Google Kubernetes Engine Reviews

Users express satisfaction regarding the cost-effectiveness and operational productivity improvements with Google Kubernetes Engine. Despite concerns over expenses related to certain services and comparisons with AWS, most feedback highlights substantial time savings and efficient management. ROI perspectives vary, but savings, efficiency, and adaptability are commonly appreciated. Startups note potential high investment value, though careful consideration of associated costs is advised. The overall Kubernetes ecosystem is praised for promoting business capability.

Enterprise buyers of Google Kubernetes Engine (GKE) experience flexible pricing based on machine type, CPU, and RAM usage. While no licensing fees apply, GKE costs can vary from $90 for small instances to around $3000 monthly for larger deployments. Redundancy and regional cluster costs are higher. GKE is generally more affordable than AWS, but its pricing is rated between six and nine out of ten, with GKE Autopilot as a potential cost-effective option.

• "The tool's licensing costs are yearly."
• "Initially, Google Kubernetes Engine was a little bit cheaper, but now its prices have been increased compared to the pricing model and the features that are made available by its competitors."
• "I rate the product's price a six on a scale of one to ten, where one is low price and ten is high price. The product is competitively priced."

Users primarily employ Google Kubernetes Engine for hosting and deploying applications, with a focus on microservices. It facilitates Continuous Integration/Continuous Deployment pipelines and enables orchestration of Docker containers. Many transition to a cloud-native architecture, leveraging GKE for scalability, resilience, and efficient management of production clusters. Additionally, it supports machine learning models, big data workloads, and assists developers in testing, training, and migrating applications from virtual machines to containers.

Many find Google Kubernetes Engine's customer service and support satisfactory, with access to 24/7 assistance and AI features for configurations. However, response times vary, with some reporting delays. While experienced users rarely need extra help, those seeking external help note room for improvement compared to competitors like Amazon. Forums are often used for self-resolution, and reliance on email or third-party support is common for some users.

Google Kubernetes Engine's setup varies in complexity. Some describe it as straightforward and fast, deploying within minutes using clicks or automation like Terraform. Others note potential challenges with complex projects, private deployments, and network configurations. Ratings indicate ease from slightly complex to very manageable, influenced by understanding Kubernetes and automation tools. Effective deployment may require enhancing skills and resources, yet good documentation and scripts aid in simplifying the process.

Google Kubernetes Engine exhibits exceptional scalability, offering seamless horizontal and vertical scaling capabilities. Users appreciate auto-scaling features, beneficial for managing workloads and cloud migrations. Some find cluster-based scaling requires additional documentation. Its adaptability for machine learning and integration with major cloud platforms enhances its appeal for developers and organizations. Numerous companies rate its scalability highly, highlighting its ability to accommodate growing teams and complex applications efficiently.

Google Kubernetes Engine is generally stable, rated around eight to ten out of ten. Users highlight its reliability, scalability, and frequent updates. While some encountered issues in complex or rapid deployments, these are exceptions. Most users find it excellent for maintaining consistent cloud-native environments, enabling easy transitions between clouds. Some face occasional support delays or regional stability variations, but overall satisfaction with its dependability remains high among users.