Software Alternatives, Accelerators & Startups

Amazon API Gateway VS Google Kubernetes Engine

Compare Amazon API Gateway VS Google Kubernetes Engine and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Amazon API Gateway logo Amazon API Gateway

Create, publish, maintain, monitor, and secure APIs at any scale

Google Kubernetes Engine logo Google Kubernetes Engine

Google Kubernetes Engine is a powerful cluster manager and orchestration system for running your Docker containers. Set up a cluster in minutes.
  • Amazon API Gateway Landing page
    Landing page //
    2023-03-12
  • Google Kubernetes Engine Landing page
    Landing page //
    2023-02-05

Amazon API Gateway features and specs

  • Scalability
    API Gateway automatically scales to handle the number of requests your API receives, ensuring high availability and reliability.
  • Ease of Integration
    Seamlessly integrates with other AWS services like Lambda, DynamoDB, and IAM, enabling a cohesive environment for developing serverless applications.
  • Built-in Security
    Provides features such as IAM roles, API keys, and AWS WAF integration for safeguarding your APIs from potential threats.
  • Monitoring and Logging
    Supports CloudWatch integration for monitoring API requests and responses, helping you maintain observability and troubleshoot issues effectively.
  • Cost-Effective
    You only pay for the requests made to your APIs and the amount of data transferred out, making it a cost-effective solution for many use cases.
  • Caching
    Built-in caching at the API Gateway level can improve performance and reduce latency for frequently accessed data.

Possible disadvantages of Amazon API Gateway

  • Complexity in Configuration
    Setting up and managing API Gateway can be complex, especially for users who are not familiar with AWS services and cloud infrastructure.
  • Cold Start Latency
    When integrated with AWS Lambda, cold starts can introduce latency which can affect the performance of your API.
  • Cost for High Throughput
    While cost-effective for low to moderate usage, the costs can escalate with high throughput and large data transfers.
  • Debugging Issues
    Diagnosis can be complicated due to the multi-tenant nature of the service and the need to dive into multiple AWS logs and services.
  • Limited Customization
    There might be constraints regarding customizations and fine-tuning your APIs compared to self-hosting solutions.
  • Vendor Lock-in
    Dependence on AWS infrastructure can lead to vendor lock-in, making it challenging to migrate to other cloud providers or solutions.

Google Kubernetes Engine features and specs

  • Managed Service
    GKE is a fully managed service, which means Google takes care of tasks like provisioning, maintenance, and updates of the cluster, reducing the operational burden on users.
  • Scalability
    GKE offers robust scalability options, allowing you to easily scale your applications up or down based on demand. This is facilitated through auto-scaling features for both nodes and pods.
  • Integration with Google Cloud Services
    GKE integrates seamlessly with other Google Cloud services such as Cloud Storage, BigQuery, and more, providing a streamlined experience for leveraging multiple cloud tools.
  • Security
    GKE offers advanced security features like private clusters, and integrates with Google Cloud IAM, which allows for fine-grained access control, helping to secure your Kubernetes environment.
  • Ease of Use
    GKE's comprehensive dashboard, command-line interface, and supporting documentation make it easy to deploy, manage, and monitor Kubernetes clusters.
  • Global Reach
    With GKE, you can deploy clusters across multiple regions and zones, giving you the ability to build highly available, geographically dispersed applications.

Possible disadvantages of Google Kubernetes Engine

  • Cost
    While GKE offers extensive features, it can be more expensive compared to other Kubernetes solutions, especially when additional services and high-availability features are utilized.
  • Limited Customization
    As a managed service, GKE has some limitations in terms of customization and control over the underlying infrastructure compared to self-managed Kubernetes environments.
  • Complexity
    Despite its ease of use features, GKE still requires a certain level of expertise to efficiently manage Kubernetes clusters, which can be a steep learning curve for beginners.
  • Dependence on Google Cloud
    Using GKE ties you to the Google Cloud ecosystem, which may limit flexibility if you decide to migrate to a different cloud provider or adopt a multi-cloud strategy.
  • Resource Constraints
    Like all cloud services, GKE nodes can be subject to resource limits and quotas imposed by Google Cloud, which can impact performance if not properly managed.
  • SLA and Downtime
    While Google Cloud offers Service Level Agreements (SLAs), there is still a risk of downtime which could affect your applications. Additionally, relying on a third-party provider means issues may take time to resolve.

Amazon API Gateway videos

Building APIs with Amazon API Gateway

More videos:

  • Review - Create API using AWS API Gateway service - Amazon API Gateway p1

Google Kubernetes Engine videos

Getting Started with Containers and Google Kubernetes Engine (Cloud Next '18)

More videos:

  • Review - Optimize cost to performance on Google Kubernetes Engine
  • Tutorial - Google Kubernetes Engine (GKE) | Coupon: UDEMYSEP20 - Kubernetes Made Easy | Kubernetes Tutorial

Category Popularity

0-100% (relative to Amazon API Gateway and Google Kubernetes Engine)
API Tools
100 100%
0% 0
Developer Tools
0 0%
100% 100
APIs
100 100%
0% 0
Cloud Computing
35 35%
65% 65

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Amazon API Gateway and Google Kubernetes Engine

Amazon API Gateway Reviews

We have no reviews of Amazon API Gateway yet.
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Google Kubernetes Engine Reviews

Top 12 Kubernetes Alternatives to Choose From in 2023
Google Kubernetes Engine (GKE) is a prominent choice for a Kubernetes alternative. It is provided and managed by Google Cloud, which offers fully managed Kubernetes services.
Source: humalect.com
11 Best Rancher Alternatives Multi Cluster Orchestration Platform
Google Kubernetes Engine is a CaaS (container as a service) platform that lets you easily create, resize, manage, update, upgrade, and debug container clusters. Google Kubernetes Engine, aka GKE, was the first managed Kubernetes service, and therefore, it is highly regarded in the industry.
Top 10 Best Container Software in 2022
If you need a speedy creation of developer environments, working on micro services-based architecture and if you want to deploy production grade clusters then Docker and Google Kubernetes Engine would be the most suitable tools. They are very well suited for DevOps team.
7 Best Containerization Software Solutions of 2022
If you’re looking for a managed solution to help you deploy and scale containerized apps on your virtual machines quickly, Google Kubernetes Engine is a great choice.
Source: techgumb.com

Social recommendations and mentions

Based on our record, Amazon API Gateway should be more popular than Google Kubernetes Engine. It has been mentiond 107 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Amazon API Gateway mentions (107)

  • 10 Lightweight API Gateways for Your Next Project
    AWS API Gateway is Amazon’s managed gateway service, designed to work seamlessly within the AWS ecosystem. It supports both REST and WebSocket APIs, with HTTP APIs being the lightweight, lower-cost option for simple proxying and routing use cases. - Source: dev.to / 4 days ago
  • 4 Cognito User Pools features you might not know about
    This opens up a world of customization options for controlling app access. For example, we can embed custom data in the ID token for the front-end client to use, enabling guards to restrict content. Alternatively, we can add custom scopes to the access token and implement fine-grained access control in an API Gateway API. All it takes is some Lambda function code, and Cognito triggers it at the right time. - Source: dev.to / 23 days ago
  • Verifying Cognito access tokens - Comparing three JWT packages for Lambda authorizers
    When the built-in Amazon API Gateway authorization methods don’t fully meet our needs, we can set up Lambda authorizers to manage the access control process. Even when using Cognito user pools and Cognito access tokens, there may still be a need for custom authorization logic. - Source: dev.to / about 1 month ago
  • Implementing advanced authorization with AWS Lambda for endpoint-specific access
    The API Gateway includes an endpoint structured like this:. - Source: dev.to / about 1 month ago
  • Turning APIs into Revenue: Passive Income Strategies for Developers
    Amazon Web Services exemplifies this approach with automatic volume discounts that encourage increased usage while maximizing revenue at each consumption level. - Source: dev.to / about 1 month ago
View more

Google Kubernetes Engine mentions (49)

  • Google Cloud Unveils A4 VMs with NVIDIA Blackwell GPUs for AI
    Integration with Google Kubernetes Engine (GKE), which supports up to 65,000 nodes per cluster, facilitating robust AI infrastructure. - Source: dev.to / about 1 month ago
  • Deploy Gemini-powered LangChain applications on GKE
    In my previous post, we explored how LangChain simplifies the development of AI-powered applications. We saw how its modularity, flexibility, and extensibility make it a powerful tool for working with large language models (LLMs) like Gemini. Now, let's take it a step further and see how we can deploy and scale our LangChain applications using the robust infrastructure of Google Kubernetes Engine (GKE) and the... - Source: dev.to / 3 months ago
  • Securing Applications Using Keycloak's Helm Chart
    Kubernetes cluster: You need a running Kubernetes cluster that supports persistent volumes. You can use a local cluster, like kind or Minikube, or a cloud-based solution, like GKE%20orEKS or EKS. The cluster should expose ports 80 (HTTP) and 443 (HTTPS) for external access. Persistent storage should be configured to retain Keycloak data (e.g., user credentials, sessions) across restarts. - Source: dev.to / 5 months ago
  • Simplify development of AI-powered applications with LangChain
    In a later post, I will take a look at how you can use LangChain to connect to a local Gemma instance, all running in a Google Kubernetes Engine (GKE) cluster. - Source: dev.to / 7 months ago
  • 26 Top Kubernetes Tools
    Google Kubernetes Engine (GKE) is another managed Kubernetes service that lets you spin up new cloud clusters on demand. It's specifically designed to help you run Kubernetes workloads without specialist Kubernetes expertise, and it includes a range of optional features that provide more automation for admin tasks. These include powerful capabilities around governance, compliance, security, and configuration... - Source: dev.to / 11 months ago
View more

What are some alternatives?

When comparing Amazon API Gateway and Google Kubernetes Engine, you can also consider the following products

AWS Lambda - Automatic, event-driven compute service

Kubernetes - Kubernetes is an open source orchestration system for Docker containers

Postman - The Collaboration Platform for API Development

Amazon ECS - Amazon EC2 Container Service is a highly scalable, high-performance​ container management service that supports Docker containers.

Apigee - Intelligent and complete API platform

Docker - Docker is an open platform that enables developers and system administrators to create distributed applications.