Tekton Reviews

It is an open-source tool initially developed by Google for internal use, later open-sourced, and widely adopted for building and deploying applications in Kubernetes environments. When deployed in a Kubernetes cluster, Tekton seamlessly integrates with the environment, streamlining the application pipeline delivery process. It automatically triggers when code is merged into the main branch, operating natively within Kubernetes without requiring additional external components. The automated pipeline, initiated by Tekton, builds the application, deploys it to specified container registries, and then to the Kubernetes cluster. Tekton's versatility shines in multi-environment setups like staging, testing, and production, efficiently managing the continuous integration (CI) part by triggering processes linked to code merges. Users often integrate Argo CD to complement Tekton in the continuous deployment (CD) phase. Argo CD pulls and deploys the latest application image within the Kubernetes cluster, creating a comprehensive and automated CI/CD workflow.

Its user-friendly features include a clean and sleek dashboard. This dashboard provides detailed logs and stages of the pipeline, offering transparency into each step of the process. In case of any failures at a specific stage, the dashboard provides comprehensive information about the issue, enabling quick identification and resolution. Another valuable aspect is its lightweight nature. There's no need for additional deployments or reliance on external vendors for CI/CD, resulting in significant cost savings. Its seamless integration with Kubernetes, being built on top of it and utilizing Custom Resource Definitions, ensures a smooth experience within Kubernetes environments exclusively. Its capability to build entire applications within containers contributes to a seamless and efficient workflow. It stands out for its customizability and scalability, allowing users to undertake diverse tasks.

It tends to occupy a significant amount of disk space on the node, which could potentially pose challenges. This aspect could be enhanced for better efficiency. Additionally, the build time, particularly for larger applications, seems a bit extended, ranging from five to ten minutes in some cases. There's room for improvement to streamline and minimize the build time.

I have been using it for the last six months.

The product appears to be stable, I haven't encountered any noticeable bugs or errors. It has proven reliable in automatically executing tasks once triggered, making it a dependable tool.

The developers' team, consisting of over thirty or forty individuals, actively uses it.

The initial setup was quite straightforward since it comprises various components that are defined separately and then combined to create a pipeline.

Deploying it was easy and seamless, but creating a pipeline involved a bit more effort, requiring attention to various details and taking some time. Despite the complexity of creating pipelines, the overall deployment and readiness of the tool for use were smooth and uncomplicated. Understanding the architecture of this technology is crucial. For newcomers, there might be a learning curve initially, making it a bit more challenging. I am the one responsible for configuring, deploying, and creating pipelines for the development team. I have established a read-only dashboard that provides a clear and concise overview of the pipeline statuses when triggered.

It is entirely open source and free of charge.

While other options like Jenkins were available, Tekton's native compatibility and endorsement by a skilled team of Google developers influenced my decision. It is a stable tool from Google, providing authentication validation for applications. Additionally, I appreciated the seamless integration with Kubernetes, making it a native and well-developed tool for CI/CD processes.

I highly recommend that you operate in a Kubernetes-based environment closely integrated with Kubernetes. However, I suggest deploying it in a separate cluster, not where your primary workloads run, to avoid potential disruptions to production cluster resources. I also recommend it for users who are already familiar with the tool. While it offers significant capabilities, harnessing its full potential requires a certain level of understanding. Overall, I would rate it seven 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.

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. 

I use the product primarily for CI/CD in application cloud-native environments. It helps us build code, and occasionally, it is also used for deployment.

The platform's most valuable feature is its cloud-native and Kubernetes-ready design.It integrates seamlessly with container environments, providing a significant advantage for Kubernetes users.

While Tekton is highly effective for Kubernetes-based setups, it might not suit users who require more control over bare-metal environments.

I have been using Tekton intermittently for the past four or five years.

The product is stable. I have not experienced any crashes, and it operates reliably as a Kubernetes controller.

I have used Jenkins and Concourse before. 

Tekton is designed specifically for Kubernetes, making it a natural fit for Kubernetes environments. 

The initial setup was quite straightforward. I recently reinstalled it with minimal effort, particularly using the Tekton operator on OpenShift. The process was smooth, and there were no major challenges encountered.

The pipeline resources are comprehensive and meet our CI/CD requirements. They help automate the deployment process efficiently, and I have not faced significant issues related to resource consumption.

The product is free and open-source. Some platforms may have additional costs for advanced features, but the core framework is free.

Tekton has been more than other solutions efficient as it reduces the need to maintain servers like Jenkins. 

Overall, I rate it a nine 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 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.

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.