This post is about AWS vs GCP. We’ll dive in and talk about each individually before comparing them.
What comes to mind when Amazon and Google are mentioned? Well, these two giants have a lot to offer, let’s get into each individually.
Amazon Web Service
This is a service provider that provides several products to help you build, test and deploy applications.
One can use it to analyze data, create content for mobile users, store it securely online or manage email distribution lists.
APIs are the building blocks of Amazon Web Services. They are tools that others can use to integrate their services with Amazon.
Amazon is a community of developers, companies, and startups that provides the tools, APIs, and infrastructure for you to create, test and deploy applications.
Every time you use an app or internet service, there’s a good chance it’s using some part of Amazon Web Services – even if they don’t know it.
Many companies use AWS like; Netflix, Reddit, Airbnb, Expedia, and Pinterest to name just a few of the thousands of companies.
Amazon Comprehend is an API that detects relationships in text and phrases to find the most common patterns.
It can also help you classify different topics within text.AWS Lambda is a function as a service.
It lets you run code without provisioning or managing servers. You can set it to automatically trigger from other AWS services or call it directly from any web or mobile app.
To use this API, you need to have an account with Amazon Web Services.
If you’re not a member, sign up for a free account and you’ll be able to use the API for free.
1. Mobile friendly access
AWS allows ease of access by providing libraries for all major programming languages.
The API is also available as a REST API that will work with any HTTP client.
2. Detailed documentation
Amazon provides a variety of different ways to access its APIs. They have a full set of documentation for all three products which includes example code, input and output data formats, code samples, and more.
3. Customer service and support
If you have any problems with AWS or have questions about the API, there’s an email address for their support team.
They can offer assistance with setting up or troubleshooting your account. They are always ready to help resolve any issues quickly.
There are also several online forums where developers can post questions and get advice from other users. Solution to problem
Amazon Comprehend analyzes text, finding patterns and simple structures within it, so you don’t have to.
It helps you detect relationships in text and phrases for a variety of use cases, from marketing to healthcare.
The API provides many functions including language detection, entity extraction, and sentiment analysis.
This API can scale to meet the needs of your application because you only pay for what you use. You can work without hassle.
It scales automatically so there are no surprises on your monthly bill. Work without the hassle of managing server instances.
All API calls are protected through authentication and endpoints using HTTPS/SSL encryption to ensure the privacy of your data.
It has all the features you need to build scalable cloud-based applications, so check out Amazon Web Services today!
All requests need to be signed.
Google Cloud Platform
It was launched in April 2011, is a cloud-based platform for hosting online applications and storing data.
The service’s suite of cloud computing tools is built around Google applications such as Google App Engine, Google Cloud Storage, BigQuery, Spanner, and other services.
GCP has helped to enable projects such as OpenStack, Docker, and Apache Beam.
Developers have been able to deploy some of these applications using Google Compute Engine and Google Container Engine.
Deployment is easy, developers can quickly use Google Cloud Launcher which has pre-configured applications that run on GCP.
Developers have also been able to use Google Kubernetes Engine for containerized deployment.
The service also provides the capability of real-time analytics with BigQuery, an enterprise data warehouse for large-scale data analysis.
1. Broad network access
One can access resources and information from anywhere with an Internet connection. This means you have flexibility.
2. Flexible deployment models
Services can be deployed on-premise, in a cloud environment, or across a hybrid of the two.
It is possible to use managed services for specific applications or run them in a customized environment.
This also provides a scalable solution as the number of resources required can be increased rapidly without having to add hardware.
3. High performance and low latency
Networking services within GCP can deliver high throughput and low latency while maintaining strong security.
These services enable developers to build fast applications that can scale rapidly.
A single, multi-tenant system is used for all customers enabling linear scalability for each customer.
This means that customers are not affected by other customers using the system.
5. Fault-tolerant architecture
The system is designed so that services can continue operating when individual instances have failed, are unreachable, or are too busy to serve requests.
6. Google App Engine
A web framework and cloud computing platform for building and maintaining web applications in Google-managed data centers.
It allows developers to build applications and websites on the same systems that power Google applications.
Structure: Applications can be written using the Python, Java, or Go programming languages/frameworks.
They are placed into a container which is then provided with a stable environment that will always be there for them.
Deployment: Takes seconds rather than minutes or hours, so changes can be pushed out quickly.
AWS vs GCP:
These two platforms are the best service providers globally. Also, they have different service catalogs. In this post, I will focus on Infrastructure as a Service(IaaS).
We’ll focus on:
a) Networking Interfaces
b) Pricing Model
c) Pivotal Cloud Foundry support
d) Cluster Management
e) Overall Comparison based on the above 4 categories.
1. Network Interface – AWS vs GCP
AWS provides two types of network interfaces to connect EC2 instances:
Direct Connect: The Direct Connect feature gives you a dedicated network connection between your local data center and Amazon’s (AWS).
It provides very low latency, high data transfer speeds, and better security than VPN connections.
VPN: The AWS VPN connection enables you to build a secure connection between your Amazon VPC and your existing data center, office network, or another Amazon VPC.
Google Cloud Platform provides two networking interfaces to connect GCP instances:
Cloud VPN: The Cloud VPN is the easiest way to create secure connections between your Google Compute Engine virtual machine (VM) instances and your existing data center, office network, or another GCP VPC.
Cloud Interconnect: The Cloud Interconnect lets you create a private connection between Google’s network and an on-premises location of your choice.
2. Pricing Model – AWS vs GCP
Like other cloud providers, Amazon and Google charge per hour of instance usage.
They also provide Reserved Instances(RIs) which one can purchase either at lower prices or long-term commitment (1 year to 7 years).
Both have different offers on plans. However, when it comes to one with the least spent GCP is affordable for all.
3. Pivotal Cloud Foundry Support
Google Cloud Platform is a Cloud Foundry Certified Provider. Google Compute Engine provides automatic scaling of the underlying virtual machines on which Cloud Foundry runs so that developers need not worry about system administration or capacity planning.
As already discussed in the networking interfaces, Google Cloud Platform is slightly cheaper than AWS.
So having a Pivotal Cloud Foundry support at this pricing model could increase the chances of GCP being selected over AWS for cloud foundry-based applications.
4. Cluster Management – AWS vs GCP
Cluster Management: AWS provides an auto-scaling feature with almost all of its EC2 instances.
There are some built-in policies to handle the scale-up and scale-down operations.
Google Cloud Platform also provides two types of cluster management:
Horizontal scaling: The most basic way to scale an application is to have more virtual machines.
Vertical scaling: Scaling vertically means adding more resources (RAM and CPU) and making your existing instances bigger.
Cluster Discovery: AWS Autoscaling can communicate with some AWS services to help decide when and how to scale.
Auto Healing: Auto healing is the ability of an instance to recover from a fault by restarting the failed instance.
It also helps to recover from data center outages and network problems such as an Availability Zone (AZ) failure.
AWS provides Auto Scaling for this purpose which works with most of its EC2 instances. Google Cloud Platform does not provide any feature for this.
AWS Elastic Beanstalk is a service for rapidly deploying and scaling web applications in the cloud.
It makes it easy to deploy your code by taking care of all the details as follows:
(a) Setting up an EC2 instance
(b) Installing and configuring your application on the instance
(c) Configuring a load balance or distributing traffic across multiple application instances.
Google Cloud Platform provides Kubernetes which is an open-source system for automating deployment, scaling, and management of containerized applications.
It provides all the functionalities similar to Elastic Beanstalk.
Health Check: AWS Elastic Beanstalk provides an application health check which checks by the load balancers to determine if a web application instance is healthy or not.
If an instance fails the health check, it will be marked unhealthy and traffic will start routing to other instances in the fleet.
Google Cloud Platform does not provide any health checks.
Scheduled Jobs: AWS Elastic Beanstalk provides the option of scheduling one or more jobs at specified times, dates, and intervals.
For example, you can configure your application to scale up during business hours and scale down during weekends or holidays.
Google Cloud Platform does not provide this feature.
Google’s immutable infrastructure is the ability to provide a secure and reliable production environment.
It automatically creates snapshots of application components and reliably deploys them, such as in the case of load balancing configuration files.
Also, provides fine-grained access control which includes user-based access management (IAM).
Has pre-built rules for Amazon EC2 instances which can be very useful in restricting access to certain resources.
AWS Security Groups provide a mechanism for controlling network access to Amazon EC2 instances within a VPC.
It allows you to specify groups of IP addresses that can access your instance and in what ways they can do it.
6. AWS vs GCP: Support
These tools are designed to make the lives of developers easier. They provide a development environment that is very similar to what they will find in production.
AWS offers many services for developing applications on the cloud, including Amazon Elastic Beanstalk, AWS Cloud9 IDE, and AWS CodeStar.
GCP on the other hand features Cloud Shell which is a browser-based development environment that can run on macOS, Linux, and Windows.
The support teams of both companies are very helpful and knowledgeable. They provide a variety of learning resources to help you learn how to use their platforms.
7. AWS vs GCP: Pricing
Both platforms offer pay-as-you-go pricing models, but the way they charge varies slightly based on what you’re using.
For example, Google charges for machine types while AWS charges for EC2 instances that are in use.
Similarly, AWS offers reserved plans where you can lock in a specific hourly rate over one or three years.
Google Cloud Platform also offers discounts for using committed use hours, but they only apply to machine types and not instance hours.
AWS vs GCP: Conclusion
Both platforms provide many features that developers need to build, manage and optimize their applications on the cloud.
But if you’re just getting started with developing massive-scale applications, Google Cloud Platform is a better choice than Amazon EC2.
It’s easy to get up and running quickly. It has a steeper learning curve but it’s worth spending extra time to learn how to use it.
AWS Elastic Beanstalk, on the other hand, is a more mature service that’s been around longer and has many features that make managing apps in production easier.
It also has some features you won’t find on GCP like scheduled jobs for optimizing costs and health checks.
But if budget is your primary consideration and you’re not as concerned with features, GCP is a great choice due to its lower pricing.
Google Cloud Platform wins this AWS vs GCP comparison for now. But both services are competitive and constantly updating their platform.
As a developer, it’s worth spending the extra time to evaluate each of them based on your requirements and see which one offers the best value for your needs.
It is clear from the above that GCP has a few advantages over AWS services in terms of hosting web application workloads.
However, AWS provides more services in terms of management and automation.
GCP dominates when it comes to PaaS hosting options which are not available on AWS.
When it comes to IaaS, both GCP and AWS are very strong with many capabilities in terms of networking, security, and computing.
Google has clear advantages over AWS for customers who are already using its services such as Google Storage which can be directly connected to App Engine without any additional costs.