Google Compute Engine: Explore the Power of Virtual Machines
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Businesses today highly rely on cloud-based applications and workflows, as they are subject to any time and anywhere accessibility. However, these applications are often vulnerable to downtime and interruptions, which directly impact business productivity.
But, with Google Compute Engine, you can ensure that your workloads remain up and running during both planned and unplanned events. According to Google, the Compute Engine offers the best compute availability, with 99.95% for memory-optimized VMs and 99.9% for other VM families.
This means your system will experience minimal downtime and interruptions, improving overall uptime and productivity.
But how does it happen? To know the answers and everything about Compute Engine, go through this blog!
What is Google Compute Engine?
It is an infrastructure as a service (Iaas), offered by Google Cloud Platform, where you can create and manage virtual machines, stating the CPU, operating system, and storage requirements as per your needs. These VMs further support services and products like Google Search, YouTube, Gmail, and more, ensuring seamless workload handling.
that lets you create virtual machines that support your applications and workloads in the cloud. It provides computing and hosting services for VMs that run over the Google Cloud Platform.
Computer Engine allows you to choose from a variety of pre-defined VMs with standard CPU and memory, or you can create VMs from scratch by defining CPU and memory requirements. Therefore, using Compute Engine, you can develop a solution that ensures the smooth working of your applications and workloads in the cloud.
Suppose you migrated to the cloud and managed your website traffic effectively. However, due to an upcoming sale, you are aware that your website traffic will increase, and to handle it, you need a scalable solution. Therefore, by creating or adding more VMs that support streamlined traffic handling, you can easily power your system for increased traffic.
Key Features Of Google Compute Engine
1. Machine Families
Compute Engine offers different machine types curated to support different workload purposes. You can choose VMs among various options available that support your specific business needs and only pay for those you use.
Let’s explore the options:
General-Purpose Machines
As the name suggests, these machines are used to serve the general purpose of business workloads. They deal with day-to-day computing purposes such as developing or testing the environment, managing cloud servers, websites, or databases, overviewing back office applications, and more.
Well known for offering a perfect balance between pricing and performance, these machines are available at a lower cost yet offer high-quality basic services. Therefore, businesses wanting to focus on their core operations can utilize these machines.
Compute-Optimized Machines
These machines are utilized for workloads that require high and consistent performance throughout, such as gaming and media streaming purposes. Due to the high CPU ratio, these machines can work smoothly throughout a workload execution.
Therefore, it is best for businesses that deal with complex calculations, extensive data processing, and bulky workloads that hamper their process continuity.
These machines are utilized for workloads that require high and consistent performance throughout, such as gaming and media streaming purposes. Due to the high CPU ratio, these machines can work smoothly throughout a workload execution. Therefore, it is best for businesses requiring high throughput, consistent performance, complex calculations, and extensive data processing.
Memory-Optimized Machines
These machine types offer a high memory ratio of up to 12 terabytes in a single instance and are best suited for workloads where memory utilization is high. They are best fit for in-memory databases that enable faster data access, recovery, processing, and in-memory analytics for immediate insights and decision-making.
These machines are best suited for companies that are into building IoT solutions and leveraging big data analytics.
Accelerator-Optimized Machines
These machines are designed to enhance the performance for workloads that require hardware accelerators such as GPUs (Graphic Processing Units) and TPUs (Tensor Processing Units).
They support compute- and memory-optimized machines, improving their CPU-to-memory ratio and ensuring optimized hardware support.
Businesses that are into 3D virtualization and rendering practices and want to boost their hardware utilization, enhance performance, and data-intensive workloads must utilize these machines in their business.
2. Workload Manager
This feature allows you to manage and evaluate your workloads against Google’s best practices to ensure that they meet the performance standards.
It performs various validation checks and analyzes workload configurations to identify and eliminate any misconfigurations that might hamper its working. Therefore, ensuring optimal quality and performance.
It monitors any kind of inconsistencies that arise during system updates and troubleshooting, helping in maintaining system integrity.
3. Sole Tenant Nodes
These are physical servers that host a specific project’s virtual machines over dedicated hardware. It creates an isolated environment for your VMs, restricting other project users from accessing it. This way, you can ensure security and strict regulatory compliance in your project.
Further, it allows you to deploy VMs as per your specific workflow needs and control their placement in the environment through Google’s algorithms or by manually specifying the desired location.
4. VM Manager
It is a collection of automation tools that help you manage the operating systems of large virtual machines, reducing your operational burden and utilizing resources efficiently.
VM Manager allows you to easily cope with bug fixes and security vulnerabilities by scheduling a patch job when you need to. It allows you to collect and review OS information to identify discrepancies and further install, remove, and update software packages that cater to these issues.
On your behalf, it takes care of patch applications, updates, and compliance reporting, freeing your time and efforts to focus on other important tasks.
5. TPU Accelerator
This feature helps you leverage the best of AI and ML capabilities in your environment.
Tensor Processing Units (TPUs) are customized AI accelerators that optimize your AI workload’s performance and overall cost. These TPUs incorporate spanning, fine-tuning training, and inference, making them ideal for large AI models.
By using these TPUs, you can empower a variety of AI models, including chatbots, vision services, media generation, personalization models, recommendation engines, and more.
6. Storage Options
Compute Engine offers a variety of block storage options along with unique pricing and performance options and Google Cloud security measures. You can opt for the one that fits your business needs the best.
Various storage options that you get:
Persistent Disk
It is the primary storage option used by Google virtual machines to store block and file data. It allows custom data encryption at rest and during a transfer, to ensure security and protection against vulnerabilities.
Moreover, PDs are located independently, so even if a VM is deleted, the data is still present in the persistent disk.
Hyperdisk
It offers high-performance block data storage capabilities for demand-based applications.
The data is distributed among different PDs, which are further managed by the Compute Engine which ensures the PDs are consistently working and offering optimal performance.
This storage option is also independent of VMs, allowing you to use the data even after a VM’s deletion. Also, you can easily update its performance, resize the existing volume, and add more volume to ensure optimal performance and space requirements.
Similar to PDs, hyperdisk also allows custom encryption at rest and during the transfer, ensuring optimal security.
Local SSD
This storage option by Compute Engine is directly connected to the server that hosts a virtual machine. Therefore, as the instance is closed or deleted, this storage option also gets deleted.
Local SSDs offer a high level of performance but are used to store temporary or low-value data, such as caches and more. These are encrypted by the system but do not offer custom encryption like other options.
Google Compute Engine Pricing
Google Cloud offers $300 credit to new users that they can use to run, test, and deploy workloads. After these credits exhaust, the pricing is decided by the pay-as-you-go method, i.e., you only have to pay for the services or instances that you use.
Google offers a pricing list with all the instance’s cost details, based on different regions. Also, you can bifurcate the price on an hourly or monthly basis.
Also, you can utilize the Google Cloud Pricing Calculator to estimate your total project cost.
Moreover, certain pricing benefits are associated with constant use of Compute Engine:
1. Sustained Use Discounts
Compute Engine offers you many cost benefits through discounts.
You get sustained use discounts, which apply automatically to your current billing cycle and are deducted under VM instances when these are used by more than 25%.
The more the resources are used or run, the more the discount increases, reaching up to 30%.
2. Committed Use Discounts
When you purchase Compute Engine resources through a committed use contract, documentation with all the details of your resources and their pricing, for a longer term, say 1 to 3 years, this discount type is applied.
This discount ranges from 55% to 70% based on the resources you are utilizing and as per your use, you continuously receive cost optimization benefits until your commitment expires. But, must be noted, that once the commitment is made, it cannot be cancelled; however, it can be auto-renewed.
3. Preemptible Instances
Compute Engine offers VM instances at a much lower price, with discounts ranging between 60 and 90%.
These instances are best suited for workloads that can tolerate interruptions yet do not majorly impact the working or productivity of the business. Therefore, they help in batch processing tasks, eliminating the need to add additional workloads.
However, the Compute Engine prioritizes other VMs over these VMs and might stop working when the allocation is full. This way, the Compute Engine understands your priority needs and ensures optimal resource allocation.
4. Right-Sizing Recommendations
Compute Engine allows you to resize your resources considering their optimal utilization. When the system identifies an underutilized resource, it automatically resizes it to its utilized capacity and further allocates the freed space to other instances. Therefore, the count of ideal and underutilized resources reduces, ultimately optimizing your cloud spending.
Google Compute Engine Vs. Google App Engine Vs. Kubernetes Engine
With several Google Cloud Platform offerings that allow cloud application deployment, you might have gotten confused as to how the Compute Engine stands different. Here is an overview of the key differences between these offerings:
Google Compute Engine | Google App Engine | Google Kubernetes Engine |
It is an IaaS offering that allows you to create and run VMs that support your applications. | It is a Paas offering that allows you to run applications in the cloud. | It is a Caas (Container as a service) offering that uses CE instances to create containers in which you can deploy, manage and scale applications. |
An unmanaged service where you have to configure and monitor the system as per your needs. | A managed service where you get everything pre-designed and only have to get your hands on it to work over it. | A managed service that takes care of all the backend activities of managing, scaling, and monitoring containers, allowing a focus on application. |
A cost-efficient option | Costs more than the Compute Engine but less than Kubernetes engine. | Costs more than other offerings. |
Offers you full control over resources, as you can choose which instances you want to use. | Google takes care of all the resource management, eliminating your control and allowing a sole focus on your application. | Allows limited control over resources and instances. |
Use Cases Of Google Compute Engine
Website And Application Hosting
Compute Engine enhances your website and application’s performance by deploying servers, storage, and other capabilities over VM instances. It allows you to up and downscale your resources to meet traffic fluctuations, ensuring that your solution is working smoothly throughout.
Miles Education was able to deploy new applications in under 100 seconds by using Google Compute Engine. Their deployment time was reduced by 3 hours to nearly 2 minutes.
Disaster Recovery
The Compute Engine is a saviour during disaster times. It allows you to create duplicate VM instances of your database, server, and other business workflows in a different region. Therefore, to cope with system failure, you can call these replicated VM instances and ensure a quick recovery.
The Google Compute Engine empowered MYND by extending disaster recovery across the entire tech environment and introducing a two-hour recovery time.
Gaming And Media Streaming
Compute Engine provides compute and accelerator-optimized virtual machines (VMs), which are high-performing instances with consistent performance and optimal hardware utilization. You can deploy various content delivery networks, servers, and other resources to offer a high gaming and media streaming experience.
YOOZOO is an entertainment firm that leveraged Compute Engine to reduce in-game latency by 38% and saw a 40% reduction in operational costs.
Data Analytics
With memory-optimized VM instances, the Compute Engine supports workloads that require heavy data processing and analytics. You can process bulk data in minimal time by running data-intensive tasks or processes such as mining, smart analytics, and more, resulting in accurate yet efficient results.
By using Compute Engine in its business, Computerlogy enhanced its social media and marketing analytics service offerings for its customers.
Final Take
By the end of this blog, now you have the answer to how Google Compute Engine contributes towards minimizing downtime and improving your overall business productivity.
Its versatile feature offerings that are applicable across various areas make it an efficient solution to power up the existing workloads of your business. The customizable pricing allows you to pay only for the services and resources you are utilizing, making it a cost-effective solution.
Serving areas with diverse requirements, such as hosting websites, ensuring seamless streaming, handling bulk data, and more, makes the Compute Engine a go-to solution for top businesses across the world.
Do you also wish to power up your business with uninterrupted continuity? Consult with a Google cloud service provider like Cyntexa to know more about it! We stand as a leading GCP partner, offering seamless Google Cloud services mainly in computing, data storage, processing, AI and ML, and more.
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Frequently Asked Questions
Google compute engine offers various security features, such as encryption of data at rest, during transit and when in use. Moreover, it practices permissions and roles allowing limited access to it.
Google cloud offers you a variety of cloud-monitoring agents through which you can scan your instances and accordingly monitor them for improvements or modifications.
Compute Engine integrates with other cloud services in several ways:
- Service accounts: The instances can be added to a managed service account offering credentials for running apps over these instances.
- Cloud storage: Google Cloud allows you the storage accessibility for all services.
- Client libraries: It authenticates calls through GCP APIs, which allows for credential sharability without modifying the application code.
- IP addresses: Compute Engine's VM instances use IP addresses to communicate with other services.