• Fraudulent transactions across Europe are an estimated €1.8 billion per annum.
• The number of bank frauds in India was up 166% in FY24.
• In the United States 26% of adults surveyed said they had personally experienced bank/credit fraud.

The explosion of online banking, neobanks, fintechs and financial applications has also made it easier for scammers to strike, making it vital to spot anomalies in transactions and strange behaviour to catch fraud early. In this scenario, Artificial intelligence (AI), Generative AI & Machine Learning (ML) are new sentinels for safe and secure business operations and technology, helping banks, financial services, and insurance (BFSI) companies stay one step ahead of fraudsters.

According to one survey, 62% of UK and US based large/mid-sized businesses intend to deploy AI-based solutions to combat the issue.

Power of AI in fraud detection: Traditional security options vs AI-driven solutions

• AI can “learn” from past fraud cases, helping ML algorithms more accurate with time. An AI model flags suspicious data/anomalies in transactional and behavioural data.
• As self-learning models, AI gets smarter over time, reducing the likelihood of repetitive errors and minimizing false positives.
• AI can not only alert the humans overseeing the systems to potential fraud, but also take action by blocking transactions or removing suspicious attached files.

AI and ML can give banks and financial companies a huge advantage with a “two-steps ahead” approach to security and risk management. For instance, for a large multinational bank, fraud detection traditionally involved wading through mountains of data, reading endless reports, and manually checking every suspicious transaction. It was a slow and painful process, often leading to delays in spotting fraud. Sometimes, customers would even have to report the problem themselves, which could mean losing a lot of money before the bank could fix the issue.

The power of AI-backed fraud prevention means that the same bank can now process copious volumes of data in real time, monitor all activity including transactions as they happen. When a possible high risk event begins to occur, it escalates this to the top of the list for review on priority. The bank can now intervene as the fraud is occurring and prevent it from happening or reduce further potential loss. Overall, this can mean better customer satisfaction with fewer losses incurred.

Using AI in fraud detection means fast detection – since AI algorithms act instantly to freeze/block a transaction/account, and offers increased accuracy over traditional methods – since AI applies dynamic rule setting, learning from itself, rather than just predefined rules. Over time, this results in cost optimization as the long-term cost of prevention vs reaction is lower.

Business impact of AI for fraud prevention

AI can be applied in multiple ways to help mitigate the risk of fraud:

• AI-driven analytics platforms can integrate diverse data sources (financial data, market data, customer data) to provide a comprehensive view of risk exposure.
• GenAI for real-time fraud detection identifies suspicious patterns of behaviour through comprehensive data analysis; this helps block and prevent potentially fraudulent activity. 
• AI-powered alert prioritization is used to classify alerts by risk level, ensuring that higher risk cases get assigned for review and intervention first, which means speedy intervention and protection for the business.
• Predictive analytics help determine future risk based on constantly updated data. AI & ML can minimize false positives, making for a seamless customer experience while ensuring security.
• Data-driven operations backed by AI/ML and robust analytics help ensure regulatory compliance and support KYC verification.
• Automation along with a strong GenAI/AI/ML powered business analytics and data engine supports scalability and boosts operational efficiency.

Use Cases for BFSI | How AI helps in fraud prevention

AI-based use cases for fraud prevention in the banking and financial services sectors can take on various forms:

1. Real-Time Anomaly Detection: Systems using GenAI can detect fraud early by learning normal behaviour and spotting unusual activity or deviations that might indicate account takeovers from identity theft or phishing. This improves speed – something that’s crucial when dealing with fraud, where every minute counts.

GenAI-powered behavioural analysis can monitor app usage, banking transactions, payments, or any other financial transaction across channels/touchpoints in real time and flag off potential threats like unusual spending pattern/unauthorized account access, blocking them and preventing fraud.

AI-backed fraud detection enables faster action, better communication and quick resolution. Traditionally, we have relied on programming languages to identify any aberrations. With ML algorithms, statistical analyses and AI, we can implement a framework that easily identifies the current unusual behaviour as well as new behaviour in the future without too many changes in the program and environment. This translates to cost savings, cuts developer time and reduces time to market/time to go live.
Dipti Pasupalak, Data & Analytics Architect, Cloud Kinetics

2. Automated Fraud Reporting and Reduced Manual Reviews: AI and ML allows for automated fraud reporting and reduces the need for manual reviews. GenAI generates suspicious activity reports (SARs) incorporating millions of data points. With a lower burden on analysts, finance and IT teams, their time can be freed up to be used to propel business growth, enhance solutions and drive innovation.

Automation also makes the process of identifying investment fraud, payment fraud, or card fraud faster, more efficient and often more accurate, with lower instances of false positives.

3. Enhanced Authentication with AI: Secure authentication powered by AI can be improved with GenAI and reduce risk in case of forgery or identity theft.

GenAI can help refine algorithms used for recognition and verification, thereby making traditional biometric verification methods more effective and limiting access to only legitimate users. This cuts the risk of unauthorized access/ account takeover fraud.

Use Case | Seamless User onboarding & authentication with AI/ML-powered solutions from AWS: In the online registration process for an account, using ML-powered facial biometrics – with pre-trained facial recognition and embedded analysis capabilities, ID verification, user onboarding and authentication – can be done securely with no need for prior ML expertise in-house.

4. Detecting Variations in Usage Patterns: AI is able to analyse metadata to detect variations from the norm that might be missed in manual reviews by the human eye. As fraudsters begin to use sophisticated methods including AI to commit fraud, the use of AI as a defense against things like deepfakes will be critical.

Take for example a scenario where a customer has been duped into sharing their net banking details with a fraudster. Normally transactions after this would not be flagged since the data compromise has not occurred on the bank’s system. But AI-based risk monitoring software will spot any unusual pattern in the transactions or amounts not in line with their normal transactions, or even things like screen resolution, currency or language used and flag it for manual tele-verification in real time, more swiftly than older methods.

Use Case | Fraud prevention with Snowflake’s scalable multi-cluster shared data architecture and advanced data governance: This can help protect merchants from fraud and risk. Snowflake-powered fraud prevention models are able to identify bad actors, detect attack vectors and block account takeover attempts.

5. Offline Fraud Prevention: AI-powered video analytics can flag off suspicious behaviour at ATMs and branches that may be linked to ATM skimming, usage of stolen cards or cheque forgery.

Use Case | Geospatial analytics and AI for fraud detection from Databricks: Geospatial data, machine learning and a lakehouse architecture from Databricks help FSI clients better understand customer spending behaviours and spot abnormal credit card transaction patterns in real time. This enhances the fraud prevention and detection capabilities of the organization, which in turn reduces losses and helps cement customer trust.

Building an AI-backed fraud detection strategy

Banks and financial institutions aren’t the only ones with an eye on AI. According to Deloitte’s Center for Financial Services, fraud losses in the United States could hit US$40 billion by 2027, on the back of GenAI.

With fraudsters already using AI, industry needs to quickly adopt an AI-backed defense as well. Here’s your roadmap:

• Create a cross-functional fraud management team: Drawn from IT, operations, compliance, legal, data sciences
• Build a multi-layered fraud detection strategy: Use AI in tandem with traditional anomaly detection systems, encryption, multi-factor authentication etc.
• Implement the right environment and tools: These must be compatible with existing infrastructure and scalable and effective. Banks must modernize their infrastructure to effectively leverage AI for fraud prevention.

By migrating to the cloud or adopting a hybrid approach and establishing a robust data platform, banks can ensure timely access to high-quality data. This real-time data empowers AI, ML, and generative AI systems to analyze patterns, identify potential fraud, and enable rapid intervention.

• Follow transparent & ethical data usage: Adhere to customer privacy norms and practise ethical data usage
• Monitor & update regularly: Retrain with new data to stay effective against new types of fraud
• Run simulations: Run controlled realistic fraud attack simulations to check robustness of the systems in place and keep ahead of advanced fraud attacks

Building an effective AI-backed fraud detection strategy into your organization requires an overall commitment to a security-conscious culture. In addition to the AI, ensure every “human firewall” is well armed to respond to fraudulent activity with regular training and a culture that encourages a security-first approach. Dipti Pasupalak, Data & Analytics Architect, Cloud Kinetics

The post How Banks & Financial Services Can Fight Fraud With AI-Driven Analytics appeared first on Cloud Kinetics.

Located in the Futura Tech Park at the Information Technology Corridor of Sholinganallur, the state-of-the-art facility was inaugurated by members of the leadership team including Haji Munshi, Group Chief Executive Officer, and Joe Francis, Managing Director – India. Several premier technology partners and customers of the company were also in attendance along with the Cloud Kinetics team. 

The opening of the new office signals a larger commitment to expanding the company’s presence in the subcontinent as a global delivery centre.

Explaining the significance of the move, country MD Joe Francis said, “India has emerged as a strong hub for Cloud Kinetics’ Consulting and Managed Services in the areas of Cloud, Applications and Data. The opening of the Chennai office will help us strengthen our position in the region even as we extend services to customers in Asia, Australia, the United States and beyond.” 

Cloud Kinetics is already a well-established name in the APAC region where it has won multiple awards for innovation and excellence in the field. With its growing presence in Asia, ANZ and the United States, the company serves technology needs across industries, enabling businesses transformation with the help of technology and digital overhauls. 

Recognizing the emergence of India as a power hub, Cloud Kinetics is focussing on growth in the region. This emerged as a theme for the launch centred around “Growth, Innovation, and Opportunity”, with the leadership outlining the potential for tapping the cloud and digital solutions to drive business growth and innovation.

As CEO Haji Munshi said, “This new office kicks off the next phase of our journey in the country. We will continue to follow the Cloud Kinetics ethos of working closely to help businesses thrive in the cloud, nurturing innovation with agile, scalable technology solutions.”

The company is taking a long-term view on presence in the region and ensuring it gives back as an active member of the local community. As part of Cloud Kinetics commitment to the environment, a tree planting exercise was also conducted on the day as a CSR effort. With the help of Praise Foundation, Eco Club students, and the Candles Volunteers, 51 fruit-bearing tree saplings were planted at Thiruthangal Nadar College, Chennai. Cloud Kinetics dedicated these trees to customers and partners who have been allies and have contributed to the company’s regional growth.

The post Cloud Kinetics Expands Regional Presence in India With A New Office in Chennai’s IT Corridor appeared first on Cloud Kinetics.

Tại đây, các nhà lãnh đạo ngành đã chia sẻ những hiểu biết sâu sắc về cách tận dụng các công nghệ mới nhất để đạt được các lợi thế cạnh tranh trong ngành của bạn dựa trên các dữ liệu mới được nghiên cứu gần đây.

Các diễn giả:

Dr. Philip Cao

Cyber Strategist & Evangelist
Co-founder & Advisor, Cloud Security Alliance - Vietnam Chapter

TS Philip Hùng Cao (còn gọi là #DrTekFarmer), EDBA, MSCS, ZTX-I, CCISO, CISM, CMSC, CCSP, CCSK, CASP, GICSP là một nhà chiến lược, cố vấn, cộng tác viên, nhà giáo dục và người truyền cảm hứng. Ông có 23 năm kinh nghiệm trong ngành CNTT/ANTT/ATTT trong các lĩnh vực và vị trí khác nhau, và hiện đang là một Người truyền bá tích cực về ANTT/ATTT và Zero Trust ở Việt Nam cũng như khu vực Đông Nam Á, Châu Á - Thái Bình Dương, Nhật Bản và toàn cầu.

Huong Mai Nguyen

Account Manager
Cloud Kinetics, Vietnam

với hơn 8 năm kinh nghiệm bán hàng trong lĩnh vực viễn thông và công nghệ. Lĩnh vực chuyên môn của tôi là điện toán đám mây, đặc biệt là public cloud. Tôi đã hỗ trợ các dự án "move to cloud" cho nhiều khách hàng, đặc biệt là các ngân hàng và các công ty digital native.

Ruby Duong

Customer Engineer
Google Cloud

Ruby Duong là Kỹ sư Khách hàng tại Google Cloud ở Singapore. Cô làm việc với các startup và doanh nghiệp vừa và nhỏ trong khu vực châu Á Thái Bình Dương về quá trình chuyển đổi công nghệ điện toán đám mây, chuyên về các công nghệ quản lý và phân tích dữ liệu, máy học và trí tuệ nhân tạo.

Sunny Nguyen

Territory Manager SMB
Google Cloud

Sunny là người quản lý khách hàng SMB mảng GCP thị trường Việt Nam tại Google Cloud ở Singapore. Sunny chuyên giúp khách hàng giải quyết các bài toán kinh doanh như tối ưu hóa chi phí, số hóa/hiện đại hóa, giải quyết các vấn đề từ nâng cao trải nghiệm khách hàng/ tự động hóa vận hành nội bộ cho đến giảm rủi ro/tăng ROI/tăng bảo mật bằng cách tận dụng danh mục công nghệ tiên tiến và hệ sinh thái đối tác trong ngoài nước và nguồn kỹ sư công nghệ của GCP.

Các luận điểm chính trong sự kiện

Người tham gia đã được trải nghiệm các mà Data Analytics & AI đang trở thành xu hướng và thay đổi các doanh nghiệp trên toàn cầu.

• Mở khóa giá trị doanh nghiệp: bạn đã nhận được các thông tin chuyên sâu về cách tận dụng dữ liệu và AI để đạt được lợi thế chiến lược, đồng thời đảm bảo tính bảo mật mạnh mẽ.
• Các giải quyết các nỗi lo về bảo mật: Tìm hiểu về các rủi ro bảo mật hàng đầu liên quan đến các giải pháp Data Analytics & AI trên nền tảng Cloud.
• Đo lường mức độ thành công: Khám phá các chiến lược để đo lường lợi tức đầu tư (ROI) của dữ liệu và các sáng kiến ​​bảo mật của bạn
• Đảm bảo tính tuân thủ: Hiểu được các phương pháp hay nhất về việc tuân thủ các quy định về quyền riêng tư dữ liệu khi sử dụng các công cụ Cloud.
• Xây dựng Văn hóa về An toàn bảo mật: có được những lời khuyên thiết thực về việc tạo ra một môi trường có ý thức cao về bảo mật trong tổ chức của bạn.

The post Securing Tomorrow: Master Data Analytics, AI & Security With Google Cloud appeared first on Cloud Kinetics.

We gathered industry professionals on 24 May at Shangri La Singapore for an exclusive roundtable discussion on how enterprises in the Manufacturing, Transport and Logistics sectors can unlock real-time visibility, minimize disruptions and streamline operations with a cloud-smart, AI-driven supply chain strategy.

Topics covered:

• Getting real-time visibility into your operations: Make smarter decisions by gaining insights into operations, including proactive monitoring and management of supply chain disruptions
• Eliminating capacity guesswork: Optimize and integrate ERP systems to enhance inventory planning and forecasting accuracy
• Unlocking innovation & agility: Streamline and automate logistics workflows for greater efficiency, speed, transparency
• Harnessing AI-powered insights: Integrate disparate data from various sources and utilize AI/ML to identify areas for process improvement in real-time

With Cloud Kinetics, you get the insights and strategies you need from our industry experts to become smarter, faster, leaner, and more responsive in your daily operations. Contact our team of cloud experts if you have any questions on these strategies or need a no-obligation discussion for your organization.

The post CXO Roundtable Dinner: Modernize Your IT Stack With <br>Cloud & AI Powered Strategies appeared first on Cloud Kinetics.

For traditional banks this doubles up as an opportunity and an urgent reminder. To compete effectively with digital banks and fintechs and thrive in this evolving financial ecosystem, senior IT/business decision-makers at established banks must prioritize modernizing legacy systems and embracing the Open Banking paradigm.

Advancing customer experience with open banking

Open banking ushers in a new era of convenience and financial control. It fosters financial inclusion, more personalized services and convenience for customers. Open banking also increases the competitiveness of banks by enabling them to provide a diverse suite of financial products & services at reduced operational costs.

Some open banking use cases include:

• Instant payments and fund transfers directly from third-party applications such as PayNow in Singapore and Unified Payments Interface (UPI) in India.
• Account aggregation features for customers to access and manage savings & deposit accounts, loans, credit cards and investments from a single application.

From monolith to microservices: The application modernization journey to open banking

For most banks, successful adoption of open-banking standards will mean substantial re-architecting of their current application estate and IT infrastructure, and accelerated integration with third parties to on-board new products & services from partners. This is a critical success factor in the open banking ecosystem.

To seamlessly integrate with various third parties through APIs, banks will require an enterprise-wide adoption of microservices and API-based architecture to consume data from core banking and other legacy backend systems. This will support agile delivery, provide scalability and flexibility with multi-cloud / hybrid cloud deployments.

A microservices-based application modernization approach will eventually enable banks to drive growth through new business models, collaborate with partners to quickly on-board new product offerings and enhance customer experience.

1. Building the optimal microservices-based architecture for open banking

The application modernization journey and timelines will depend on the product roadmap, technology readiness and current IT architecture of the bank.

Banks with monolithic applications, legacy core banking systems and legacy integration platforms will need to adopt a phased approach to minimize business risks and potential disruptions. A phased approach will also allow banks to on-board partners and build marketplace offerings like digital wallets, lending and insurance services for customers in an incremental manner.

The figure here below illustrates an indicative microservices-based reference architecture for a bank along with key components such as API gateway, service orchestrator and microservices-based core services.

• The first step in the application modernization journey would involve building a service orchestration layer (Figure 1, point# 2) to efficiently manage commonly used cross-cutting concerns and non-functional requirements such as security, configurations, log aggregation, distributed tracing, service discovery and circuit breaker.
• All the above services can be developed as common components designed to ensure the core business logic is separated from cross-cutting non-functional concerns.
• The service orchestration layer along with an API gateway will interface with the core banking platform and expose APIs to both internal and external parties for accelerated integration.
• In subsequent phases, banks can start decomposing their monolithic core applications using various Microservices design patterns such as Strangler and Sidecar aligned to product domains such as account services, payment services and underwriting services (Figure 1: point# 3). For example, account services would include features such as account opening, customer onboarding and account updates.

2. Microservices-based application modernization: Challenges & way forward

Transitioning from a monolith to microservices can be a complex but rewarding undertaking for banks. Often, banks are concerned about technical complexity, security challenges and change management.

The right application enablement partner will equip you with a comprehensive roadmap, from initial strategy and architecture design to seamless implementation and ongoing support, ensuring your microservices journey is smooth and efficient.

3. Modernizing banking applications with Cloud Kinetics

Cloud Kinetics helps banking & financial services customers to amplify the value of cloud with our Application Modernization approach, driving business agility & flexibility.

Our modernization competencies focus on Application Portfolio Assessment, Microservices Architecture, Serverless, API Integration, Security & Compliance combined with DevOps & Continuous Delivery Approach. Our strategic partnerships with industry leaders like AWS, Azure, GCP (hyperscalers), Kong (API gateway), CAST (portfolio assessment) enable us to deliver a seamless solution for our customers.

Customer impact story: App modernization, cloud-native design & a one-stop digital marketplace for a leading fintech

Our customer is a leading fintech company that facilitates financing through credit guarantee schemes for micro, small & medium enterprises (MSMEs). They felt their current platform was lacking the comprehensiveness, accessibility and user-friendly experience that MSMEs now demand in a digital-first world.

With Cloud Kinetics, the customer embarked on a transformation journey to modernize their platform and provide MSMEs with a one-stop digital marketplace, with opportunities for cross- and up-selling products and services.

Cloud Kinetics developed the digital lending platform on AWS, using microservices architecture to create a cloud-native lending platform that was secure, scalable and adaptable to evolving needs. Cloud Kinetics also built a digital marketplace for the customer that expanded beyond loans, offering MSMEs financial products like working capital solutions, insurance options, and seamless integration with credit guarantee schemes. The interface enabled the bank to offer MSMEs a more intuitive experience and better manage their financial health.

The post Unlocking Open Banking’s Potential: Microservices As The Key To App Modernization appeared first on Cloud Kinetics.

Based on inputs from Cloud Kinetics FinOps team  

Operating in the cloud promises a boost to agility, innovation, time to market and more. But if you don’t have the centralized coordination and collaborative approach that FinOps brings, you could be wasting millions in cloud spends every year!

For many organizations, investments in cloud spend run into the billions every year as they tap into the agility, reliability, and flexibility that the cloud offers. With the sudden increase in cloud investment has come the problem of excessive and wasteful spending. If your organization is on the verge of implementing FinOps but you’re unsure of what it entails or have cloud spending related concerns, answers to these top 5 most common questions on cloud costs should clear things up.

Over 30% of cloud spend is reported to be wasted every year. This number is projected to hit $30 billion by the end of the year.

Implementing FinOps – cloud financial management practices designed to maximize business value – is the most effective way for organizations to gain better control on cloud spend, avoid waste and keep projects running efficiently without compromising on end results. Here are some of the most common questions and concerns our customers, stakeholders and decision-makers have before embarking on a FinOps journey.

Our in-house experts at Cloud Kinetics, led by FinOps Managed Services Director Aubrey Bent, provide insight and pointers based on their extensive experience working with a global client base.

1. What is the best way to kickstart FinOps practices in my organization?

When it comes to FinOps, one step at a time works better than a big-bang approach. Implement the approach in small incremental steps, allowing the organization to fully understand and slowly settle into the new approach. Here’s a roadmap:

• Get senior stakeholder management support and sponsorship.
  Identify pain points like cloud costs, cost overruns or lack of cost visibility and define the goals right from the team composition to the operating model and milestones for the first phase. For instance, you may need to make decisions on things like whether a FinOps centre of excellence team is being set up.
• Create a FinOps roadmap/plan to define the future state.
  This should include an operating model to clearly define what the FinOps team will be doing. A Responsible, Accountable, Consulted, Informed (RACI) model will have to be created explaining what each person’s roles and responsibilities are and identify KPIs to measure the FinOps function and performance of business and application teams.
• Prepare an engagement plan.
  This will help show how you will engage and collaborate with your finance, business, engineering and procurement teams.
• Create an ongoing review plan.
  After about 3-6 months, gradually move onto the next phase where you can implement your KPIs, do some more dashboards for creating useful cost optimization reports, and bring automation in as well. The system will evolve over time and you will get better results.

2. How important is training to FinOps success?

Training and education is paramount to the successful implementation of FinOps. It’s also where the entire exercise can fail.
Get internal teams – such as the business and app teams – together. Conduct these 4 training activities on an ongoing basis.

• Kickoff meeting
• Brownbag sessions to educate teams on the FinOps Framework and tooling
• Implementation of recommended actions, ensuring teams are doing these regularly to achieve cost savings.
• Monthly or quarterly scorecards to measure performance and optimization every month.

Repeat these actions month on month till it becomes part of the team’s DNA – if they don’t do it on a regular basis, FinOps cannot be successful.

3. How do we effectively measure FinOps results – any metrics to look at?

• You can define several measurable parameters. For instance, Reserved Instance or Savings Plan Coverage must be >80% every month. Another metric could be that after 30 days of idle instance, you stop or decommission your instance.
• You could track accountability and enablement with a metric like Cloud Enablement %, the number of business leaders trained and certified / the total number of business leaders in the organization as a percentage.
• The Cost Optimization Realized Savings % measures the ratio of total cloud services optimized to total cloud services optimizable. This brings attention to areas for potential cost savings – pricing optimizations like Committed Use Discounts as well as resource optimizations of wasteful resources that haven’t brought/added any business value. The latter could be from over-sized databases, idle instances, etc.
• Annual Forecast Accuracy % is another useful metric that looks at the ratio of actual annual cloud spend vs the forecast cloud spend per annum. The number stabilizes as the gap between actual and forecast narrows, allowing the business to plan better and avoid any unexpected spikes in spends.

4. What are some typical challenges businesses face when managing cloud spend, and what are some best practices to address them?

FinOps to manage cloud spending might sound simple, but there can be some challenges.

The hardest one is to change the ways of working within an organization especially if someone has come from an on-premises world and is also new to cloud. It needs a mindset shift.

Surveys show that 30% of the challenge is getting the DevOps team to do the actions needed to enable FinOps. DevOps teams tend to already be very busy doing development and project work which is their priority and key focus.

Additionally, FinOps can become complex because of the intrinsic need for collaboration and getting the finance team and the procurement teams involved isn’t always straightforward.

The best way to overcome these issues is to educate them and train them on the benefits and value from FinOps, so that all the teams are ready to come on your journey. FinOps is relatively new to the cloud industry and many people do not know about it, so training sessions and brownbag sessions help build cadence with them and smoothen the process.

The next thing is to try and automate these actions as much as possible so that less manual effort is required from them.

5. What are some tools or services that Cloud Kinetics offers that can help businesses better manage their cloud spend?

Cloud Kinetics has best-in-class partnerships with multiple providers/tools in the field, including Apptio and Spot by NetApp. We have extensively utilized Cloudability by Apptio for FinOps in our engagements with customers as we have found that it meets most of our customers requirements – from easy-to-use dashboards and a benchmarking scorecard to insights into right sizing and unused resources.

Cloudability has APIs allowing one to integrate with DataDog, PagerDuty, ServiceNow etc. For example, if you have a workflow or want to put your billing into one central location like ServiceNow it can integrate as well. This tool can store the data for 1-2 years, allowing for forecasting, right sizing recommendations, unlike native tooling which has a limited window for storage of billing data.

That said, at Cloud Kinetics we ensure we always choose the best-fit solutions and tools for your organization based on your requirements and goals.

You can also download the FinOps 101 Handbook HERE

The post Save Money In The Cloud <br>With FinOps: Your Top 5 <br>Cloud Cost Qs Answered appeared first on Cloud Kinetics.

As more organizations embrace the cloud, securing cloud-native applications has become increasingly complex. Fragmented multi-vendor solutions attempt – and struggle – to shield an attack surface that’s expansive, dynamic and vulnerable. The solution to this growing challenge in cybersecurity could lie in cloud-native application protection platform or CNAPP.

CNAPP is a comprehensive solution that gives DevSecOps and DevOps teams unified automated security that oversees containers, workloads, compliance and more – the entire application lifecycle. It is being used by organizations to crank up security as well as visibility across hybrid and multi-cloud, and private and public cloud environments. But first, let’s see why there’s such a strong case for CNAPP and how it fares over traditional solutions.

Why traditional cybersecurity solutions aren’t always optimal

How did security end up being so complicated? Organizations have grown their cloud investments over time and added solutions and products in phases, organically. The accompanying security products layered over these have also been heterogeneous and operated in silos. The result? DevSecOps is fashioned sometimes from as many as 10 different tools each working in isolation!

Add to that the fact that cloud environments often involve microservices, containerization or serverless architecture. A far cry from traditional IT environments. This is why traditional intrusion detection and firewalls just don’t cut it when it comes to the distributed and dynamic cloud environments of today. These modes of security were designed to serve a fixed network perimeter like a data centre. Not the complex distributed cloud environments that are par for the course today.

The most significant driver is the need to unify risk visibility across the entire hybrid application and across the entire application life cycle. This simply cannot be achieved using separate and siloed security and legacy application testing offerings. – 2023 Gartner® Market Guide for Cloud-Native Application Protection Platforms

Your cloud security & CNAPP

What is CNAPP? A cloud-native application protection platform offers a simplified security architecture to enable enterprises to reduce complexity and costs of security solutions that operate in silos. CNAPP lets a business benefit from a unified continuous security structure without any added investments by way of more manpower or investment in more tools.

The compelling case for CNAPP in cybersecurity

The global CNAPP market is set to grow at 19.9% (CAGR) between 2022 and 2027, to USD 19.3 billion, driven by a growing risk of breaches and reported incidents of cyber threats, an increasing use of cloud solutions, a manpower crunch within the IT security teams in-house, as well as the potential vulnerability posed by an increasingly WFH/remote workforce.

By 2025, 60% of enterprises will have consolidated cloud workload protection platform (CWPP) and cloud security posture management (CSPM) capabilities to a single vendor, up from 25% in 2022. 2023 Gartner® Market Guide for Cloud-Native Application Protection Platforms

CNAPP was built to protect cloud-based infrastructure and applications. The solution is agile, dynamic and scalable. Large existing cloud users like ISVs and SaaS companies have begun to see the benefits of CNAPP.

The issue of combined risk is something CNAPP is capable of dealing with. While security solutions like cloud infrastructure entitlement management (CIEM), cloud workload protection platform (CWPP) and cloud security posture management (CSPM) do offer data on vulnerability and risk they are unable to come together in a way that – as Gartner puts it – connects the dots. CNAPP identifies the effective risk across the various layers that comprise cloud-native applications, helping prioritize risk and easing the burden on overstretched security and developer teams.

Here are some features of CNAPP that make it the smart choice for enterprises that operate in the cloud.

• Is a combined cloud security solution
• Is purpose-built for cloud-native environments
• Is integrated with the app development life cycle
• Does not add additional complexity to the application
• Supports scanning and quick response to any misconfiguration

How to choose a CNAPP solution

There is a palpable shift underway in the market, to consolidate cloud security solutions and benefit from the ease and visibility that a single CNAPP solution brings.

If you are considering CNAPP, here is a quick guide to choosing the right partner. The exercise will be most effective if those doing the selection are drawn from the various teams that will be involved with or impacted by the solution – namely, developers, development security, app security, cloud security, workload security and middleware security teams.

Make a CNAPP decision for your cybersecurity!

Finding a good partner for your CNAPP solution is critical and Cloud Kinetics has the expertise you need. Cloud Kinetics offers CNAPP in partnership with Plerion, an all-in-one Cloud Security Platform that supports workloads across AWS, Azure and GCP. If securing your entire cloud with an all-in-one cloud security platform is on your mind, we can help!

Cloud Kinetics is an award-winning, certified cloud transformation and managed services partner headquartered in Singapore and operating globally. We use cutting-edge platform-driven services to accelerate and secure our clients’ digital and business transformation journeys. Get in touch with our cloud experts for a non-obligatory discussion at contactus@cloud-kinetics.com

You can also download the CNAPP Cloud Security Handbook Here

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