Tekton Reviews

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

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

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

I have been using it for the last six months.

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

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

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

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

It is entirely open source and free of charge.

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

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

I use Tekton generally for CI purposes and automation APIs.

We have created a Helm template for Tekton, and we're currently working on scripts. This allows us to create pipelines on the fly, which has significantly streamlined our workflow.

I have full control over it, actually, in my team. Another thing is that Tekton is based on Kubernetes. In Kubernetes, we have the concept of cron jobs which run on a time-to-time basis. In Tekton, we have the concept called task or task runs. We can expose an API and use the trigger and trigger-binding concept, allowing us to trigger tasks whenever needed. This mechanism is very nice.

RBAC is really needed for Tekton. Also, if you have too many PVCs and don't clean them up, it may stop working due to the limited number of PVCs you can create in a cluster.

I have been using it for the past two years.

Tekton is a stable product. One issue we might run into is when there are too many PVCs that haven't been cleaned up. We have mitigated this by creating a CronJob that runs every midnight to clear those tasks.

Tekton is scalable if well-planned. However, it is not a plug-and-play solution for now. You need to write the tasks according to your business case, which might differ from team to team or service to service.

While setting up, I was initially active on their Slack channel where I was able to get help. They were responsive.

Neutral

We were using Jenkins before Tekton.

The initial setup was daunting and took me four months to set it up and get the flow. There is a steep learning curve, especially with concepts like event listeners, event triggers, and trigger binding.

Tekton was initially very daunting, and it took me a long time to get the flow. However, once you get it, it’s awesome.

I'd rate the solution six out of ten.

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.

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.

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 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. 

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.

Generally, we are using Tekton for deployments instead of Jenkins. We create pipelines in Tekton for a number of services, each with different logs and requirements, especially in our DevOps practices. I have been using this Tekton pipeline for nearly six months.

The main benefits we have seen from using Tekton include saving time compared to Jenkins. The user interface is easier to use, and there are no plugins required for installation, unlike Jenkins. Time savings and ease of use are significant advantages.

Tekton has a user interface that facilitates time savings, making it more user-friendly than Jenkins. It is easier to handle and eliminates the need for plugin installations.

The user interface of Tekton could be improved. Sometimes, it takes more time during production deployments than expected.

I have been using the solution for nearly six months.

Tekton is stable, easy to use, and currently provides good stability.

Tekton is scalable, and most of our team members are using the Tekton pipeline.

As of now, I haven't asked for technical support. I would approach technical support if I encounter any problems.

Positive

Before Tekton, we used Jenkins. Tekton is better than Jenkins in terms of user interface and ease of integration without the need for plugins.

The initial setup took about one week, and there were some doubts on how to operate and execute deployments. But after learning about the tools, the setup was smooth, and everything was configured properly.

Four teams were involved in the deployment process: the ECS team, tenant ops team, DevOps team, and development team.

There are efficiency gains due to time savings in pipeline setup compared to Jenkins. This is a major point of efficiency for Tekton.

I would recommend Tekton to other users who are considering its implementation. It's better compared to Jenkins.

I'd rate the solution eight out of ten.