Service and Support
Customer service and support of Istio are mixed. Many users handle issues independently using community knowledge. Some find technical support lacking, yet those who work closely with Istio staff praise their expertise. Others appreciate well-documented resources available online. Community responses are considered timely, though some note that a paid support option might be beneficial. Many rely on existing documentation rather than contacting direct support, indicating varied satisfaction levels.
Deployment
Many users report that Istio's initial setup varies in complexity. Some find it straightforward, especially with command-line experience and proper documentation. Other users highlight challenges due to Istio's configuration flexibility and multi-cluster options. Training and a learning curve are emphasized for larger deployments. While Helm and Istio operator streamline the process, prior knowledge and GitOps can aid in managing configurations efficiently. Istio's open-source nature and extensive documentation generally support ease of deployment.
Scalability
Istio demonstrates strong scalability, efficiently managing clusters and integrating with Kubernetes. Users appreciate its load balancing and auto-scaling capabilities. Some challenges exist, including occasional performance issues and design bottlenecks, but improvements are ongoing. Managed services, like those from Google, enhance scalability. Organisations observe that Istio scales decently, though awareness of control and data plane scalabilities is necessary. With features like AWS EKS cluster autoscaler, Istio effectively meets scalability needs for significant user volumes, earning high ratings.
Stability
Istio exhibits stability, handling moderate traffic effectively. Users generally find it reliable, though configuration challenges are noted. Deployment and resource management impact its steadiness. While bugs occur, users address them, especially in larger implementations, often rating it between seven to nine out of ten. Initial learning curves may present issues, but once set up correctly, it functions consistently. Users appreciate its robustness, especially in production, trusting it for critical workloads.
