Tekton Reviews

We use Tekton for build and deployments. For LMP testing, we use the Tekton pipeline. We also use GitHub CI/CD. For infrastructure pipelines and Infrastructure as Code (IaC), we use Tekton. Previously, we used Jenkins pipeline for normal Pipeline as Code (PSC). After that, we migrated to Tekton.

After seeing Jenkins and Tekton, I think Tekton is quite built on top of Kubernetes, so the learning curve is minimal. If you are working with Kubernetes, then OpenShift created Tekton on top of that, making it easily adaptable.

Tekton is highly customizable. With Kubernetes, we can customize on our own and create custom builders. If teams have time and want to make enhancements, they can do it themselves. Whatever OpenShift is providing regarding Tekton is sufficient.

It is easy to use because we don't need to write every pod step every time. A proper DevOps engineer can help once or twice, and development teams can easily adapt to that, make small shell script changes in the steps, understand the process, and work with it.

I didn't get the intention of scalability. Scalability means based on the load, it will automatically gain resources and run. The question of pipeline scalability remains unclear. It's quite easy to use. We can attach storages and increase them. With proper admin privileges, we can do virtually anything. In AWS, I have seen two pipelines: one pipeline from GCP CAS and another from on-premises CAS. In the sandbox environment, I have seen the ROSA platform for AWS ROSA. The implementation is quite straightforward, with everything being similar.

I have been using Tekton in my organization for around one and a half years. It has been used for quite a long time in the organization, but I have been exposed to it for one and a half years.

I didn't face any issues with stability. The technology is good, but if the actual resources are not high for that pipeline, then it will slow down. It is purely based on resources. Stability-wise, it is very stable, and we can seamlessly integrate. Tekton runs on CAS only.

It's a very good product. I have experience with Jenkins, which is purely based on Java. Based on the Jenkins pipeline, I would suggest Tekton is a very advanced solution and easily usable.

Tekton is customizable because with Kubernetes, we can customize on our own. Custom builders can be created. If teams have time and want to make enhancements, they can do it themselves. Whatever OpenShift is providing regarding Tekton is adequate.

In my organization, we have a Dev enablement team, which is the DevOps team. They provide comprehensive support, so we are not exposed to that part.

I have been using Tekton for just one and a half years, so I should have more experience to provide comprehensive advice. I am just a user of Tekton and am not familiar with their pricing structure.

We have been working on CAS for the last six months. I signed up for Tekton because I'm extensively exposed to it. I cannot comment on other products as my experience is purely in development.

To the best of my knowledge, I will give quality answers to whatever I know.

We use Tekton as a pipeline, specifically a CI/CD pipeline. We have created all these stages, such as build, deploy, and test, within Tekton in an OpenShift cluster. We use these technologies for all our development code. We have written our developing code in Java, Scala, and Tekton. 

Our workflow includes creating embedding vectors, detecting secrets in the GitHub repository, and more, all managed by Tekton stages.

Moving from Jenkins to Tekton has significantly reduced our costs. Previously, we were spending around $6,000 per day on our Jenkins pipeline for the same workload, whereas now we only spend around $1,000 dollars per day. This reduction is due to Tekton's cloud-native nature, which allows for efficient resource consumption and auto-scaling. By implementing Tekton, we have achieved a six times cost reduction.

Tekton is a cloud-native solution. It offers optimal resource consumption, allowing tasks to be run more efficiently and at a lower cost. Tekton pipeline resources can be triggered automatically by GitHub through webhooks. With Tekton, tasks like build, test, deploy, and vulnerability scanning are streamlined. 

Additionally, custom tasks offer the ability to integrate notifications to the building team via Slack or email, and the pipeline will only start after approval, enhancing the efficiency of deployment processes.

One area for improvement is the number of CRDs created during installation. Tekton currently creates 10 to 11CRDs, which can be overwhelming. Instead, it would be better to have just one CRD that can handle all the information and create other necessary components automatically. 

Additionally, more integration capabilities for security, such as DAST, SAST, and IAST, should be directly built into Tekton to facilitate easier implementation of security features.

I have been working with Tekton for almost four years.

In OpenShift clusters, we have encountered issues related to memory and CPU usage, and webhook configurations not triggering as expected. This has sometimes resulted in redundant pipelines running simultaneously for the same feature branch. We resolved this by creating our own customized operator to ensure only the latest pipeline runs.

We found Tekton to be scalable. We manage this by configuring CPU and memory limits for each task, allowing tasks to start with minimal resources and scale up as needed, ensuring optimal resource utilization.

We have not directly escalated issues to the Tekton technical support team. Instead, we address issues by creating our own customization operators to resolve them internally.

We previously used Jenkins. While Jenkins required writing in Groovy script and developers needed to be familiar with Jenkins files, Tekton simplifies this process by automatically handling tasks based on cluster definitions.

The initial setup in an OpenShift cluster is user-friendly, taking around five to ten minutes to configure. For Kubernetes, it might take fifteen to twenty minutes. 

One area that could be improved is reducing the number of CRDs created during installation from around twenty to thirty to just one CRD to streamline the setup process.

We implemented Tekton with our own internal team. We configured timeouts, SSL certificates for webhooks, and resource limits to ensure efficient operation.

Shifting to Tekton from Jenkins has considerably reduced our costs, with savings from six thousand dollars per day to approximately one thousand dollars per day. This sixfold reduction is due to Tekton's efficient cloud-native features and resource optimization.

I would recommend Tekton for creating CI/CD pipelines due to its ease of learning, adaptation, and cloud-native features. Tekton allows for the creation of cluster tasks without requiring developers to write complex configuration files, unlike Jenkins.

I'd rate the solution eight out of ten.

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 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.

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

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

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

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

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

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

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

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

Positive

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

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

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

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

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

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

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

I'd rate the solution ten out of ten.

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.

I have been using Tekton for close to the last three years. The major reason is that I'm part of the IBM Cloud Kubernetes service, and most of my work is on Kubernetes. Tekton being Kubernetes native, was one of the reasons to adopt it. IBM is already doing a lot of work around Tekton.

Tekton has significantly helped us take the workload off Jenkins. This has directly impacted the cost of maintaining Jenkins. Tekton being lightweight means that the resource impression is much less compared to Jenkins when running inside Kubernetes clusters. If we were running 200 complex jobs or pipelines with Jenkins, we have been able to do the same in Tekton with a much smaller number of resources, almost half.

I appreciate its declarative style, which is easier to operate compared to something like Jenkins. Tekton offers better control in writing different pipelines or workflows, and its style is easier to understand. 

Additionally, Tekton's inclusion in Kubernetes deployment offers better visibility on how Tekton is performing within a cluster. It is lightweight and not as heavy as Jenkins to maintain.

I haven't come across any complex issues so far, but I would like to know more about complex implementations done by different teams and how they have scaled their Tekton architecture. It would be beneficial to find case studies or more information on these implementations.

I have been using Tekton for close to the last three years.

We have not faced significant stability issues or bugs. We keep up with Tekton version upgrades to maintain compliance. IBM is active in the Tekton community, so we have internal support and can reach out to the community if needed. We haven't had any issues where Tekton has caused production problems or customer issues.

Tekton has really helped us in terms of scalability by reducing the cost of maintaining Jenkins through its lightweight design. We're able to run the same number of complex jobs in much less resource capacity as compared to Jenkins. We're still using Travis CI, Jenkins, and Tekton and haven't fully transitioned, so the complete scalability of Tekton will be seen over time.

Since IBM is pretty active in the Tekton community, we do have some internal support. We can always reach out to folks who are ready to help.

Positive

Initially, we were using Travis CI and Jenkins a lot. While I still use them, much of our work has shifted to Tekton due to its Kubernetes-native functionality.

The initial setup of Tekton can be between easy to moderate. It depends on the type of workload running in the Kubernetes cluster. For simple implementations, it is not that tough to start. However, building complex workflows and pipelines might take some time.

An internal team handles Tekton upgrades and compliance issues. They reach out to us if any bugs or issues need to be sorted out on our end.

Tekton has significantly reduced our costs compared to Jenkins. The lesser resource requirement for running complex jobs translates into direct cost savings.

For anyone starting with Tekton, it would be best to go through the documentation, examples, and videos available on the Tekton project GitHub repo and YouTube. Start with smaller implementations and see how they work out before completely replacing existing CI/CD tools.

I'd rate the solution 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 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.