Service and Support
Customers describe Tekton's service and support as knowledgeable and effective, often resolving issues through documentation and the GitHub community. While response times can vary, especially in open-source forums, Red Hat's involvement ensures reliable assistance. Some organizations rely on internal or community support without directly contacting Tekton's team, while others praise the helpful Slack community. Improvements in onboarding and documentation could benefit users, especially during critical deployments. Customers appreciate the proactive support from IBM and Google.
Deployment
Experiences with Tekton's initial setup varied. Some found it straightforward, leveraging command-line tools and benefiting from clear documentation. Challenges included complexity in setting up pipelines, integrating third-party tools, and handling authentication parameters. Users noted simplicity in installing the operator on Kubernetes and OpenShift, but highlighted issues with scalability and specific configuration adjustments. Technical knowledge of Kubernetes and CI/CD processes was helpful, and setting up complex workflows required more time and understanding.
Scalability
Tekton is considered highly scalable, leveraging Kubernetes for efficient management of tasks. It is used by many teams across various organizations, handling numerous jobs simultaneously. Users appreciate its ability to scale infrastructure quickly and manage resources across multiple regions. While generally effective, some see room for improvement, particularly in resource quota expansion. Tekton's cloud-native design allows it to adapt to varied needs and environments, although it requires careful planning and customization.
Stability
Tekton is stable and reliable. Users rate its stability between seven to ten out of ten. Occasional minor issues arise, often related to configurations or Kubernetes dependencies, but these are typically resolved. Users appreciate the scalability, especially in Kubernetes environments. Some face compatibility or API version challenges, but documentation aids resolution. Tekton performs well with autoscaling, and experts find it stable when implemented correctly, though some experience downtime or performance issues linked to infrastructure.