Tag: cloud migration

  • Accenture and AWS Unveil AI and Cloud Solutions for Mid-Market Businesses

    Accenture and AWS Unveil AI and Cloud Solutions for Mid-Market Businesses

    Accenture has partnered with Amazon Web Services (AWS) to introduce a suite of AI and cloud tools specifically designed for mid-sized companies. The offerings, available through AWS Marketplace, cover cloud migration, security, data management, customer service, and AI testing.

    Key solutions include tools for moving virtual machines to AWS, optimizing cloud spending, securing cloud environments, and testing AI systems for potential risks. The collaboration is part of Accenture Edge, a business unit focused on organizations with annual revenues between USD 300 million and USD 3 billion. Accenture Edge aims to deliver tailored technology solutions for mid-market needs.

    Customer service technologies, such as conversational AI and virtual agents, are also included. Additional tools help companies identify data sources and dependencies during cloud migrations.

    Accenture highlighted its work with 407 ETR, an electronic toll highway operator in Toronto. The company used Accenture’s NeuraFlash unit and AWS to build a new customer service system without disrupting existing operations—demonstrating how the collaboration can modernize customer-facing technology smoothly.

    Accenture shares rose 1.6% before the opening bell on Tuesday, extending Monday’s gains. This move follows Anthropic’s partnership with Accenture to test the safety of advanced AI models.

  • Leading Modernization Engineering Services Firms for Legacy Technology Transformation

    Leading Modernization Engineering Services Firms for Legacy Technology Transformation

    Modernizing legacy technology is no longer just an IT upgrade—it has become a strategic necessity for enterprises aiming to keep applications secure, reduce technical debt, and prepare systems for cloud computing, automation, and artificial intelligence. Businesses are increasingly turning to engineering and IT services companies that can assess legacy systems, migrate workloads, rebuild applications, and introduce modern architectures without disrupting daily operations. Industry research highlights several global technology providers for their capabilities in application and legacy modernization.

    10 Leading Firms Transforming Legacy Technology

    Here are ten companies that stand out in the modernization engineering services space:

    Accenture

    Accenture offers a broad application modernization practice covering legacy assessment, architecture planning, cloud migration, application transformation, and mainframe modernization. The company also uses automation and AI-assisted approaches to help enterprises modernize large application estates.

    Tata Consultancy Services (TCS)

    TCS works with large enterprises on application modernization, cloud transformation, and legacy technology upgrades. Its scale and global delivery network make it a major provider for organizations managing complex technology environments. TCS was named a Leader in Forrester’s 2024 assessment of application modernization and migration services.

    Infosys

    Infosys takes an AI- and cloud-first approach to modernization. Its services cover legacy applications, mainframes, databases, cloud migration, technology upgrades, and the transition of monolithic applications to microservices.

    Capgemini

    Capgemini helps businesses modernize applications and technology environments while moving toward cloud-native architectures. The company has been recognized among the leading providers in application modernization and migration services.

    HCLTech

    HCLTech is a major player in legacy and application modernization. Its services focus on helping enterprises move away from older technology environments while adopting cloud, automation, and modern engineering practices. HFS Research included HCLTech among its 2025 Market Leaders.

    Cognizant

    Cognizant offers end-to-end modernization services, from application assessment and migration to cloud-native transformation. Its Skygrade platform uses automation, modern tooling, and generative AI to support large-scale cloud modernization programs.

    IBM

    IBM Consulting focuses strongly on hybrid cloud and AI-led application modernization. Its services include migrating and modernizing existing applications, containerizing legacy systems, and incrementally improving older applications rather than replacing everything at once.

    Wipro

    Wipro provides modernization through rehosting, re-platforming, refactoring, and rearchitecting applications. Its services also cover integration and data modernization, with GenAI being used to speed up parts of the transformation process.

    EPAM Systems

    EPAM has an engineering-focused modernization practice covering applications, platforms, and data. It also uses AI for legacy code migration and documentation, alongside cloud, containerization, and platform engineering capabilities.

    LTIMindtree

    LTIMindtree is a notable provider for enterprises looking to modernize legacy and mainframe environments. The company has been included among major application modernization providers assessed by industry research firms.

    Final Take

    Modernization engineering is becoming a long-term technology strategy rather than a one-time migration project. Companies need to balance legacy systems with cloud adoption, AI, security, and the need to release software faster. The right modernization partner depends on the size of the technology estate, the complexity of legacy applications, and the organization’s cloud and AI roadmap. For large-scale transformation, companies such as Accenture, TCS, Infosys, Capgemini, HCLTech, and Cognizant remain prominent names, while IBM, Wipro, EPAM, and LTIMindtree offer additional options across different modernization needs.

    Frequently Asked Questions

    What are modernization engineering services?

    Modernization engineering services help businesses upgrade legacy applications, migrate systems to cloud platforms, improve architecture, introduce automation, and integrate artificial intelligence while maintaining business continuity and reducing technical debt.

    Why do companies need modernization engineering services?

    Companies use modernization engineering services to address outdated technology, improve application performance, strengthen security, reduce maintenance costs, support scalability, and create technology environments capable of adapting to changing business requirements.

    Which companies provide modernization engineering services?

    Leading providers include Accenture, Tata Consultancy Services, Infosys, Capgemini, HCLTech, Cognizant, IBM, Wipro, EPAM Systems, and LTIMindtree, offering different combinations of application, cloud, mainframe, data, and digital engineering modernization capabilities.

    How does AI support application modernization?

    AI can assist modernization by analyzing legacy code, generating documentation, identifying dependencies, suggesting code improvements, automating testing, and accelerating migration activities, helping engineering teams modernize applications more efficiently.

    How should businesses choose a modernization engineering partner?

    Businesses should evaluate a provider’s legacy technology expertise, cloud capabilities, engineering experience, security practices, AI adoption, industry knowledge, delivery scale, modernization methodology, and ability to support long-term transformation goals.

  • Application Modernization Guide: How to Modernize Legacy Software Systems

    Application Modernization Guide: How to Modernize Legacy Software Systems

    Legacy software often works quietly in the background, running payroll, managing inventory, processing claims, and keeping operations moving. But the business around it changes quickly. New products need faster releases. Customers expect digital experiences. Teams need systems that connect with modern platforms. The gap between what the business needs and what its software can deliver keeps widening.

    Application modernization closes that gap. It updates software, architecture, infrastructure, or interfaces while preserving the capabilities already in place. The real goal is freedom to change.

    Why Legacy Software Becomes a Business Constraint

    Leaving a legacy system alone feels safe. It works, and change brings risk. But the real question is not whether it works today; it is whether it can handle what the business needs tomorrow.

    Consider a retailer using an old pricing system built on fixed, batch-updated price lists. The business wants dynamic pricing based on demand and stock levels. The system cannot supply real-time data for that, so engineers spend months building workarounds instead of shipping the actual feature.

    Three pressures make this worse over time:

    • Fewer skilled professionals know these old systems, so maintenance gets harder and more expensive.
    • Rigid interfaces make it difficult to connect with modern APIs and cloud tools.
    • Technical debt stretches testing and release timelines.

    Together, these pressures slow down launches, raise costs, add risk, and make it harder to keep pace with the market.

    The Six Paths Forward: Understanding the 6 R’s

    A widely referenced framework describes six modernization strategies, often called the 6 R’s. Each answers a different question about an application’s future:

    • Rehost — Move the application to a different infrastructure without changing its code or architecture.
    • Replatform — Move to a new platform with minimal changes, often to take advantage of cloud services.
    • Refactor — Restructure existing code to improve its internal quality while preserving external behavior.
    • Rearchitect — Significantly alter the application’s architecture to enable new capabilities or scale.
    • Rebuild — Rewrite the application from scratch while keeping its scope and specifications.
    • Replace — Retire the application and adopt a commercial or off-the-shelf solution instead.

    None of these paths is inherently better than the others. A billing engine that rarely changes may suit rehosting well. An order system that must evolve every month likely justifies rearchitecting, even at higher upfront cost.

    Building a Modernization Strategy

    The first decision is not which technology to adopt. It is which applications deserve investment at all. A system with high business value and high technical risk should sit ahead of one that is outdated but operationally minor.

    At this point, sequencing and management matter more than the actual toolkit. Identify all dependencies that each application has, because modernizing one system may involve renegotiating links to a dozen other systems. Outline clear ownership for each stage to prevent scope and risk tolerance decisions from getting stuck between teams.

    Do not simply choose the latest or most fashionable modernization path. Avoid one large cutover. Instead, test a small move to see whether it behaves as expected in production, and roll it back if it does not. Design for uptime rather than treating it as an afterthought or allowing it to become a barrier to design.

    This discipline is well captured by the strangler fig pattern, where new functionality is added around an old system and incrementally replaces it over time.

    Measuring Success and Avoiding Modernization for Its Own Sake

    The strongest measures link technical change to operational outcomes, such as:

    • Releasing changes sooner
    • Recovering faster from incidents
    • Integrating new services with less effort
    • Running systems at a sustainable cost against a baseline established before the work begins

    A quieter risk is modernizing without a clear destination. Adopting microservices or containers just because they are the current pattern, rather than because the system actually needs them, produces an architecture that looks modern but remains just as hard to change. The complexity has moved, not disappeared.

    Final Thoughts

    Modernization is not a single project or a finish line. It is the ongoing work of finding which technical limits are quietly slowing the business down and removing them before they force a crisis. Judged by that standard, and not by how new the software looks, modernization earns its investment.

    Frequently Asked Questions

    What is application modernization?

    Application modernization is the process of updating older software, architecture, infrastructure, or interfaces so an application can support current business needs without losing its core capabilities.

    Why do businesses need to modernize legacy applications?

    Legacy applications can become difficult and expensive to maintain as technology, customer expectations, and business requirements change. Modernization can help improve release speed, integration, reliability, and operating costs.

    What are the 6 R’s of application modernization?

    The six common approaches are rehost, replatform, refactor, rearchitect, rebuild, and replace. Each option suits different business needs, technical conditions, and investment levels.

    How should a company decide which applications to modernize first?

    Companies should consider both business value and technical risk. Applications that are critical to operations but difficult to maintain or change generally deserve higher priority than systems with limited business impact.

    How can businesses measure the success of application modernization?

    Success can be measured through practical business and operational outcomes, such as faster releases, quicker incident recovery, easier integration, lower maintenance effort, and more sustainable technology costs.

  • 10 Common AWS Migration Pitfalls and Proven Solutions for 2026

    10 Common AWS Migration Pitfalls and Proven Solutions for 2026

    AWS migrations remain one of the most predictably difficult engineering projects a company can take on, despite over a decade of mature tooling and frameworks. Roughly a third of migrations either fail outright or blow past their budget, and the average overrun lands around 23% above what was planned. The reasons rarely have anything to do with AWS’s capabilities. They come down to ten specific, well-documented failure points, and every one of them has a known fix.

    Most Failures Start Before a Single Workload Moves

    The single biggest predictor of a troubled migration is starting without a workload-by-workload strategy. AWS defines seven migration patterns: rehost, replatform, refactor, repurchase, retain, retire, and relocate. Treating every application the same way is one of the most common and costly mistakes teams make. A legacy batch job and a customer-facing API have nothing in common strategically, and forcing both through identical lift-and-shift treatment usually means overpaying for the simple one and under-optimizing the complex one.

    Right behind strategy sits dependency mapping. Enterprises consistently underestimate how much undocumented coupling exists across applications, shared databases, batch jobs, and external integrations. Poor mapping is cited repeatedly as a leading cause of migration failure. AWS Application Discovery Service and X-Ray help, but they are not a substitute for sitting down with the engineers who actually own each system.

    Technical Failures to Focus On

    Once strategy is settled, the recurring technical issues are remarkably consistent across nearly every account of AWS migrations gone wrong:

    • Underestimated data migration complexity
    • Security misconfigurations introduced during the rush to cut over
    • Wrong instance sizing based on old hardware specs rather than actual utilization
    • Downtime during cutover that nobody fully planned for

    The fix for the sizing problem is almost embarrassingly simple: size from CloudWatch usage data, not the specs of the server you’re replacing. Teams that do this consistently land on smaller, cheaper, more stable configurations, and Graviton instances are worth testing before any Savings Plan gets locked in.

    Cost Overrun Nobody Sees Coming Until the Bill Arrives

    Post-migration cost overruns deserve their own callout because they catch finance teams off guard more than any other item on this list. The mechanism is almost always the same: a double-run period — old infrastructure and new infrastructure running in parallel — gets treated as a scheduling detail instead of a budgeted financial risk. Every month that overlap continues, the organization pays twice for the same workload, and that erosion compounds fast. The teams that avoid this treat double-run as a named risk with an owner and a hard timebox from day one.

    All Ten Issues at a Glance

    Here are the ten most common AWS migration problems and their practical solutions:

    1. Poor planning — Use a workload-by-workload strategy aligned with the AWS 7 Rs framework.
    2. Inadequate dependency mapping — Combine AWS tools with direct engineer interviews.
    3. Underestimated data migration complexity — Test migrations early and plan for data validation.
    4. Security misconfigurations — Implement least-privilege IAM policies and AWS Control Tower guardrails.
    5. Wrong instance sizing — Size based on CloudWatch usage data, not old server specs.
    6. Unplanned downtime — Create detailed cutover plans with rollback procedures.
    7. Cost overruns from double-run — Treat double-run as a named risk with a hard timebox.
    8. Skill gap — Use a dedicated migration team with hands-on experience.
    9. Governance gaps — Establish clear governance and cost ownership from the start.
    10. Poor stakeholder communication — Maintain regular alignment across teams and leadership.

    What This Means for Your Migration

    None of these ten problems are exotic or AWS-specific; they show up in cloud migrations across every provider, repeated almost word-for-word in nearly every postmortem written about failed projects. The organizations that avoid them do one thing consistently: they treat governance, dependency mapping, and cost ownership as part of the technical plan, not as paperwork that happens around it.

    Cloud migration is more than moving workloads from on-premises infrastructure to AWS. A successful migration requires careful planning, governance, security, cost management, and cross-functional collaboration. Addressing common migration challenges early helps organizations reduce risk, minimize downtime, optimize cloud spending, and accelerate business transformation.