My main use case for Chef involves doing automation work in my environment. I use Chef to automate deployments and configuration for building application components across cloud infrastructures, such as automating scheduled jobs or scripts to process billing data or generate invoices. Additionally, I have automated similar workflows using Ansible, Bash, Python, GitHub Actions, and pipelines to ensure secure repeatable pipelines. Chef is a requirement where I currently work, and I am confident that I can quickly adapt my automation skills to use cookbooks and workflows effectively.

My main use case for automation tools such as Chef, Ansible, or scripting is to help with configuration and operational workflows to ensure repeatability, specifically to provision and configure cloud infrastructure and applications using Terraform or any cloud ARM or CloudFormation. I automate CI/CD pipelines for building, testing, scanning, and deploying microservices to Kubernetes, along with scheduling and automating routine operational tasks. This usage helps reduce manual errors and accelerates deliveries while improving reliability and compliance across multiple environments.

Chef offers valuable features in infrastructure as code, where it uses cookbooks and recipes written in Ruby language for detailed and flexible configuration of systems and applications. Idempotency is one of the major components, as Chef ensures that configurations are applied without any unintended side effects, making deployments more reliable. Chef's scalability allows for managing configuration across thousands of nodes effectively, which is critical for large-scale environments in production. Moreover, Chef integrates with multiple cloud platforms, such as AWS and Azure, has an ecosystem of community cookbooks, and allows for automated compliance checks with Chef InSpec. Its extensibility, custom resources, and handlers enable tailoring Chef for any organizational needs. Chef's ability to automate complex configuration workflows while maintaining the CI/CD pipeline contributes significantly to DevOps automation.

In day-to-day work, Chef helps me manage configuration consistently across hundreds or thousands of cloud instances without any manual intervention, significantly reducing human error. It aids in quickly provisioning and configuring new environments in multiple clouds such as AWS or Azure, using Chef cookbooks integrated with Terraform or CloudFormation to scale rapidly during peak demand or new project launches. It also automates updates and patches across all nodes simultaneously, reducing compliance and security downtime or tracking efforts. For example, while working on AKS and EKS clusters, Chef's integration with cloud platforms helped automate node configuration and application deployment, which was critical during cluster scaling and updates. The ecosystem of community cookbooks has accelerated this process, and Chef's scalability and cloud integration have enabled me to maintain a high level of availability while reducing operational overhead. This approach helps deliver faster, more reliable infrastructure changes in multi-cloud setups.

Chef has automation capabilities that enhance operational efficiency by minimizing manual tasks. The idempotent nature of Chef ensures consistent application of configurations, and its integration with the CI/CD pipeline facilitates continuous delivery and infrastructure updates in alignment with DevOps and SecOps practices. Additionally, the flexibility to create custom resources and handlers allows it to be tailored to unique organizational needs and complex workflows.

Chef is one of the most powerful tools; however, there are areas where improvements could enhance usability and efficiency. The learning curve is steep due to Chef's Ruby-based DSL and the complex components of cookbooks and recipes, which can be challenging for new users, especially those without programming backgrounds. Simplifying the syntax or providing more abstractions could aid in adoption and speed up execution. At times, Chef runs can be slower when compared to other configuration management tools, particularly in larger environments, so optimizing performance and reducing runtimes could enhance responsiveness. Additionally, the complexity in debugging failed Chef runs or complex recipes can be difficult due to limited error visibility. Regarding integration with modern tools, while Chef integrates well with many platforms, cloud-native integration with new cloud technologies and container orchestration tools would be advantageous. The quality of community cookbooks could also be a factor that could make Chef more accessible and easier to manage, further strengthening its position in DevOps automation.

Better documentation and tutorials, along with improvements to the GUI and visualization capabilities, would greatly benefit usability. Enhancements to collaboration features that support better teamwork, such as version control, integration, and change tracking, would also be valuable. Moreover, a robust testing framework focused on cloud-native practices would improve the user experience and align Chef more closely with modern DevOps methodologies.

Several additional improvements could enhance Chef, such as better error messaging. More clear and actionable error messages during cookbook runs would significantly reduce troubleshooting time. Additionally, improved documentation with real-world step-by-step examples for common use cases would facilitate quicker onboarding. Simplified cookbook testing through more integrated and user-friendly testing frameworks would ensure quality prior to deployment. Small UI improvements in Chef Automate would provide easier navigation and visualization of nodes, states, and compliance. Establishing better integration with modern CI/CD tools, while Chef supports many, could streamline workflows with deep native integration with popular pipelines such as GitHub Actions or Azure DevOps. These combined small improvements along with larger enhancements could make Chef more user-friendly and efficient for teams.

I have been working in my current field for the last eight plus years.

I would rate customer service as a four out of ten.

Positive

My advice for those looking into using Chef is to understand that it is a powerful and mature configuration management tool, but it comes with a steep learning curve, particularly for those new to Ruby or infrastructure as code concepts. Investing time in learning the Chef DSL and the structures of cookbooks is essential. I recommend starting with small, well-defined projects to build confidence before scaling up to more complex environments. It is also beneficial to use infrastructure as code tools such as Terraform in conjunction with Chef and to focus on security best practices by integrating Chef with secrets management tools such as Azure Key Vault or AWS IAM rules. Implementing observability and monitoring strategies to track configuration drift is advisable. Leveraging community cookbooks and resources can help accelerate learning, and it is crucial to plan for robust testing and validation. Finally, staying updated on improvements in Chef and related tools will help continuously enhance automation workflows. With this kind of consideration, Chef can become a highly effective tool for scalable and automated infrastructure management.

Chef remains a strong and reliable tool that is flexible. I recommend organizations evaluate their team's skill set and project requirements to determine if Chef aligns well with their automation goals. Continuous improvements in integration with modern CI/CD pipelines and enhanced user experience would further solidify its position in the industry. Chef's flexibility and extensibility through cookbooks and the DSL make it adaptable to a variety of use cases. I would rate this product an overall eight out of ten.

I have used Chef for more than six years to automate daily tasks and tasks related to building infrastructure and configuring Apache Cassandra servers.

I generally remember creating the cassandra.yml file and configuring the seed and data directories for Apache Cassandra. Whenever we needed to change the data directory folder or modify anything related to cluster names or replication strategies, we used Chef because it is a multi-layer cluster of Apache Cassandra.

Additionally, we used Chef for scaling out to provision new Cassandra instances in AWS.

Apart from that, I use Chef to deploy cron jobs for nodetool, snapshot, and incremental backups, and to automate the cleanup of old snapshots and backups.

In my experience, the best features I find in Chef are predictable and scalable environments, and it seamlessly integrates with cloud providers such as AWS and Azure. There is a way to do test-driven development using Test Kitchen and ChefSpec, and there are also compliance and security checks that we used.

When we use Chef, we comply with profiles such as benchmarking of CIS infrastructure, validating the configurations of industry standards, and using it for continuous integration and continuous deployment pipelines for secure configurations. We also enforce SSL and TLS authentication, firewall rules, and OS-level operations.

Using Chef for automating infrastructure and applications in my organization has helped us reduce manual tasks by more than forty percent, thereby saving significant revenue for the client. The customer is satisfied using Chef for automating these services, with most regular day-to-day operations being reduced because of this automation.

At this point, I do not have any thoughts on improvements for Chef. However, I think it would help if we had some kind of GUI-based monitoring system where we can see all the cookbooks and all the runbooks are predefined, and we just have to use them by changing the variables.

I have used Chef for more than six years to automate daily tasks and tasks related to building infrastructure and configuring Apache Cassandra servers.

In my experience, Chef is quite stable most of the time. Whenever we encounter issues with Chef server, we simply restart the service and it works seamlessly.

In terms of scalability, we did not have much requirement to scale. However, whatever we had, Chef running on a single EC2 machine meets our needs.

Customer support is quite good.

Positive

I started with Chef and I am still working with Chef. Now I am exploring cloud-native services related to Chef or configuration management, where we use OpsWorks instead of Chef. We are moving to OpsWorks because most of the servers are in AWS and it integrates easily using OpsWorks.

The pricing, setup cost, and licensing are managed by another team. However, within my scope of work, we have Chef servers automatically installed, and I log in to Chef server to run those cookbooks.

I am definitely able to save a lot of time doing the same manual tasks every day, which are operational. In terms of revenue, I have not observed much because it is holistically depending on the project. However, we have seen significant improvement in the time and the way we make changes to the infrastructure, so it is good from the developer perspective, even if it may not be great from a business point of view.

It is because it was traditionally built on Chef and we are improving the way Chef works. I have not had a chance to evaluate other options.

On a scale of one to ten, I would rate customer support an eight.

Chef is a traditional configuration management tool that is very easy to understand and deploy, and I get predefined cookbooks from the internet, which helps me move forward quickly without spending a lot of time developing the cookbooks.

I think Chef is quite good, and the focus should be more on customer support and providing monitoring and observability capabilities, which would be beneficial. I rate this review as a nine overall.

I used Chef in my first organization and continue to use Chef in my current organization, though not as actively. I have used Chef for approximately one and a half years, applying it specifically for projects while using it more rarely for configuration management.

I use Chef primarily to automate server configuration tasks, where I created and updated Chef cookbooks to install required packages, configure services, and maintain system settings across multiple servers. I work with Chef recipes to ensure all environments, including Dev, Stage, QA, and Prod, are correctly configured. By automating this configuration, we reduced manual interventions and deployment time. Additionally, I have used Chef for application deployment to automate the deployment of our application stack, writing recipes that handle installation, configuration, server restarts, and other environment variables. This ensures reliable and repeatable deployments across all servers and reduces the likelihood of human errors. Furthermore, we have used Chef for compliance and hardening, as Chef helps enforce compliance and security settings on the servers, ensuring system-level configurations such as user access, security policies, and service settings align with our standards.

All the use cases—configurations, deployment, compliance, and other common situations—demonstrate how helpful Chef is. We found it very beneficial, which is why both my past organization and my current organization are using it. In most cases I analyzed, Chef helped me very well.

The best features Chef offers include Infrastructure as Code, which makes everything repeatable, version controlled, and automated. Chef's server model is another standout feature, as it has a central Chef server that stores cookbooks, nodes, and their configurations. Scalability is also a significant advantage, as Chef can manage hundreds or thousands of servers effortlessly, allowing for easy rollout of a single cookbook change to all machines. Additionally, idempotency ensures that applying the same configuration again does not disrupt anything; for instance, if a package is already installed, Chef will not reinstall it. Moreover, Chef provides extensibility and reusability, allowing creation of custom resources or the use of numerous community cookbooks from Chef Supermarket, showcasing many useful features.

The feature I rely on most day-to-day is scalability, as it helps me manage hundreds or thousands of servers effectively. At my large organization, we have to manage many servers, and Chef is instrumental in that process. Idempotency is also quite useful, ensuring that whatever configuration changes we make do not break anything, such as not reinstalling packages that are already installed.

I would mention two improvements I wish for in Chef: first, the attribute-driven configuration allows flexible customization of the same cookbook for multiple environments, whether Dev, Prod, or Stage. The second is self-healing infrastructure, which continuously verifies that the system matches the desired state and can auto-correct configuration changes during the next run.

Chef can improve upon the speed of Chef client runs, as large cookbooks or many resources can slow down chef runs. Potential improvements could focus on faster compile and converge phases and better parallel execution of resources to enhance performance. Additionally, intelligent caching of attributes and cookbook dependencies could reduce total execution time and improve responsiveness. Another area needing attention is better error messages, as we have found that Chef errors can sometimes be vague or too low-level to understand. More readable, human-friendly error outputs would be incredibly helpful.

I have been working in the SRE field for five years, starting my career in 2021, and I am still working as an SRE now.

In my practical experience, Chef's scalability handles a large number of nodes easily, allowing us to manage hundreds of servers consistently using the same set of cookbooks. The centralized control Chef provides simplifies scaling and ensures stable and predictable performance. However, I have noticed minor challenges where cookbook dependency chains can become heavy in very large environments, and Chef server needs proper resource sizing, including CPU and memory.

Chef has provided a return on investment, particularly in needing fewer employees, as the tool significantly reduces the amount of human work required for many tasks.

My advice to others looking into using Chef is to start with the basics and gradually build upon them, as Chef has a learning curve due to its Ruby-based DSL. I recommend starting with simple cookbooks to understand resources, attributes, and templates before moving to more complex modules. It is also crucial to use version control from day one and to test everything before production in Chef. Being powerful, Chef can have both positive and negative impacts, so keep configurations declarative rather than imperative, maintain clear documentation, and aim for small automation wins. Ensure Chef server or Automate is well-maintained by starting small, keeping cookbooks modular, testing thoroughly, using version control, and documenting clearly, as Chef is incredibly powerful when implemented with structure, collaboration, and incremental automation.

I have shared my experiences regarding Chef, including the pros and cons and aspects that could be improved, such as error outputs. I have experienced many awesome and great things about Chef.

Positive