How enterprises can accelerate legacy modernization?

How enterprises can accelerate legacy modernization?

Reasons To Consider Legacy Modernization

Many CIOs acknowledge the need for legacy transformation and a move towards an agile, modern system. Outdated software slows down the business to respond to changing market needs and puts them behind their competition. A lengthy update or an upgrade approach would become a bottleneck and risk to the company’s day to day operations. Today enterprises are looking for an agile and quick digital transformation approach that makes the process simple to modify and quick to adapt. They also have to address the training needs within the organization during such modernization efforts.

Few other factors include

  • Better user experience
  • Digitization of an offline process
  • Out of support software or infrastructure systems
  • Limitations in their current technology stack/product
  • Enhanced features with better performance
  • Data Monetization
  • Innovative products/Services
  • Ease of integration with other systems

Choosing the right Modernization Approach

There are many ways to transform legacy systems. Enterprises use their own strategies to achieve legacy modernization. Fully automated migration is an efficient option that uses migration guides, checklist, migration tools and code generators to convert legacy data and code to modernize platforms. It also allows enterprises to tackle legacy modernization without distracting business operations. Refactoring a legacy application reduces the potential risks and enhance IT efficiencies.

Sun Technologies’ unique agile framework enables enterprises to enhance their legacy systems and drive legacy transformation. Our experts build smart workflows for your business processes, make strategic insights, and accelerate your legacy transformation. Our agile framework comprises of a checklist, guide, tools, and framework. The checklist and guide help identify the right approach and provide proper paths to achieve the goal.

Checklist before getting started with legacy modernization

  • What is our primary objective in modernizing the legacy systems?
  • Are we choosing the right modernization approach?
  • Impact Analysis chart
  • What are the best practices to follow to accomplish the modernization process?
  • What are our next steps for legacy modernization?
  • Are there any processes or workflows to be digitized?
  • How would the switch over happen?

How does Sun Technologies accelerate legacy modernization?

There are several approaches towards accelerating modernization; however, at Sun Technologies, we follow an iterative process to accelerate the legacy transformation that reduces risks while providing the agility to meet the dynamic requirements of the business. We start with the evaluation and assessment of the current state of the legacy systems. Our team of solution architects start with impact analysis of various interdependent systems and prioritize the application stack. We decide and prioritize applications that are important and have low impact and risks for modernization. Our code generator reduces the development time significantly, helping businesses to see quick wins and benefits of legacy transformation efforts. We also have a properly layered tech stack where multiple teams can work together.

Post modernization, we have DevOps tools to guarantee there is no data or functionality loss. Our experts ensure that all dependent upstream and downstream systems work seamlessly through detailed data distribution & validation across multiple integration points. From upgrading platform, database, tech stack, Sun Technologies’ solution experts can make it simple and deliver the desired output. We also ensure we develop a roadmap that reduces the complexities while maximizing the benefits of digital transformation, agile development, UI/UX, and quality assurance.

Resulting System Benefits Include:

  • Competitive advantage
  • Better user experience
  • Future ready business
  • Ability to make quick changes
  • Faster time to market
  • Secure systems
  • Better user experiences
  • Integrates with a third-party system

Conclusion

Software modernization is dynamic, requires highly skilled resources, and is risky, irrespective of the chosen method and technique. Yet, the findings are valuable to the risk and gives competitive edge to your business.

“Gartner predicts more than half the global economy turns digital by 2023.”

Our legacy modernization solutions streamline business processes from planning to implementation and provide more value by improving operational efficiency, business agility, and ROI. Sun Technologies helps enterprises accelerate legacy modernization through fast, secure, and state of the art modern technologies and code generators. Get in touch with us today!

Tahir Imran

Tahir Imran

With over 18+ years of experience in Software design and development, Tahir's expertise lies in designing and developing high-quality products and solutions spanning multiple domains. He is versatile and always eager to tackle new problems by constantly researching and deploying emerging techniques, technologies, and applications.

Share on facebook
Facebook
Share on twitter
Twitter
Share on linkedin
LinkedIn

Recent Posts

 

Interested in Legacy Mordernization?

  We deliver result-driven solutions to boost the competency level and productivity.

Data Security with Data Classification

Ensure data security with data classification to protect your organization’s sensitive data

Data protection is at risk during this pandemic and likely a target of malicious behavior or intrusive cybercriminals. Data classification offers one of the best ways for enterprises to define and assign relative values to their data and ensures data security The process of data classification enables you to categorize your stored data by sensitivity and business effect, so you realize the risks connected with the data. Instead of handling all data the same way, you can manage your data in ways that reflect its value to your business.

Data exists in three primary states, i.e., at rest, in process, and transit. All three states need distinctive technical solutions for data classification. Also, you should apply the same standards of data classification for each. The confidential data needs to stay confidential when at rest, in process, and transit.

Data can be Structured or Unstructured

General classification processes for structured data found in spreadsheets and databases are less complicated and time-consuming to manage.  Unstructured data that include documents, source code, and email are more complex than structured data. Usually, companies have more unstructured data than structured data.

At Sun Technologies, we believe that one of the best data protection aspects is the right data classification. If you know what and where your critical data is, you would secure it reasonably and save your company from possible heavy penalties and compliance breaches. A little while back, we have seen the GDPR compliance violation at H&M with the largest financial penalty following illegal employee surveillance. The company could have avoided the threat if it had followed privacy compliance policies and addressed the data within data classification plans.

Process of Data Classification

  1. Establish a data classification strategy, including goals, workflows, data classification scheme, data owners, and managing data
  2. Figure out the critical information you store
  3. Apply tags by labeling data
  4. Use results to enhance security and compliance
  5. Data is vigorous, and classification is an ongoing process
Data classification process

Guidelines to Classify the Data

Enterprises can achieve data discovery through various automated tools that are available in the industry. But most importantly, your enterprise should define the classification scheme and criteria initially. At Sun Technologies, we follow the reliable and demonstrated framework to classify, declassify, and secure sensitive data. The following are some of the steps from our extensive framework.

1. Define the business objective

The initial step is to understand the business objectives and evaluate your enterprise’s risk and compliance needs. Then categorize the ranking of risks and a list of initiatives to reduce the risk. 

2. Understand the requirements and classify data accordingly

At times, it is challenging to meet the compliance needs to meet the critical business requirements. Thus, a reliable data classification program needs to be developed to classify the data according to its risk and value. We have established a dedicated and demonstrated extensive framework by complying with SOX, NIST, CERT, PCI, PII, HIPAA, and many other regulatory requirements. The scheme is a combination of people, process, innovation, and technology, which will find new data elements, shadow IT, structured and unstructured data. And also, it discovers sensitive data in areas you usually never expect. It will identify the broken process, bad actors, data drift, and declassify the data. With that information, We would suggest implementing a sufficient number of DLP tools to secure data-at-rest, data-in-process, and data-in-transit across the IT industry to deliver comprehensive data security. 

3. Categorize, Monitor, Track, and Response

Including a proper incident life cycle management to data classification is vital. It reports the incident occurrences and recommends how to respond to that incident, perform the root cause analysis, etc. Sun Technologies has a fully managed SIEM and SOAR capability, which will get the logs and events from your DLP solutions and associate them with external threat intelligence feeds to give environmental and functional alerts through a dashboard. This enables our SOC team to efficiently detect and resolve attacks of all types by providing compliance status, risk profile and categorized incidents that produce the biggest threat to data.

Benefits of Data Classification

Classifying data helps enterprises ensure regulatory compliance and enhance data security.

Data Security

Classification is an efficient way to safeguard your valuable data. Identify the types of data you store and discover the location of sensitive data, and this makes you to:

  • Prioritize your security measures, revamping your security controls based on data sensitivity
  • Recognize who can access, change or delete data
  • Evaluate risks, such as breaches that impact business, ransomware attack or other threat

Regulatory Compliance

Compliance regulations need enterprises to secure data, such as cardholder information (PCI DSS) or EU residents’ data (GDPR). Classifying data allows you to find the data subject to specific regulations so you can apply them for the required controls and pass audits.

The following defines how data classification can help you meet general compliance standards

  • GDPR— Data classification helps you endorse the rights of data subjects, including satisfying data subject access request by restoring the set of documents with information about a given individual.
  • HIPAA— Knowing where all health records are stored helps you implement security controls for the right data protection.
  • ISO 27001 — Classifying data based on value and sensitivity helps you meet requirements for preventing unauthorized disclosure or modification.
  • NIST SP 800-53— Categorizing data helps federal agencies suitably plan and control their IT systems.
  • PCI DSS— Data classification allows you to find and protect consumer financial information used in payment card
Share on facebook
Facebook
Share on twitter
Twitter
Share on linkedin
LinkedIn

Cloud Data Security Trends

Cloud Data Security Trends

Data is shifting to cloud

Enterprises are increasingly storing a considerable amount of sensitive data in public clouds. But, initiatives to protect that data lag similar to on-premises efforts. Substantial amounts of critical data are not secured enough. Data security is the most crucial factor to consider.

One of the most significant challenges for enterprises is to make sure the data remains secure and tracked as the data travels throughout the cloud environment. Moving to the cloud changes a company’s attack profile; the surface area increases. By adapting both visibility, to figure out sensitive data and automation to enforce policies, enterprises can better reduce threats.

Consider the following to strengthen your data security in cloud computing.

  • Categorize your sensitive data        

  • Implement the least privilege model

  • Audit activity across your environment

  • Use data masking techniques that include encryption

  • Make sure your cloud provider provides an SLA that meets your availability needs

These best practices enable you to achieve data integrity, confidentiality, availability, and data security in the cloud.

Cloud data security challenges

No wonder the expectations and challenges correlated with securing cloud resident data incorporated a combination of technology, people, and process—with the most significant challenge being employees signing up for cloud applications and services without IT approval.

1.Lack of Visibility/Control

One of the advantages of using cloud-based technologies is that the user does not have to manage the resources required to keep it working (For example, servers). Yet, handling off the responsibility for managing the up-to-date software, platform, or computing resource can result in less visibility and control over that asset.

2.Managing the effect of the Shared Responsibility Security Model

The Cloud Service Provider (CSP) is responsible for protecting its network and infrastructure. Their SecOps team observes the computing, storage, and network hardware composing the cloud platform. As a result, the client is responsible for their data and application security, such as patching and access control problems that arise with working in the cloud. 

3.Fast Changes and High-Volume Feature Releases

CSPs often introduce new features and solutions to attract new customers and keep current customers from defecting. Few of these changes can have massive effects on SecOps. 

4.Immaturity of IaaS and SaaS Security

CSPs make multiple security tools available in their cloud platforms, including cloud-based IDSs and virtual web application firewalls. However, these CSP security offerings subject to be incomplete compared to their conventional data center counterparts. This gap makes SecOps teams having to install and manage their tools.

5.Managing Hybrid and Multicloud Architectures

Few enterprises are 100% in the public cloud. Many companies have data across public, on-premises, and private cloud architectures, and others have applications and data that bridge AWS, Azure, and Google cloud. Such hybrid cloud architecture builds up tricky security dynamic for SecOps to track. It requires many overlapping and redundant systems for various cloud instances. This increases the possibilities of human error and the need for automation further.

6.People Shortage

A shortage of proficient, available, and affordable SecOps workforce is becoming an increasingly urgent issue for almost every security enterprise that’s working in the cloud.

Causes of Data loss associated with public cloud

The growing use of sanctioned and unsanctioned cloud-based applications with security programs for the cloud that are often less mature than present on-premise initiatives has led to a significant loss of corporate data. The main contributors to data loss included violations of security policy, the implications of employees using their own devices, and the lack of adequate access controls.

Enterprises are making investments across various data security disciplines

Enterprises figured out massive enhancements needed to protect sensitive data regardless of location. And 40% of respondents expect cybersecurity spending to increase considerably.

According to McAfee, the organization’s use of cloud solutions grown by 50% between January and April 2020. Simultaneously, external threat actors increased by 630%. The report also focuses on cloud-native security considerations as critical for company workloads operating in the cloud. In response, some tasks should be automated, such as:

  • Configuration management
  • Cloud security administration
  • Other manual processes

Prediction: Enterprises must carefully realize and follow the shared cloud security responsibility model: vendors are accountable for operating a protected IT infrastructure. Customers are responsible for managing encryption, access, and disaster recovery protocols.

Different teams presently handle cloud and on-premises data security, but most enterprises aim for a unified function

The capability to obtain greater operational efficiencies by unifying security policies across on-premises and cloud-resident data regulate compliance.

Ensuring data confidentiality and data security in the cloud

Ensuring data confidentiality is complex for both maintaining trust in your enterprise and meeting compliance needs. The high-profile breaches consistently in the news highlight the high cost of data security problems. In general, national and international guidelines that include the Health Insurance Portability and Accountability Act (HIPAA) and the General Data Protection Regulation (GDPR) need enterprises to ensure the security and privacy of various critical data types impose including stiff fines for compliance failures.

The most massive threat to data confidentiality is the capability for unauthorized access to sensitive data. There are two methods for dealing with this risk, which can be used together or individually:

 Discover and categorize your data. To ensure the sensitive data is stored only in protected locations and accessible only by authorized users. Also, you need to know which of your information is exposed and the place of the data. Knowing which data needs protection will help you set priorities and apply multiple security controls based on classification outcomes.

Use data masking. This approach involves securing sensitive data by encapsulating it with characters or other data. Data can be hidden in real-time or its original location when requested by an application or a user.

One of the secure and most common data masking approaches is encryption, making it impossible for unauthorized parties to view or realize stored or shared data. Encryption can be asymmetric, which needs a public key and a private key, or symmetric, which utilizes just one private key for encryption and decryption. Actual encryption key management is involved; in general, you must create policies that guarantee only trusted people can access them. Cloud encryption solutions help you to prevent prying eyes from accessing your secured data.

Summary

To summarize, while cloud migration can drive your business growth, any compromise in cloud security can push you down. Passwordless methods are popular nowadays, and they ensure safety, as they are used to hold out against cybercriminals, who try to hack passwords for accessing cloud-based apps. One single method or technology won’t protect your cloud data, but a cluster of multiple technologies can surely complement one another. Enterprises invest heavily in the cloud security workforce, i.e., towards skills, competencies, and governance tools. An organization’s own IT department’s role is indispensable as security and privacy have always been two major checkpoints in adopting cloud.

Share on facebook
Facebook
Share on twitter
Twitter
Share on linkedin
LinkedIn

Run Serverless containers on AWS / GCP / Azure

Run Serverless containers on AWS / Azure / Google Cloud

What Is Serverless Cloud Computing?

Serverless is a cloud computing deployment model to execute applications by running functions on-demand. The main advantage of serverless is that it allows an application, or part of an application, to be deployed in whenever required. It does not require an always running execution environment. serverless computing is an execution strategy for the cloud. A cloud provider may be google cloud or Aws or Azure, dynamically allocating and charging the user for—only the compute resources and storage required to deploy a specific piece of code.

Thus, serverless execution models can help to save money. Instead of maintaining a server 24/7, companies can deploy code in a serverless environment and pay only for the consumed resources.

serverless execution models

Some of the brand cloud migration consulting providers of IT help in the form of cloud services are Amazon Web Services, Google Cloud, Microsoft Azure, IBM Cloud, etc. Undeniably, there are other best-quality companies in this escalating international mix, with names such as Salesforce, Alibaba, Rackspace, TenCent, Equinix, Oracle, Dell EMC, and other Tier 2 and 3 players. But just because these companies are not in the top four doesn’t mean they won’t be the right choice for your business. Smaller and more professional is what many organizations prefer and search out.

This article will explore three of the top four at a high business level. The effect of the Big 3 in the market, think of them in this prospect: 

  • Next-gen and small-to-medium-size companies usually buy azure
  • Google Cloud used mainly by developers working on enterprise applications; and
  • AWS is being bought by everybody else—about one-third of the market

Container Workloads: “Do It Yourself” vs. Managed Services 

The most crucial factor you have to examine when running container workloads on cloud providers is whether you need to use managed services or commodity services (“do it yourself”).

 “Do It Yourself” gives you more control over your container environment’s abilities. The typical cloud services can save time in maintaining the systems, as they are centrally managed and more stable. Altogether using managed services to run container workloads can free up your engineering resources to focus on higher-value work.

There are various options within managed services, such as how much of the infrastructure management you need to control and how much you want the cloud providers to take on for you. Usually, the trade-off is between cost, convenience, and control.

What Services Does Each Cloud Provider Offer?

Kubernetes plays a prominent role in the container function space, and all three principal providers deliver a managed Kubernetes service. Initially, it was Google Cloud with Google Kubernetes Engine (GKE) in 2014, followed by Azure with Azure Kubernetes Service (AKS) in 2017, and ultimately AWS followed with Elastic Kubernetes Service (EKS) in 2018. While there are dissimilarities in their details, all of these services are broadly alike in their general contribution. 

Each cloud provider also provides a registry service to build and store your container images. Google has Google Container Registry (GCR), Amazon has Elastic Container Registry (ECR), Azure has Azure Container Registry (ACR). 

What Services Does Each Cloud Provider Offer?

What is AWS, Azure, Google Cloud: Advantages and Disadvantages

1. AWS

The cloud service platform from Amazon is Amazon Web Services (AWS), which offers services in various domains that include storage, compute, delivery, and other functionalities.  AWS helps enterprises to scale and grow. AWS uses these domains in the form of services that can be used to deploy various types of applications in the cloud platform. These services work with each other and yield a productive and scalable result. AWS services are divided into three types:

  • Infrastructure as a service (IaaS)
  • Software as a service (SaaS)
  • Platform as a service (PaaS)

Amazon launched AWS in 2006. It is the most-purchased cloud platform among existing available cloud platforms. Cloud platforms provide many advantages such as cost minimization, management overhead reduction, and many others.

AWS cloud service platform

Advantages:

  • AWS was first to market in 2006. More than two years, there were no serious competitors. It bolsters this leadership by continuing to invest in its data centers. Thus its dominates the public cloud market
  • One of the main reasons for its popularity is the enormous scope of its global operations.
  • AWS has a massive and growing array of available services. And also the complete network of global data centers
  • Gartner has outlined AWS as “the most mature, enterprise-ready (cloud services) provider, with the vastest abilities for ruling a huge number of resources and users “

Disadvantages

  • Expensive
  • They also have adversity managing these costs effectively when running a considerable volume of workloads on the service
  • Complex process

2. Microsoft Azure

Azure provides a set of container services that is similar to AWS. AWS Fargate and ECS are Azure Container Instances (ACI), an alternate clustering solution for containerized workloads. The main difference between AWS ECS and ACI is that ACI is sketched from the ground up to run on servers managed by Azure rather than by the users themselves. Ultimately, Azure’s equal to App Mesh is Azure Service Fabric.

Azure is designed and built by Microsoft and launched in 2010. It competes directly with AWS by offering services in domains that include database, developer tools, compute, storage, networking, and other functionality, enabling enterprises to grow their businesses.

Azure services are classified as:

  • Platform as a service (PaaS),
  • Software as a service (SaaS) and
  • Infrastructure as a service (IaaS)

They all can be used by software employees and developers to create, manage, deploy services and applications through the cloud.

azure developer services

Advantages

  • Microsoft came four years after AWS but gave itself a kick-start by taking its popular in-house business software– Office, Windows Server, Dynamics Active Directory, SQL Server, Sharepoint, .Net, and others
  • A big reason for Azure’s success is apparent: Many companies deploy Windows and other Microsoft software. Because Azure is fully integrated with these other applications, businesses that use a lot of Microsoft software prefer to use Azure
  • Existing Microsoft enterprise customers can enjoy Significant discounts on service contracts

Disadvantages

  • Gartner has had some reservations about the design and makeup of the platform. “While Microsoft Azure is an enterprise-ready platform, Gartner clients report that the service experience feels less enterprise-ready than they expected, given Microsoft’s long history as an enterprise vendor,” the researcher said
  • This doesn’t occur with all customers, but there are enough unsatisfied customers to take into account their objections

3. Google Cloud

Google Cloud is a cloud computing platform. It was developed by Google and launched in 2008 and written in C++, Java, Python, including Ruby. It also offers various services that are IaaS, PaaS, and Serverless platform. Google cloud is classified into different platforms, such as Google Compute Engine, Google Cloud Datastore, Google Big Query, Google Cloud SQL, Google App Engine, and Google Cloud Storage. Google cloud platform offers high-level computing, networking, storage,  and databases. It also provides different networking options, such as cloud CDN, virtual private cloud, cloud DNS, load balancing, and other additional features.

Even before Google Cloud emerged, Google was an innovator in container-based services and even containers themselves: Google engineers were incorporated into the introduction of containers to the Linux kernel by introducing groups back in 2006.

serverless computing platform

Advantages 

  • Users count on Google’s engineering expertise.
  • Google has an ideal offering in application container deployments
  • GCP focuses on high-end computing offerings such as machine learning and big data, analytics
  • It also delivers substantial scale-out options and data load balancing

Disadvantages 

  • Google doesn’t deliver as many different services and features as AWS and Azure
  • Although it is quickly expanding, it also doesn’t have as many global data centers as AWS or Azure

Conclusion

While AWS or Azure might better meet your production needs, GCP may be the best choice for new product assessment and initial development workloads.  AWS grabs the prize with 62 percent (for now) when it comes to market share. This is due to the length of time on the market, and the number of features reaches. However, that doesn’t certainly translate to what’s better for your company. Our aim with this head-to-head comparison is to help enterprise owners like you make decisions. If most of your business functions run on Microsoft products, Azure might work better for you. Companies that need less reach and more innovation might prefer Google Cloud Platform.
In the end, the choice is yours. Choose wisely
Share on facebook
Facebook
Share on twitter
Twitter
Share on linkedin
LinkedIn

Understanding Lift and Shift Cloud Migration: Best practices to follow

Understanding Lift and Shift Cloud Migration: Best practices to follow

Cloud Adoption

Migrating to the cloud is a complex process that must be customized to address the technical, functional, and operational needs of an organization. A successful migration strategy should not only address the short-term aims, such as decreasing hosting costs, but also the long-term goals, like better alignment between IT and business objectives. To meet these goals, organizations tend to focus on three main cloud migration strategies. We’ll explore each below.

3 Types of Cloud Migration Strategies

The process, method, and tools for migrating workloads to the cloud are considerably dependent on the aimed cloud migration models: IaaS, PaaS, and SaaS. Let’s have a look at each of these migration approaches.

 IaaS (rehost, replatform)

  • Moving applications to an IaaS (Infrastructure-as-a-Service) model denotes moving an existing application or workload from on-premise deployment to a cloud-giver’s infrastructure
  • With this approach, there are no severe architectural modifications to make.
  • The simplest way to migrate applications to Infrastructure-as-a-Service is rehosting using the “lift-and-shift” migration approach.

 PaaS (refactor, rebuild)

  • The Platform-as-a-Service method uses cloud-provider configured environment to run the code of your application
  •  This approach needs applications to be importantly refactored or modernized to fit into the destined cloud platform
  • This migration approach will include certain factors such as library updates, code rewrites, deployment pipeline modifications, and more for the workload to get fit into the Platform-as-a-Service application framework
  • In a few circumstances, the application might have to be entirely rebuilt from scratch
  • In both cases, the changes mean spending a reasonable amount of money and time.

 SaaS (replace)

  • Adopting a Software-as-a-Service model denotes replacing components or functionalities of your existing workload with a SaaS service offered by another enterprise
  • While this strategy may be quicker than a PaaS migration, it also has all the challenges of adopting a new technology. This would include creating new interfaces, restructuring parts of the architecture, educating your teams on its use, and more.
  • Other factors such as access management, complications of data migration, vendor lock-in, and so on are also a factor.

Among all these options, the simplest and fastest way to get an existing application to the cloud is with a lift-and-shift, Infrastructure-as-a-Service migration

What is Lift and Shift?

“Lift and Shift” has proven to be a unique approach for many organizations looking for a quick, low-risk method to move their workloads to the cloud. But what if you had an additional option to lift and optimize your primary infrastructure as part of your cloud journey?

Think strategy: Lift–and-shift is one of the approaches to migrating your apps to the cloud, which means moving an application and its correlated data to a cloud platform—without restructuring the application.

There’s no all-purpose transition for moving an application from your on-site data center to the cloud. However, there are accepted core migration paths; many consider lift and shift (re-hosting) to be among them. Life-and-shift provides a way for businesses to secure their investments in business logic, workflow, and data trapped in on-premises hardware.

Lift and Shift Cloud-Migration

Migrating your application and correlated data to the cloud with less or zero changes is the lift-and-shift migration approach. Applications are expertly “lifted” from the present environment and “shifted” just as it is to new hosting premises, which means in the cloud. There are often no severe alterations to make in the data flow, application architecture, or authentication mechanisms.

The lift-and-shift approach opens ways to IT modernization by moving to open and more expandable architecture in the cloud. Organizations ponder lift-and-shift for solid business reasons such as cost-effectiveness,  improved performance, and flexibility.

Nevertheless, one business strategist provides a more organic explanation. He confronts that applications perform and emerge depending on their environments; and that the cloud offers larger size and diversity of services versus on-site data centers.

When is the Lift-and-Shift Cloud-Migration Model the best fit?

With the lift-and-shift method, on-premise applications can move to the cloud without remodelling. Since they cannot take full advantage of native-cloud features every time, this may not be the most cost-effective migration path. To avoid bounce back, businesses require a cost-allocation strategy and clear-cut roles within their organization to monitor cloud spending. This will most likely need additional tools.

Lift-and-Shift Applications can Deliver

  • Rapid+ cost savings. Companies lowered IT costs by more than 25% through lift-and-shift
  • A way to the cloud now
  • Cloud disaster recovery. Moving data to a cloud platform gives companies a second, largely available, site
  • Relaxation from technical debt. Legacy systems tend to be slow and extravagant to maintain. Extra horsepower, like Amazon’s x1e.32xlarge, may offer the boost you need now
Cloud-Migration Model

Advantages of the Lift and Shift Approach

Let us evaluate some of the principal benefits of using the Lift-and-Shift method:

  • The lift-and-shift cloud migration method does not demand any application-level modifications as it is solely being re-hosted on the cloud.
  • Workloads that demand expensive hardware ( ie. graphical cards or HPC) can be moved directly to specialized Virtual Machines in the cloud, which will give related capabilities.
  • A lift-and-shift approach permits you to migrate your on-premise identity services components that include Active Directory to the cloud with the application.
  • Compliance and security management in a lift-and-shift cloud migration is similarly easier as you can translate the specifications to controls that should be deployed against storage, compute, and network resources.
  • The lift-and-shift method uses the same design constructs even after the migration to the cloud. That means there are no essential changes needed in terms of the business procedures associated with the application and monitoring interfaces.

 

 

Lift and Shift Migration Approach

Cloud Migration Steps: Ensuring a Smooth Transition

Step 1: To begin with, select the platform you wish to migrate to.

Step 2: Evaluate all the connections in and out of the application and its data.

Step 3: If you are lifting and shifting multiple applications, consider automating the various migrations.
Step 4: It would be best if you consider containerization to duplicate the current software configurations. This will also permit you to test configurations in the cloud before moving to production.
Step 5: Take the back up of databases from the existing system and also the supporting files. Restore the backups once the new database is ready.
Step 6: Once migrated, test the application.
Step 7: Check that all the existing data compliance and regulatory needs are running in the new cloud deployment.
Step 8: During the migration, do not introduce new features. This may result in many hours of additional testing to ensure you have not created any new bugs.
Step 9: Once testing is done, retire your old systems.

Ultimately, we would always advise working with a provider who has expertise in migrating applications. Sun Technologies can help you decide what the right method of migration is for your organization,, offer guidelines for the future of your application, and ensure that this is all hitched in with your broader cloud strategy.

Lift and optimize: Modernize and Migrate

Take a look at how our clients have benefited from our transformational method to cloud migration with the below capabilities:

  • Transformed a 105,000+ line program and later was awarded to modernize the rest of the existing applications
  • Effectively managed the complexity of effectively project that contained more than 250,000 lines and more than 24,500+ test cases
  • Upgraded Windows Operating Systems to supported versions
  • Swapped monitoring and management tool-chains
  • Delivered workloads into management tooling and deliver, both Azure and native AWS
  • Supports any standard Microsoft supported upgrade path (eg, no 32-bit to 64-bit upgrade)
  • All automation runs on a clone of source in the target cloud to preserve rollback
  • Applies to Windows 2003 SP2 and above
  • Customer UAT’s applications before cutover

Trusted Cloud Migration Partner

You require a cloud migration provider to traverse costs and technical complexities. Sun Technologies is one of the secure, fast, automated cloud onboarding solution companies with governed migration services. It also strengthens APIs to mirror existing server environments and move them into private, public, or hybrid clouds without interrupting existing workload functions and performances.

Benefits of Cloud Adoption for Your Business

  • Fast migration times escalate client’s cloud adoption and time to value
  • Less, predictable downtimes to make sure maximum application uptime for constant 24/7/365 operations
  • A successful cloud migration guarantees both speed and zero risks. Companies can’t afford to have downtime or wait for snags to smooth out. At Sun Technologies, we do not touch the live copy so that you can test on the replicated copy in the cloud until cutover. No disruption, no downtime
  • Re-engineering applications become more straightforward once the data is in the cloud
Share on facebook
Facebook
Share on twitter
Twitter
Share on linkedin
LinkedIn

Replatforming the Legacy COBOL Applications to a Modern Technology for a Leading Financial firm

Case Study

Replatforming the Legacy COBOL Applications to a Modern Technology for a Leading Financial firm

Whom we worked with

A Leading Financial Institution in New York State. It is a Federally-chartered wholesale bank providing a reliable source of liquidity to financial institutions

Our Solution

  • Provided an automated migration path allowing the bank’s resources to concentrate on maintenance, test and enhancement of the new applications
  • Proposed “MVC- N Tier” architecture by enhancing the performance of the systems
  • Converted the 50000 COBOL lines to only a 10000 lines JAVA program which is more readable and easy to understand
  • Achieved genuine modernization of the legacy applications by re-hosting the applications from Microfocus platform to an open source platform
  • Automated the entire test cases of the COBOL program for easier migration
  • Suggested to re-engineer the long running reports to a more stable DB2 environment stored procedure for reports generation
  • Additional features such as Rich responsive user interface and cross browser support were also incorporated in the converted applications
  • Reports were migrated to a more flexible report format- crystal reports

Challenges

  • To Rewrite the 50000 plus COBOL lines into a new programming platform
  • To achieve genuine modernization of the legacy applications by re-hosting application environment to updated platforms
  • To automate the testing of the applications with new features being added iteratively

Impact

  • Developers and Testers were well aware of the process, technology and the culture during migration of the applications
  • Suggested some initial program conversion to be tested and moved into production
  • Build a flexible and highly performing environment between different architectures and platforms for easier migration

How we helped

  • Understand the applications and timelines for migrating critical applications
  • Created a unified automated application process, without affecting everyday business operations
  • Rewrite the full code that can be easily understood
  • Dedicated offshore team to support the migration of applications
  • Check the compatibility with standardizing JAVA as the development language

Cloud Migration

Trusted Cloud Migration Technology Partner

Trusted Cloud Migration Technology Partner

Cloud Migration Services

Sun Technologies offers end-to-end IT services to deliver effective cloud migration including Consulting & Assessment (ROI Analysis for Cloud), design, concept proof, implementation and testing.

Our Cloud architects provide the Technology advice, implementation know-how, and resources (tools, people etc.) to ensure smooth migration to the cloud.

Proven track record on what customers look for Cloud Migration services provider?

Leveraging assessment and roadmap, we ensure the rapid and successful migration of applications, datacenters, data, and platforms

Application Migration

  • Migrating On-Premise workloads over cloud
  • Legacy application migration to cloud (Application Modernization)
  • Experienced resources to handle business-critical application migration

Data Center Migration

  • ON-Prem to Cloud / Hybrid Cloud Migrations
  • Automated Disaster Recovery process
  • Compliance (Add Security and compliance expertise)
  • Expertise on AWS, Google Cloud, Microsoft Azure or IBM Cloud
  • Certified professionals and hands-on live project experience

Data Migrations

  • Execute end-to-end data migration of multiple databases to new servers
  • No downtime during Migration and source database is fully accessible during the transition
  • Follow stringent compliance to industry standards of ETL
  • Our professionals execute both homogeneous and heterogeneous database migrations
  • We offer on-the-go live support and 24×7 assistance

Platform Migration

  • End-to-end Platform Migration solution based on your environment
  • Executing end-of-life migration to determine the suitability of new platforms 
  • Testing of live load in the new platform
  • Complete stack of technology and tools to address every unique Platform Migration

             The Cloud Platforms we work on

What are the Benefits of our Cloud Migration Services?

  • Risk-free Migration with uncompromised security and Data Integrity
  • Experienced in migrating high volume workloads of complex systems
  • Certified Associates on AWS, Azure, GCP
  • Zero Down-Type Seamless migrations
  • Hybrid Architecture
  • Automation Adaption for Migration, Validation, Infrastructure setup on cloud




Case studies

Case studies

Reach out, we'd love to hear from you!