Cloud Based Logistics Software: How to Migrate Legacy Software and Microservices Modules (Amazon Web Services)

Have you already come to the point where you need to reconsider your supply chain strategy? This is likely because your legacy systems get more expensive to manage and struggle to cope with the after-pandemic state, economic crisis, and all-remote working environment. This scenario has already put on track a massive implementation of cloud based logistics software, with 41% of companies doing it for cost reductions, 53% for improved resiliency, 48% for sustainability, and 41% for increased visibility over real-time data to take action faster.

What's even more intriguing is that there's no longer any hesitation among supply chain executives about cloud migration. The key question now is how to do it efficiently while maximizing ROI.

This article explains how to do it right and why AWS is a top choice in addressing logistics challenges.

Microservices: the foundation of cloud-native development

It’s clear from the Accenture survey mentioned above that cloud transformation is key to lowering operational risks and combating disruptions companies face during unpredictable times. This is made possible by the microservices-based nature of modern software architecture.

Microservices are the fundamental building blocks of cloud-native development, capable of creating more resilient, flexible, agile, and robust operations. This is especially critical in the supply chain industry, where ensuring a seamless flow of goods remains paramount regardless of external challenges.

In the context of the supply chain industry, we can think of microservices as a way to break down complex logistical operations into smaller, specialized tasks or components. Each component or "microservice" is responsible for a part of a specific function within the supply chain, such as order processing, inventory management, or route optimization.

Just like team members in a well-organized group, these microservices operate independently but communicate seamlessly through APIs. For example, the order processing microservice can send information to the inventory management microservice, ensuring product availability is tracked and managed in real time.

Microservices provide an optimal pathway for digital transformation, ensuring a smooth shift from legacy architecture to the desired target architecture.

For businesses considering this change, it’s best to start by analyzing their existing legacy applications to identify and isolate those functions that can exist independently as services. This marks a small start in a larger process - replacing legacy system parts with new microservices step by step.

One major advantage of microservices is their capacity for independent development and deployment. This means organizations can change individual applications or microservices without disrupting the entire supply chain operation. This selective approach saves money upfront and creates a spacious room for additional modernization in the future.

Major cloud logistics platforms: AWS, Microsoft Azure, and Google

For supply chain innovators, the migration journey starts with recognizing the challenges they face in their operations. This first step paves the way for the next one: choosing the technology providers that will best address their specific needs.

Among the well-known providers of cloud computing logistics services are Amazon Web Services (AWS), Microsoft Azure, and Google Cloud. In the final quarter of 2022, Amazon Web Services (AWS) led the cloud infrastructure market with 32%, followed by Microsoft Azure at 23% and Google Cloud at 10%.

As they cater to various business needs and preferences, each cloud provider brings to the table its unique strengths. Let’s take a quick overview.

1. AWS (Amazon Web Services)
AWS is the most widely recognized leader in cloud computing, offering more than 200 services across computing, storage, databases, analytics, machine learning, and more. It is primarily used to handle many immediate requests, adapt to changing user demands, and expand to new geographical markets.

Strengths: Known for scalability, reliability, and global reach, AWS serves organizations of all sizes, from startups to Fortune 500 companies, but is best for large-scale enterprises and ambitious projects.

Use cases: Popular for hosting websites, running applications, and handling data storage, AWS also excels in areas like IoT, serverless computing, and cloud-native development.

2. Microsoft Azure
Azure by Microsoft is the second most established provider of a robust cloud platform with strong integration into Microsoft's software ecosystem, including Windows Server, SQL Server, and other Microsoft products. The IoT-focused infrastructure offers a range of tools for designing, maintaining, and configuring sensors as well as powerful real-time data analytics, machine learning, and insight processing capabilities.

Strengths: Enterprises favor Azure for its hybrid cloud solutions, AI and machine learning capabilities, IoT products, and extensive developer tools.

Use cases: Azure is used for hosting Windows-based workloads, running enterprise applications, and seamlessly integrating with Microsoft development tools like Visual Studio, all while providing robust security and compliance capabilities.

3. Google Cloud
Google Cloud offers cutting-edge cloud solutions focusing on data analytics, machine learning, and application development, mostly suitable for small and medium businesses. It has a special offer for startups registered in accelerators or venture funds, allowing them to use its infrastructure at discounted rates.

Strengths: Known for its data analytics and AI prowess, organizations choose Google Cloud when seeking advanced data-driven insights and innovations.

Use cases: Google Cloud is great for data analytics, machine learning projects, and cloud-native application development, leveraging Google's expertise in these domains.

Why is AWS the leader in cloud services for logistics?

Having been in the market for nearly 17 years, AWS is the most mature cloud provider, serving millions of customers worldwide across various use cases. As we mentioned, it provides a wide range of services, including basics like computing and storage, as well as newer technologies like ML, AI, data analytics, and IoT.

So, what does it all mean for the logistics industry?

Below we list 8 reasons why AWS is a top choice for supply chain organizations in particular.

#1 AWS follows a pay-as-you-go model.

Businesses pay only for what they use, allowing them to align their expenses with their actual needs and adapt to changing demands without long-term commitments. This flexible approach aligns perfectly with the dynamic nature of supply chains, where demands can fluctuate. Moreover, it creates room for businesses to experiment with new services and technologies without a significant upfront investment, enabling effective budget allocation.

#2 With AWS, businesses can scale their infrastructure up or down as needed.

AWS’s flexibility is a good fit for various logistics situations. Whether there's a surge in product demand or a need to streamline operations during low-season periods, AWS's flexibility allows supply chain organizations to scale their infrastructure up and down, ensuring the right capacity at the right time.

#3 AWS has robust security that safeguards sensitive information.

In logistics, where handling extensive data is a daily norm, stringent security measures are paramount. AWS recognizes its significance by offering a comprehensive security infrastructure with security features as follows:

• Advanced encryption techniques, such as SSL/TLS for data in transit and AES-256 encryption for data at rest.
• Identity and Access Management (IAM) allows to create precise access policies, define roles, and allocate permissions to users, groups, or AWS services, ensuring secure login with options like AWS Multi-Factor Authentication and AWS Single Sign-On (SSO), which significantly reduces the chances of unauthorized access.
• Compliance certifications like ISO, SOC, PCI, HIPAA, etc., ensure adherence to industry-specific security standards, making it easier for logistics organizations to comply with regulatory mandates.
• Security monitoring and logging via services like AWS CloudTrail and Amazon CloudWatch for continuous security monitoring and logging.
• Distributed Denial of Service (DDoS) protection which ensures the availability of critical logistics systems even during cyberattacks.

#4 AWS constantly innovates with automated AI and ML solutions.

AWS offers logistics companies AI and ML capabilities to enhance operations, including predictive analytics, automated routing, demand forecasting, and much more.

Moreover, in 2016, Amazon introduced many new AI services to compete with Google's Cloud AI. They've since added services like SageMaker, which quickly trains machine learning models for faster use, and AWS DeepLens, a smart video camera with deep learning capabilities. AWS DeepLens is valuable for developing innovative solutions like object recognition, anomaly detection, and automation in warehouse operations.

#5 AWS has 102 availability zones within 32 geographic regions and 550+ points of presence around the globe.

For supply chain companies, this expansive network provides a strategic advantage. It ensures low-latency access to cloud resources, data storage, and services in close proximity to key markets and distribution hubs. Moreover, this global reach enhances disaster recovery and business continuity, helping supply chain companies manage risks and stay resilient worldwide.

#6 AWS provides a highly secure data transport solution designed for handling massive volumes of data, reaching petabyte scale.

This gives logistics and data-driven businesses a dependable method to securely manage their extensive data needs, improving data transfer, storage, and access within AWS. This is especially valuable for logistics companies looking to efficiently move vast volumes of logistic data while minimizing the associated high network costs.

#7 AWS allows logistics companies to integrate their existing applications, management tools, and databases, ensuring a smooth migration process.

By easily connecting their current technology stack with AWS, logistics firms can quickly start benefiting from AWS's advanced capabilities, such as cloud-based data analytics, machine learning, and scalable infrastructure. Moreover, when doing so, they also can maintain the continuity of their day-to-day operations without experiencing disruptions during the migration to the AWS cloud logistics platform.

#8 Matson's seamless migration of their entire IT infrastructure to AWS is a clear example of how AWS can handle various logistical challenges effectively.

Matson is a major player in U.S. transportation, dealing with ocean, intermodal, and logistics services. They've been around for 135 years and own 22 ships that mainly operate in the Pacific Ocean.

There's no better way to describe a personal success story than the way CIO Peter Weis did.

“We chose the AWS Cloud because it provides unmatched security, performance, and cost benefits. Having moved 100 percent of our enterprise applications from on-premises data centers to the AWS Cloud, we are now free to focus on further innovation.”

We can only add that numerous participants in the logistics industry need advanced IT systems to manage modern demands, resources, and logistic complexities effectively.

Just look at Matson, now running all its essential applications on the AWS Cloud. These consist of their specialized order-to-cash reservation and invoicing systems, terminal operations, international equipment management, national logistics apps, and customer-facing websites. This transition has empowered Matson to provide its customers with more efficient and seamless services across its entire transportation and logistics network.

Transform your logistics operations with the dynamic and adaptable nature of AWS cloud architecture. Check out our software architecture consulting services.

Opportunities offered by cloud based logistics software

You may already notice three substantial opportunities that cloud based logistics platforms provide, which are all over our discussion. We’d like to pinpoint them separately.

The power of data analytics for forecasting and decision-making.

Modern supply chains are highly complex, involving multiple stakeholders, global distribution networks, and a vast amount of data generated by IoT devices, sensors, and customer interactions. Many organizations aiming to gather, interpret, and use this information to base decisions on accurate data can greatly benefit from cloud offerings.

By moving to the cloud, logistic businesses can gain a holistic view of the supply chain. First, cloud based logistics platforms can handle large volumes of data, making it feasible to process and analyze vast datasets in real time. Second, cloud logistics software often includes advanced analytics tools, including predictive analytics, which can forecast demand, identify potential disruptions, and recommend optimal actions – which is especially valuable in the light of pandemic consequences, severe natural disasters, geopolitical risks, and other dynamic disruptions.

Integration of various supply chain components, accessible via an open API.

As mentioned earlier, the microservice architectural style allows independent maintenance and deployment of multiple components, applications, or services that communicate through APIs. For instance, when an order is placed, the order processing microservice can use an API to update inventory levels instantly. This fundamental capability opens the door to the integration of other logistic services and operations that work following the same logic.

In turn, customers can integrate these services into their own business systems and customize them based on their specific needs and preferences. For instance, a retailer may integrate order processing and inventory management services but not shipment tracking if they handle deliveries through a third-party provider.

All this means that cloud based logistics platforms offer a dynamic and adaptable framework. Businesses can use its capabilities to create customized cloud logistics solutions that meet their unique requirements, increasing efficiency, transparency, and collaboration in the supply chain ecosystem.

Cloud computing in logistics can lead to cost savings in maintaining in-house IT infrastructure.

Cloud for the logistics industry allows supply chain service providers to address the swift transformations happening within the industry. It’s primarily due to its pay-as-you-go model, which helps reduce IT expenses related to infrastructure maintenance and software setup, making it accessible to small businesses that prefer subscription-based technology.

Implementing microservices on AWS

The core microservice architecture on AWS can be summarized as follows:

• User instances operate on AWS CloudFront CDN, while static content resides in Amazon S3.
• Incoming traffic passes through Amazon Automatic Load Balancer (ALB), which directs it to the Kubernetes clusters running microservices within Docker containers on Amazon ECS.
• Data caching is handled by ElastiCache and storage is managed by databases such as Aurora, RDS, or DynamoDB.

This workflow guarantees limitless front-end scalability via CloudFront CDN, back-end scalability through ECS, and application resilience with caching and secure data storage options.

For a brief tutorial on implementing microservices on AWS, here is a step-by-step guide.

Modern web apps frequently rely on REST or RESTful APIs for communication between their JavaScript-framework-driven front-end and back-end. Static content is often served through CDNs like Amazon CloudFront and stored in object storage services like Amazon S3, ensuring minimal latency for end-users connecting via edge nodes.

AWS offers two primary approaches for supporting stable RESTful API operations: serverless computing with AWS Lambda and managed Kubernetes clusters using Docker containers via AWS Fargate.

AWS Lambda is a PaaS where users simply upload code, and AWS manages the rest. This serverless platform approach ensures speed, unlimited scalability, and cost-efficiency in running microservices. However, due to architectural limitations, Lambda is best suited for short-term operations, offering high levels of security and operational ease.

AWS Fargate, on the other hand, is a PaaS that provides managed Kubernetes clusters to run Docker containers with microservices. This requires some technical expertise but still delegates most responsibilities to AWS. Through API calls, users can manage clusters, run and stop Docker containers, operate load balancing, security groups, IAM, and more. AWS ECS and EKS grant easy access to container management or Kubernetes clusters for both in-house and remote teams.

To minimize latency, processed data from microservices should be stored in a database and cached. NoSQL databases such as AWS's options are ideal for scaling microservices due to their persistence-focused nature.

Three main approaches reduce operational complexity when designing and implementing microservices architecture using AWS:

1. API implementation: AWS API Gateway enables users to create and run RESTful APIs without managing servers, acting as an entry point for web or mobile applications.
2. Lambda implementation: AWS Lambda pairs with API Gateway for serverless applications composed of microservices through synchronous calls.
3. Deployment of Lambda-based apps: AWS CloudFormation with its Serverless Application Model (SAM) allows for discovery, definition, and management of serverless applications.

Users should also be prepared to address cross-service challenges such as service discovery, data management, communication, messaging, infrastructure state management, orchestration, decentralized monitoring, centralized log analysis, chattiness, and auditing.

AWS offers comprehensive solutions, both managed and open-source, for implementing microservices. This ensures efficient communication between services, reduced latency, and stable operations.

Challenges of adopting cloud computing in logistics

When companies think about moving their solutions to the cloud, they often run into common challenges that can slow down the process. Even if they're already using the cloud for logistics, they might still have concerns about it for different reasons.

Data migration

Logistics companies often deal with vast amounts of data, including shipment records, inventory data, and customer information. Any discrepancies or loss of data during migration from traditional storage systems to the cloud can have severe consequences on operations and customer service.

In certain situations, data breaches can even happen due to customer oversight or issues with third-party service integration. This can only mean you must thoroughly plan this process or look for help from experts who have access to reliable data migration tools to minimize disruptions.

Security and compliance

The logistics sector is subject to various industry-specific regulations and standards, such as those related to data privacy, cargo security, and quality control. While it's true that the cloud for logistics providers ensures a secure infrastructure and even compliance certifications in the case of AWS, it doesn't equate to guaranteeing data security and compliance during data migration.

So, ensuring data security and compliance of migrated data and applications often requires additional measures and responsibilities beyond what the provider offers. This case is more about a shared responsibility, where both the provider and the customer have roles in maintaining security and compliance.

Staff training

To make the most of a logistics cloud solution, staff members need the right training. This includes learning how to navigate cloud infrastructure, understand security protocols, and optimize cloud resources. Without these skills, organizations may find it difficult to realize the full potential of their cloud technology investments.

To ease this corporate cloud adoption, organizations should establish structured training programs tailored to the specific needs of each department. These programs should include hands-on training, workshops, and access to resources so employees can quickly become “cloud native” and effectively contribute to the organization's digital transformation.

Conclusion

Supply chain management has evolved significantly, with a global shift towards adopting the cloud, including AWS migration. Businesses are now prioritizing the gradual modernization of their application ecosystem to improve efficiency and freeing resources to rearchitect applications that drive business value.

ElifTech is a forward-thinking provider of innovative logistics cloud solutions. If you're interested in:

• Customized cloud based logistics software designed specifically for the 3PL community.
• Robust infrastructure, combining AWS with your business systems, advanced sales capabilities, and enhanced tracking technology.
• Modern, scalable, and reliable cloud logistics platform tailored to your evolving needs.
• Deep expertise of AWS's diverse set of tools and services.
• Exploring opportunities for implementing microservices through detailed system analysis.
• Developing and deploying microservices architecture tailored precisely to your unique business requirements.
• Getting continuous post-migration support and consulting services.

...then you can rely on our comprehensive offerings to upgrade your logistics and supply chain operations.

Modernize your logistics workflows with limitless cloud capabilities, AWS strengths, and the resilience of microservices architecture. Partner with ElifTech for a seamless transition to a smoother, more predictable, and sustainable future.