Financial Operations, or FinOps, is a framework for managing cloud costs and optimizing cloud spending. The goal of FinOps is to control the cost of cloud adoption without hampering developer creativity and freedom.  FinOps isn’t just about reducing costs but maximizing the value of all cloud expenditures.

The 2024 State of FinOps finds that reducing waste is the highest priority for FinOps practitioners indicating that businesses are looking at ways to reduce spending without reducing the value they are getting from cloud investments.

In another survey carried out by Everest Group, 82% of global organizations struggle with more than 10% of their cloud spending getting wasted. Out of these, 68% experience more than 20% wastage.

The FinOps Imperative  

FinOps empowers organizations to extract business value from the Cloud, wherein cost optimization is a core value proposition. By ensuring different stakeholders have ownership and accountability of the Cloud spend, FinOps ushers in a cultural change by facilitating close collaboration between different teams to achieve conflicting business objectives such as speed, cost, and quality of IT infrastructure.

By implementing FinOps best practices, organizations can effectively manage cost, and resource utilization and maximize ROI. Based on our experience with customers, here are some of the best practices for managing and reducing wasteful expenditure.

Reducing Cloud Waste

1.   Compute

Right Sizing: It is important to select the right Cloud resources and align it with business objectives to achieve the desired level of performance cost-effectively. For instance, compute instances are available with various combinations of CPU speed, CPU count, memory, networking, storage I/O, and GPUs. Right instance selection will require analysis of current workload, and future growth as well as analysis of resource utilization data available from Cloud observability tools.

Use Autoscaling and Load Balancers: Cloud empowers users with automated scaling capabilities, so users can programmatically configure auto-scale to add resources when there is heavy traffic and scale down when the traffic reduces. You can also use load balancers to manage sudden spikes in traffic to distribute calls and optimize performance. Resources can be optimized by observing auto-scaling. For example, if there is frequent scaling up due to high memory usage while CPU usage is very low, it will be more sensible to select a memory-optimized compute resource.

Turn off idle resources: Unlike traditional environments, the ability to shut down resources is one of the major benefits of Cloud. However, as organizations experience a Cloud sprawl with multiple accounts, they often end up paying for idle servers that are left on after a project is over. Tools enable to manage multiple Cloud usage via a central dashboard such as AWS Organization and Google Cloud’s Organization Resources.

Move to Serverless: Based on workload and utilization, one can reduce waste by moving to serverless architecture. Serverless does not require to rent servers and savings are a result of the pay-for-use model and reduced dependence on operations staff. Serverless is suited for non-production environment where latency is not very crucial and automatic pause can be configured to save costs.

2.   Storage

Right Sizing: Selecting the right storage option is imperative to extract the best value. For instance, the selection of hard drives or SSDs must be aligned with performance, latency, and throughput requirements. Different storage tiers such as hot, cool, cold, and archive must be selected based on data size and access pattern. Migration to newer SKUs may also result in saving –for example, EBS volume migration from gp2 to gp3.

Storage Lifecycle: Database backups, snapshots of storage, and logs require large storage capacity and form a significant proportion to cloud cost. Based on business requirements, data must be automatically moved from expensive tiers to cheaper ones and deleted when the retention period is complete.

3.   Unattached/Abandoned Resources

Often when host VMs are removed, resources like network interface cards, managed disks, EBS volumes get unattached but are not deleted. It is important to monitor, switch off/delete these resources to reduce wastage. Robust enforcement of resource provisioning using Infrastructure-as-code can prevent such occurrences while periodic checking for infrastructure anomalies can help detect abandoned resources.  

4.   Idle Resources

Apart from compute and storage, one must monitor other idle or under-utilized resources such as load balancers, containers, app services, and empty databases.

5.   Data Transfer

Ingress and egress charges are costs associated with data transfer across cloud regions, across zones, to and from the internet, and to and from on-premises networks. Generally, Cloud vendors do not charge for ingress, but charge for data egress. The cost of data egress often comes as a shock but designing a thoughtful architecture can significantly cut down data transfer cost by limiting the movement of data out of the region or from the Cloud environment. For example, if some of your on-premises applications are frequently accessing cloud data, it may be time to migrate these applications.

Partner with FinOps Experts for Cost Management

FinOps require unique skills and expertise—it entails deep understanding of different Cloud environment and services, market understanding, expertise in monitoring and management tools and deep experience to identify waste and optimize performance. Working with the right partner brings the insights, experiences and best practices garnered from different customers to reduce the learning curve and maximize the benefits of Cloud quickly and easily.   

If you want to know more about NewVision’s FinOps practice or want help with Cloud cost optimization strategies, write to us at contact@newvision-software.com.

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NewVision Software and Avo Automation are the Gold Sponsors for Eurostar 2024! Come meet us and discover the future of Digital Assurance. 

Say no to maintenance mayhem as we navigate through the frontiers of Digital Assurance together. With NewVision’s Test Automation as a Service and Avo Automation’s No Code Platform, we’re here to transform your testing process. Our partnership empowers you to focus on what matters – delivering flawless software.  

Join us in transforming the way you work and elevate your software quality to new heights. We’re thrilled to meet you at Eurostar 2024! 

Meet our Team at Eurostar 2024

Saksham Sarode

Practice Head - Digital Assurance and RPA, NewVision Software

Dev Mehta

VP – Marketing & Strategic Alliances, NewVision Software

Sanal Nair

CMO & Head of Global Partnership, Avo Automation

Santosh Chitriki

Director - Product Specialist, Avo Automation

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Learn about the partnership between NewVision and a tax & audit consulting firm to improve their IP Data Management Platform. NewVision adopted a three-phase strategy to overcome challenges like a complicated platform and slow testing cycles, leading to an 82% reduction in overall execution time. Find out how this collaboration enhanced the effectiveness and quality of audit services.

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Abstract

Discover how NewVision’s technical expertise transformed the application of US-based educational support services providers. Facing challenges with an legacy platform, the client sought a partner to modernize their system, enhance performance, and ensure data security. Through meticulous analysis and innovative solutions, we improved application performance by 25%, ensuring therapists and students have secure and seamless access, Explore the details of this successful collaboration and its impact on elevating educational therapy services. 

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GenAI will reshape how businesses approach customer care, back-office operations, administration, sales and marketing, HR, training, and everything else. The year will mark the shift from concept to creating solid impact in business operations. Research by the International Monetary Fund finds AI can impact about 60 percent of jobs in advanced economies and 40 percent of jobs in emerging economies.

Knowledge workers will experience profound benefits as GenAI’s research and summarization capabilities will drive productivity and change the way accomplishing tasks.

GenAI will improve customer care with personalized, efficient service

GenAI in customer care operations in 2024 will improve CX with personalized responses and recommendations. Agents will be better prepared and more responsive as GenAI can anticipate potential concerns and provide solutions. Natural Language Processing (NLP) capabilities will exponentially increase customer satisfaction as systems will understand and process user queries contextually to provide better care.

Back-Office Operations: Streamlining Efficiency Through Automation

GenAI’s integration will transform back-office operations by introducing extensive automation, allowing employees to focus on strategic aspects. Organizations will become more productive with GenAI’s summarization capability and collaborate better with automated scheduling and coordination. Its impact will encompass sales, marketing, HR automation, supply chain management, and project execution. It will also play a crucial role in enhancing cybersecurity defenses by simulating scenarios and address evolving threats.

GenAI to Majorly Impact Software Development

GenAI will bring disruptive changes in software development with a flurry of innovation and deliver dramatic improvements in generating code snippets, troubleshooting, and optimizing algorithms. Software engineers will be able to allocate more time to conceptualizing and refining solutions.

GitHub research finds that 88% of developers using Microsoft Copilot are more productive; 74% can focus on more satisfying work; and reduce the time for searching for information (77% of developers). This shift towards AI-driven automation will not only expedite project timelines but also enhance the adaptability and responsiveness of software development.

GenAI will drive digital product design with its ability to summarize and create new content from tons of existing data collapsing the time to research, identify new opportunities, and generate ideas.

AI models get smarter on synthetically generated data, eliminating the need to rely on only real-world data. The Gartner predicts by 2024, AI will generate 60 percent of synthetic to simulate reality, and future scenarios and derisk Artificial Intelligence.

GenAI and Data Analytics

GenAI’s advanced algorithms and machine learning capabilities will empower organizations with improved data accuracy and reliability, identify new data sources, and analyze vast datasets with unparalleled speed and accuracy.

Data cleansing capabilities will significantly improve with intelligent detection of patterns and anomalies in large datasets. GenAI will automatically categorize and tag data based on its attributes, reducing the efforts to organize data repositories. Data consistency will become easier with standardized data formats and structures across different sources and systems through automated data governance processes.

Innovating with Responsible GenAI

Even as we embrace the transformative potential of GenAI, it’s crucial to confront the inherent risks and challenges related to accuracy, cybersecurity threats, and regulatory compliance. It requires a proactive approach to address these issues with ethical development practices and regulatory frameworks, and collaborative efforts among industry stakeholders, policymakers, and developers to establish guidelines that are aligned with global values to usher in positive societal impacts while mitigating unintended consequences.

Buzz to Impact: GenAI heralds a New Era in Business Transformation

The widespread adoption of GenAI in 2024 will witness a shift from hype to tangible impact as businesses integrate GenAI into their operations to experience transformative changes in the way they think and work. With its advanced capabilities such as summarization, NLP, and synthetic data generation, GenAI is poised to revolutionize processes, enhance productivity, and elevate decision-making. From enhancing software development to transforming analytics, GenAI will catalyze a wave of innovation that empowers businesses to adapt and thrive in the digital age.

GenAI heralds a New Era in Business Transformation

Are you ready to embrace the future?

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Abstract

Discover how NewVision enhanced health data management for a leading US-based healthcare platform, reducing customer onboarding time by 60%. Our automation-first approach addressed manual inefficiencies and standardized testing processes, resulting in significant enhancements to data quality and processing speed. Learn more! 

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Abstract

The case study outlines NewVision’s successful implementation of ‘Automation as a Service’ to address testing challenges faced by a US-based digital sports platform. The client’s manual regression testing processes were impeding release cycles and leading to critical defects in production. NewVision swiftly proposed and executed a solution involving rapid assessment, automated test execution, and integration with DevOps pipelines. Learn about the success highlights, including substantial cycle time reductions, cost for automation tools, and early defect detection through CI-CD enabled automation test execution.

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