Tekton Reviews

Tekton is used as a Kubernetes native tool for creating CI/CD pipelines. It is used for creating multiple tasks that can run as pipeline runs for several services. This helps in reducing time wastage and has several benefits. I work mostly on creating tasks and pipelines while my colleague handles the initial setup and login.

Tekton is beneficial for our CI/CD processes by enabling multiple task runs, which means we can use the same task for multiple services or deployments, saving time. It scales automatically based on the number of tasks or pipelines running, which is efficient and effective for our development needs.

One valuable feature is the ability to create multiple tasks and reuse them for several task runs as pipeline runs. Another advantageous feature is its security as it is inside the Kubernetes cluster, which confines data usage internally.

Regarding areas for improvement in Tekton, I have not encountered significant issues. It works well for our use case. However, incorporating AI could be a potential enhancement in the future.

I have been using Tekton for one year and two months, primarily for a project called Anthem.

Throughout my one year of usage, I have not faced any stability issues with Tekton. It handles multiple services and deployments efficiently.

Tekton automatically scales up when needed, such as when multiple developers push code simultaneously. It does this effectively without causing any issues.

We have not had any need to escalate issues or contact technical support because Tekton has been functioning well for our needs.

Positive

Before Tekton, we used Jenkins and Skaffold. While Skafold lacked a dashboard and had other limitations, Tekton offers a user-friendly interface and various benefits for CI/CD processes, which makes it preferable.

The initial setup of Tekton was straightforward, with comprehensive documentation available. This made the process clear and accessible.

Two people manage Tekton, with my colleague handling the initial setup, and I focus on creating tasks and pipelines.

Using Tekton has resulted in cost savings. It required fewer resources compared to Jenkins, running efficiently within a Kubernetes cluster without high memory or CPU usage.

Setting up Tekton has been cost-effective, as it can run multiple pipelines simultaneously with limited resources, unlike Jenkins, which had higher resource consumption.

We previously used Jenkins and Skaffold but switched due to Tekton's advantages in simplicity, UI, and effective resource management.

I am preparing documentation to compare Tekton and Jenkins for a new project. The goal is to highlight Tekton's benefits and potentially advocate for its adoption.

I'd rate the solution ten out of ten.

When we migrated to Tekton, IBM Continuous Delivery provided pipelines, which you can run on Tekton. Tekton provides a feature where you can schedule the job. You can just go and create schedule triggers. Since part of our services has to go through audit, compliance, and monitoring, we had to run multiple operational tasks in our day-to-day job. These tasks included monitoring our database backup and scanning the servers or applications we were running.

We have to scan the Docker images we run on IKS and OpenShift clusters to ensure the running server doesn't contain any CVEs. We have jobs in place to scan those images. We need to track all this as part of our automation jobs. We have a small team of two to three members, and we have come up with a lot of automation tools. We started running all this using Tekton pipelines, which has been greatly helpful for us. It has become very productive and saved a lot of time for our team and many other teams.

We started generalizing our tools and sharing them with others. All the cloud services have been using it because they have to go through the same audit, same compliance, and same monitoring use cases. Instead of them coming up with their own automation, we have come up with a common toolchain.

We created the template and shared it with the cloud service team. They started using it, which saved resources and time for multiple things. Last year, that was a major achievement. Tekton has been very useful in scheduling data. We don't need to worry about getting reports, collecting evidence, or monitoring everything because they are being done perfectly.

As part of our CI/CD, anything we do today runs on a Tekton pipeline. If we are doing continuous integration and deployment, we run it on a Tekton pipeline. Since we have been using different languages like Java, Go, Node.js, and React.js in our development work, we have to integrate security checks. From day one, we have to integrate security into our development.

As part of continuous integration, we have started adding those tasks. That has beautifully worked for us. All the security checks as part of continuous integration or delivery ensure that we are not deploying any vulnerable images, vulnerabilities, or CVE packages in our production server. We are adding all those security checks as part of our CICD. We can add small checks as part of Go or run a Go scan. That was one good thing that was helpful for our team and many other teams.

I'm part of one of the open-source projects. When any event occurs, I want the pipeline to run by itself. If a security event is triggered, the pipeline should detect and automatically remediate it, which does not currently happen.

Tekton should include many features to integrate event-driven pipelines. For example, when GitOps triggers an event, you have to trigger a pipeline. Such event-driven things could be improved.

I have been using Tekton for four years.

Tekton is a stable product. You can run your pipeline on your own machine. I don't want to run this pipeline in a managed worker or somewhere where other services are maintained. I can have my own private worker and run the pipeline there. The machine on which I'm running Tekton could be a compliant machine.

I rate the solution’s stability a nine out of ten.

Tekton is a scalable solution.

I rate the solution’s scalability an eight out of ten.

We used to run all of our operational jobs using Jenkins jobs. We had set up virtual machines to run the Jenkins server, and it used to go in a queue and take a lot of time. As all cloud services were using the same server, it was getting into a queue and taking time to deploy. We were facing a lot of issues, and it was affecting our productivity. Then, we decided to migrate to Tekton.

The continuous delivery team internally integrating Tekton might face challenges, but we haven't faced any challenges implementing the tool.

I would highly recommend Tekton to other users because it's faster and more productive. For example, all our IBM Cloud Services initially used Jenkins as a pipeline for all the operational and compliance-related work. Now, everybody is migrating to Tekton and using it.

Overall, I rate the solution a nine out of ten.

I am a PHP developer, and I create software for my clients. In the IBM cloud, I manage all my source code by GitLab. Every project I develop is ultimately deployed into a container on Kubernetes. Toolchains on IBM Cloud manage all the steps to deploy my projects, and all of these toolchains are made with Tekton.

One of the best things I appreciate is that Tekton runs on the Kubernetes platform. This is very useful when working on a project with other team members. For instance, suppose we have a very big project that requires building a large amount of source code or running many unit tests. During the build and unit test phases, Tekton on Kubernetes allows us to have a scalable machine to handle these tasks. This scalability is the most useful aspect for me.

On the other hand, if you have a simple project but many programmers continuously commit code, having a scalable machine to manage the entire toolchain is also very beneficial. The tool is easy to understand and comes with documentation. 

One feature I appreciate in Tekton is the ability to segment your toolchain into different tasks. For example, before building my source code, I can personalize a task to check the syntax with tools like Linter. Additionally, before running unit tests, I can check for updates to an SQL database or generate documentation using Javadoc style. Personalizing each task and segmenting the toolchain is extremely useful for me.

The tool should improve in terms of output flexibility. It runs on a specific Kubernetes machine, and the persistent memory storage is on a single partition. Improving this aspect could make analyzing logs and toolchain outputs from external tools easier.

I have been using the product for a couple of years. 

In my specific case, when I started a couple of years ago, I experienced some problems in the toolchain. When some steps of the toolchain failed, the errors were not correctly managed. However, after a couple of months, all the features became stable and efficient. I'm very satisfied now.

The solution is scalable because it runs on the Kubernetes platform. My company has three users. 

I have only contacted IBM Cloud support and not Tekton's. 

I used Jenkins before Tekton. 

Setting up Tekton in the IBM cloud environment is easy. It's very useful and straightforward. I tried using it in a different environment, and I must admit that while there is good documentation, you need a strong base of skills in Linux and other areas because Tekton uses several tools with Python, Java, etc. It's not too easy, but it's not too difficult either.

The solution is open-source. 

I chose IBM Cloud because my first experience with it was very positive. IBM Cloud allows you to choose a target deployment platform, a container you can scale and configure with resources. It’s extremely easy to create a toolchain, starting with your Git project and automatically deploying it on this application container every time without configuring the environment.

Before using Tekton, you should evaluate several aspects of your project: its size, the frequency of commits, and the target of your deployment. From a technical perspective, you need basic skills with the Linux command line and a minimum understanding of Kubernetes.

I rate the overall product a ten out of ten. 

We are consolidating everything in Kubernetes. We are looking for a cloud-native CI/CD solution and came across Tekton as one of the options. We are using Tekton in parallel with ArgoCD. The CI part is done by Tekton with multiple steps supported by Tekton extensions, including Git clone and build steps.

It is ease of use for us. We have found Tekton to be very scalable in Kubernetes, running multiple jobs seamlessly without an issue. It is also easier to use once you get it rolling.

The ability to scale is valuable. Tekton scales up or down within Kubernetes without an issue, making it easier to use. Tekton is very efficient at handling multiple jobs.

Improvement is needed in the build step. Tekton currently supports Kaniko, but an official Docker builder would be beneficial to reduce build times. The extensions should also be improved. 

Additionally, the current extensions for Tekton could benefit from development. Moreover, it would be helpful if it included an out-of-the-box graphical interface, as we need to install it as an extension.

It might be two to two and a half years, maybe.

Tekton is running on our own infrastructure. Stability relies on the quality of our infrastructure; there are no issues with Tekton itself.

Tekton is scalable within Kubernetes, managing multiple jobs seamlessly.

The Slack community is good and helpful. We have received support by posting issues in the community.

Neutral

We have used multiple solutions, including GitHub Actions, Argo Workflows with ArgoCD, and Bitbucket pipelines. Currently, we are using GitHub Actions along with Tekton.

The initial setup of Tekton involves installing it, which is easy with a few commands. However, defining and writing pipelines can be complex and requires practice.

Tekton is handled by the DevOps team, which consists of five members.

We have previously evaluated GitHub Actions, Argo Workflows with ArgoCD, Bitbucket pipelines, and multiple other solutions.

If you want to consolidate everything with Kubernetes, Tekton is a better option as it is part of the main tech stack comprising Kubernetes.

I'd rate the solution seven out of ten.

We are using Tekton for continuous integration and continuous delivery to deploy our code to production.

By using Tekton, we have streamlined our deployment process and enabled continuous integration and delivery, which is crucial for maintaining our production systems.

The most valuable aspect of Tekton is its Kubernetes maintenance, allowing us to use it anywhere that supports Kubernetes. It is an open-source tool, which makes it highly adaptable.

Improvements could include introducing a UI-based pipeline development feature, such as drag and drop, which would help individuals with limited technical knowledge start building pipelines. However, I acknowledge that might be too ambitious.

I have been using Tekton for over six months.

We have experienced some performance issues with our clusters, leading the deployment team to create new clusters for enhanced performance. Teams are in the process of migrating to these new clusters.

Scalability-wise, Tekton should be adequate since it supports Kubernetes natively. Although I have limited knowledge in this area, it should scale by adding pods and clusters.

I have only received communications regarding migration from customer service. There haven't been any significant issues requiring their contact.

Positive

Previously, I was not involved in using any CI/CD platform, as there was a separate deployment team handling it. Therefore, Tekton is my first experience with a CI/CD solution.

The initial setup was challenging due to the various core concepts involved and multiple required connections, such as GitHub and cloud. Understanding triggers, events, and pipelines was important, but it posed a learning curve.

The setup process was managed by involving a senior colleague with experience, which aided in deploying successfully.

It is an excellent choice for CI/CD, primarily due to being open source and Kubernetes-native, which avoids vendor lock-in and allows flexibility in backend changes with minimal settings adjustments.

I'd rate the solution eight out of ten.

In my company, we use Tekton for the pipeline, specifically Bitbucket pipelines. We have some cluster setups as well. In order to run some testing of the cluster, we chose to handle pipelines via Tekton.

The best feature of Tekton is that it is a Kubernetes-native tool for CI/CD. The tool offers flexibility and compatibility. If we look under the Kubernetes-native area, Tekton is built to run natively on Kubernetes, so it leverages Kubernetes 'scalability, security, and robustness, making it an ideal cloud-native application. I can relate to the pipeline customization in Tekton. It provides a highly customizable and reusable pipeline component. You can define tasks and pipelines that suit your specific workflow needs and easily reuse them as a different service platform. If you see the interoperability, Tekton is designed to indicate that there are other tools and services in the Kubernetes ecosystem. It makes it easy to incorporate things into the existing workflow.

Earlier, I used to use Jenkins pipeline, but compared to Jenkins, Tekton is better. Tekton is quite a user-friendly tool. The tool offers good dashboard access, and it is extremely user-friendly. If you are a beginner, then accessing the flexibility part can be overwhelming. We think the learning curve of the tool is steep, especially for those who are not already familiar with Kubernetes. There is a need to improve the recommendations and create more tutorials for the tool. The tool is very user-friendly for advanced users and not for beginners. There are some limitations, especially since the tool primarily operates through YAML configurations and command lines with limited graphical user interface options. While there are some third-party tools that look like Tekton's dashboard, there are still basic and compact major systems like Jenkins or GitLab.With more advanced built-in CGI and GUI, as a user, we can make it easier to monitor and manage Python faster. We can also improve the data handling and debugging. The debugging of failed pipelines in Tekton can be challenging. The error messages are not very descriptive, and the tool has limited support for step-by-step debugging. So, the improvement in error handling and data handling for debugging needs to be improved so that it could significantly improve the developer experience.

I have been using Tekton for three years. In our company, we have been using the tool for more than eight months. I am just a user of the tool.

In our company, there are around more than 5,000 employees. There are actually many things under the cloud and platform delivery and infrastructure. We don't know the exact number of employees who are using the tool. I believe over 100 people in my company use the tool.

In my entire career, I never went to the support team for help. If I had any doubts or any kind of features, I was able to Google it or use ChatGPT.

The solution is deployed on the cloud.

Beginners should go through the product documentation. There are many tutorials available on the product that can help a person to configure the pipeline and task functions. Once you get a proper idea of the architecture of Tekton and how it works, only after knowing how to use the tool will a person get to apply the practical knowledge in the Tekton tools. I suggest that businesses get an idea about Python and how it works, as they need to understand the architecture of Tekton.

I rate the tool an eight out of ten.

Our primary use case is for cloud integration and cloud deployment. Tekton is a cloud-native tool that we utilize in Kubernetes and OpenShift. It helps us with code integrations and code deployment. We use it for automating various processes and integrating it with our DevOps environment.

Tekton has improved our performance by allowing us to define metrics and resource limits, enhancing the performance of our whole pipeline. The ability to customize tasks and use custom containers has also allowed us to tailor our workflows to our needs.

The customization is valuable. We can make a lot of customizations, and data sharing between tasks using workspaces is very convenient. Moreover, the flexibility and ease of use in creating and attaching new tasks make it very user-friendly. The Tekton UI and user interactions are very good.

Tekton could improve by adding better documentation. The documentation needs improvement to clarify supported features and required integrations. Additionally, while it is currently a cloud-native solution limited to Kubernetes, an option to run it locally on our own systems would be very useful. Security integrations and third-party integrations also need enhancement.

We have been using the Tekton solution for nearly two years.

Tekton is stable and performs well. However, it would benefit from adding new features quickly to stay relevant and helpful.

Tekton is highly scalable due to its cloud-native nature.

We have not escalated any queries to Tekton itself. Since Tekton comes as an integral part of Red Hat, we rely on existing documentation and haven't had any issues requiring direct technical support.

Neutral

In the past, we used Jenkins for CI/CD. Each tool has its own use case and pros and cons, but Tekton's cloud-native capabilities and ease of deployment and maintenance make it a better fit for our needs.

The initial setup of Tekton is very straightforward. We install it as an operator in our cluster, making maintenance tasks like auto-upgrades and updates easier.

There is no specific cost related to resource optimization provided by Tekton. We need to manage the resource limits and requests ourselves to prevent resource exhaustion, especially when running on cloud platforms like AWS, Azure, or GCP.

I recommend Tekton to anyone closely interacting with Kubernetes. It is particularly useful for larger teams with complex application deployment requirements. However, for smaller teams or simpler use cases, it may not be necessary.

I'd rate the solution six out of ten.

We use the solution in CI/CD pipelines for application deployment. 

The tool's most valuable aspect is its compatibility with the cloud-native environment. It can be easily installed on Kubernetes and leverages its resources to run CI/CD pipelines.

Some of the tool's cons include its minimalistic dashboard, which lacks detailed information and control compared to other tools like Jenkins or GitLab. Additionally, it's primarily used by Japanese companies.

Another drawback is its dependency on the Kubernetes cluster for deployment, which could be a limitation. One feature I would like to see included or enhanced in Tekton is the ability to reuse specific pieces of pipelines as reusable modules.

I didn't choose this tool because they already used it when I joined this company. I don't like this tool because it has many limitations. I believe many other tools are better than Tekton.

Integration with other solutions involves mainly API calls. Tekton lacks a mature dashboard, making integration more challenging than tools like GitLab or Jenkins.

I encountered some challenges, particularly with compatibility between different versions of Tekton and Kubernetes. For example, the Tekton version couldn't be installed on Kubernetes version 1.24 due to compatibility issues. Some versions of Tekton don't support certain Kubernetes features, leading to installation issues. It depends on Kubernetes, and matching Tekton versions with compatible ones is essential.

The tool has increased our operational costs due to the need for repetitive tasks and code duplication. Unlike other tools like GitLab or Jenkins, it often requires duplicating resources across clusters or regions. This duplication elevates maintenance costs, as any code changes must be applied in multiple locations.

I have been working with the product for ten months. 

The solution is stable, and I haven't encountered any performance issues. 

I find Tekton to be scalable. It leverages Kubernetes as its underlying system, allowing for scalability. For instance, if you need to run numerous concurrent jobs, Tekton can accommodate this requirement. My company has 70-100 users. 

We have deployed Tekton across multiple locations, departments, and cross-tenants. It has been used for about three or four years and is utilized by various teams to deploy applications in different clusters and locations.

Since the tool is open-source, we resolve issues ourselves. 

The installation process is straightforward, which stands out as one of Tekton's notable advantages. Deploying a YAML file onto your Kubernetes cluster is all it takes, and the installation on Kubernetes is quick. I believe it's achievable in less than a minute. In contrast, other tools like GitHub or Jenkins often require significant setup time.

There is minimal ongoing maintenance required. However, upgrading to the latest version can sometimes be challenging due to compatibility issues between Tekton and Kubernetes. Upgrading Tekton may also necessitate upgrading the Kubernetes cluster, which can incur additional maintenance costs.

The tool increases our operational costs because it requires repetitive tasks. Other tools like GitLab or Jenkins can reduce costs, as they eliminate much of this repetition. Currently, we often need to duplicate resources. For example, if we want to install based on manifests in a new cluster, we must copy all the base modules to another cluster and keep them in the repository. This duplication can increase the maintainability costs, as any changes to the code must be made in multiple places.

The tool is open-source and free to use. 

I wouldn't recommend the product to others. I recommend GitLab for anyone looking to work on mature CI/CD pipelines. I rate the overall product a four out of ten.