Service and Support
Istio's support features mixed experiences. Users often rely on self-help and community forums due to inconsistent technical assistance. Open-source users typically find online resources and documentation sufficient but recognize the need for more robust support, especially for new issues. Engineers within the community are highly regarded for their expertise. Some users enjoy responsive community support, with responses usually within a day. There is an acknowledgment that a paid support option could add value.
Deployment
Many find Istio's initial setup varies in complexity based on team expertise and infrastructure. Generally, those familiar with command-line tools and Kubernetes find it straightforward, especially with istioctl and Helm charts. While documentation aids the process, a learning curve exists, particularly for complex configurations. Setup can be simple for basic needs but grows intricate with larger deployments. Istio's flexibility necessitates understanding of the configurations, though its open-source nature and community support offer valuable resources.
Scalability
Istio demonstrates effective scalability, especially in Kubernetes environments. Users note efficient load balancing and automated service registration, minimizing manual efforts. DevOps teams appreciate its integration capabilities, managing significant user loads. Some adjustments, like moving control planes to managed services, enhance scalability. Design and setup play crucial roles in overcoming challenges, with performance issues addressed through scaling mechanisms like load balancers and auto-scaling. Overall, Istio supports large-scale environments, though continuous improvement is acknowledged.
Stability
Istio is generally stable, with ratings ranging from seven to ten out of ten for stability. It occasionally experiences bugs, especially under large-scale implementations, but these are usually resolved quickly. Misconfiguration can lead to issues, but proper setup makes it quite robust. Stability largely depends on deployment methods, resource allocation, and configuration. Users with moderate traffic report satisfactory performance without major problems. Training and experience can mitigate early-stage configuration troubles.