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 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.

We are using Tekton for building some of our CI pipeline, continuous integration pipeline, as well as integrating some of our other pipelines, such as test pipelines.

In terms of cost savings, Tekton does not require licensing. If you have a Kubernetes or OpenShift environment, everything related to Tekton is free. Additionally, there are time-saving benefits as Tekton makes it easy to bring up pipelines quickly, which is particularly useful if the environment is lost.

The most beneficial aspect of Tekton is its compatibility with containerized applications. Since I am skilled in Docker, Kubernetes, and OpenShift, Tekton aligns well with these technologies. Unlike Jenkins, which requires an external node, Tekton eliminates that need. 

The installation process is seamless, requiring fewer resources compared to Jenkins. Tekton supports CLI and graphical user interfaces, is Kubernetes-native, and is particularly suited for event-driven cases. Each component is managed as code in YAML, making it easy to maintain and set up pipelines in different infrastructures.

Tekton lacks integration capabilities compared to other CI/CD tools like Jenkins and Travis. For instance, Jenkins offers plugins that facilitate easy integration with other software delivery tools. 

Tekton needs to improve its endpoint communication routes for better integration. Another area for improvement is security management. 

Jenkins offers RBAC for user access management, which Tekton lacks. Additionally, Tekton currently has no backup mechanism for execution logs, which puts run-related data at risk of loss.

I have been working with Tekton, along with Argo, for the last four years.

Tekton is stable. I have never encountered scenarios where Tekton-based components were in a degraded state or not working.

I have not worked on Tekton from a scalability perspective so I cannot comment on its scalability.

I raised a feature request for parallel execution at the step level in the official Tekton forum but did not receive a solution. Technically, the support was skilled, and I would rate them a seven out of ten. However, from the perspective of the solutions provided, I was not satisfied.

Neutral

In our discussions, we frequently compared Tekton with Jenkins due to Jenkins' widespread use and its robust plugin ecosystem.

Initially, we deployed Tekton using the required YAML files. Currently, we deploy using the operator, making the process about 70% easier with some issues.

I deployed Tekton individually. Not many people were involved in the process.

Tekton does not require licensing fees. If there is a Kubernetes or OpenShift environment, everything related to Tekton is free. This results in significant cost savings compared to licensed tools like Jenkins, Travis, or Bamboo.

We compared Tekton with Jenkins and Travis, noting that Jenkins and Travis have better integration features but Tekton offers advantages in resource requirements and ease of deployment.

I recommend Tekton for CI/CD pipelines due to its event-driven capabilities and Kubernetes-native approach. The setup, maintenance, and cost benefits are significant. Tekton's approach to managing pipelines as code ensures that you can easily recreate and maintain your pipelines across any supported infrastructure.

I'd rate the solution six 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 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.