#Hyperdisk

[govindhtech]

Principal Advantages Of The Storage Pool + Hyperdisk On GKE

Do you want to pay less for storing GKE blocks? Storage Pool for Hyperdisks may assist Whether you’re managing GKE clusters, conventional virtual machines, or both, it’s critical to automate as many of your operational chores as you can in an economical way.

Pool Storage

Hyperdisk Storage Pool are a pre-purchased collection of capacity, throughput, and IOPS that you can then supply to your applications as required. Hyperdisk is a next-generation network connected block storage solution. Hyperdisk block storage disks allow you to optimize operations and costs by sharing capacity and performance across all the disks in a pool when you put them in storage pools. Hyperdisk Storage Pools may reduce your Total Cost of Ownership (TCO) associated with storage by up to 30–50%, and as of Google Kubernetes Engine (GKE) 1.29.2, they can be used on GKE!

Thin provisioning in Storage Pool makes this feasible by enabling you to use the capacity that is allocated inside the pool only when data is written, not when pool disks are provided. Rather of provisioning each disk for peak demand regardless of whether it ever experiences that load, capacity, IOPS, and throughput are bought at the pool level and used by the disks in the pool on an as-needed basis, enabling you to share resources as needed:

Why is Hyperdisk used?

Hyperdisk, the next generation of Google Cloud persistent block storage, is different from conventional persistent disks in that it permits control of throughput and IOPS in addition to capacity. Additionally, even after the disks are first configured, you may adjust their performance to match your specific application requirements, eliminating extra capacity and enabling cost savings.Image Credit Google Cloud

How about Storage Pool?

In contrast, storage pools allow you to share a thinly-provisioned capacity pool across many Hyperdisks in a single project that are all located in the same zone, or “Advanced Capacity” Storage Pool. Rather to using storage capacity that is provided, you buy the capacity up front and just use it for data that is written. Throughput and IOPS may be adjusted in a similar manner in a storage pool referred to as “Advanced Capacity & Advanced Performance.”

Combining Hyperdisk with Storage Pools reduces the total cost of ownership (TCO) for block storage by shifting management responsibilities from the disk level to the pool level, where all disks within the pool absorb changes. A Storage Pool is a zonal resource with a minimum capacity of 10TB and requires a hyperdisk of the same kind (throughput or balanced).

Hyperdisk

Storage Pool + Hyperdisk on GKE

Hyperdisk Balanced boot disks and Hyperdisk Balanced or Hyperdisk Throughput attached disks may now be created on GKE nodes within Storage Pool, as of GKE 1.29.2.

Let’s imagine you want to be able to adjust the performance to suit your workload for a demanding stateful application that is executing in us-central-a. You decide to use Hyperdisk Balanced for the workload’s block storage. You employ a Hyperdisk Balanced Advanced Capacity, Advanced Performance Storage Pools in place of trying to right-size each disk in your application. The capacity and performance are paid for beforehand.

Pool performance is used up when the disks in the storage pool notice an increase in IOPS or throughput, while pool capacity is only used up when your application writes data to the disks. Prior to creating the Hyperdisks inside the Storage Pool(s) must be created.

Google Cloud Hyperdisk

Use the following gcloud command to establish an Advanced Capacity, Advanced Performance StoragePools:gcloud compute storage-pools create pool-us-central1-a --provisioned-capacity=10tb --storage-pool-type=hyperdisk-balanced --zone=us-central1-a --project=my-project-id --capacity-provisioning-type=advanced --performance-provisioning-type=advanced --provisioned-iops=10000 --provisioned-throughput=1024

The Pantheon UI may also be used to construct Storage Pools.

You may also provide your node boot disks in the storage pool if your GKE nodes are utilizing Hyperdisk Balanced as their boot drives. This may be set up at cluster or node-pool construction, as well as during node-pool updates. You may use the Pantheon UI or the following gcloud command to provide your Hyperdisk Balanced node boot drives in your Storage Pool upon cluster setup. Keep in mind that your Storage Pool has to be established in the same zone as your cluster and that the machine type of the nodes needs to support Hyperdisk Balanced.

You must use the storage-pools StorageClass argument to define your Storage Pool in order to deploy the Hyperdisk Balanced disks that your stateful application uses in it. The Hyperdisk Balanced volume that your application will utilize is then provisioned using a Persistent Volume Claim (PVC) that uses the StorageClass.

The provisioned-throughput-on-create and provisioned-iops-on-create parameters are optional and may be specified by the StorageClass. The volume will default to 3000 IOPS and 140Mi throughput if provisioned-throughput-on-create and provisioned-iops-on-create are left empty. Any IOPS or Throughput from the StoragePool will only be used by IOPS and Throughput values that exceed these preset levels.

Google Hyperdisk

The allowed IOPS and throughput figures vary based on the size of the drive.

Only 40 MiB of throughput and 1000 IOPS will be used by volumes allocated with this StorageClass from the Storage Pools.

Next, create a PVC with a reference to the StorageClass storage-pools-sc.

The pooling-storage-sc When a Pod utilizing the PVC is formed, Storage Class’s Volume Binding Mode: Wait For First Consumer is used, delaying the binding and provisioning of a Persistent Volume.

Finally, utilize the aforementioned PVC to include these Hyperdisk Volumes into your Stateful application. It is necessary to schedule your application to a node pool that has computers capable of attaching Hyperdisk Balanced.

NodeSelectors are used in the Postgres deployment to make sure that pods are scheduled to nodes that allow connecting Hyperdisk Balanced, or C3 machine types.

You ought now be able to see that your storage pools has your Hyperdisk Balanced volume deployed.

Next actions

For your stateful applications, you may optimize storage cost reductions and efficiency by using a Storage Pools + Hyperdisk approach for GKE.

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[devsnews]

Google Compute Engine C3 Virtual Machines (VMs) and Hyperdisk are two products the Google Cloud Platform offers. Google Compute Engine C3 VMs are cloud-based virtual machines that offer high-performance virtual computing power, allowing users to run large-scale applications. Hyperdisk is a highly available, high-performance, low-latency block storage system that offers persistent storage for Google Compute Engine instances. It is designed for applications that require high availability and scalability.

[ark101]

HYPERDISK v1.0

High Quality Music Player

Available in two colors

- Icicle White ❄

- Cherry Red 🍒

[More colors coming soon]

Some more fake Y2K advertising. Hope you enjoy :)

[retrocgads]

UK 1995

[hardwaresfera]

HyperDisk, un pequeño SSD externo de 45 gramos que esta en Kickstarter

Toda la información en: https://hardwaresfera.com/noticias/perifericos/hyperdisk-un-pequeno-ssd-externo-de-45-gramos-que-esta-en-kickstarter/

Actualmente los SSD están a un precio realmente asequible, entre otros, porque las memorias NAND Flash han bajado de precio. Ha pasado la fiebre de los smartphone y eso nos beneficia a todos. Esto permite que se estén desarrollando otras soluciones muy interesantes, como el HyperDisk. Y es que esta unidad SSD extremadamente compacta está …

[monsieur-immortel]

[govindhtech]

Reduce the Google Compute Engine Cost with 5 Tricks

Google Compute Engine Cost

Compute Engine provides several options for cutting expenses, such as optimising your infrastructure and utilising sales. Google Cloud is sharing some useful advice to help you save Google Compute Engine cost in this two-part blog post. This guide has something for everyone, regardless of whether you work for a huge organisation trying to optimise its budget or a small business just starting started with cloud computing.

Examine your present budgetary plan

It would be helpful to have a map of your present circumstances and spending structure before you embark on a journey to optimise your Google Compute Engine cost. This will allow you to make well-informed decisions regarding your next course of action. That billing panel is the Google Cloud console. It provides you with a detailed breakdown of your spending, tracking each expense to a specific SKU. It can be used to examine the overall financial picture of your company and to determine how much a given product will cost to use for a given project.

You can find resources you are no longer paying for but no longer require by taking a closer look at your spending. Nothing is a better method to save money than simply not spending it, after all.

Examine the automated suggestions

On the page where your virtual machines are listed, have you noticed the lightbulbs next to some of your machines? These are Google Cloud’s automated suggestions for things you could do to cut costs. The following project management categories cost, security, performance, reliability, management, and sustainability are addressed by Recommendation Hub, a new technology. The recommendations system can make suggestions for actions that you might think about based on its understanding of your fleet structure. Helping you cut costs without sacrificing fleet performance is Google Cloud’s main objective.Image credit to Google Cloud

The machine can be scaled down according to its utilisation, or the type of machine can be changed (e.g., from n1 to e2). You get a summary of the recommended modification along with the expected cost savings when you click on one of the recommendations.  You have the option of applying the modification or not. Recall that the instance must be restarted in order for modifications to take effect.Image credit to Google Cloud

Check the types of discs you have

You must attach at least one persistent disc to each virtual machine in your fleet. Google Cloud offers a variety of disc formats with varying features and performance. The kinds that are offered are:

Hyperdisk

With a full range of data durability and administration features, Hyperdisk is a scalable, high-performance storage solution built for the most demanding mission-critical applications.

Hyperdisk Storage Pools 

Hyperdisk Storage Pools are pre-aggregated volumes, throughput, and IOPS that you can reserve in advance and allocate to your apps as required.

Persistent Disk 

Your virtual machines default storage option is called Persistent Disc. It may be regional or zonal. has four variations:

Standard

The desktop computer’s equivalent of an HDD disc. offers the least expensive storage with a slower I/O speed.

SSD

A speed-focused option with excellent I/O performance, albeit at a higher cost per gigabyte.

Balanced

The default setting for newly created compute instances; it strikes a compromise between “Standard” and “SSD.”

Extreme

Suitable for the hardest workloads. enables you to manage the disk’s IOPS in addition to its size.

Local SSD

An SSD that is physically attached to the host that powers your virtual machine is called a local SSD. incredibly quick but transient.

Since persistent disc storage is the most widely used type of storage, let’s concentrate on it. The Balanced disc, which offers a decent compromise between performance and cost, is the default disc type used when building a new virtual machine. Although this works well in a lot of situations, it might not be the ideal choice in every situation.

Fast I/O to disc is not needed, for instance, by stateless apps that are a component of auto-scaling deployments and keep all pertinent data in an external cache or database. These apps are excellent candidates for switching to Standard discs, which, depending on the region, can be up to three times less expensive per gigabyte than Balanced discs.

A list of the discs used in your project can be obtained using: the list of gcloud compute discs with the format “table(name, type, zone, sizeGb, users)”

You must clone the disc and make changes to the virtual machines that use it in order to start using the new disc in order to alter the disc type.

Free up any unused disc space

Moving on to storage, there are other factors besides disc type that influence price. You should also consider how much disc utilisation affects your budget.You will be paid for the full 100 GB of persistent disc space allocated for your project, whether you use 20%, 70%, or 100%. You may still want to monitor your boot discs closely even if your application does not use Persistent Discs for data storage.

If your stateless programme really needs a disc with many gigabytes of free space, think about reducing the size of the discs to match your actual needs. Because they enjoy round numbers, people frequently build 20 GB discs even when they only require 12 GB. Save money and act more like a machine.

Agree to make use of CUDs, or committed use discounts

Compute Engine is not the only product to which this advice is applicable. You can receive a significant discount if you can guarantee that you’ll use a specific number of virtual machines for three or more years, or at least a year! You can get substantially cheaper costs for local SSDs, GPUs, vCPUs, memory, sole-tenant nodes, and software licences by using a range of (CUDs). You are not even limited to allocating your vCPU and memory to a certain project, area, or machine series when using Flex CUDs.

Discounts for committed use are offered on a number of Google Cloud products. If you’re satisfied with Google Cloud and have no intention of switching providers anytime soon, you should seriously think about utilising CUDs whenever you can to save a lot of money. When it comes to computing, you can buy CUDs straight from the Google Cloud dashboard.

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[fotonistan-blog]

HyperDisk Kickstarter, Uygun Fiyatlı 1.000 MB/sn Cep Tipi SSD Sürücü

HyperDisk Kickstarter, Uygun Fiyatlı 1.000 MB/sn Cep Tipi SSD Sürücü

HyperDisk süper hızlı SSD sürücüleri için güçlü bir Kickstarter’a sahiptir. Cep boyutunda olan bu sabit sürücü, 1000 MB / sn’ye kadar aktarım hızlarıyla 2 TB’a varan bir kapasiteye sahiptir.

Süper hızlı, süper küçük ve uygun fiyatlı bir sabit disk arıyorsanız , HyperDisk Kickstarter  başlamak için iyi bir yer olabilir.

1000 MB / sn’ye kadar aktarım hızlarına sahip olan ve 512 GB, 1 TB ve 2 TB…

[maxgainzzz]

AudioEye, Inc. (AEYE: OTCQB) | Global Agency HyperDisk Marketing Selects AudioEye to Provide Sustainable Web Accessibility to Clients Worldwide

from OTC Markets Group - News, Filings & Corporate Actions http://www.otcmarkets.com/stock/AEYE/news?id=195155

[govindhtech]

Hyperdisk Storage Pools: A Guide to Block Storage Management

Hyperdisk Storage Pools, the first block storage solution from a hyperscale cloud provider to allow thin-provisioning, data reduction, and capacity pooling, will be generally available, as Google cloud revealed at Google Cloud Next 2024. By reducing your Total Cost of Ownership (TCO) by up to 30–50%, Hyperdisk Storage Pools enable you to streamline block storage management, modernise SAN-based operations, and increase efficiency. Storage Pools are available right now via the Google Cloud console. Let’s examine Hyperdisk Storage Pools’ operation and integration into your environment in this blog post.

Hyperdisk Storage Pools can store big amounts using Compute Engine. A Hyperdisk Storage Pool provides pre-purchased capacity, throughput, and IOPS to applications as needed. Create, manage, and use discs in pools with Hyperdisk Storage Pools for multiple workloads. Manage discs in bulk to save money and increase capacity and performance. By employing exactly the storage you need in Hyperdisk Storage Pools, you simplify capacity forecasts and decrease management by going from hundreds of discs to one pool.

Benefits of storage pools include:

Thin provisioning and data reduction enable Hyperdisk Storage Pools store data efficiently and achieve best-in-class TCO.

Hyperdisk Storage Pools take advantage of thin provisioning and data reduction to maximize resource utilization and minimize TCO.

Management overhead reduced Higher Flexibility – Hyperdisk Storage Pools allow workload owners to provide larger discs and only use what they need, eliminating capacity and performance forecasts and rescaling downtime.

Workloads use Hyperdisk volumes the same way with storage pools. No downtime or workload disruptions are needed.

Data on discs in a storage pool remain isolated as if they were not.

Use storage pools

Storage pools solve these issues:

Trouble predicting resource requirements when transitioning on-premise SAN workloads to Google Cloud.

Estimating application performance and capacity can take weeks and be error-prone, delaying a cloud migration or application rollout.

In Hyperdisk Storage Pools, you can overestimate the capacity needed to make discs and then only use the disc space you write data on.

Underuse of resources

Ensuring volume utilization is difficult and painful. Block storage is often underutilized because peak capacity and performance must be provided to avoid outages and slowdowns. However, few applications reach those levels.

Using Hyperdisk Storage Pools, you establish a pool to meet workload capacity needs. To keep utilization below 80%, the Hyperdisk Storage Pool automatically adds capacity.

Complex workload block storage management

Managing hundreds or thousands of disc volumes takes time and resources away from innovation.

When creating VM discs in a storage pool, you can choose a size bigger than expected workload. Workloads write to discs, reducing storage pool capacity. You only subtract the block storage you use from the storage pool capacity, not the disc creation amount. The disc size you choose limits capacity. Only change the disc size if this limit is reached.

If you build discs in the storage pool and your workload exceeds capacity planning over numerous discs, you can expand capacity. All discs in the storage pool can use the extra capacity.

Hyperdisk Storage Pools options

Features of storage pools include:

Allocating blocks as needed instead of all at once is capacity thin provisioning. This prevents low storage utilisation, where lots of disc space is assigned but not used.

Data reduction: Storage pools improve efficiency with various data reduction technologies. Data type strongly affects data reduction. Data compressed or encrypted before storage in a Hyperdisk Storage Pool won’t reduce.

To prevent failures caused by insufficient capacity, Hyperdisk Storage Pools automatically adds capacity when utilisation surpasses 80% of provisioned capacity.

Hyperdisk Storage Pool operation

A storage pool with the aggregate capacity and performance your workloads need is created, then discs are added. Connect the discs to your VMs. Create discs with a larger size than needed. This allows future growth without disc resizing.

Only the disc space your workloads require after data reduction is withdrawn from the Advanced capacity storage pool if the disc was generated there.

To increase disc capacity, increase the storage pool’s provided capacity. The discs’ disc space can then rise to the size you set when creating them. By generating discs in an Advanced capacity storage pool with a big initial size and allocating additional space, you consolidate disc storage administration and decrease costs.

Storage pool capacity is managed. Increase or decrease a storage pool’s provided capacity to change disc capacity. If the storage pool’s usage capacity or the aggregate capacity of all discs reaches 80% of its specified capacity, an advanced capacity storage pool automatically adds capacity. If auto-grow fails, you can manually add storage pool capacity up to 1 PiB.

If a storage pool achieves 100% utilization and has no free space, writes to all discs fail unless data or discs are deleted. Most commercial software treats full disc write errors like hardware failures.

To avoid out-of-space issues, actively maintain and monitor your storage pool. You should also know how your workload will react to a disc out of space issue in a storage pool.

Hyperdisk Storage Pool provisioning

You can configure a Hyperdisk Storage Pool with Standard or Advanced capacity.

Storage pools standard capacity

Standard capacity provisioning creates discs in the storage pool until all discs exceed the pool’s capacity. Standard capacity storage pool discs use capacity like non-storage pool discs.

Storage pools with high capacity

Advanced storage pools allow thin-provisioning and data reduction for capacity, allowing you to provision discs with more capacity than purchased. Advanced capacity storage pools use capacity based only on bytes written to discs after data reduction, so you can give end users and applications more capacity than you paid.

Advanced capacity lets you build discs in the storage pool that exceed its provisioned capacity by up to 500%. Data written determines storage pool capacity, not disc capacity. Advanced capacity storage pool discs use capacity differently from Standard capacity and non-storage pool discs.

You can fill discs in an Advanced capacity storage pool to their allotted size if the data written to all discs doesn’t exceed the capacity. The auto-grow feature adds capacity to the storage pool if utilization reaches 80% of provisioned capacity. If the storage pool is full, writes to all discs will fail until you delete data or discs to reduce its capacity. Since most software applications treat writes to full discs as hardware failures, it’s important to both:

Monitor your storage pool to minimise disc space shortages.

Know how your workload reacts if it does.

Remember that storage pools can’t see your file system. Deleted data is still in use until your OS marks it unused using DISCARD or TRIM. Most third-party OS images and all Google-provided OS images do this by default, but you should confirm this if you are not using one. Find out how to verify or configure this feature at Disable lazy initialization and enable DISCARD commands.

Hyperdisk Storage Pool Types

The discs you can generate in a Hyperdisk Storage Pool depend on its type.

Hyperdisk Throughput Storage Pool: You choose capacity and throughput while creating the storage pool. Created Hyperdisk Throughput discs in the storage pool use some allotted capacity and throughput.

Hyperdisk Balanced Storage Pool: You set capacity, throughput, and IOPS while constructing the storage pool. You employ some of the storage pool’s capacity and performance to make Hyperdisk Balanced discs with capacity and performance above baseline.

High-throughput storage pools

Storage Pools can manage Hyperdisk Throughput disc utilization.

Performance

Storage pooled discs perform the same as non-pooled discs.

Pricing

Capacity, throughput, and IOPS determine Hyperdisk Storage Pool pricing.

Standard capacity storage pools price capacity like discs. Standard capacity in a Hyperdisk Balanced Storage Pool costs the same as standalone capacity.

Thin provisioning and data reduction cost more, hence advanced capacity is more expensive. Despite this premium, thin-provisioning and data reduction can lower block storage costs by increasing efficiency and utilization.

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[govindhtech]

Google Cloud Advanced Performance Storage Pools Start Today

Block storage in Cloud

Hyperdisk Advanced Performance Storage Pools

Hyperdisk Storage Pools with Advanced Capacity, which help you reduce the Total Cost of Ownership (TCO) of your block storage capacity, were made generally available earlier this year. With Hyperdisk Storage Pools with Advanced Performance, Google is introducing that same breakthrough to block storage performance today. Now that you can provision IOPS and throughput aggregately, which Hyperdisk Storage Pools will dynamically allocate as your applications read and write data, you can significantly simplify performance planning and management and greatly boost resource usage.

With the Google Cloud console, you can begin using Advanced Performance Storage Pools right now.

The difficulty lies in allocating an appropriate quantity of performance resources

Clients have reported difficulties in striking a balance between making the most of all of their block storage performance resources and guaranteeing that their workloads have the resources necessary to be successful. This problem stems from what is known as the “sum of peaks” problem. Customers will provision their block storage at the maximum performance they have seen to guarantee that their workloads are never performance starved; nevertheless, in the majority of cases, their disks consume much less than that performance. This indicates that the performance usage of your disks is consistently low.

Utilizing Advanced Performance Storage Pools, reduce TCO by 40–50%

To address this issue, Google created Advanced Performance for Hyperdisk Storage Pools. You may now achieve high performance utilization and successful workloads simultaneously with Advanced Performance Storage Pools. When you provision performance in aggregate in a Hyperdisk Storage Pool with Advanced Performance, the Storage Pool intelligently divides those resources among the disks in the Pool as required. All without altering the behavior of drives, allowing your applications to function normally. Without compromising application success or resource efficiency, you can now more easily plan for your performance requirements and reduce your total cost of ownership.

To show how Hyperdisk Storage Pools with Advanced Performance can reduce your total cost of ownership, let’s examine a few workloads. Consider two workloads: a database workload that needs 75K IOPS at peak (such as when quarterly reports are due) but only 35K at steady state, and an enterprise application suite that needs 25K IOPS at peak (such as when all users are signed in simultaneously) but only 10K at steady state.

Since these workloads’ steady state performance would be around half of their allocated performance, they would function at 40–45% performance utilization outside of a pool. But because a Hyperdisk Storage Pool with Advanced Performance’s dynamic resource allocation guarantees that these workloads operate at about 80% utilization, the customer can supply far lower performance resources and reduce their TCO from 40–55% without modifying their applications.WorkloadPerformance RequirementsGCP Storage PoolsAlternative Cloud ProviderPools TCO SavingsEnterprise applicationsPeak IOPS: 25KAvg IOPS: 10KPeak Tput: 400 MiB/sAvg Tput: 160 MiB/s$33K/mo.$74K/mo.55%Databases (e.g. SQL Server)Peak IOPS: 75KAvg IOPS: 35KPeak Tput:  1.2 GiB/sAvg Tput:  560 MiB/s$15K/Mo.$25K/Mo.40%Price:IOPs – $.0095Throughput – $.076$81.92 / TiBIncludes: 1 TiB capacity, 5K IOPS, 200 MiB/s

Plan ahead and simplify block storage performance

A major advancement in performance resource provisioning is Advanced Performance Storage Pools. Infrastructure managers have historically had to decide between risking application failure by optimizing operational efficiency or accepting poor utilization. This implies that they must take on significant managerial effort and actively oversee each volume’s success.

Block storage performance management is made easy with Hyperdisk Advanced Performance Storage Pools. An Advanced Performance Storage Pool’s disk IOPS and throughput are “thin-provisioned.” To put it another way, you can provision up to five times the IOPS and throughput in a pool to the disks in the pool while maintaining resource-neutral performance at the disk level.

This results in great efficiency (because you no longer need to actively manage the IOPS and Throughput allocated to each disk) and eases deployment planning (since you no longer need to guess precisely what performance demands each disk should have). All you have to do is build the disks you need, as performanta as possible, and allow the Advanced Performance Storage Pool to provide resources as needed.

Early adopters of Advanced Performance Storage Pools, like REWE, have recognized the benefits of the product.

Start now

The same process used to create Hyperdisk Storage Pools can also be used to start Hyperdisk Advanced Performance Storage Pools. Go to Compute Engine by logging into the Google Cloud dashboard and selecting Storage. Next, establish your Storage Pool, choose Advanced Performance as the volume type (Balanced or Throughput), and enter the entire capacity and performance that the pool will require. Starting with the creation of new Hyperdisk volumes, you may start using the pool’s capacity as well as the extra advantage of dynamically sharing performance across your resources.

We believe that Advanced Performance Storage Pools will significantly enhance your ability to manage and get the optimal performance of your applications. The regions and zones that will receive Hyperdisk Advanced Performance Storage Pools are now being served. Start using Advanced Performance Storage Pools right now by opening the Google Cloud dashboard and navigating through Google Cloud’s documentation to establish, use, and maintain your pools.

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[govindhtech]

Compute Engine’s latest N4 and C4 VMs boosts performance

Customers’ workloads are diverse, consisting of multiple services and components with distinct technical requirements. A uniform approach hinders their ability to scale while attempting to maintain cost and performance equilibrium.

In light of this, Google cloud introduced the C4 and N4 machine series, two new additions to their general-purpose virtual machine portfolio, at Google Cloud Next ’24 last month. The first machine series from a major cloud provider, the C4 and N4, are driven by Google’s Titanium, a system of specially designed micro controllers and tiered scale-out offloads, and make use of the newest 5th generation Intel Xeon processors (code-named Emerald Rapids).

C4 and N4 provide the best possible combination of cost-effectiveness and performance for a wide range of general-purpose workload requirements. While N4’s price-performance gains and flexible configurations, such as extended memory and custom shapes, let you choose different combinations of compute and memory to optimise costs and reduce resource waste for the rest of your workloads, C4 tackles demanding workloads with industry-leading performance.

C4 and N4 are built to satisfy all of your general-purpose computing needs, regardless of whether your workload demands constant performance for mission-critical operations or places a higher priority on adaptability and cost optimisation. The C4 machine series is currently available in preview for Compute Engine and Google Kubernetes Engine (GKE), while the N4 machine series is currently available broadly.

N4: Flexible forms and price-performance gains

The N4 machine series has an efficient architecture with streamlined features, forms, and next-generation Dynamic Resource Management, all designed from the bottom up for price-performance advantages and cost optimisation. With up to 18% better price-performance than N2 instances and up to 70% better price-performance than instances, N4 helps you reduce your total cost of ownership (TCO) for a variety of workloads as compared to prior generation N-Family instances. N4 offers up to 39% better price-performance for My SQL workloads and up to 75% better price-performance for Java applications as compared to N2 across key workloads.Image credit to Google cloud

Additionally, N4 offers you the most flexibility possible to accommodate changing workload requirements with bespoke shapes that provide you with fine-grained resource control. Custom shapes add a cost optimisation lever that is now exclusive to Google Cloud by letting you only pay for what you use, preventing you from overspending on memory or vCPU. Additionally, custom shapes provide seamless, reconfiguration-free migrations from on-premises to the cloud or from another cloud provider to Google, as well as optimisation for special workload patterns with unusual resource requirements.

In order to support a wider range of applications, N4 additionally offers 4x more preconfigured shapes at significantly bigger sizes up to 80 vCPUs and 640GB of DDR5 RAM as compared to similar offerings from other top cloud providers. Predefined forms for N4 are offered in three configurations: regular (4GB/vCPU), high-mem (8GB/vCPU), and high-cpu (2GB/vCPU).

In comparison to other cloud providers, N4 delivers up to 4 times the usual networking speed (50 Gbps standard) and up to 160K IOPS with Hyperdisk Balanced. Most general-purpose workloads, including medium-traffic web and application servers, dev/test environments, virtual desktops, micro services, business intelligence applications, batch processing, data analytics, storage and archiving, and CRM applications, are well-suited for N4. These workloads require a balance between performance and cost-efficiency.

Dynamic Resource Management

On N4 and Titanium, Google’s next-generation Dynamic Resource Management (DRM) improves upon current optimisation techniques to deliver a greater price-performance, reduce expenses, and support a wider range of applications.

Google cloud worldwide infrastructure is supported by a Google-only technology called dynamic resource management, which handles workloads for YouTube, Ads, and Search. The most recent iteration of dynamic resource management uses Titanium to precisely forecast and consistently deliver the necessary performance for your workloads. Dynamic resource management on N4 offers shown dependability, efficiency, and performance at scale.

C4: Cutting-edge features and performance in the industry

C4 is designed to handle your most demanding workloads. It comes with the newest generation of compute and memory, Titanium network and storage offloads, and enhanced performance and maintenance capabilities. When compared to similar services from other top cloud providers, C4 offers up to 20% better price-performance; when compared to the previous generation C3 VM, C4 offers up to 25% better price-performance across important workloads.Image Credit to Google cloud

In addition, C4’s Titanium technology provides up to 80% greater CPU responsiveness than prior generations for real-time applications like gaming and high-frequency trading, which leads to quicker trades and a more fluid gaming experience12. Demanding databases and caches, network appliances, high-traffic web and application servers, online gaming, analytics, media streaming, and real-time CPU-based inference with Intel AMX are all excellent fits for the high performance of C4.

Additionally, C4 transfers processing for virtual storage to the Titanium adapter, which enhances infrastructure stability, security, performance, and lifecycle management. Titanium enables C4 to provide scalable, high-performance I/O with up to 500k IOPS, 10 GB/s throughput on Hyperdisk, and networking bandwidth of up to 200 Gbps13.

Better maintenance controls are another feature that C4 provides, allowing for less frequent and disruptive planned maintenance with increased predictability and control. C4 instances can support up to 1.5TB of DDR5 RAM and 192 vCPUs. Standard, high-memory, and high-processor variants are offered. Customers of Compute Engine and Google Kubernetes Engine (GKE) can now access C4 in Preview.

N4 and C4 work well together

They are aware that choosing the ideal virtual machine is critical to your success. You can reduce your overall operating costs without sacrificing performance or workload-specific needs when you use C4 and N4 to handle all of your general-purpose tasks.

Utilise virtual machines (VMs) that expand with your company. Combining C4 and N4 offers you flexible options to mix and combine machine instances according to your various workloads, along with affordable solutions that put performance and reliability first.

Availability

Us-east1 (South Carolina), Us-east4 (Virginia), Us-central1 (Iowa), Europe-west1 (Belgium), Europe-west4 (Netherlands), and Asia-southeast1 (Singapore) currently have widespread access to N4. Customers of Google Kubernetes Engine (GKE) and Compute Engine can now access C4 in Preview.

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Z3 VMs Unveiled: Discover Unmatched Efficiency in Google

Storage-dense workloads require reliable performance, high SSD density, and data-preserving maintenance. They launched google cloud first storage-optimized VM family, the Z3 machine series, last week at Google Cloud Next ‘24. Z3 VMs offer more storage capacity for fewer cores, reducing total cost of ownership by offering more storage capacity for fewer cores. They also have an industry-leading 6M 100% random-read and 6M write IOPs, an incredibly dense storage configuration of up to 409 SSD (GB) per vCPU, and a highmem configuration.

Google Compute Engine and Kubernetes Engine customers get the enterprise-grade performance and reliability of the 4th Gen Intel Xeon scalable processor, Google’s custom Intel Infrastructure Processing Unit (IPU), and the latest Local SSD in the Z3 machine series. Next-generation Local SSDs in Z3 offer 3x disc throughput and 35% lower disc latency than previous generations. Z3 is perfect for horizontal, scale-out, flash-optimized, data warehouse, and other dense storage applications.

Z3 initially comes in two configurations: 176 vCPU with 1.4T DDR5 memory and 88 vCPU with 704 GB and 36TB of next-generation Local SSD.

Improvements in maintenance New infrastructure lifecycle technologies in Z3 VMs improve maintenance management and specificity. It’s receive system maintenance notices several days in advance. You can schedule the maintenance event or let it default. This lets you plan ahead for disruptive events and gives us better performant and secure infrastructure. In-place updates and planned maintenance events will protect your data.

Powered by Titanium Google’s Titanium system of custom silicon, security microcontrollers, and tiered scale-out offloads powers Z3 VMs. Workload performance, lifecycle management, dependability, and security improve. Titanium gives Z3 up to 200 Gbps of fully encrypted networking, 3x faster packet-processing than previous generations, near-bare-metal speed, integrated maintenance updates for most workloads, and improved controls for critical applications.

We’re excited to work with Google Cloud on its first storage-optimized VM family after a successful cooperation since 2016. This partnership delivers Intel’s 4th Gen Intel Xeon processor and Google’s proprietary Intel IPU for increased efficiency and performance. Intel Corporation General Manager-Intel Xeon Products Suzi Jewett

Hyperdisk storage Google Cloud’s latest block storage is Hyperdisk. Hyperdisk, built on Titanium, decouples storage processing from the virtual machine host to boost performance, flexibility, and efficiency. Data-intensive applications like data analytics and databases may easily fulfil storage I/O needs using Hyperdisk’s dynamic storage performance and capacity scaling. You no longer need pricey, massive compute instances to improve storage performance.

Start Z3 now Us-central1 , europe-west4 , and asia-southeast1 have Z3 VMs. When building a new VM or GKE node pool in Google Cloud, pick Z3 under the new Storage-Optimized machine family to use Z3 instances. Visit the Z3 machine series page. Ask your Google Cloud sales person for area availability.

Introduction Virtual machines (VMs) are essential in cloud computing, where efficiency, speed, and scalability are key. The revolutionary Z3 VMs have changed virtualization. This detailed tutorial explores it’s unmatched IOPS . capabilities and the features and benefits that make them industry leaders in performance.

Understanding IOPS Before discussing Z3 VMs, they must understand IOPS in cloud computing. IOPS, which monitors storage device read and write speeds, is a key system performance parameter. Higher IOPS numbers mean faster data transfer speeds and better responsiveness, making them crucial for fast, flawless applications.

The Z3 VMs Benefit Unmatched Performance

A complex design powers Z3 VMs’ unmatched performance. Z3 VMs have industry-leading IOPS thanks to powerful processors and optimized storage. Z3 VMs enable lightning-fast performance for data-intensive workloads and real-time transactions, improving cloud infrastructure efficiency.

Scalability, Flexibility Z3 VMs’ unrivalled performance, scalability, and flexibility enable enterprises to adapt and develop in a changing digital landscape. Z3 VMs optimize resource utilization and cost effectiveness by effortlessly scaling resources up or down on demand. Z3 VMs give startups and established enterprises the agility and scalability they need to stay ahead.

Better Reliability Cloud computing requires reliability since even a small outage can have serious repercussions. Because of this, Z3 VMs prioritize stability and resilience. By using redundant components and robust failover techniques, Z3 VMs reduce downtime and maintain continuous availability, boosting mission-critical application confidence.

Applications in Real Life

The unequalled IOPS of Z3 VMs opens up many opportunities across sectors and use cases. From real-time data processing for high-frequency trading platforms to lightning-fast inference for AI-driven apps, Z3 VMs enable organizations to innovate and evolve. Z3 VMs provide the performance and stability you need to succeed in finance, healthcare, e-commerce, or other fields.

Conclusion Finally, Z3 VMs offer unmatched IOPS performance, scalability, and dependability, marking a milestone in cloud computing. Businesses may boost innovation and efficiency by using Z3 VMs to maximize their cloud infrastructure. Z3 VMs are ready to lead the digital age in speed, scalability, and reliability as technology advances and high-performance computing demands rise.

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Introducing Google Axion Processors: A New Era for Cloud

Google Axion Processors

Arm Based CPU

At Google, they continuously push the limits of computers to investigate what can be done for big problems like global video distribution, information retrieval, and, of course, generative AI. Rethinking systems design in close cooperation with service developers is necessary to achieve this. Their large investment in bespoke silicon is the outcome of this rethinking. Google is excited to present the most recent iteration of this effort today: Google Axion Processors, Google’s first specially made Arm-based CPUs intended for data centers. Later this year, Axion which offers performance and energy efficiency that leads the industry will be made accessible to Google Cloud users.

Axion is only the most recent model of customised silicon from Google. Google’s first Video Coding Unit (VCU) increased video transcoding efficiency by 33x in 2018. Five generations of Tensor Processing Units have been launched since 2015. Google invested in “system on a chip” (SoC) designs and released the first of three generations of mobile Tensor processors in 2021 to boost bespoke computing.

General-purpose computing is and will continue to be a vital component of their customers’ workloads, even if Google investments in compute accelerators have revolutionised their capabilities. Extensive computation power is needed for analytics, information retrieval, and machine learning training and providing. The pace at which CPUs are being improved has slowed lately, which has affected customers and users who want to satisfy sustainability objectives, save infrastructure costs, and maximise performance. According to Amdahl’s Law, unless Google make the corresponding expenditures to stay up, general purpose compute will dominate the cost and restrict the capabilities of their infrastructure as accelerators continue to advance.

Google BigTable

In order to deliver instances with up to 30% better performance than the fastest general-purpose Arm-based instances currently available in the cloud, as well as up to 50% better performance and up to 60% better energy-efficiency than comparable current-generation x86-based instances, Axion processors combine Google’s silicon expertise with Arm’s highest performing CPU cores. For this reason, on current generation Arm-based servers, Google have already begun implementing Google services such as BigTable, Google Spanner, BigQuery, Blobstore, Pub/Sub, Google Earth Engine, and the YouTube Ads platform. Google also have plans to deploy and expand these services, along with others, on Axion shortly.

Superior effectiveness and performance, supported by Titanium

Axion processors, which are constructed around the Arm Neoverse V2 CPU, offer massive performance gains for a variety of general-purpose workloads, including media processing, web and app servers, containerised microservices, open-source databases, in-memory caches, data analytics engines, and more.

Titanium, a system of specially designed silicon microcontrollers and tiered scale-out offloads, provides the foundation for Axion. Platform functions like networking and security are handled by titanium offloads, giving Axion processors more capacity and enhanced performance for workloads from customers. Titanium also transfers I/O processing for storage to Hyperdisk, Google’s recently launched block storage solution that can be dynamically supplied in real time and decouples performance from instance size.

Titanium

A system of specially designed silicon security microcontrollers and tiered scale-out offloads that enhances the dependability, security, life cycle management, and performance of infrastructure.

Google-powered Titanium

Titanium is a free platform that supports Hyperdisk block storage, networking, the newest compute instance types (C3, A3, and H3), and more on Google Cloud.

Included in the system are:

Titan security microcontrollers are specially designed to provide Google Cloud’s infrastructure a hardware root of trust.

Titanium adaptor: specialised offload card that offers hardware acceleration for virtualization services; frees up resources for workloads by offloading processing from the host CPU

Titanium offload processors (TOPs) are silicon devices placed across the data centre that are used as a scalable and adaptable method of offloading network and I/O operations from the host CPU.

Enhanced functionality of the infrastructure

Titanium offloads computation from the host hardware to provide additional compute and memory resources for your applications.

Hyperdisk Extreme block storage allows for up to 500k IOPS per instance, which is the greatest among top hyperscalers.

200 Gbps or more of network bandwidth

Full line rate network encryption that offers security without compromising speed

Consistent performance comparable to bare metal for the most delicate workloads

Smooth management of the infrastructure life cycle

Infrastructure changes are made easier by Titanium’s modular hardware and software, which also provide offloading capabilities and workload continuity and security.

Advanced maintenance controls for the most critical workloads and seamless upgrades for the majority of workloads

It is possible to start remote infrastructure upgrades from any location.

The Titanium adaptor’s dedicated domains for networking and storage enable for the autonomous upkeep and upgrades of individual services, keeping them apart from the host’s burden.

“Building on Google’s high-performance Arm Neoverse V2 platform, Google’s announcement of the new Axion CPU represents a significant milestone in the delivery of custom silicon optimised for Google’s infrastructure.” The greatest experience for consumers using Arm is guaranteed by decades of ecosystem investment, Google’s continuous innovation, and its contributions to open-source software.”

Customers want to accomplish their sustainability objectives and operate more effectively, not only perform better. In comparison to five years ago, Google Cloud data centres are now 1.5 times more efficient than the industry average and provide 3 times more processing power with the same amount of electrical power. Google lofty objectives include running their campuses, offices, and data centres entirely on carbon-free energy sources around-the-clock and providing resources to assist with carbon emission reporting. Customers may optimise for even greater energy efficiency using Axion processors.

Axion: Interoperability and compatibility with out-of-the-box applications

Additionally, Google has a long history of supporting the Arm ecosystem. They worked closely with Arm and industry partners to optimize Android, Kubernetes, Tensorflow, and the Go language for the Arm architecture. Google also constructed and made them open-sourced.

Armv9 architecture

The standard Armv9 architecture and instruction set serve as the foundation for Axion. Google have made contributions to the SystemReady Virtual Environment (VE) standard, which is designed to ensure that Arm-based servers and virtual machines (VMs) can run common operating systems and software packages. This standard makes it easier for customers to deploy Arm workloads on Google Cloud with minimal to no code rewrites. Google is gaining access to an ecosystem of tens of thousands of cloud users that are already using Arm-native software from hundreds of ISVs and open-source projects and deploying workloads thanks to Google’s partnership.

Axion will be available to users across a variety of Google Cloud services, such as Cloud Batch, Dataproc, Dataflow, Google Compute Engine, and Google Kubernetes Engine. The Google Cloud Marketplace now offers Arm-compatible apps and solutions, and Google just released preview support for the Migrate to Virtual Machines service, which allows you to migrate Arm-based instances.

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