The prevailing theme for CTOs in 2024 is digital growth. Cloud native businesses are continuing to scale on the cloud, tapping into the rapidly growing market, as evidenced by the surge in end-user spending on public cloud services to an estimated $597.3 billion in 2023, up significantly from $491 billion in 2022.
Combine that with the accelerating trend of enterprises embracing digital transformation at a pace where Gartner predicts that by 2026, “75% of organizations will adopt a digital transformation model predicated on cloud as the fundamental underlying platform.” Then add to that the explosion of GenAI and dropping interest rates, and you’re looking at an unprecedented technology shift that will have an immediate impact on IT budgets.
However, this mass migration to the cloud does come at a cost. Whether due to rapid scaling, cloud migrations or legacy code, most businesses are running their applications on inefficient workloads, leading to wasted resources and costing billions of dollars. Nearly a third of all funds allocated to cloud and data technologies are either squandered or unaccounted for, underscoring the need for more prudent monitoring, management and optimization in cloud infrastructures.
Optimization Challenges for Enterprise Innovators
For CTOs to create new revenue-driving applications or take advantage of the GenAI revolution, they need the budget to do so. That’s where optimization comes in. By optimizing their compute infrastructure, environments and applications, IT leaders can reduce costs and reallocate those budgets to new features, products and services. However, there are a number of challenges that often appear on the path to optimization.
Stuck on the Periphery
Current cloud optimization solutions can only take your cost reduction so far. They are primarily composed of basic tools from CSPs and APMs that focus on visibility. Intel Tiber App-Level Optimization recently conducted a survey, where we found that the most common tools in an optimization tech stack remain in these categories, with 38% reporting usage of log management and analysis tools and 34% for APM/monitoring/observability, while rightsizing, runtime, FinOps and code profilers all reported fewer than 27%. This leaves development teams to their own devices when it comes to actual performance improvements.
Silos and Separations
Especially with enterprises, it’s difficult to get IT departments on the same page when it comes to optimization. In addition to the challenge of creating a culture that prioritizes cost optimization, there’s the struggle to get all of the development teams to share solutions, best practices and strategies. Even if there is excellent interdepartmental communication, most optimization solutions are tech-specific, only impacting a single platform, runtime or infrastructure.
Manual Efforts Leading to Delays
Many of the best practices for optimization demand manual tuning and reconfiguration, requiring developers to dive into legacy code and make the adjustments themselves. Even SaaS solutions typically offer recommendations, which still need the user to activate and apply. Ultimately, the cost reductions will come at the expense of new innovations, because developers that are improving old workloads can’t be creating new products and features.
Missing a Moving Target
Many companies can benefit greatly from methods like PGO (Profile Guided Optimization), rightsizing recommendations, manual code adjustments and cloud governance. However, while these techniques are effective, they are hard to scale with a microservice architecture or large-scale data streaming and processing. Optimizing with these inconsistent and time-consuming practices does not account for the dynamic nature of cloud environments.
The Autonomous Approach to Optimization
With autonomous, continuous application performance optimization, IT leaders teams can take their cost efficiency to the next level and reallocate those savings to new services and innovations. For businesses that are mature in their cloud optimization journey, Intel Tiber App-Level Optimization offers unparalleled results for additional cost reductions on top of previous initiatives.
Intel Tiber App-Level Optimization is able to achieve additional optimization, on top of previous initiatives, by optimizing at the core of the application, on the runtime level. While other cloud solutions optimize on the periphery of your app but stay clear of improving performance within the app itself, Intel Tiber App-Level Optimization autonomously optimizes the runtime of the application for performance improvements, leading to more efficient infrastructure, reduced CPU utilization, and lower compute costs.
CTOs don’t need to worry about their teams being siloed, because Intel Tiber App-Level Optimization is a holistic solution, with seamless integration across the cloud stack. Now multiple teams working on separate products can share the same solution, whether they’re developing on Kubernetes, backend applications, or Big Data environments, including Databricks and Cloudera.
Intel Tiber App-Level Optimization operates autonomously, requires no code changes, and integrates seamlessly with new workloads. According to our survey, 59.6% of decision makers consider optimization tools that are autonomous in nature to be very important to extremely important. With automation, developers and data engineers are unburdened from manual retuning, configuration and application of recommendations. When no administrative or technical overhead is needed, R&D teams can focus on creating new revenue pipelines.
Continuous optimization allows real-time improvements tailored to dynamic compute environments, accounting for surges in usage, feature updates, and even lift and shift migrations. Intel Tiber App-Level Optimization allows developers to hit that moving target repeatedly and at scale, so if it’s activated in Q1, those improvements will accumulate over the year to reach 2024 KPIs.
“Intel is one of the most innovative technology companies in the world, and enables our customers to use Intel Tiber App-Level Optimization the first-of-its-kind real-time, autonomous software optimization to create efficiencies and to enhance customer experiences.”
Juan Orlandini
Chief Architect and Distinguished Engineer
Insight
Helping Your Customers Grow With Confidence
Whether you are an ISV, MSP, VAR or GSI, offering autonomous optimization solutions to your clients can significantly enhance their confidence in managing and growing their cloud infrastructure. These solutions come with the backing of Intel’s robust security, ensuring that your clients’ data and operations are protected to the highest standards. This assurance of security is not just a feature; it’s a foundational aspect that reinforces trust and reliability in the services you provide.
Introducing autonomous optimization to your clients opens up new avenues for budget reallocation. The savings realized from improved efficiency can be redirected towards developing new services, product features, and applications. This reinvestment not only drives innovation within your clients’ organizations but also demonstrates the tangible value of the solutions you’re providing. As their trusted advisor, you’re not just selling a service; you’re enabling growth and expansion.
Lastly, by improving application performance through autonomous optimization, you are directly contributing to the success of your clients. Better performance leads to enhanced user experiences, operational efficiency, and overall business outcomes. As you help them succeed, you establish yourself as a key player in their journey, fostering long-term loyalty and trust. This approach positions you not just as a vendor, but as a strategic partner integral to their business growth.