Tekton Reviews

I use the platform to manage development pipelines. Our infrastructure is integrated with Kubernetes, and we utilize it within an OpenShift environment for automation. I have developed various pipelines and plugins for both front-end and back-end applications, including Angular for the front end and Quarkus, a Java framework for microservices, for the back end. The platform supports tasks such as code cloning, testing, and deployment by integrating SonarQube, Argo, and Nexus tools.

The product's best feature is its ease of implementation. It is well-suited for microservices architecture and integrates seamlessly with Docker and other tasks. The orientation towards microservices makes managing different tasks and projects efficient.

Initially, working with YAML configuration can be challenging using the solution. 

I have been using Tekton for two years.

I have not encountered any stability issues with the platform.

Approximately four people in our organization use Tekton. It is a scalable platform. 

The setup process is simplified by its integration with Kubernetes and its examples for various tasks.

I suggest utilizing available tasks and resources, such as copying and using tools like ChatGPT, to write and configure tasks. 

The platform is user-friendly and provides good support for managing different pipelines.

I rate it an eight out of ten. 

I primarily use Tekton for continuous integration purposes. When we build applications, we use Tekton for CI. For deployments, we use ArgoCD. Most of the time, we use Tekton to facilitate the CI process.

Tekton is primarily a time-saving solution. While it does take some time to set up initially, it is very efficient once running. It helps manage deployments and separates processes accordingly, which benefits both developers and me. Developers don't have to worry about the deployment or integration part as Tekton takes care of those aspects, making it easier for me to manage the pipeline.

Tekton allows you to categorize tasks according to your needs and minimizes the amount of code needed. For instance, you can separate tasks to suit your requirements. Additionally, when integrating with Terraform, Tekton makes it easy to trigger only specific parts of the infrastructure, which is beneficial for ops engineers.

For infrastructure deployment, integration is somewhat complex, especially when using Terraform with Tekton. It would be beneficial if this process were simplified.

I have been working with Tekton for about one year now.

Sometimes, when there are updates and patches, it can cause issues. For example, building a Docker image may require changing the base image due to upgrade issues. However, understanding Tekton properly helps in resolving such issues easily.

Tekton is very scalable. It's particularly effective for managing resources across multiple clusters and regions, integrating resources from different cloud providers.

Before Tekton, I used Jenkins and GitHub Actions for CI/CD pipelines. I also used Bitbucket pipelines for smaller web-related projects. These options required maintaining multiple pipeline files, unlike Tekton, which allows for streamlined categorization and management.

For infrastructure deployment, we categorize each Terraform file according to the specific components needed, such as VPCs and subnets. We maintain separate repositories for Tekton files and deploy specific components by providing the necessary paths and executing the appropriate files. Depending on whether it's a development or production environment, we maintain the appropriate pipelines.

I'd rate the solution eight out of ten.

I use it for the CI/CD pipeline. The client wanted to create a pipeline for this workflow to be deployed in his kubernetes cluster whenever he made changes. We had three different pipelines for three stages: one for dev, one for production, and the other for QA. The client was unfamiliar with this process, so he wanted us to create three different environments to eliminate manual processes.

With the help of Tekton Hub, we accessed example tasks that were very useful for everyone involved. From that hub, we took a sample task and created our own. It was straightforward to set up. We built the software image, and once that was done, we implemented the deployment process in the same pipeline, where the Helm Chart gets updated with the image name using the check command.

We also integrated the branch nodes through the request process, making it easy to trigger deployments cleanly. Compared to other tools like Argo CD and Argo Workflows, we found them very helpful, as they require different UIs and workflows.

The most valuable features are trigger functionality and the dashboard because they easily highlight our errors. Tekton allows us to see both CI/CD in one place. Unlike other products, Tekton makes managing the entire CI/CD process much easier than separating it into different parts. 

Tekton could use better documentation. We struggled due to the lack of clear documentation for triggers. Everything else was documented very well, but that section needs improvement.

I have been using Tekton for one year.

Tekton is very stable. They release a beta version approximately every two months, but they maintain the stable version until they are confident that the beta version is ready for use.

Scaling up and down is straightforward. The cleanup process in the pipeline section is also very easy. We can quickly delete any tasks.

We never had a chance to contact the support team.

Tekton is open source, so we never encountered any pricing issues. We were able to use it free of cost from end to end.

I was part of the DevOps team, and once our developers completed their code, it was easy for us to trigger workflows. When they wanted to deploy to different environments, like from development to QA and then to production, Tekton made it very user-friendly. Developers often lack knowledge of operations, so they don’t always know how to trigger processes. With Tekton, we managed to achieve this seamlessly without requiring developer intervention.

Tekton is easy to use for someone familiar with the CI/CD process and who has experience with manual authorization and deployment in Kubernetes. There may be a learning curve for beginners, but anyone with basic knowledge of Docker and Kubernetes will find it easy.

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

We use Tekton primarily as a CI/CD tool. We develop the product, and after developing the product, we deploy it to the cloud. Before deployment, Tekton is used as a CI/CD tool to validate and check our test cases, vulnerabilities, and licensing issues. If any test cases are written, they will first validate Tekton cases. Once the test cases pass, it moves on to check for vulnerabilities and licensing issues using Fosa, which is one of our QA and Check Point tools.

Tekton has significantly improved our organization, especially in the area of reusability. When we moved to Tekton from Jenkins, I felt that the tasks could be reused for any number of pipelines within the same cluster, which was not the case with Jenkins. This reusability is a major benefit. Moreover, it has streamlined our CI/CD pipelines, making the deployment process much more efficient. Tekton provides a clean UI interface and allows us to run multiple tasks simultaneously, which has enhanced our efficiency and productivity.

The most valuable features of Tekton include the reusability of tasks, the clean UI interface, and the binding of services and secrets. The tasks can be reused for multiple pipelines, making it very efficient. The UI interface appears very clean and user-friendly. The binding of services and secrets is also very clear and well-organized.

One area where Tekton can improve is log management. Currently, logs are often deleted after a day, making it challenging to refer back to logs from previous pipelines. It would be beneficial to have access to logs for at least the past two or three days. 

Additionally, stability needs to be improved. Sometimes Tekton crashes or freezes during important deployments, and this can cause delays. Enhancing stability and log management would greatly benefit users.

I have been using Tekton for almost three years, approximately from the time our organization migrated from Jenkins to Tekton.

The stability of Tekton needs improvement. Occasionally, Tekton crashes or freezes during important deployments, which requires waiting and troubleshooting. This instability can be problematic, especially during critical launches.

Tekton's scalability is generally good, but there is room for improvement. The resource quotas are somewhat limited, and increasing the resource quotas could enhance scalability further. The ability to run pipelines in parallel is a good feature, but expanding the resources would improve scalability even more.

Our organization has sufficient technical support for Tekton. However, there are times when more support would be beneficial, especially when dealing with production launches and critical deployments.

Neutral

Before Tekton, we used Jenkins. Our organization decided to switch due to the cost, performance, and the ability to leverage new tools and applications.

The initial setup of Tekton was somewhat challenging. It took a while to understand the various components, such as service binding, role binding, and how to create routes and bind services. It was a bit difficult at first because I was the first person in my team to explore Tekton, but after gaining an understanding, it became much easier.

The deployment and implementation were handled within our organization. A few team members, including myself, explored the functionalities and shared our knowledge with the rest of the teams.

The return on investment from Tekton is primarily seen in time savings. Once the initial setup is complete, the automated processes reduce the time needed for deployments and streamline the workflow.

I'd rate the solution seven out of ten.

We are utilizing Tekton as a pipeline tool for their CI/CD process, which involves connecting GitLab to Nexus, then Nexus to Argo CD, and ultimately to Kubernetes.

We are a Kubernetes-centric company, so it's advantageous for us to use a cloud-native, Kubernetes-driven solution. Tekton is serverless and runs on OpenShift, and we leverage Tekton to take full advantage of the Kubernetes features such as running and scaling the solution in PaaS.

There is a need for substantial improvement in connecting with other tools and open-source software. Configuring Tekton requires a deep understanding of Kubernetes, which can be difficult for developers. Furthermore, there is no existing template that gives defaults for developers to build a pipeline, making it challenging for them to use. In conclusion, Tekton is not particularly user-friendly for developers and has room for improvement.

I would like Tekton to change its dashboard to be similar to the one GitLab offers.

I have been using the solution for one year.

We are not relying heavily on Tekton or OpenShift for stability since our applications used in the DevOps culture are not critical ones, thus reducing the risk.

Tekton is a scalable product that we have not yet taken full advantage of. Although our needs are relatively simple, focusing on DevOps delivery, we have not reached the desired level of use.

Setting up Tekton initially was not a simple process. We did not choose to use Tekton, but rather it was selected due to its availability. IBM promotes Tekton and its integration with OpenShift, so when we set up OpenShift a year and a half ago, we also set up Tekton. We have already implemented GitLab Runner for multiple projects, replacing Tekton. GitLab Runner has been found to be advantageous for developers, due to its ease of use. As a result, we are now running two distinct pipelines for different projects, with the majority of developers preferring GitLab Runner over Tekton.

I give the initial setup a five out of ten.

The implementation of Tekton took some time due to operational challenges, rather than a lack of technical knowledge. These challenges included a lack of understanding of Tekton and the availability of the infrastructure personnel. The overall implementation took us around one month.

We collaborated with IBM and Red Hat vendors to set up the OpenShift PaaS solution. To ensure a successful outcome, we conducted a proof-of-concept (POC) in parallel with the vendors.

I give the solution a five out of ten.

We have around 50 people using the solution in our organization.

From a usage perspective, people are trying to move up from Tekton to GitLab in our organization.

Using Tekton depends on the strength of our Red Hat resources. I recommend GitLab over Tekton.

I used Tekton to integrate data functionality within a major automobile industry. I created Tekton pipelines in Kubernetes clusters to complete the CI/CD end-to-end from the source code repository in the Google Cloud Platform. This involved taking the ML training model and deploying it in the Kubernetes clusters, Cloud Run, and App Engines.

Tekton has provided flexibility and robustness in our processes. However, I faced challenges with the integration with the source code repository. The tool is very robust and provides great flexibility once you understand how to use it, but it is initially difficult to learn and understand.

The most valuable feature is the pipeline. When you run a pipeline, all the jobs are called. It is a very valuable feature that enhances job maintenance overall. 

Another valuable feature is the standalone task that sticks to isolation. This feature is very good for our needs.

I faced significant challenges with integration, particularly with Git or any source code management and Workload Identity Federation. The documentation is also not mature, making it hard to use. Improvement is needed in the documentation and the overall integration process. 

Additionally, I am not sure if Tekton can be used efficiently in multi-cloud scenarios such as Anthos.

I have been working with Tekton for the last 12 months.

The stability of Tekton heavily depends on the developer's knowledge of Kubernetes deployments and managing Tekton parts. For instance, handling the logs, maintaining the load, and managing resource allocation are essential skills required for ensuring stability.

Scalability isn't perfect yet; Tekton is not very mature in the market with only a few companies using it. The ability of Tekton to adapt to needs is somewhat limited. Overall, I would rate its scalability as a seven. The ability to create different pipelines and reuse jobs seems to be the most robust scalability feature.

I have not communicated with technical support for Tekton. I followed the official documentation, created my own YAML files, and started deploying pipelines and operators.

Neutral

I used different tools for similar use cases based on the requirements of my engineers and the clients. Tekton was introduced to me in 2022, and I used it accordingly. I did not make the decision to switch; I just used what was provided.

The initial setup is simple and involves a few commands. The configuration process, however, might cause some challenges, particularly with integrating third-party tools or handling CI/CD pipelines.

I was the only person in my team handling the deployment and application of Tekton. A single person with knowledge of tools like Ansible, CI/CD tools, DevOps, and cloud services can manage this process.

It is essential to have a straightforward, end-to-end sample for implementation, including steps involving job, trigger, and pipeline settings. Syntax and URL validation validators are important for the effective use of Tekton. They will help check the correctness of the code and improve efficiency.

I'd rate the solution six out of ten.

In my company, we use Tekton for the pipeline, specifically Bitbucket pipelines. We have some cluster setups as well. In order to run some testing of the cluster, we chose to handle pipelines via Tekton.

The best feature of Tekton is that it is a Kubernetes-native tool for CI/CD. The tool offers flexibility and compatibility. If we look under the Kubernetes-native area, Tekton is built to run natively on Kubernetes, so it leverages Kubernetes 'scalability, security, and robustness, making it an ideal cloud-native application. I can relate to the pipeline customization in Tekton. It provides a highly customizable and reusable pipeline component. You can define tasks and pipelines that suit your specific workflow needs and easily reuse them as a different service platform. If you see the interoperability, Tekton is designed to indicate that there are other tools and services in the Kubernetes ecosystem. It makes it easy to incorporate things into the existing workflow.

Earlier, I used to use Jenkins pipeline, but compared to Jenkins, Tekton is better. Tekton is quite a user-friendly tool. The tool offers good dashboard access, and it is extremely user-friendly. If you are a beginner, then accessing the flexibility part can be overwhelming. We think the learning curve of the tool is steep, especially for those who are not already familiar with Kubernetes. There is a need to improve the recommendations and create more tutorials for the tool. The tool is very user-friendly for advanced users and not for beginners. There are some limitations, especially since the tool primarily operates through YAML configurations and command lines with limited graphical user interface options. While there are some third-party tools that look like Tekton's dashboard, there are still basic and compact major systems like Jenkins or GitLab.With more advanced built-in CGI and GUI, as a user, we can make it easier to monitor and manage Python faster. We can also improve the data handling and debugging. The debugging of failed pipelines in Tekton can be challenging. The error messages are not very descriptive, and the tool has limited support for step-by-step debugging. So, the improvement in error handling and data handling for debugging needs to be improved so that it could significantly improve the developer experience.

I have been using Tekton for three years. In our company, we have been using the tool for more than eight months. I am just a user of the tool.

In our company, there are around more than 5,000 employees. There are actually many things under the cloud and platform delivery and infrastructure. We don't know the exact number of employees who are using the tool. I believe over 100 people in my company use the tool.

In my entire career, I never went to the support team for help. If I had any doubts or any kind of features, I was able to Google it or use ChatGPT.

The solution is deployed on the cloud.

Beginners should go through the product documentation. There are many tutorials available on the product that can help a person to configure the pipeline and task functions. Once you get a proper idea of the architecture of Tekton and how it works, only after knowing how to use the tool will a person get to apply the practical knowledge in the Tekton tools. I suggest that businesses get an idea about Python and how it works, as they need to understand the architecture of Tekton.

I rate the tool an eight out of ten.

We use Tekton for CI/CD automation, continuous integration, continuous deployment, and general-purpose automation.

The platform's most valuable features are the cloud-native approach and atomicity. Unlike other monolithic solutions, it is early in adopting a cloud-native platform for CI/CD, which enhances scalability. Additionally, its ability to operate at a granular level allows us to create small automation jobs and combine them into larger tasks, making it very useful.

One project involved automating our deployment processes across multiple environments. By leveraging the solution, we reduced deployment times significantly and increased reliability, allowing for more frequent releases and improved overall productivity.

The product's scalability can be challenging when multiple users access it simultaneously. We have seen some resource crunches, typical for any product supporting a large user base. 

One of the main challenges has been managing complex pipeline dependencies. As the scale of our projects, ensuring that all dependencies are correctly defined and executed in the right order can become cumbersome.

Integration is an area where it lags compared to other CI/CD tools like Jenkins, which has a rich plugin ecosystem. It lacks sufficient vendor support for plugins, requiring users to write their integration scripts, which is less convenient.

Enhancements in documentation and user onboarding would be beneficial. Clearer guides and tutorials could help reduce new users' learning curves and facilitate smoother integration with existing workflows.

The support team is knowledgeable and responsive when resolving issues, though improvements in onboarding and documentation could further enhance the overall experience.

Neutral

The initial setup was somewhat complex, requiring a thorough understanding of Tekton's structure. Once configured, it provided a flexible and scalable solution for our CI/CD needs.

We implemented the product with the help of our in-house team. 

We evaluated other CI/CD tools before choosing Tekton. Tekton's flexibility and cloud-native approach were key factors in switching.

The platform's custom tasks feature allows organizations to create standardized team tasks. It enables enterprises to build a flexible framework atop Tekton, making it easier to define workflows with standard inputs and outputs.

It does not differentiate between continuous integration and deployment, offering a unified framework. It provides tooling to run code that builds or deploys applications, allowing for flexible task configurations and parallel processing.

We manage version control through Git repositories, where we store our Tekton pipeline definitions. It allows us to track changes and revert to previous versions, maintaining a robust versioning system for our CI/CD processes.

It has the potential to be a long-term solution due to its scalability and flexibility. However, continuous improvements in user experience and community support will be key factors in its sustained adoption within our organization.

Security is managed through role-based access controls (RBAC) and secret management features. We ensure that sensitive information, such as API keys, is stored securely and that only authorized users can access critical pipeline functions.

Overall, I rate it a six out of ten.