Ansible Alternative

Infrastructure management can be expensive and dangerous if not carried out effectively, and it is a huge problem for an organization. It is always possible to develop in-house skills within the organization, hire a service provider, or employ trusted solutions that do not require a large team of YAML experts. Internal Developer Platforms offer a new solution, allowing teams to automate and simplify their work as a new option to Ansible.

For those who would like to see concrete examples, Kapstan's case studies demonstrate how various groups globally are becoming increasingly empowered to tailor their surroundings using IDPs.