Overseas cloud service providers Google Cloud and Amazon Cloud

[Introduction]: 1. Network protocol stack The network protocol stack is a highlight of Google Cloud, which uses Google's global ultra-low latency internal network. Google Cloud uses software-defined networking (SDN), code-named Andromeda globally, to provide hard-to- aws vs azure vs google cloud pricing...

1. Network protocol stack

The networking stack is a highlight of Google Cloud, which uses Google's global ultra-low latency internal network. Google Cloud uses software-defined networking (SDN), globally code-named Andromeda, that delivers incredible performance, especially for low-latency microservices and big data processing aws vs azure vs google cloud pricing.

Virtual Private Clouds (VPCs) in Google Cloud are global, you can define them in different regions if you choose, and the entire network is software-defined with a lot of flexibility. Your load balancer works at the edge location, providing global load balancing and automatic scaling.

With Google Cloud, you can build a global infrastructure with Geo distributed data very easily. This is very difficult for other cloud providers.

2. Developer experience aws vs azure vs google cloud pricing

Google Cloud's console experience is probably the best of all cloud providers, especially with cloud scripting (cloud shell) where you can get a terminal directly from your browser and securely connect to a virtual machine (VM) from your browser, Without having to set up any SSH keys, it's perfect aws vs azure vs google cloud pricing!

Google Cloud VMs are very fast to start, much faster than AWS, which makes horizontal scaling especially sensitive. Its pricing is fair, and you can customize the amount of CPU and RAM you need, which is very convenient! Google Cloud allows almost all instance types to connect GPUs. This can turn any standard or custom instance into a machine learning (ML) enabled VM aws vs azure vs google cloud pricing .

With Cloud Identity, Google Cloud's identity management works brilliantly. It integrates with G suite and provides single sign-on (SSO), so there is no need to use other cloud providers' very popular solutions like OneLogin.

Finally, most services provide emulators without using any third-party tools or complex integrations.

Which overseas cloud service provider Google Cloud (Google Cloud) or Amazon Cloud (AWS) has more advantages?

3. Pub/Sub (publish/subscribe)

AWS provides many services for messaging such as SQS, SNS, Kinesis, Event Bridge, Kafka, etc. whereas Google Cloud only provides Pub/Sub. To be honest, you don't need anything else, it's a very good and cheap service for a variety of use cases from data streaming to microservices. It's a global service that scales to handle huge amounts of data, and it's very fast.

Pub/Sub is very easy to integrate and use, and it supports many clients and protocols. It also provides two modes for consumers: push and pull. Best of all, it's very cost-effective and completely serverless!

4. Database

Google has a particular focus on data, and they are very good at managing and scaling big data, providing flexible solutions for each use case.

Especially they offer 3 solutions that I don't think other competitors have, and these are big data solutions. Companies, along with other cloud providers, are building data lakes to be more cost-effective by storing large amounts of data in cheap storage like S3. They use traditional frameworks like Spark on Electronic Medical Records (EMR) to process it and optimize it to be able to query it from S3 using formats like Parquet.

Maintaining a data lake is complex, especially when data changes frequently. This can become unmanageable and eventually the cost will rise. Wouldn't it be great if we could store big data in a scalable and cost-effective database? This will be much easier. Google Cloud has some great options. While object storage has always been cheap, these 3 solutions can be used for big data as long as they're not too bulky.

5. Big Table

Big Table is a fully managed NoSQL database. It can be compared to AWS DynamoDB, but they are different. DynamoDB is a NoSQL that scales to handle millions of transactions, but can only store 400Kb per item, and its goal is not to handle big data.

Big Table, on the other hand, is a petabyte-scale database. It provides consistent sub-10ms latency, so it's very fast and reliable, and it's also easy to scale and cost-effective.

Which overseas cloud service provider Google Cloud (Google Cloud) or Amazon Cloud (AWS) has more advantages?

6. Big Query

BigQuery is Google Cloud's gold product, and since it's such a big product, it's hard to explain what it is. It's defined as: A serverless, highly scalable, and cost-effective cloud data warehouse designed to help you make fast, informed decisions so you can easily transform your business.

The closest AWS products are Redshift and Redshift Spectrum. BigQuery is serverless and scalable to query large amounts of data, it has built-in ML and BI models for a variety of use cases. What I like about BigQuery is that you can do anything with it, you can store logs or billing information. It has higher latency than BigTable, but is also a bit cheaper.

As a data warehouse for BI, Redshift might be better, but for artificial intelligence (AI) and machine learning (ML), BigQuery is better.

7. Spanner

Cloud Spanner is a fully managed, scalable relational database service for regional and global application data. I don't think there is a similar database in other cloud providers. It's massive, but also totally relevant. It allows you to use regular SQL at scale with strong consistent transactions.

Do you remember the tradeoff between SQL and NoSQL? Now they're gone, you can use SQL and scale globally, but it's not cheap.

8. ML/AI

Google has the best machine learning platform. It provides tools for all types of users and use cases. The number of services is huge, from low-level virtual machines for deep learning to high-level APIs.

With SageMaker, AWS is slowly catching up and has gotten very close to Google Cloud, but Google Cloud still offers a newer and more accurate toolset. It provides virtual machines specifically for deep learning, better integration with Kubernetes and machine learning training, etc.

9. Kubernetes

There is not much to say about Kubernetes, Google Cloud has advantages over other cloud providers. Google Cloud is cheaper, newer, faster, and easier to use than other cloud providers. GKE is probably the best cloud service in the world due to its flexibility and price advantage. It allows easy migration from on-premises to cloud. It's secure and easy to set up, offers great autoscaling, and is easy to monitor.

The best part is that Google Cloud empowers Kubernetes and provides a friendly ecosystem to run almost any workload, from microservices or data flow to big data pipelines. The Kubernetes ecosystem is huge, and all of these tools have been validated and tested in Google Cloud.

AWS is more focused on serverless and Google Cloud is focused on Kubernetes, both technologies are great.

10. Cost

In general, Google Cloud is cheaper than other cloud providers because it always depends on what service you use and how you use it. If you use Kubernetes, Google Cloud is the clear winner in terms of cost efficiency.

It's also the clear winner when it comes to compute and storage costs. Google Cloud offers a better way to subsidize long-term usage, and snap-up virtual machines are very cheap.

The price of a GKE cluster running on a Snapshot VM is hard to match.

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