Latest news with #AWSLambda
Yahoo
16-05-2025
- Business
- Yahoo
DoiT Achieves the Amazon Web Services SMB Competency
AWS recognizes DoiT's achievements in delivering comprehensive customer solutions across SMBs, adding to existing competencies like GenAI and Cloud Operations SANTA CLARA, Calif., May 16, 2025--(BUSINESS WIRE)--DoiT, a global leader in enterprise-grade cloud intelligence, announced today that it has achieved the Amazon Web Services (AWS) Small and Medium Business Competency. DoiT Cloud Intelligence™ delivers valuable outcomes for organizations of all sizes thanks to an action-oriented approach that prioritizes outcomes over endless alerts. DoiT is a leading partner of AWS. In late 2023, the companies signed a massive Strategic Collaboration Agreement to drive $5 billion in business and further deliver intelligent cloud consumption. Last year, DoiT achieved two new Competencies for GenAI and Cloud Operations, along with three Service Delivery Programs (Amazon Elastic Kubernetes Service, AWS Graviton and AWS Lambda). These accomplishments are all in pursuit of top-level service for DoiT's 2,400+ AWS customers. "DoiT is deeply committed to our partnership with AWS, and this accomplishment is another benchmark in our ever-expanding dedication to serve AWS customers," said Jaret Chiles, chief services officer at DoiT. "This achievement enables us to continue delivering market-defining support to AWS customers in search of innovative cloud solutions. We understand the unique challenges these customers face and are excited to continue delivering innovative, action-focused outcomes." DoiT Cloud Intelligence takes an intent-aware approach to cloud optimization across critical architectural principles. Blending operational intelligence, workload intelligence, human intelligence and ops automation, DoiT Cloud Intelligence delivers action-oriented, intent-aware solutions to help customers optimize, scale and innovate. DoiT Cloud Intelligence offers a comprehensive suite of tools designed to drive cloud success, including: CloudFlow: Take action on savings recommendations, resource scheduling and more through DoiT CloudFlow's AI-powered, no-code interface that's designed to reduce cloud expenses and ensure compliance. DataHub: Ingest third-party data to generate unit economics and see combined analytics for all your costs in a single pane of glass. Cloud Diagrams: Visualize your entire cloud architecture to easily detect critical issues, identify performance problems and drive seamless operations across environments. Analytics and Attributions: Translate your public cloud bill into language your business understands. Drive cost accountability so that your stakeholders take ownership of their usage. To learn more about how DoiT partners with AWS to drive digital transformation, visit About DoiT DoiT is a global leader with its DoiT Cloud Intelligence™ platform, providing AI-powered solutions that help businesses maximize the value of their cloud investments. With expertise in AWS and other cloud platforms, DoiT Cloud Intelligence™ empowers companies to contextualize data mining, uncover the root causes of cloud inefficiencies and close the loop with engineering teams. View source version on Contacts Media contact:Metis Communicationsdoit@ Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Business Wire
16-05-2025
- Business
- Business Wire
DoiT Achieves the Amazon Web Services SMB Competency
SANTA CLARA, Calif.--(BUSINESS WIRE)--DoiT, a global leader in enterprise-grade cloud intelligence, announced today that it has achieved the Amazon Web Services (AWS) Small and Medium Business Competency. DoiT Cloud Intelligence™ delivers valuable outcomes for organizations of all sizes thanks to an action-oriented approach that prioritizes outcomes over endless alerts. DoiT is a leading partner of AWS. In late 2023, the companies signed a massive Strategic Collaboration Agreement to drive $5 billion in business and further deliver intelligent cloud consumption. Last year, DoiT achieved two new Competencies for GenAI and Cloud Operations, along with three Service Delivery Programs (Amazon Elastic Kubernetes Service, AWS Graviton and AWS Lambda). These accomplishments are all in pursuit of top-level service for DoiT's 2,400+ AWS customers. "DoiT is deeply committed to our partnership with AWS, and this accomplishment is another benchmark in our ever-expanding dedication to serve AWS customers,' said Jaret Chiles, chief services officer at DoiT. "This achievement enables us to continue delivering market-defining support to AWS customers in search of innovative cloud solutions. We understand the unique challenges these customers face and are excited to continue delivering innovative, action-focused outcomes." DoiT Cloud Intelligence takes an intent-aware approach to cloud optimization across critical architectural principles. Blending operational intelligence, workload intelligence, human intelligence and ops automation, DoiT Cloud Intelligence delivers action-oriented, intent-aware solutions to help customers optimize, scale and innovate. DoiT Cloud Intelligence offers a comprehensive suite of tools designed to drive cloud success, including: CloudFlow: Take action on savings recommendations, resource scheduling and more through DoiT CloudFlow's AI-powered, no-code interface that's designed to reduce cloud expenses and ensure compliance. Take action on savings recommendations, resource scheduling and more through DoiT CloudFlow's AI-powered, no-code interface that's designed to reduce cloud expenses and ensure compliance. DataHub: Ingest third-party data to generate unit economics and see combined analytics for all your costs in a single pane of glass. Ingest third-party data to generate unit economics and see combined analytics for all your costs in a single pane of glass. Cloud Diagrams: Visualize your entire cloud architecture to easily detect critical issues, identify performance problems and drive seamless operations across environments. Visualize your entire cloud architecture to easily detect critical issues, identify performance problems and drive seamless operations across environments. Analytics and Attributions: Translate your public cloud bill into language your business understands. Drive cost accountability so that your stakeholders take ownership of their usage. To learn more about how DoiT partners with AWS to drive digital transformation, visit About DoiT DoiT is a global leader with its DoiT Cloud Intelligence™ platform, providing AI-powered solutions that help businesses maximize the value of their cloud investments. With expertise in AWS and other cloud platforms, DoiT Cloud Intelligence™ empowers companies to contextualize data mining, uncover the root causes of cloud inefficiencies and close the loop with engineering teams.
Yahoo
15-05-2025
- Business
- Yahoo
Virtual Machine Market Size to Surpass USD 35.37 Billion by 2032, Owing to Rising Cloud Adoption and Demand for Scalable IT Infrastructure
The Virtual Machine (VM) market is experiencing significant growth, driven by the increasing adoption of cloud computing, the need for cost-effective computing solutions, and the demand for scalable IT infrastructure. Pune, May 15, 2025 (GLOBE NEWSWIRE) -- Virtual Machine Market Size Analysis: 'The Virtual Machine Market size was USD 10.43 Billion in 2023 and is expected to reach USD 35.37 Billion by 2032, growing at a CAGR of 14.6% over the forecast period of 2024-2032.'Get a Sample Report of Virtual Machine Market@ Major Players Analysis Listed in this Report are: Inc. (Amazon Elastic Compute Cloud (EC2), AWS Lambda) Citrix Systems Inc. (Citrix Hypervisor, Citrix Virtual Apps and Desktops) Hewlett Packard Enterprise LP (HPE Synergy, HPE SimpliVity) Huawei Technologies Co. Ltd. (FusionCompute, Huawei Cloud Stack) International Business Machine Corporation (IBM PowerVM, IBM Cloud Virtual Servers) Microsoft Corporation (Microsoft Hyper-V, Azure Virtual Machines) Oracle Corporation (Oracle VM VirtualBox, Oracle Cloud Infrastructure Compute) VMware Inc. (VMware vSphere, VMware Workstation Pro) Parallels Inc. (Parallels Desktop, Parallels Remote Application Server) Red Hat Inc. (Red Hat Virtualization, Red Hat OpenStack Platform) Cisco Systems (Cisco UCS Manager, Cisco HyperFlex) Intel Corporation (Intel VT-x [Virtualization Technology], Intel Server GPU) Virtual Machine Market Report Scope: Report Attributes Details Market Size in 2023 US$ 10.43 Billion Market Size by 2032 US$ 35.37 Billion CAGR CAGR of 14.6 % From 2024 to 2032 Base Year 2023 Forecast Period 2024-2032 Historical Data 2020-2022 Key Regional Coverage North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe [Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]). Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia Rest of Latin America) Key Growth Drivers Increasing Adoption of Cloud Computing and Virtualization Drives Growth in the Virtual Machine Market Do you have any specific queries or need any customization research on Virtual Machine Market, Make an Enquiry Now@ Cloud-Driven Demand Accelerates Virtual Machine Market Expansion with Focus on Flexibility and Cost Efficiency The Virtual Machine market is rapidly expanding as demand for flexible and efficient computing is increasing. With the rapid expansion of cloud computing, VMs have been increasingly accepted due to their ability to reduce resource wastage and cost. Cloud-based virtual machines are especially popular in hybrid and multi-cloud scenarios, providing businesses with the flexibility to run applications on-premises, in the cloud, or various clouds, and be able to leverage cloud services alongside their on-premises systems. The U.S. Virtual Machine (VM) Market was valued at USD 2.61 billion in 2023 and is projected to reach USD 8.09 billion by 2032, expanding at a CAGR of 13.4% from 2024 to 2032. This increase is fueled especially by the broad implementation of cloud and virtualization and AI related workloads.' VMs are widely used in organizations for simplifying infrastructure management, improving scalability as well as operating efficiency. Increasing adoption of hybrid and multi-cloud solutions, combined with advancements in hypervisor technology, is driving market growth. Segment Analysis By Type, System Virtual Machines Lead 2023 Market with 64% Share, While Process VMs Set to Surge at 15.6% CAGR Through 2032[ In 2023, the System Virtual Machine segment dominated the market, accounting for 64.00% of total revenue. This leadership is due to its wide adoption in data centers, enterprise IT, and cloud. System VMs also allow running multiple OSes on a single physical server, contributing to resource optimization and cost reduction for enterprises. Advances in hypervisor technology and cloud VM products have also increased speed and security, and hence usage. The Process Virtual Machine segment is expected to register the largest CAGR of 15.6% during the forecast period. This expansion is driven by the increasing demand for efficient runtime environments. Process VMs are most commonly used to run software applications, but they are also widely implemented in developed containerized applications, serverless computing, and other cloud computing applications, processes, and IT operations these days. By vertical, BFSI leads the Virtual Machine Market with a 29% Share in 2023; the Government Sector is set for the Fastest Growth Amid Digital Transformation. The BFSI sector contributed the highest revenue share of 29.00% in 2023, as the industry increasingly adopts virtualization to have a scalable and secure IT infrastructure. Banks are improving their data security, high-frequency transaction, and disaster recovery capabilities, using virtual machines. The Government & Public sector is expected to grow at the highest CAGR during the forecast period, as organizations in this sector are among the early adopters of new and emerging technologies, as they can be effectively used to thwart cyber-criminal activities. Virtual Machine Market Segmentation: By Type System Virtual Machine Process Virtual Machine By Organization Size Large Enterprises SMEs By Vertical BFSIs Telecommunications & ITES Government & Public Sector Healthcare & Life Sciences Others North America Leads Virtual Machine Market with 38% Share in 2023; Asia Pacific Emerges as Fastest-Growing Region at 15.7% CAGR. North America held the virtual machine (VM) Market share of around 38% in 2023. This leadership is attributed to the robust adoption of cloud technology, powerful IT infrastructure, as well as the massive implementation of virtualization technologies in enterprises across the region. The dominance of North America is attributed to leading cloud service providers, large-scale investment in data centers, and the rising need for a virtualized environment in BFSI, healthcare, and the government sector. Asia Pacific is the fastest-growing region in the Virtual Machine (VM) market, projected to expand at a CAGR of 15.7% over the forecast period. This fast-growing market is driven by the increasing demand for cloud-based virtualization, growth in the spending towards IT, and the increase in digital businesses in developing economies such as China, India, and Southeast Asia. Virtualization is gaining adoption from governments and organizations in the region to increase operational efficiency, handle mass storage of data, and bolster cybersecurity systems. Recent Developments In November 2024 an HPE VM Essentials virtualization product that can operate across HPE and non-HPE platforms. This solution looks to supply customers with a consume- what-you-need model virtualization solution that can possibly be of interest to those that are tired of the virtualization alternatives. In November 2024, Microsoft unveiled major improvements to its Azure Cloud platform, announcing new virtual machines (VMs) and improved cooling and power delivery technologies to accommodate the increasing requirements of Artificial Intelligence (AI) of Contents – Major Key Points 1. Introduction 2. Executive Summary 3. Research Methodology 4. Market Dynamics Impact Analysis 5. Statistical Insights and Trends Reporting 6. Competitive Landscape 7. Virtual Machine Market Segmentation By Organization Size 8. Virtual Machine Market Segmentation By Vertical 9. Virtual Machine Market Segmentation By Type 10. Regional Analysis 11. Company Profiles 12. Use Cases and Best Practices 13. Conclusion About Us: SNS Insider is one of the leading market research and consulting agencies that dominates the market research industry globally. Our company's aim is to give clients the knowledge they require in order to function in changing circumstances. In order to give you current, accurate market data, consumer insights, and opinions so that you can make decisions with confidence, we employ a variety of techniques, including surveys, video talks, and focus groups around the world. Related Reports: Applied AI Service Market Business Software And Services Market Case Management Market Online Survey Software Market Cloud Workflow Market CONTACT: Contact Us: Jagney Dave - Vice President of Client Engagement Phone: +1-315 636 4242 (US) | +44- 20 3290 5010 (UK)Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
India.com
05-05-2025
- Business
- India.com
From Code to Cloud: Radhakrishnan Pachyappan's Digital Journey
Radhakrishnan Pachyappan traces his engineering journey from a single‑room office in Chennai to the advanced cloud war‑rooms of Plano, Texas, anchoring more than a decade of transformation projects that now stabilize workloads across automotive retail, finance, and insurance. Over twelve years he has learned that scalability is neither a perk nor a late‑stage upgrade; it is the bedrock on which modern digital trust is built. He treats API idempotence the way an accountant respects balanced ledgers, and he embeds observability early so that controllers and engineers share the same vocabulary of metrics. Certifications—AWS Solutions Architect Professional, Microsoft C#, .NET MVC, Azure Fundamentals, and more—underline his range, but the true yardstick remains the serenity with which his platforms absorb seasonal surges that would rattle less intentional systems. Cloud maturity turns theory into practice in his refactor of a corporate‑ and retail‑car‑reservation platform for a leading automotive manufacturer, where he decomposed monoliths into AWS Lambda micro‑services fenced by authorizers and web‑application firewalls. DynamoDB tables negotiate their own write capacity in real time; Step Functions coordinate overnight reconciliations without blocking daytime transactions; and Jenkins pipelines shepherd commits from GitHub through SonarQube quality gates to production in under an hour. The result is velocity without volatility—feature squads deploy weekly, and administrators modify inventory or fee structures with zero downtime. 'My experience of implementing large‑scale reservation platforms has taught me that every service boundary is a promise of independence. Honor that promise, and traffic surges feel perfectly ordinary.' Modular Mastery for Relentless Scale Radhakrishnan Pachyappan sharpened his composable mindset while rescuing Inspire—a deal‑modeling engine a global consulting giant depends on for client pricing—from legacy bottlenecks. Stateless Lambdas fronted by API Gateway replaced brittle servers, S3 events refreshed master data automatically, and Code Pipeline compressed release cycles from days to hours, slicing overall processing time by 60 percent. What had once required overnight batch jobs now completes before a coffee break, proving that serverless is not merely cost‑efficient—it is decisively faster. Modularity extends beyond code to culture. Weekly 'failure rehearsals' throttle staging environments, compelling runbooks to demonstrate their mettle under synthetic stress while SonarQube blocks merges that exceed agreed cyclomatic‑complexity thresholds. Dashboards map every pull request to deployment frequency, tying individual behavior to business cadence in real time. Governance therefore shifts from a periodic inspection to an always‑on feedback loop, turning quality into a shared gamified objective. 'Implementing cloud transformations at a broad scale has shown me that cost savings endure only when latency budgets and compliance rules are welded into sprint zero—retrofitting discipline is the costliest refactor of all.' Industry Velocity Across Domains Radhakrishnan Pachyappan draws on manufacturing floors, trading desks, and underwriting models to guide design reviews that respect each sector's non‑negotiables. Sensors on assembly lines demand millisecond telemetry or risk idle machinery; finance mandates deterministic audit trails for every state change; insurance models rely on unbroken lineage across datasets to ward off risk exposure. When he led fifteen specialists on the automotive fleet initiative, he paired Flutter for mobile and Angular for web, sharing TypeScript logic without sacrificing native idioms. Terraform declared every environment, while Artifactory pinned container images to guarantee reproducibility. Mapping technical debt to unit economics, he shows product owners why a deferred refactor costs multiples downstream. Concurrency ceilings translate into currency terms, lending architecture meetings the same clarity as balance‑sheet reviews. That business fluency secures a budget for resilience features—rate limiters, circuit breakers, blue‑green deploys—that technical teams often struggle to prioritize. Consistent delivery metrics emerge: on‑time launches, uptime north of 99.99 percent, and change‑failure rates beneath industry benchmarks. Stakeholders learn to equate architectural rigor with predictable revenue, anchoring the notion that robust systems are not overhead but strategic advantage. Leadership Mentorship and Culture Radhakrishnan Pachyappan treats mentorship as a multiplier, hosting office hours where engineers defend design trade‑offs in plain language rather than jargon. Pull‑request reviews home in on naming clarity and algorithmic intent with equal vigor, because self‑documenting code accelerates future velocity. Rotating on‑call leadership ensures every team member feels the weight—and therefore the value—of operational excellence. He seeds psychological safety by framing failures as learning artifacts. Post‑incident reviews ask, ' What telemetry would have flagged this sooner?' rather than ' Who missed the signal?' That shift converts war‑room anxiety into design‑backlog prioritization, embedding reliability into the next iteration instead of burying it in a blame ledger. 'In guiding multi‑industry digital initiatives I have learned that culture is architecture's invisible load‑balancer. When teams feel safe to surface risk early, systems remain safe to carry the business later.' Governance, Compliance, and Observability Radhakrishnan Pachyappan insists that observability must be as integral as business logic, embedding distributed traces, structured logs, and real‑time metrics from sprint zero. He treats dashboards as shared contracts: if an SLA matters, there is a gauge; if a threshold can break budget, there is a redline alarm. Automated canaries run after every infrastructure change, capturing latency deltas before users do. Compliance shifts from annual audits to living documentation. Infrastructure‑as‑code doubles as evidence; change histories link git commits to incident tickets; and policy‑as‑code tools assert encryption, data residency, and retention rules at deploy time. Auditors no longer sift through binders—they scroll dashboards with time‑based diffs. When anomalies slip through, sampling pipelines fork suspicious traffic into secure sandboxes for forensic replay. Root‑cause findings feed back into Step Function branches, closing the governance loop so that the next violation is pre‑empted. This virtuous cycle keeps regulators satisfied and keeps operations focused on innovation rather than remediation. AI as the Emerging Design Partner Radhakrishnan Pachyappan is piloting reinforcement agents that tune DynamoDB capacity units and tighten WAF rulesets in near real time, trimming hot‑partition incidents by double digits during holiday spikes . Security payload inspectors now spin up sandbox replicas the moment anomalous fields appear, turning quarterly audits into continuous compliance streams. These AI teammates surface anomalies and propose remedies before alerts reach human operators, nudging architects from reactive firefighting toward proactive mentoring. Development workflows evolve in parallel. Junior developers push code while AI bots annotate concurrency footprints and suggest shard keys, leaving senior engineers to validate domain heuristics rather than syntax minutiae. The resulting feedback loop compresses onboarding curves and produces infrastructure that effectively learns its own limits. Radhakrishnan's next experiment integrates UML‑driven behavior diagrams with generative policy engines, compiling governance rules directly from design artifacts. In that future, architects curate principles, and AI enforces them at runtime—closing the loop between intent and execution. Navigating the Next Horizon Radhakrishnan Pachyappan measures success by the silence of well‑behaved systems: when capacity doubles and dashboards stay green, stewardship trumps spectacle. He charts a five‑year vision blending event streaming, supervised learning, and self‑healing pipelines, each observable from a single pane that even a day‑one hire can navigate. In markets chasing novelty, his compass aims for maintainability, clarity, and intelligence advancing together. Leadership, he believes, is succession planning in disguise. By turning architectural principles into shared muscle memory, he ensures that platforms and people will outlast his own tenure. As organizations stride into AI‑augmented cloud landscapes, the blueprint he offers—disciplined, observable, culture‑forward—remains the surest route to innovation without compromise.
