Tekton Reviews

We use the product to create and configure pipelines, manage continuous integration and continuous deployment (CI/CD) processes, and handle deployment activities for various environments such as development, staging, and production. It is instrumental in managing deployments in a microservice architecture.

The platform's most valuable feature is the ability to manage pipelines step-by-step. The 'promote' feature is beneficial as it simplifies deployment processes by allowing easy promotion of applications to different environments without needing to re-run CI/CD processes. 

The product's version update management process needs improvement. Synchronization issues with other tools or libraries, like OTEL and Datadog, have been noted. Automated handling of these updates would be beneficial, as manual updates can be cumbersome.

I have been using Tekton for more than two years.

There have been occasional system downtime issues. I rate the stability an eight out of ten. 

The solution scales effectively through its integration with Kubernetes and microservice architectures. I rate the scalability an eight out of ten. 

I have not contacted Tekton's support team directly, but we have engaged Google support when necessary. Our internal team handles initial issues and escalates to the community or support teams as needed.

Tekton is a powerful and flexible open-source tool for CI/CD pipelines. It is effective for building, testing, and deploying applications in cloud environments. Its open-source nature allows for extensive configuration and customization.

Overall, rate it a nine out of ten as a product. It stands out well compared to other solutions like Jenkins. 

We don't know the customer's end goal, but we are developing a cloud-agnostic platform based on their wishes. That's why we moved almost all our architecture to Kubernetes. For our development pipeline, which is cloud-agnostic, we also put all our CI/CD pipelines on Kubernetes. We decided to use Tekton because it's Kubernetes-native for CI/CD. Currently, it works on Kubernetes in the GCP and Azure. So we use Azure Kubernetes Services and GCP.

The first functional requirement we wanted from Tekton or any other CI/CD pipeline was to be cloud-agnostic. We met this requirement with Tekton. One of our main goals was to improve the development experience. We wanted a narrow branch approach so developers could easily create isolated environments for feature branches. In this environment, it's good to have independent assets like the build system. For example, if a developer wants to develop and use microservices, they can create a feature branch, and Tekton and any build assets are isolated to this branch. Tekton allows this because it is a native Kubernetes build system and works with Kubernetes namespaces as an isolation strategy. You can isolate most Tekton assets in the Kubernetes namespace for your feature branch. This allows you to freely change Tekton assets and objects to adapt to your feature branch and requirements. Additionally, when you remove a namespace, all Tekton assets are removed with it, so you don't need to clean up build assets manually.

Based on the event triggers, we found a workaround proposed by the Tekton team. This involves trigger groups. However, I'm a bit worried about scaling Tekton from the point of view of big CI/CD processes. As you know, Tekton uses a Kubernetes native approach with a controller feature. The controller is a service that controls every aspect of Tekton's work in the cluster. The problem is that this controller works in a single zone. You can configure the number of replicas for this controller for high availability, but the controller doesn't allow a sharding strategy. For example, you can't set up the controller to process only a subset of the Tekton objects in your cluster. This singleton approach could lead to performance problems in the future. Currently, our production controller takes around 500 megabytes of RAM. If our environment grows, it might take one or two gigabytes. It would be better to have a sharding or partition strategy to distribute the load from the single controller to multiple ones.

I have been using Tekton for the past six months actively, but extensively I started exploring it two months ago.

Tekton is convenient because, previously, I had experience with GCP Cloud Builds. The good thing about Tekton is that it works well with autoscale in Kubernetes. You can set up zero nodes, and when you run your Tekton CI/CD pipeline, the number of nodes will grow automatically. This allows for cost efficiency from a build point of view because you won't need to have pre-existing nodes for your workloads.

My organization is promising to move all our builds to Tekton. Of course, we have some concerns about scalability, but for now, it works okay.

We found the solutions faster than the technical team answered us. They have a standard GitHub community forum or issues list where you can ask questions and create issues. But I think their response is not so fast. It took around maybe one week to get an answer from them. But, of course, it's understandable because this is open source and not a paid project for them. 

The process of installation has worked smoothly. You just run a couple of commands, and Tekton is installed in your Kubernetes cluster. There are no problems here at all. We did meet some issues with the default configuration of Tekton because, by default, Tekton uses the Affinity feature, some kind of PostgreSQL feature. This feature, when enabled, prevented better scaling. We turned it off, and everything worked as we expected. By default, this feature is turned on, and we met some scalability issues. This feature allows assigning different pods for the same pipeline to the same node. But if you set up different requests and limits for different stages of your pipeline, assigning them to the same node prevents scaling up the node pool. That's why we turned this feature off. Now everything works okay. So maybe the default configuration of Tekton is not perfect, at least for our scenario.

Initially, our project was located in the GCP, but our customer wanted to make it cloud-agnostic. They wanted to move it to Azure and maybe on-premises afterwards.

Based on our requirements, the main need was for a cloud-agnostic platform, which is why we chose to run everything in Kubernetes, and Tekton fits this task easily. If you're familiar with other CI/CD pipelines like GitHub Actions or GitLab CI and they meet all your requirements, it might be good to stick with them. They are quite similar in functionality. Tekton stands out because it provides supply chain security out of the box with Tekton Chains, which we use. It includes built-in tools to sign and verify images. GitHub Actions and GitLab CI don't have this feature out of the box, so you'd need to implement it yourself. For better security, Tekton might be a better fit.

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.

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. 

At our company, we use Tekton for the deployment pipeline, and it's also implemented in the Kubernetes cluster. Tekton manages the CI/CD pipeline processes. 

The flexibility of Tekton is the most valuable feature. Multiple pipelines can be built using Tekton, and the solution acts as an operating system for the CI/CD operations. 

Tekton lacks sufficient documentation, which makes it quite difficult for startups to handle the product. 

I have been using Tekton for one and a half years. 

In our organization, we have faced some issues with the stability of the solution. It's unclear to our company team that how the product handles the APIs, because resources are available for Tekton with varying API versions. The aforementioned fact creates confusion about which API version to use in Tekton which can be solved only by thorough reading of the documentation. But at our company, we haven't faced any bugs in the solution. 

It's a scalable product. There are about five Tekton users in our organization. 

Our organization's issues with the solution were solved using the documentation and the GitHub repository. 

At our company, we are planning to switch to a simpler solution than Tekton due to its lack of documentation and simplicity. 

At our company, we are able to install Tekton seamlessly without any issues. 

At our company, we used the open-source version of Tekton to manage the infrastructure. 

The main trouble with Tekton is that you need to understand the native concepts and the instructions that can be used to manage the pipeline. I would advise others to use Tekton only for complex deployment processes and also if there is a need to integrate the CI/CD software within the Kubernetes cluster for cost-effective reasons, otherwise simpler solutions like GitHub Actions can be used.

Everyone should gain sufficient knowledge and training on Tekton before using the product. Once a team has adopted Tekton, switching to another product can be difficult. 

Tekton allows integration to make the deployment process smoother. In our company, Tekton is implemented within the cluster and thus actions like AWS resource modifications, addition of images to the container registry and permission updates can be carried out to improve organizational capabilities and efficiency in deploying applications. 

A beginner with a proper understanding of Tekton documentation, implementation and knowledge of CI/CD processes will probably not face any difficulty with the product. I would overall rate Tekton a seven out of ten. It's a high-end solution and if a user has enough time and resources, then Tekton can be used to solve every issue regarding deployment processes. Organizations with small teams should rather choose an easier solution than Tekton. 

I installed Tekton as an operator in OpenShift. Tekton is a pipeline tool. It operates within OpenShift, which is similar to how Kubernetes resources are managed. With Tekton, we utilize CRDs to define pipelines. Using the Tekton dashboard, we can create CI integrations for our applications. For instance, I used Tekton to manage CI for a Cloud-based Java application and an ongoing frontend application. Tekton's form-based approach is convenient for declaring variables and commands, handling secrets, and authentication. Overall, Tekton's ease of use and competitiveness compared to tools like Jenkins or GitHub Actions made it the preferred choice.

I use Tekton for pipelines in its original form, leveraging all the information and documentation available.

Tekton boasts multiple integrated features, making it a versatile tool. Tekton simplifies tasks by providing a beautiful interface and clear interactions. It seamlessly integrates with GitHub, enabling direct interaction. It is convenient to declare comments and variables within the same interface, eliminating the need to search for them before executing commands. In essence, Tekton functions as a comprehensive dashboard, encompassing all necessary features.

The deployment could be more accessible.

I have been using Tekton as a partner for one year and two months.

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

The documentation is very good.

The first time I connected to Docker Hub through Tekton, I encountered an issue with authentication parameters. Initially, I couldn't find where to declare the authentication credentials. These files had to be declared as a config map in OpenShift. Once configured, this config map had to be used as a parameter with Tekton. Although I spent some time searching for this information, eventually, It became straightforward, especially after using it in multiple projects.

Tekton was installed with OneClick. It's very fast to install this operator on OpenShift. It takes about fifty seconds to deploy entirely

Tekton integrates seamlessly with GitHub, creating three distinct environments: pre-production, development, and testing. Each environment is efficiently managed using Spectrum. It maintains its variables and comments before launching pipelines in any environment, ensuring clear separation. Installing it on OpenShift is considered one of the most valuable tools for DevOps engineers, providing a comprehensive view of the application.

Tekton was utilized within OpenShift and deployed on an on-premise server. We employed Argo CD for deployment. Kubernetes manifests were authorized and stored in GitHub. Tekton is tailored for the GitOps approach and is recommended to be integrated directly with GitHub repositories. With Tekton, CI pipelines were initiated. After completing the CI process, an image was generated and stored in GitHub. Subsequently, this image was utilized by Argo CD as a container for deployment, and OpenShift deployed it using Kubernetes manifests.

I recommend Tekton to my friends who work on a per-shift basis instead of Jenkins because, with Tekton, you don't need to install plugins or configure them. All the necessary plugins are already installed in the base image of the tool you want to use. You must install that base image, which is readily available in the developer hub or from another image provider. 

Tekton is easy to use in the pharmaceutical industry. This ease of use stems from its versatility in supporting two main types of workflows: working with AML files or utilizing forms with cases to manage and specify parameters and comments.

We are an organization focused on automating infrastructure and creating CI/CD pipelines for application development.

My advice is to leave it for open source rather than having the technical enterprise handle it, allowing students and universities to engage with it. As an instructor, It is advantageous for them to learn and adopt Tekton because it's relatively easy compared to Jenkins. Many students and Jenkins users struggle to learn about CI/CD and default pipelines, so I strongly recommend using Tekton.

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

We mostly use Tekton to run all of our pipelines. We create unit tests and also use it for Jira build messages as well as the Docker build application. We check the logs within Tekton itself and create a manifest to deploy in our development, test, and other environments.

We can create multiple pipelines with Tekton. I find it beneficial to show data from Tekton to another GitHub or Bitbucket pipeline.

It would be better if Tekton could show the YAML file while it is running, similar to GitHub pipelines, to provide more visibility on what's happening. We need information on the duration and specifics of the running pipeline for easier analysis.

It's been one year since we started using Tekton.

Tekton is a stable product. It comes integrated with OpenShift. We can definitely use it, and it supports authorization and authentication, enhancing security.

We can easily scale Tekton as it is integrated with OpenShift clusters.

Previously, I was using a setup PSD pipeline.

The initial setup is not straightforward. We run it on-premises, meaning there must be an open-source cluster with a Tekton pipeline. The pipeline pods should also run in the same cluster.

The implementation is usually handled by the DevOps team.

Pricing varies based on whether the user is an enterprise or individual. Exact pricing details are managed by the company.

I recommend Tekton, but users should have some underlying knowledge about how CI/CD pipelines work.

I'd rate the solution eight 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.

I use Tekton generally for CI purposes and automation APIs.

We have created a Helm template for Tekton, and we're currently working on scripts. This allows us to create pipelines on the fly, which has significantly streamlined our workflow.

I have full control over it, actually, in my team. Another thing is that Tekton is based on Kubernetes. In Kubernetes, we have the concept of cron jobs which run on a time-to-time basis. In Tekton, we have the concept called task or task runs. We can expose an API and use the trigger and trigger-binding concept, allowing us to trigger tasks whenever needed. This mechanism is very nice.

RBAC is really needed for Tekton. Also, if you have too many PVCs and don't clean them up, it may stop working due to the limited number of PVCs you can create in a cluster.

I have been using it for the past two years.

Tekton is a stable product. One issue we might run into is when there are too many PVCs that haven't been cleaned up. We have mitigated this by creating a CronJob that runs every midnight to clear those tasks.

Tekton is scalable if well-planned. However, it is not a plug-and-play solution for now. You need to write the tasks according to your business case, which might differ from team to team or service to service.

While setting up, I was initially active on their Slack channel where I was able to get help. They were responsive.

Neutral

We were using Jenkins before Tekton.

The initial setup was daunting and took me four months to set it up and get the flow. There is a steep learning curve, especially with concepts like event listeners, event triggers, and trigger binding.

Tekton was initially very daunting, and it took me a long time to get the flow. However, once you get it, it’s awesome.

I'd rate the solution six out of ten.