Tekton Reviews

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. 

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.

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 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.

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 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.

The platform's most valuable feature is its wireless capability, which makes installation easy and sets up the flow.

The product's UI could be improved, as there are occasional latency issues. The triggering part, especially the CRD installation needs enhancement.

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

The platform could be more scalable. 

The technical community support could be better.

Neutral

The initial setup process is easy. 

The product is free of cost.

We used Tekton to integrate it with different DevOps tools. We used various SaaS tools like Fortify and Jenkins and security tools such as JMeter and Google Lighthouse. 

I rate it a seven 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.