Presidio is always looking for the latest technologies, whether from established companies or disruptive newcomers, that can help address customer pain points. Take for instance a common challenge for organizations that have migrated to the cloud and now need to increase efficiency and minimize costs. While a range of cloud optimization approaches exist, many companies focus on only a single aspect of efficiency, and some approaches can be time-consuming and complex to implement.
Presidio’s longtime technology partner Intel addresses cost optimization and acceleration at an application layer with a new, unique and little-known software solution: Intel Workload Optimizer by Granulate. It optimizes applications without altering the application code and is purpose-built for servers and cloud compute instances based on Intel® Xeon® Scalable processors to accelerate select workloads in Linux environments. And, it allows customers to see which of their workloads may benefit most from optimization through a free 24-hour assessment.
This emerging solution is a game-changer in cloud optimization, offering a significant performance boost and cost savings.
Cloud migration methods and optimization challenges
Cloud computing offers many advantages – rapid deployment, flexibility, scalability, unlimited storage, and minimal capital expenditure, to name a few – so it’s little wonder modern businesses embrace cloud as an essential feature of a well-rounded IT strategy. But, cloud migration strategies and rationales can differ markedly. Typically, businesses move to the cloud in one of two ways: first, some choose to optimize certain applications for the cloud as a part of the migration process to take advantage of cloud native technologies, enhance functionality, and optimize consumption costs. However, it requires redeveloping the application, which can take months or even years to accomplish. This method is ultimately effective but can be costly, disruptive and time-consuming. And, it diverts developer resources away from important initiatives such as creating new products.
The faster, more common transition to the cloud involves a “lift-and-shift” operation, moving workloads to a public cloud provider such as Azure or AWS without changing the application code. This method is especially appealing to organizations that have reached peak capacity and must choose an alternative: upgrade hardware, acquire more data center space, or migrate some or all workloads to the cloud. On-prem data centers might require more time and resources than many organizations care to expend, so they choose lift-and-shift as the most expedient solution.
But often the focus is on simply getting there first, then figuring out how to optimize later through one or more of these approaches:
- Billing and instance analysis – determining how resources are being used and looking for opportunities to adjust instances for cost savings along with alternative cost plans or reserved instances. In addition, using tools to analyze instances, making recommendations whether to keep, adjust or remove each instance, can be a time-consuming task.
- Manual processes – Reviewing and modifying resources allocated to workloads as needed.
- Turning off VMs when not in use to save money.
While all of these methods are useful and billing analysis is critical, another level involves the analysis and optimization of resources used by the application workloads themselves. Intel has just simplified both cloud migration strategies with the Intel Workload Optimizer, delivering immediate and ongoing savings.
Why Intel Workload Optimizer is unique
What makes this autonomous optimization software solution stand out is its revolutionary approach: whereas traditional optimization solutions are directed at the instance selection level, Intel Workload Optimizer works at the transaction level, optimizing the actual application workload as it’s running. In other words, software acceleration without any code changes.
The Intel Workload Optimizer software utilizes machine learning to determine resource usage patterns and data flow, identifying data bottlenecks and resource contention within workloads, and then automatically adjusts kernel-level and runtime-level resource management decisions to accelerate data flow through an application by using patented algorithm models that find and fix bottleneck instances autonomously. In addition, it optimizes memory allocation, continuously adapting resources and runtime levels in real-time without human interaction, as well as resource scheduling and prioritization for the operating system.
Intel Workload Optimizer can be used in an on-prem data center or public cloud environment, optimizing resource management without the need for IT staff intervention. It’s ideal for many key Linux workloads, including proprietary applications such as Java and Python, big data apps such as Spark and Hadoop, and stream processing applications such as Kafka. It brings an important suite of new, resource-conserving optimization capabilities that are otherwise unmatched.
Advantages of real-time continuous optimization with Intel Workload Optimizer
As mentioned earlier, organizations have their choice of multiple strategies to achieve cloud migration, mitigate high consumption costs associated with lift-and-shift operations, and more. Intel Workload Optimizer software can deliver immediate benefits to complement them all.
- Realize maximum performance gains and cost savings when running on Linux-based servers or instances powered by Intel Xeon Scalable processors:
- Reduce costs up to 60% by handling compute workloads with 60% fewer cloud instances or servers.
- Up to 40% improved response time.
- Up to 5X increased throughput.
- Zero code changes required.
- No-cost, no-risk gProfiler assessment upfront: Presidio can help organizations run the open-source gProfiler on multiple instances or VMs over a 24-hour period to provide an accurate estimate of the improvements in performance and cost reduction. It identifies which applications are running, which workloads would benefit most from optimization, and what potential cost-savings can be realized per application. Previewing the size and scope of real-time benefits enables customers to pay for the solution only in areas that would see significant improvement and cost savings – something few other optimization solutions can match.
- Ease of deployment – With a few simple steps, Intel Workload Optimizer can be installed in minutes, including its dashboard to track immediate performance benefits and savings.
- Continuous, autonomous operation – Unlike other solutions, which require third-party tools and monitoring, Intel Workload Optimizer is entirely self-contained, running on its own in the background. IT staff can “set it and forget it” as they move on to focus on more strategic matters, such as product development and long-range planning.
Discover your performance and cost-saving advantages with Intel Workload Optimizer
For most organizations, cloud is an essential element in their IT strategy – but it requires optimization to achieve maximum cost-effectiveness, utilization and performance. Intel Workload Optimizer delivers a revolutionary new, easy and efficient way to achieve immediate optimization and significant cost savings.
To learn more about the benefits you can gain, contact Presidio to schedule an application optimization review and free assessment.