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Turbonomic Announcing Support for AWS GovCloud and Azure Government Cloud

Posted by Asena Hertz on Sep 13, 2021 1:54:21 PM
Asena Hertz
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Today, Turbonomic is announcing support for AWS GovCloud and Azure Government Cloud and it is generally available to all Turbonomic customers. These clouds have been designed to address explicit regulatory and compliance requirements for U.S. government agencies and customers who have more sensitive workloads they want to deploy in the cloud.

While AWS GovCloud and Azure Government Cloud address the most rigorous of U.S. government security and compliance requirements, customers still face the challenge of how to continuously ensure their application’s performance at the lowest possible cost.

Turbonomic Application Resource Management delivers the smartest cloud optimization on the market - the only automation software that ensures mission-critical cloud applications always perform at the lowest possible cost. Software (not people) continuously matches real-time application demand to the public cloud’s unprecedented number of configuration options across compute, storage, and database, as well as account for reservations (whether you bought them and need to use them… or purchasing them can further optimize your cloud investments).

And now it’s all available on GovCloud.

Cloud Compute Optimization

Turbonomic’s cloud computing optimization capabilities automatically determine the correct VM instance type for your cloud application workloads. The following metrics are considered for every compute scaling decision:

  • VCPU
  • VMem
  • Network & Storage IO
  • Throughput
  • Reserved Instance Inventory
  • Pricing/Discounts
  • Disk count, quota, available region capacity, and more

IOPS-Aware Scaling

Additionally, to scale cloud compute most effectively for performance at minimal cost, you must account for the different IOPs limits across the different cloud virtual machine sizes. After all, if your application does not have the IOPs capacity to read/write commands, it’s not performing, which is why Turbonomic considers the total IOPS needs of all attached volumes for every compute scaling action. It includes percentile analytics and uses highly accurate per-disk IOPS data.

Reservation and Discount-Aware Scaling

It’s no secret that controlling cloud costs is top of mind for customers. It’s why so many turn to reserved instances or discounts from cloud providers for the promise of up to 70% savings. But while these offerings can help reduce costs, they also increase complexity. It’s not uncommon for customers to find that their purchasing commitments limit their cloud elasticity. It’s hard enough trying to figure out the right compute configurations, now you must figure out which RIs are best suited to those configurations?

With automated RI-aware scaling Turbonomic helps in two ways:

  1. Make the best use of the RIs you’ve already purchased, increasing the reservation-to-VM coverage. When Turbonomic will consider what is available in the current RI inventory and size to an available RI, resulting in optimal performance at the lowest cost. The same applies to idle workloads, even if already covered by RI, Turbonomic will precisely size them to a best compute offering that will provide better savings and performance. The new size could be a different RI, and the current RI might be used by a different VM that could benefit from it. Read the blog, Multicloud Reserved Instance Management Made Easy with Turbonomic, to learn more.
  2. Plan for the RIs You’ll Need. The same analytics operating in real-time, can model out RI purchase recommendations. You can run a plan to see not only what cloud VM/instances you need to purchase to support your cloud applications, but the recommended RIs you can purchase to safely minimize your costs.

Cloud Storage Optimization

Cloud storage is the # 1 global cloud service used by market size. The optimization of this resource is often overlooked, resulting in cloud bills that could have been avoided, as well as risks to application performance by way of throughput and IOPS starvation. The same powerful analytics that determine the right compute scaling actions, also do so for cloud storage. Turbonomic considers IOPS and throughput, to determine when you need to…

  • Scale between cloud tiers (AWS & Azure) for performance (IOPS, throughput) and cost *
  • Size up volumes for performance (IOPS, throughput) *

Note, the actions above are disruptive on Azure and non-disruptive on AWS due to the native capabilities of each cloud provider.

  • Modify capacity of IOPS & throughput limit for Azure Ultra, or IOPS limits for EBS io1 & io2.

Likewise, thanks to the non-disruptive nature of making these changes in Azure Ultra and Amazon EBS io1 & io2, Turbonomic can execute these actions without downtime.

Delete Unused Volumes - Automatically!

Not only can you increase volume sizes to improve performance with Turbonomic, but you can also partake in volume delete actions. This feature gives you the ability to identify and delete unattached cloud volumes at scale. Not only that, but these actions can also be fully automated and give you detailed accounts on the time the volume was unattached and the last attached virtual machine. How’s that for only paying for what you use?

PaaS Optimization

Scaling DBaaS for Performance and Cost

Today, companies run on data. Applications generate, collect, and analyze data so we can make smarter, more informed business decisions. So, it’s no surprise that cloud databases are one of the most highly adopted PaaS services.

Even though many of the administrative tasks are simplified by the cloud provider’s DBaaS, the most important task remains in the hands of Database Admins (DBAs): choosing the right database configuration so that the performance of the cloud applications that rely on this service will not suffer and you’re not paying for more than you need. Adding to the complexity is the fact that the “right” configuration changes as the service and its users do, so this is a choice that must always be open to reconsideration.

It’s an impossible task for a human being, requiring continuous evaluation of all the relevant performance metrics of each individual database server and the ability to choose the optimal configuration at any given time. In practice, DBAs usually choose to over-provision because application performance is paramount. But when you consider that cloud databases are generally 3-5x more expensive per instance than VMs, it’s no surprise that they are one of the biggest sources of cloud cost overruns. With Turbonomic you can get cloud database scaling done right and done continuously.

Azure SQL Database Scaling

Today, Turbonomic optimizes Azure SQL Databases, continuously evaluating real-time demand and generating actions to:

  • Scale Between Azure Database Tiers: Move between Azure SQL DB Tiers based on utilization (DTU*) with near-zero downtime.
  • Size Up/Down Database Volumes: Non-disruptively increase or decrease disk size (for used space)

AWS RDS Scaling—coming soon!

Support for AWS RDS scaling will be out later this year. There are two aspects to RDS scaling: Compute and storage scaling. Turbonomic considers both aspects when generating actions. It continuously analyzes vCPU, vMem, DB Cache Hit Rate, Storage Amount, and IOPS in order to generate specific scale up or scale down actions, which include: 

  • A change in the compute tier
  • A change in the storage tier
  • A change in the Storage Amount
  • A change in the Provisioned IOPS (for the io1 storage type)
  • A combination of these actions

Customers of Turbonomic that utilize optimization on PaaS resources ensure the applications that rely on these services always perform while also achieving up to 66% additional savings, which is on top of the savings they receive from IaaS optimization.

Kubernetes Optimization—Any Cloud, Any Flavor

Kubernetes is the container platform of choice for modern applications. It offers even more powerful levers to elastically scale to changing demand. Turbonomic supports any upstream version of Kubernetes, optimizing the platform on any cloud for performance as well as cost with the following actions:

  • Container Rightsizing: Scale container limits/requests up or down based on application demand--execute the actions in real-time or as part of the DevOps deployment process. Watch & learn more here.
  • Continuous Pod Moves: Automatically (and non-disruptively) move pods to avoid resource congestion and defragment the cluster. Watch & learn more here.
  • Intelligent Cluster Scaling: Turbonomic can see when pods have too little or too much cluster capacity, and will give the action spin up another node (or even suspend nodes).
  • Container Planning: Simulate how to optimize the existing environment to unlock capacity for growth so you can onboard more applications and lines-of-business. Watch & learn more here.

If You Want Cloud Elasticity, You Need to Automate Cloud Optimization

We’ve talked at length about the how Turbonomic will optimize cloud compute, cloud storage, cloud databases, as well as any upstream version of Kubernetes in the cloud—and now all this goodness is available to GovCloud and Azure Government Cloud customers. A critical component to optimization is operationalizing the actions Turbonomic generates. As much as possible, in order to maximize the benefits of cloud elasticity, you want the actions to be automated. This is why, in addition to offering the smartest cloud optimization, Turbonomic uniquely gives our customers ways to mobilize their organization to drive greater automation.

Application-Awareness—Bridge the Gap Between LOB and Cloud Ops

One of the biggest challenges Cloud teams face when they want to automate cloud optimization is the ability to demonstrate to Application and Product Owners that what they’re doing won’t hurt their applications and will instead ensure great customer experiences. Turbonomic can ingest application data from Instana, Dynatrace, AppDynamics, New Relic, Azure AppInsights, and more to correlate the response-time or transaction throughput of those mission-critical applications to the dynamic resourcing. Customers can see that as demand fluctuates, response-time stays low, while Turbonomic continuously optimizes cloud resources. For customers without APM, we offer a native solution—because every customer should understand how cloud optimization impacts the customer experience, as well as the bottom-line.

Percentile-Based Scaling

Performance degradation or cloud cost overruns are more likely to occur when scaling to peaks or averages—more often the latter, performance is paramount after all. It’s hard to get scaling right once, impossible to get it right continuously. Turbonomic uses percentile-based scaling to help customers achieve true cloud elasticity.

As part of Turbonomic’s analytics, we are looking at elasticity in terms of percentile values (vCPU, vMem, and IOPS) to make resourcing allocation decisions. Click this link to learn more about Proving Elasticity through Percentiles.

Customizable Observation Periods

Dynamic, fluctuating demand is true for just about every application. But how and when that demand fluctuates is unique. With Turbonomic, customers can configure observation periods to ensure that Turbonomic is analyzing data that accounts for their unique business cycles.

Turbonomic support for AWS GovCloud and Azure Government Cloud is currently available for all Turbonomic customers. If you are interested in seeing it in action, contact us for a demo!


Topics: AWS, Azure, Cloud

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