Author: Cloudtek

Onuka Kalu is a Google-certified Associate Cloud Engineer (ACE) with vast knowledge of the Google Cloud Platform (GCP). He is a product of the Google Africa Developer Scholarship (GADS). Cloudtek was born out of his passion to give back to the society and to serve as a gateway to the world of cloud technology; His target is to simplify the complexities of cloud computing, and empower curious minds to grasp its potential fully, become world-class cloud computing experts. Hence, the slogan ... Follow the Cloud. It is ideal for everyone who wants to become a Google Associate Cloud Engineer. He holds a bachelor of science degree from the University of Nigeria Nsukka. He has authored many inspirational books, among them is ‘The Threshold of Life’. He is a technopreneur, Success enthusiast, and senior partner at Conquestlane Global Services.He is happily married with children.
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Latest Google Cloud Innovations: Accelerating Digital Transformation in 2023.

Google Cloud Innovations

Table of Contents

Introduction

There are many latest cloud innovations that have been released by Google Cloud in the year 2023. Google Cloud is no doubt a leading provider of cloud computing services. As a major player in the world of cloud technology, Google Cloud is constantly innovating, offering a wide range of innovative cloud services to help businesses succeed in this digital age. New Cloud computing features and services are being released all the time by Google Cloud into the ever-ephemeral world of cloud technologies.

In this blog post, we will take a look at some of the latest Cloud innovations from Google Cloud, and how they can help businesses to succeed. Here are some of the latest cloud innovations in Google Cloud technology

AI and Machine Learning

Google Cloud Next ’23 was held in August 2023, and it was a bazaar of the latest cloud innovations with announcements about new products, features, and partnerships. Artificial intelligence (AI) and machine learning (ML) are two of the most transformative cloud innovations that topped the chart. Google Cloud is at the forefront of AI and ML innovation and offers a wide range of services to help businesses harness the power of these technologies.

Here are some of the highlights of the latest cloud innovations on Google Cloud technologies which can help businesses in a variety of ways;

Duet AI from Google Cloud

The Duet AI is one of the versatile Google Cloud innovations of 2023. It is a new AI-powered assistant that can help you with a variety of tasks, from writing code to answering questions to generating creative content. Duet AI can help you to automate tasks, improve productivity, and make better decisions. It is a notable Cloud innovation in Google Cloud AI stable. Duet AI is a new AI platform that brings together the power of Google Cloud AI services with the familiarity of Google Workspace. Duet AI enables users to interact with AI models in a natural language way and to embed AI capabilities directly into their workflows. Duet AI is now generally available in Google Workspace, it was launched in beta in May 2023 and became generally available in August 2023. Duet AI Use cases include:

  • Code Generating: For instance, if you work in a software development company, you can use Duet AI to generate code for new features or to refactor existing code. Duet AI can also help you to develop new applications more quickly and to improve the quality of its code.
  • Natural language processing: It is ideal for any customer service company. You can use Duet AI to answer customer questions and resolve customer issues. It can also help the company to provide better customer service and reduce the workload on its customer service representatives.
  • Creative writing: A marketing company can leverage Duet AI to generate creative content for its marketing campaigns. Duet AI can help the company to create more engaging campaigns that reach a wider audience.

Google Cloud TPUv5e

The Cloud TPUv5e is one of Google Cloud’s exciting latest cloud innovations launched in Google Cloud AI in 2023. TPUv5e is the latest generation of Google’s Tensor Processing Unit (TPU) custom-designed for machine learning. It offers up to 40% better performance and up to 80% better energy efficiency than the previous generation of TPUs. It is Google’s most cost-efficient, versatile, and scalable purpose-built AI accelerator to date. It is designed to support both large-scale AI training and inferencing, making it ideal for a wide range of AI workloads. The Google Cloud TPUv5e was launched in beta in June 2023 and became generally available in August 2023. Some Use cases of Google Cloud TPUv5e include;

  1. Google Cloud TPUv5e is very versatile in the health sector as it can be used to train and deploy machine learning models for image recognition and medical diagnosis. Thus it can help healthcare companies to improve the accuracy of their diagnoses and provide better care to their patients.
  2. TPUv5e can be used in the financial sector to train and deploy machine learning models for fraud detection and risk assessment. This can help the institution to reduce fraud losses and to protect its customers.
  3. A retail company can use TPUv5e to train and deploy machine learning models for product recommendation and customer segmentation. This can help the company to increase sales and to improve the customer experience.

Vertex AI Vision

Vertex AI Vision is a new service that makes it easy to build and deploy custom computer vision models. Vertex AI Vision is a powerful tool that can help businesses accelerate computer vision development, reduce costs, and improve accuracy. It is one of the latest Google Cloud innovations launched in preview in October 2022 and became generally available in May 2023. Some Use cases include:

  1. E-commerce businesses can use Vertex AI Vision to build and deploy computer vision models for product recognition and self-checkout. This can help them to improve the customer experience and reduce costs.
  2. It can also be used in the manufacturing sector. Vertex AI Vision can be used to build and deploy computer vision models for quality control and defect detection. This can help the company to improve the quality of its products and to reduce costs.

Vertex AI Natural Language 

The Vertex AI Natural Language is a new service that makes it easy to build and deploy custom natural language processing models. It is a managed service that makes it easy to build and deploy custom natural language processing (NLP) models. It provides a variety of features and services, including pre-trained models, custom training, and deployment. Google Cloud Vertex AI Vision was launched in preview in October 2022 and became generally available in May 2023.

Data and Analytics

Google Cloud is also a leader in data and analytics. Google Cloud offers a wide range of services to help businesses to collect, store, process, and analyze their data.

Datastream for BigQuery

Google Cloud Innovations

One of the most recent cloud innovations in Google Cloud data and analytics is the launch of Datastream for BigQuery. Datastream for BigQuery is a new service that makes it easy to replicate data from operational database sources directly into BigQuery. It is a fully managed, serverless change data capture (CDC) service that streams data from operational databases into BigQuery in near real-time without having to manage complex data pipelines. Datastream for BigQuery is a versatile tool that can be used by businesses of all sizes to improve their data pipelines. It was launched in beta in September 2022 and became generally available in May 2023. Some use cases include:

  1. A retail company can use Datastream for BigQuery to replicate data from its point-of-sale systems into BigQuery in near real-time. This can help the company to track inventory levels, identify trends, and make better business decisions.
  2. It is useful in the financial sector where it can be used to replicate data from its core banking system into BigQuery in near real-time. This can help the institution to detect fraud and manage risk more effectively.
  3. Healthcare providers in the health sector can also leverage Datastream for BigQuery to replicate data from its electronic health record system into BigQuery in near real-time. This can help the provider to improve patient care and conduct clinical research more efficiently.

BigQuery Omni

The launch of BigQuery Omni is one of the latest cloud innovations in Google Cloud data and analytics. It is a cross-cloud analytics solution that enables businesses to analyze data where it is stored and to replicate data to BigQuery when needed. It enables businesses to query data across multiple clouds and on-premises data sources. This makes it easy to get a unified view of your data, regardless of where it is stored. It was launched in beta in September 2022 and became generally available in May 2023. Some Use cases of BigQuery Omni include:

  1. BigQuery Omni can be used by retail businesses to analyze data from its on-premises point-of-sale systems and its cloud-based e-commerce platform in a single place. This can help the company to track inventory levels, identify trends, and make better business decisions.
  2. A financial institution can use BigQuery Omni to analyze data from its on-premises core banking system and its cloud-based risk management system in a single place. This can help the institution to detect fraud and manage risk more effectively.
  3. A healthcare provider can use BigQuery Omni to analyze data from its on-premises electronic health record system and its cloud-based imaging system in a single place. This can help the provider to improve patient care and to conduct clinical research more efficiently.

In addition to the Cloud innovations mentioned above, here are some other recent news on the Latest Google Cloud innovations:

  • Google Cloud partners with Salesforce to provide a more seamless BI experience. This partnership will enable Tableau users to seamlessly analyze data from BigQuery and to launch Tableau directly from Google Sheets. The partnership is one of the latest cloud innovations that can benefit businesses by improving the customer experience, increasing sales and marketing productivity, and improving operational efficiency. Businesses can use Google Cloud AI and machine learning to analyze customer data from Salesforce and use that data to provide more relevant recommendations and offers to customers. Google Cloud and Salesforce can also help businesses automate tasks and streamline business processes, which can lead to reduced costs and increased profits.
  • Google Cloud announces a new partnership with VMware to make it easier for customers to migrate their on-premises workloads to the cloud. This partnership will provide customers with a single point of contact for support and a streamlined migration process.

Obviously, the new partnership between Google Cloud and VMware is good news for businesses that are looking to migrate their on-premises workloads to the cloud. The partnership will make it easier, faster, and more cost-effective for businesses to migrate their workloads to Google Cloud. It is one of the latest cloud innovations that will also provide them with access to Google’s high-performance and reliable infrastructure.

  • Google Cloud announces a new service called Cloud Spanner Change Streams. Google Cloud Spanner Change Streams is a powerful new service that can help businesses get more value from their data and make better decisions faster.
  • Google Cloud Spanner Change Streams enables businesses to stream changes to their Cloud Spanner data to other systems in real-time. This can improve data integration, enable real-time insights, and reduce costs.
  • Cloud Data Fusion is a new service that makes it easy to build and manage data pipelines. Google Cloud Data Fusion is a powerful tool that can help businesses accelerate their data integration efforts, reduce costs, improve data quality and reliability, and increase data accessibility. Cloud Data Fusion as one of the best cloud innovations from Google can help you to build and manage data pipelines to get the most out of your data.
Google Cloud Innovations

Conclusion

Google Cloud is constantly innovating, and new features and services are being released all the time. The latest innovations from Google Cloud include AI and ML accelerators, data and analytics services, security and compliance services, and customer success services. These latest Cloud innovations on Google Cloud technology can help your business in a variety of ways, from automating tasks to improving productivity to making better decisions. These latest Google Cloud innovations are designed to help businesses to accelerate their digital transformation and to achieve their business goals.

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GCP App Engine: 2 Powerful App Engine Environments

App Engine

Table of Contents

Introduction

App Engine is a GCP’s Platform-as-a-service (PaaS) that helps developers easily build and deploy web applications in the cloud. The App Engine in the GCP manages the hardware and network infrastructures required to run your codes so that you can focus on innovation. It is especially suited for building scalable web apps and mobile backends. The GCP App Engine is not a one-size-fits-all solution, rather it offers two distinct environments – the Standard Environment and the Flexible Environment. This blog article will explore both App engine environments – exploring their features, use cases, and key differences to help you make informed decisions in building and deploying cloud applications.

APP Engine
GCP App Engine

Understanding the GCP App Engine

App Engine is a fully managed platform that simplifies application development, deployment, and scaling. It allows developers to focus on writing code without worrying about infrastructure management. With built-in services like auto-scaling, load balancing, and security, App Engine provides an environment that fosters rapid development and deployment. App Engine offers two environments the Standard and the Flexible environments.

The Standard Environment

The GCP App Engine Standard Environment is the simplest among the two. The Standard Environment is easily used to deploy applications and autoscale workloads. It runs on usage-based pricing with a free daily quota. The Standard environment is characterized by the following features:

  • Managed Runtime
    It is a managed runtime environment. In the Standard Environment, you use a runtime provided by Google, which means Google takes care of the underlying infrastructure, including server provisioning and scaling. Developers can concentrate solely on writing code.
  • Limited Language Support
    The Standard Environment supports a narrower range of programming languages compared to the Flexible Environment. Currently, it supports specific versions of Java, Python, Go, PHP, and Node.js. This limitation can be a deal-breaker if your project requires a less common language.
  • Auto-Scale Workloads
    The standard environment offers automatic scaling based on traffic. When there’s an increase in user traffic, the Standard Environment automatically allocates additional resources to handle the load. Conversely, it scales down when traffic decreases, saving on costs.
  • Sandboxed Environment
    Applications run in a sandboxed environment, ensuring that they don’t have direct access to the underlying infrastructure. Constraints like no writing to local files – writes to database System only; requests time out at 60 seconds; limits placed on third-party software apply. While this enhances security and stability, it can be restrictive for some use cases.
  • Stateless Applications
    Standard Environment applications are inherently stateless. They are designed to handle HTTP requests and can’t maintain long-lived connections. For stateful applications, you may need to explore other options.

The Standard Environment is an excellent choice for projects with the following characteristics:

  1. Web Applications: If your project primarily involves building web applications using popular languages like Python, Java, or Node.js, the Standard Environment can be a great fit.
  2. Low to Moderate Traffic: It’s suitable for applications with relatively consistent and predictable traffic patterns. The automatic scaling ensures cost-efficiency.
  3. Stateless Applications: Projects that don’t rely heavily on maintaining session states or require persistent connections can thrive in the Standard Environment.
  4. Prototyping and Quick Development: Developers can quickly prototype and develop web applications without worrying about the underlying infrastructure.

The Flexible Environment

App Engine Flexible environment offers developers the ability to build and deploy containerized Apps with a click. Some key characteristics of the flexible environment include;

  • Custom Runtime:
    The Flexible Environment offers more flexibility regarding runtime environments. It allows you to manage the environment runtime, which means you can use languages and libraries not supported in the Standard Environment. This versatility opens the door to a wider range of development options.
  • Docker Containers:
    The Flexible Environment leverages Docker containers, unlike the Standard Environment which uses a predefined runtime. This enables you to create custom runtime environments with specific configurations and dependencies.
  • Scalability:
    The Flexible Environment also provides automatic scaling but is more adaptable to different workloads. It can handle applications with varying resource requirements more effectively.
  • Stateful Applications:
    Unlike the Standard Environment, the Flexible Environment allows for stateful applications. You can maintain long-lived connections and store session states if your project requires it.
  • Direct Access to Resources:
    There is no sandbox Constraints in the Flexible environment. Developers have more control and can access and configure underlying App Engine resources if necessary. This is particularly useful for complex applications with specific infrastructure requirements.

Some key features of the Flexible Environment include;

  1. Custom Runtimes
     If your project relies on a programming language or library that’s not supported in the Standard Environment, the Flexible Environment is the way to go. You can create custom Docker containers tailored to your needs.
  2. Highly Variable Workloads
    Applications with unpredictable traffic patterns or resource demands benefit from the adaptability of the Flexible Environment’s scaling capabilities.
  3. Stateful Applications
     If your project involves maintaining session states, and long-lived connections or requires direct access to underlying resources, the Flexible Environment is a more suitable choice.
  4. Microservices Architecture
    The Flexible Environment is well-suited for building and deploying microservices, thanks to its support for custom runtimes and containerization.

Comparing the 2 App Engine Environments

Now that we’ve explored the individual characteristics and use cases of both App Engine environments, let’s highlight the key differences between them:

Comparing App Engine Environments

Cost Considerations

When choosing between the Standard and Flexible Environments, cost is a crucial factor to consider. The pricing models for each environment differ:

  • Standard Environment: Pricing is based on the number of instance hours and the amount of data stored. It can be more cost-effective for applications with consistent, moderate traffic.
  • Flexible Environment: Pricing is more complex, as it depends on factors such as the type and number of virtual machines (VMs) used, storage, and network egress. While it can be costlier, the flexibility it offers may justify the higher cost for certain projects.

Conclusion

The Google Cloud Platform’s App Engine is a powerful tool that makes deployment, maintenance, and scalability easy so that developers can focus only on innovation. The choice between the Standard and Flexible Environments depends on the specific requirements of your project.

While the Standard Environment is well-suited for web applications with consistent traffic, stateless designs, and languages supported by the platform; and is an excellent choice for quick prototyping and development. The Flexible Environment provides greater flexibility in terms of language support, custom runtimes, scalability, and infrastructure control. And it’s the right choice for projects with custom requirements, stateful applications, or variable workloads.

However, the decision to choose any of the environments should be based on your project’s unique needs, scalability requirements, and budget considerations. By carefully reviewing these factors, you can leverage Google Cloud’s App Engine to create robust, efficient, and scalable web applications that meet your cloud computing goals,

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Disk Options: 4 Best Disk Options in Google Cloud Platform

Disk options

Table of Contents

Introduction

Google Cloud Platform (GCP) offers a variety of disk options to meet the needs of different workloads. Choosing the right disk option that suits your cloud computing needs can ensure that your data is stored securely and efficiently. The ability to choose from different disk options is an important feature of GCP, and this plays a critical role in data storage, retrieval, and overall performance.

 In this blog post, we will explore the different disk options available in GCP and their respective use cases.

What You Should Know About Google Cloud Platform Disks

At this point, it is very pertinent that we establish a fundamental understanding of what GCP disks are and how they work. This will help you in making the right decision as you choose from a variety of disk options in the GCP.

In cloud computing, disks are virtual storage devices that can be attached to virtual machines (VMs) to store data. These disks can be categorized into two main types namely, the persistent disks and local disks.

Different Disk Options in GCP

The different disk options available in the Google Cloud Platform

1.1 Persistent Disks: Durable block storage that is attached to virtual machines (VMs). Every single VM comes with a single root persistent disk. They are network-attached, highly available storage devices that offer durability and reliability. They come with the following attributes;

  • They are attached to a virtual Machine through the network interface
  • They are durable and can survive VM terminate
  • They are bootable. They can be attached to a VM and boot from it, and the image is loaded onto them during the first boot.
  • They use snapshots for incremental backups
  • They have high-performance capability and so can scale with size.
  • They support disk resizing even while running and attached
  • They can be attached in Read-only mode to multiple VMs
  • They can survive VM deletion if “Delete boot disk when an instance is deleted” is disabled.
  • They can either be zonal or regional. Zonal Persistent Disks are designed for high availability. They replicate data across multiple zones within a region, ensuring data durability even in the event of a zone failure.
  • Encryption keys e.g. Google-managed, Customer-managed, Customer-supplied keys.

Persistent disks come in two basic disk options: Standard Persistent Disks and Solid-State Drives (SSD) Persistent Disks.

  1. 1 Standard Persistent Disks: Standard Persistent Disks provide a balance between performance and cost. They are ideal for workloads with moderate read and write demands. An example of a standard persistent disk is a Standard Hard Disk Drive (HDD)

They provide a balance between performance and cost, making them a versatile choice for various use cases including;

  • Web Hosting: Standard Persistent Disks are suitable for hosting websites, content management systems, and web applications that require consistent, reliable storage.
  • Database Servers: For databases that have moderate read and write workloads, Standard Persistent Disks offer a cost-effective solution without compromising on data integrity.
  • File Storage: If you need a centralized file storage system for your organization, Standard Persistent Disks can handle the load efficiently.
  1. 2 SSD Persistent Disks: Solid State Drive (SSD) Persistent Disk is the ideal choice if you need high I/O (Input/Output) performance. This is because they offer low-latency access to data and are well-suited for applications that require fast data retrieval.

They are ideal for applications that demand rapid data access like;

  • Big Data Analytics: When dealing with large datasets and complex analytical queries, SSD Persistent Disks can significantly reduce query execution times.
  • Real-Time Data Processing: Applications like gaming servers, real-time analytics, and video streaming benefit from the low-latency access provided by SSD Persistent Disks.
  • High-Traffic Websites: E-commerce platforms and news websites with high traffic volumes can rely on SSD Persistent Disks to serve content rapidly to users.

Local SSD Disks

Local disks, on the other hand, are physically attached to the VM host machine. They offer high-speed storage but come with a significant drawback – they are not persistent. Local disks are best used for temporary data storage or caching, where data durability is not a primary concern. They are a specialized storage option in GCP. Attributes of the local SSD disks include;

  • Local SSD disks are physically attached to the Virtual Machine (VM)
  • They are more ephemeral than they provide, meaning data stored on them is lost if the VM is terminated or undergoes a maintenance event.
  • They have more IOPs, lower latency, and higher throughput than persistent disks.
  • They have 375 GB capacity per disk and can be up to 8 disks with a total of 3TB.
  • In Local SSD disk data can survive a reset, but not a ‘VM Stop’ or ‘terminate’
  • Local SSD disk is VM-specific. They cannot be reattached to a different VM.

Local SSD disk Use Cases include:

  • High-Performance Computing (HPC): Local SSDs shine in HPC scenarios where extremely fast data processing is required. These workloads typically involve simulations, scientific computing, and modeling.
  • Temporary Data Caching: Applications that need to cache data temporarily for faster access can leverage local SSDs.

Managing Persistent Disk

1. Cloud persistent Disk

  • A single-file system is best
  • Resize or grow disks
  • Resize file system
  • Built-in Snapshot Service
  • Automatic encryption

2. Computer Hardware Disk

  • Partitioning
  • Repartitioning disk
  • Reformat
  • Redundant disk arrays
  • Subvolume management and snapshots
  • Encrypt files before writing to disk

Maximum Persistent Disks attached to a VM:

Machine Type                                 Disk Number

Shared-core                                                 16

Standard                                                       128

High Memory                                              128

High CPU                                                      128

(Memory optimized, compute optimized)

RAM Disks

A RAM disk in GCP is a temporary storage device that uses the memory of the Compute Engine instance. RAM disks are much faster than traditional hard drives or solid-state drives because they do not have to access physical media. This makes them ideal for applications that require high performance, such as caching, databases, and logging. RAM disks can be a trusted disk option for improving the performance of your GCP applications.

Attributes of RAM Disks

  • RAM disk is created using the tmpfs filesystem
  • They are faster than local disk, slower than memory
  • It is used when your application expects a filesystem structure and cannot directly store its data in memory.
  • Fast scratch disk, or fast cache
  • They are very volatile, so their contents are lost or erased when the instance is restarted or fails
  • RAM disks share memory with your applications, so you need to make sure that you have enough memory, You may need a larger machine type if RAM was sized for the application
  • RAM disks are not backed up automatically, so consider using a persistent disk to back up RAM disk data
Disk options
Summary of the 4 best Disk Options in GCP

Beyond the basic Disk Options

There are other disk options in the GCP that are beyond the scope of this article but worth mentioning. Options like Google Cloud Storage Which though it is not a traditional disk attached to a VM, is a highly scalable, durable, and cost-effective object storage solution. It’s designed for storing massive amounts of unstructured data.

The Cloud Filestore is a shared file storage option that can be used for file sharing and collaboration. It is a good choice for workloads that require high performance and availability, such as media editing, content management systems, and collaboration platforms. I shall treat cloud storage and cloud filestore in subsequent posts.

How to Choose the Right Disk Option

Choosing the best disk option for your needs depends on your specific workload requirements. We will also look at some of the criteria that you must take into consideration as you choose the right disk option for your needs. Criteria like

  • Performance: How much performance do you need? Assess the I/O and latency needs of your application. If high-speed access is critical, SSD Persistent Disks or local SSDs may be the best option.
  • Availability: How much availability do you need? You must consider Geographic locations: If you have specific geographic or compliance requirements, choose the appropriate disk option and data center location.
  • Scalable solution: Think about your future scalability needs. Some workloads may require rapid scaling, which some scalable disk options can accommodate.
  • Durable storage: Consider the importance of data durability. If data loss is unacceptable, opt for solutions like Zonal Persistent Disks or Google Cloud Storage, which provide data redundancy.
  • Capacity: How much capacity do you need?
  • Cost: How much are you willing to spend? Evaluate your budget constraints. Standard Persistent Disks are cost-effective, while SSD options come at a higher price point.

Considering these factors will help you can choose the disk option that best meets your needs.

Conclusion

The rationale for choosing the best out of a variety of disk options in the Google Cloud Platform is to optimize performance, ensure data durability, and manage costs effectively. From Standard Persistent Disks to high-speed SSDs and advanced options like Zonal Persistent Disks, GCP provides a wide array of choices to meet diverse cloud computing needs. By understanding the characteristics and use cases of each disk option and carefully considering your application’s requirements, you can make informed decisions that drive the success of your projects in the GCP.

In addition, remember that to make the right choice among different disk options you can use the GCP pricing calculator to estimate the cost of the different disk options. You can also monitor your workload performance to ensure that you are using the right disk option.

I believe you are now more informed about a variety of disk options in GCP. Watch out for more exciting posts from me. But till then keep following the Cloud. Should you have questions, feedback, or comments please feel free to use the comment box. It will help us to serve you better.

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