Tekton Reviews

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.

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.

While working with the client at Deloitte, we focused on enhancing our DevOps practices and ensuring site availability through continuous integration and deployment (CI/CD) pipelines. Jenkins was the primary technology in use at that time. However, the client expressed interest in transitioning to cloud-native, more efficient solutions to create a futuristic platform. We chose Tekton due to its compatibility with Red Hat OpenShift, which was already part of the client's Red Hat subscription. Tekton's ease of customization and availability as a default plugin in Red Hat OpenShift made it the preferred choice for our project.

Tekton's most important feature is its cloud-native nature. Unlike Jenkins, which may not scale as efficiently, Tekton's CI pipeline can automatically scale up to handle increased workload demands without needing manual adjustments.

Another important aspect is the level of customization offered by Tekton. Each task in the CI pipeline can be customized independently, allowing developers to write code in various languages like shell scripting, Java, or Python and incorporate them into the pipeline as needed. This level of abstraction and customization greatly benefits developers in creating efficient CI pipelines.

Also, it can be challenging to understand the logs and troubleshoot issues without clear guidance. It's not always easy to reach technical support and get immediate answers. In my opinion, improvement in this area would be beneficial.

When we started with Tekton around 2021 or early 2022, the community support was somewhat limited, which posed challenges when dealing with issues or debugging. We had to rely on Red Hat OpenShift support to overcome these challenges. However, I believe that these issues will naturally improve over time as the developer community grows stronger. From a technical perspective, I haven't had the opportunity to deeply evaluate the product end-to-end, especially in the past year or so, when I've been less involved with it.

During my time at Deloitte, I worked on a project using Tekton. I have one year of working experience with the tool.

Tekton is generally stable, although we observed occasional minor issues or bugs. I don't believe these were major issues caused by Tekton itself. It could have been due to configurations or other factors we missed initially. We were able to identify and fix these issues later on. But in general, Tekton is stable, and there's always room for improvement as it matures.

Since the Red Hat community developed Tekton, we had strong support from our Red Hat subscription. This meant that if we encountered any issues, we could directly contact the Red Hat technical team for assistance, and they were able to support us. By following the documentation and clicking through the necessary
steps in OpenShift, all the components were automatically set up behind the scenes, making Tekton ready to use without much hassle.

The initial installation and setup of Tekton were relatively straightforward and not too time-consuming. The documentation provided clear instructions on setting up the base Tekton server configuration. Additionally, integrating Tekton with Red Hat OpenShift was made more straightforward due to the platform's user-friendly plugins.

It is worth the investment because, from my perspective and expertise, it proves to be beneficial when used efficiently. For instance, if we compare it to running a Jenkins server, which has limited resources and can handle a specific number of applications, Tekton can provide better scalability and efficiency at a larger scale.

If you're dealing with many applications and need a reliable, scalable, and efficient system, I'd recommend going with Tekton, as it's more mature and has a growing developer community. However, if you prefer sticking to traditional technologies like Jenkins, especially if your team is already familiar with them and needs a quick ramp-up, that's also a viable option.

I would rate the solution an eight 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.

I am using Tekton for continuous integration in our project.

The feature that I like most about Tekton is that it is built for Kubernetes, so we can utilize our resources effectively.

Tekton should have more accessibility for some rare use cases so that we can have more references when applying some techniques to our pipeline.

I have been using Tekton since February.

If we set it up correctly and know exactly what we have done, it is very stable because it runs on top of Kubernetes.

I can't give an opinion right now because I haven't applied the scale to our deployment. It's only in our staging environment.

I haven't contacted support yet since most of my errors are addressed in their GitHub repository.

Positive

I had some experience using Tekton when my company migrated the CI panel from another platform.

The initial setup is rather easy because the tutorial is easy to follow.

Tekton is free to use. It's open source.

I would recommend Tekton to my coworkers if they use Kubernetes most at work. However, if my colleagues don't use Kubernetes, I wouldn't recommend Tekton to them because it is very difficult to understand Tekton if you aren't familiar with Kubernetes.

I'd rate the solution eight out of ten.

The CI solution of the team I worked for was based on Tekton. Since Tekton is a Kubernetes native framework, we can easily configure it within a Kubernetes cluster, which has many benefits.

I would say the customization ability that Tekton provides is good. As an example, if we look at the pipeline structure of Tekton, a Tekton Pipeline was built with Tekton Tasks. We can specify a Tekton Task within the pipeline YAML. Otherwise, we can specify the task in a separate YAML and add it as a reference within the pipeline so that we can use the Tekton Task as a reusable component in other pipelines as well. Another thing is that we can execute a Tekton Task based on conditions such as "when" expressions. Furthermore, Tekton provides Tekton Triggers. We use Tekton Triggers to dynamically execute a pipeline based on an event, which is also a very useful feature for us. These customization features of Tekton made it more valuable and flexible to use for us.

The product's documentation is an area of concern, making it an area where improvements are required.

Apart from the documentation, there is one more thing that I believe needs to improve in Tekton. In the Tekton pipeline structure, there is an optional feature called finally section, where we can add all the core Tekton Tasks, which have to be executed even in a pipeline failure scenario. But the issue is that we cannot give a sequence for the tasks in the finally section, so all the tasks are running simultaneously. I believe if we had a feature to help users add a sequence for the tasks in the finally section, then it would make our lives easier.

The scalability could improve a lot in the future.

I have been using Tekton for a year. I am a user of the tool.

Sometimes, we face some version compatibility issues, but when we upgrade the version, it gets rectified. Stability-wise, I rate the solution an eight out of ten.

I know that there are more than 20 people using Tekton within our company. As the CI solution in our company is based on Tekton, many people, including new joiners, also have to learn Tekton. Scalability-wise, I rate the solution a seven out of ten.

When our company faced challenges with the tool, we had to do our own trials and errors to find a solution. Sometimes, we had to go through some GitHub issues related to the challenges we faced, but most of the time, we couldn't find an exact solution by looking at the GitHub issues. So we had to try to resolve the issues we faced in Tekton with the knowledge we had. We did not contact Tekton's support team.

Tekton's integration capabilities have helped our company's development workflow. Tekton is a Kubernetes native framework, so most of the command lines that we use in Kubernetes could also be used within Tekton framework. Basically, configuring Tekton Pipelines within our Kubernetes cluster was very easy compared to using other solutions. Overall, the development workflow was easy when using Tekton.

As a beginner who is trying to use Tekton, it will take some effort to learn it because the documentation in Tekton has to improve a lot. There are no tutorials to learn about Tekton because I personally learned it from my seniors and my experience and even when we faced challenges in the development, we couldn't find a solution on the internet. We had to do our own trial and error to find a solution, which was one of the main challenges while using Tekton.

I recommend the tool to others as using Tekton makes our lives easier. As far as I know, many companies don't know about Tekton. If they knew that there is something called Tekton, they would definitely adjust to it. 

I rate the tool a nine out of ten.