Cloud platforms offer far more flexibility than many organizations fully leverage. From automation to cost control to fine-grained security settings, tools for customization are built in—yet commonly underutilized. Whether due to lack of awareness, competing priorities or the sheer complexity of cloud ecosystems, businesses frequently leave valuable optimization opportunities on the table.
Customizing its own cloud platform can give a business a strategic edge. Below, 19 members of Forbes Technology Council share impactful yet often-overlooked ways for businesses to tailor their cloud environments to their specific needs for stronger performance, greater efficiency and more strategic value.
1. Leverage MSP Expertise For Industry-Specific Solutions
Managed service providers can provide tailored, industry-specific solutions for cloud platforms to help businesses achieve organizational goals and show the value each prioritized decision has on digital transformation, ROI and intended outcome. MSPs are integral to organizational success when it comes to leveraging cloud-based solutions securely and safely without compromising on innovation. – Jonathan Lerner, InterVision
2. Harness The Power Of A Coherent Enterprise Data Fabric
True customization stems from a coherent enterprise data fabric, underpinning all applications, AI ecosystems and customer experiences. Although companies access baseline AI models and generic apps, their edge lies in leveraging unique data in concert with macro data. This data-driven approach enables bespoke solutions, which differentiate businesses to deliver unparalleled customer value. – Daniel Kearney, Firmus Technologies
3. Implement Latency-Aware Workload Orchestration
A hidden cloud optimization is latency-aware workload orchestration—dynamically shifting workloads between regions based on latency, cost and regulations. This boosts speed, lowers costs and mitigates risks. An AI trading platform can move closer to exchanges for faster execution, while gaming servers reduce lag. Despite its advantages, most businesses overlook this adaptive strategy. – Gaurav Mehta, JPMorgan Chase
4. Adopt AI-Driven Dynamic Scaling And Predictive Workload Management
Most businesses overlook AI-driven dynamic scaling and predictive workload management in cloud platforms. By using advanced machine learning models to forecast resource needs, companies can auto-optimize computing, storing and using the network, slashing costs while improving performance. Why pay for idle resources when AI can actually and precisely fine-tune efficiency in real time? – Raghu Para, Ford Motor Company
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5. Enforce TTL-Based Infrastructure Policies
Implement a lease-based (TTL-based) infrastructure provisioning policy to gate R&D spend without slowing velocity. For Day 2 optimization, track expired leases to quantify cost avoidance and measure lease extensions to fine-tune engineering toil. This approach strengthens FinOps and platform engineering collaboration for impactful, cost-efficient outcomes. – Kyle Campos, CloudBolt
6. Switch To Serverless Computing Architectures
Serverless computing architecture is the most underutilized way to customize cloud platforms. Many businesses stick to the server-based models and miss out on the flexibility and efficiency. Serverless solutions allow for cost efficiency, enable scaling on demand, allow developers to focus on delivering features without having to worry about managing infrastructure, and reduce operational overhead. – Ashish Gupta, Capital One
7. Utilize Event-Driven Automation
Many businesses underutilize event-driven automation in cloud environments, which allows cloud resources to dynamically respond to real-time conditions like usage spikes, security threats or cost inefficiencies. By leveraging event-driven architectures, companies can customize their cloud platforms to be more intelligent, cost-efficient and secure. – Sanjay Gidwani, Copado
8. Unify Data, Cloud And AI Strategies
In this day and time, businesses need to combine their data, cloud and AI strategies, as they are deeply interlinked and can make or break success. The data storage, volume growth, data platform and governance strategy, as well as the enterprise AI tooling and AI platform, observability and monitoring—all impact the type of cloud and platform requirements. A unified strategy leads to seamlessly bringing all the pieces together. – Simana Paul, SumUp
9. Track Cloud Vendor Roadmaps To Maximize Adoption
One big miss for businesses is not looking at the roadmaps and releases of cloud vendors and not using them. For software as a service products, it is important to look at the releases, plan to add them to the sprint pipeline and have users adopt them. With zero upgrade costs, businesses need to leverage new release features and have reports on adoption of these releases as a core metric. – Buyan Thyagarajan, Eigen X
10. Apply Predictive Auto-Scaling To Reduce Downtime And Costs
Using AI-driven auto-scaling policies is an overlooked way to customize cloud platforms. Instead of relying on static scaling, businesses can leverage machine learning models to predict workloads and dynamically allocate resources. This reduces costs, enhances performance and prevents downtime, making cloud operations more efficient, adaptive and cost-effective. – Praveen Tripathi, HCLTech
11. Deploy AI-Powered Customer Sentiment Analysis
Deploy AI-powered sentiment analysis on customer interactions across communication channels. By systematically analyzing customer emails, chat transcripts and feedback, businesses can uncover nuanced insights about customer preferences, pain points and emerging trends. This data-driven approach transforms raw customer communication into actionable strategic intelligence. – Todd Fisher, CallTrackingMetrics
12. Customize Kubernetes Health Checks And Alerting Rules
Many businesses overlook customizing Kubernetes health checks and alerting rules to match their specific application needs. Tailoring these settings ensures faster detection of performance issues, reduces noise from irrelevant alerts and enables proactive troubleshooting—improving reliability and operational efficiency. – Ben Ofiri, Komodor
13. Bridge Gaps With Custom Serverless Functions
Many businesses overlook the customization of cloud platforms through custom functions that can bridge gaps between cloud services, third-party tools, internal systems and digital banking solutions. Many companies rely on built-in automation features but fail to fully leverage serverless functions to create highly tailored workflows, event-driven processes and cost-efficient solutions. – Deep Varma, Alkami
14. Migrate DFIR Operations To The Cloud
Many businesses overlook the benefits of moving digital forensics and incident response operations to the cloud. Traditional on-premises infrastructure often faces storage and computing limitations, slowing investigations. Cloud-based DFIR enables quick resource allocation, streamlined data sharing and automated scaling, contributing to faster resolution of corporate incidents. – Yuri Gubanov, Belkasoft
15. Evaluate Resource Usage To Right-Size Workloads
Organizations may overlook the opportunity for cost optimizations in the cloud. A typical plan for migrating to the cloud might be a simple “lift and shift.” However, after evaluating actual resource usage, there is usually an opportunity to right-size workloads. This can even include a hybrid approach where only certain workloads migrate; it doesn’t have to be all-or-none to make an impact. – Mike Lefebvre, SEI
16. Enable Multicloud Networking To Improve Resilience
Businesses often stick to one provider, but multicloud networking allows them to distribute workloads across AWS, Azure and Google Cloud for better resilience. If there’s an outage with one of these providers, multicloud networking can quickly shift the workload onto another and avoid outages. – Lisa Loud, Secret Network Foundation
17. Utilize Real-Time Processing For Smarter AI Integration
Many businesses overlook real-time data processing capabilities as a solution to cloud-platform integration. Static data systems made it impossible for AI agents to analyze data from the source, and these newer systems, coupled with in-memory storage formats like Apache Arrow, provide analytical capabilities that enable AI systems to process all available data. – Guillaume Aymé, Lenses.io
18. Reinforce Brand Identity With Custom Configurations
If there is an ability within a cloud platform to configure your brand and identity—from logo to color scheme to avatars—do it! This creates continuity and reinforcement around your brand. – Shaz Khan, Vroozi
19. Train Custom ML Models For A Competitive Edge
Numerous companies fail to utilize custom machine learning models hosted on cloud platforms. Tailored models automate unique processes that provide specific insights and enhance both decision-making and operational efficiency. Customization generates better results and provides businesses with a competitive edge. – Roshan Mahant, LaunchIT Corp.
