peax cloud

Case Study – AI4VI

selastyle — Mon, 19 Oct 2026 13:12:37 +0000

Secure and Automated AWS Infrastructure for Forensic AI

Industry: Healthcare, Government, Research, Artificial Intelligence
Platform: Amazon Web Services (AWS)
Client: National Center for Forensic Medicine / AI4VI
Services: Cloud Infrastructure Automation, Infrastructure as Code, Security, Cloud Operations, AI Infrastructure, Governance

About the Customer

The National Center for Forensic Medicine (NCFM), operating under the Israeli Ministry of Health, serves as Israel’s central authority for forensic identification and related medical examinations.
Following the events of October 7, 2023, the center faced unprecedented challenges in identifying victims through forensic methods, including comparisons of ante-mortem and postmortem medical imaging.
To advance forensic identification capabilities, Prof. Ilan Tsarfaty of Tel Aviv University initiated AI4VI (Artificial Intelligence for Victim Identification), an innovative research initiative aimed at accelerating forensic identification through artificial intelligence.
The project requires highly secure and scalable technology infrastructure to support AI research and the processing of sensitive forensic and medical imaging data.

Customer Challenge

The AI4VI project required a secure, scalable, and standardized AWS environment to support research involving sensitive medical imaging and forensic information.
Initially, the AWS infrastructure had been configured manually, creating operational challenges around configuration consistency, infrastructure deployment, and ongoing environment management.
As research activities evolved, manually provisioning and modifying AWS resources became increasingly inefficient and increased the possibility of configuration inconsistencies between environments.
The sensitive nature of forensic and medical imaging data also required strict security controls, including appropriate access permissions, encryption, data segregation, and adherence to AWS Israel Region data residency requirements.
The project needed an infrastructure operating model capable of supporting changing research requirements while maintaining consistent configurations and minimizing manual administrative tasks.
Managing such an environment required specialized AWS infrastructure, security, and automation expertise, allowing researchers to focus on developing AI identification capabilities rather than repeatedly configuring cloud resources.
The AI4VI team therefore worked with Peax Cloud to standardize and automate the AWS environment, simplify its operation, and establish a secure foundation for continued AI research.

Partner Solution

Peax Cloud Cloud partnered with the National Center for Forensic Medicine and Prof. Tsarfaty’s research team to implement a standardized, Terraform-based AWS infrastructure automation framework.
The solution includes:

Infrastructure as Code: Peax Cloud transformed the manually configured AWS environment into a Terraform-managed infrastructure, providing repeatable resource provisioning and consistent configurations.
Standardized Infrastructure Management: Reusable infrastructure configurations were established to simplify the deployment and modification of AWS resources as research requirements evolve.
Security and Access Control: IAM roles, encryption, and data segregation policies were implemented to help protect sensitive forensic and medical imaging information.
Data Residency: The infrastructure was designed to maintain forensic data within AWS Israel Region boundaries.
Scalable AI Infrastructure: Secure compute and storage resources were provisioned to support AI model development, medical imaging analysis, and future research workloads.
Operational Automation: Terraform automation reduces manual provisioning effort and provides a structured approach to managing cloud infrastructure changes.

Peax Cloud provides AWS infrastructure and automation expertise to support the management and evolution of the environment.
The Terraform-based approach enables infrastructure changes to be implemented consistently, reducing manual configuration activities and simplifying the deployment of resources for new research requirements.
Standardized infrastructure definitions also support consistent security configurations and make the AWS environment easier to maintain as the project expands.
This operating approach helps reduce the infrastructure management burden on research teams while providing a secure, scalable foundation for advanced forensic AI development.

Results and Benefits

Reduced Operational Complexity: Terraform automation replaced manually configured infrastructure with a standardized approach, reducing the effort required to provision and modify AWS resources.
Improved Infrastructure Consistency: Infrastructure as Code enables repeatable deployments, reducing configuration differences and the potential for manual errors.
Enhanced Security and Governance: IAM controls, encryption, and data segregation provide a stronger foundation for protecting sensitive forensic information.
Faster Research Environment Provisioning: Automated infrastructure deployment allows researchers to establish or modify AWS environments more efficiently, supporting faster experimentation and development cycles.
Improved Operational Manageability: Standardized infrastructure configurations simplify ongoing infrastructure changes and provide greater consistency as research requirements evolve.
Support for AI Innovation: The AWS architecture provides scalable infrastructure for developing advanced forensic identification capabilities, including future integration of additional medical imaging and forensic analysis methods.
Greater Focus on Research: By reducing infrastructure configuration and management complexity, the project allows research teams to devote more effort to AI model development and forensic identification innovation.
The solution provides AI4VI with a secure, reproducible, and efficiently manageable AWS foundation capable of supporting its continued research and future expansion.

The post Case Study – AI4VI appeared first on peax cloud.

CampusIL and MidLink Making Open edX Aspects Production-Ready

info@sela-style.co.il — Mon, 02 Feb 2026 15:11:07 +0000

Introduction

CampusIL, Israel’s national digital learning initiative led by the Israel National Digital Agency, set out to strengthen its data-driven decision-making capabilities. With more than 1.2 million learners and over 30,000 courses and Custom Course Experience (CCX) classrooms delivered to date, CampusIL required a scalable and reliable analytics platform to support educators, learners, and policymakers.

The foundation for this effort was Open edX Aspects, an open-source analytics framework designed to transform LMS activity data into actionable insights. While powerful, Aspects in its default form, can
be challenging to run at national scale, requiring careful attention to performance, scalability, and cost-effectiveness.

To address this, CampusIL partnered with MidLink Cloud, an AWS Consulting Partner specializing in cloud migration and modernization. MidLink focuses on delivering scalable, secure, and cost-efficient production-ready and well-architected cloud environments. Leveraging its expertise, MidLink implemented and optimized Aspects on AWS, transforming it into a robust, cloud-native solution capable of meeting CampusIL’s national-scale needs.

The Challenge

Open edX Aspects provides strong capabilities for learner analytics. However, institutions often encounter challenges when attempting to run it in production. Common hurdles include:

Scalability – efficiently handling millions of daily learner events.
Performance – delivering timely insights without delays.
Operational Complexity – deploying, maintaining, and monitoring large-scale analytics clusters.
Cost Optimization – avoiding unnecessary over-provisioning while ensuring stability.

For a national initiative such as CampusIL, with more than 1.2 million registered users, and a scope of Aspects’ database including more than 704.7 million events (representing a small part of CampusIL history, since January 2024 only, and with additional historical data to be added), these challenges risked delaying access to the actionable insights required to inform policy, course design, and learner support strategies.

CCX is an Open edX feature, which allows course creators to create a private, customized version of an existing course for a specific group of students. Using content from the original course, it enables a new schedule or private instance, and is frequently used by organizations/ instructors to run their own private MOOCs or to re-run content for a specific cohort. As part of its roadmap, Open edX plans to allow CCX functionality on top of Content Libraries.

CampusIL relies heavily on CCX to deliver hybrid learning that blends self-paced online study with teacher-led classroom instruction. This approach supports K–12 STEM – an Israeli Ministry of Education priority, aimed at building
a tech-ready workforce.

To further enhance the mechanism, CampusIL developed a unique process for opening a CCX course, which tags the classrooms according to knowledge fields, schools, areas and other data. This metadata is then ingested into Aspects, where it becomes available for reporting, filtering, and analytics across the platform.

MidLink’s Contribution

Making Open edX Aspects Production-Ready

Rather than reinventing the wheel, CampusIL and MidLink built on the strengths of the open-source Aspects framework. MidLink’s role was to harden, scale, and optimize Aspects for production readiness on AWS.

Key enhancements delivered included:

Cloud-Native Architecture: Running Aspects on Kubernetes with modern CI/CD pipelines (ArgoCD, GitHub Actions).

Dynamic Scalability and Cost-Effectiveness: Auto-scaling ensures the platform flexibly adjusts resources to actual demand, supporting more than 2 million of daily learning events, while maintaining infrastructure efficiency.
AWS Well-Architected Foundation: Leveraging AWS Graviton for cost/performance optimization, along with CDN and WAF for secure delivery.
Observability and Reliability: Full operational visibility via Grafana dashboards, ensuring performance and stability are continuously monitored.
Operational Simplification: Providing a deployment approach that removes barriers to adopting and maintaining Aspects at scale.

This modernization allowed CampusIL to unlock the full potential of Aspects – not just as an open-source framework, but as a production-ready national analytics platform.

Outcomes for CampusIL

The impact of the production-ready deployment is measurable and observable:

Enhanced Data-Driven Decision-Making: Raw learning events are transformed into dashboards and visualizations, enabling instructors and administrators to optimize course design, learner engagement, and educational outcomes.

Operational Efficiency and Cost Savings: Auto-scaling ensures infrastructure matches workload demand, preventing over-provisioning and enabling cost-effectiveness.
Proven Scalability: The platform reliably processes over 2 million learner events per day, across more than 3,000 courses and more than 30,000 opened courses and CCX classrooms – demonstrating national-level scalability – with the largest course having more than 15K blocks (university acceptance test preparation course).
Simplified Management & Faster Insights: Cloud-native automation reduces operational complexity, ensuring analytics are delivered quickly and consistently.
Observable Performance: CampusIL monitors analytics performance in Grafana, providing continuous evidence of stability, throughput, and growth capacity.
Information Security: A strict information security team that defines cross-organizational security requirements and policies, including the implementation of raw-level security and extended permission management, integrated with Open edX.

The Partners Behind the Outcome

“The insights made available to the CampusIL team and its partners enable the maximization of pedagogical investment by identifying which courses are more preferred and which are less so. The more successful courses can be further refined, invested in, and replicated to create future offerings. This directly enhances CampusIL’s ability to optimize its active course catalog, thereby increasing the number of learners and encouraging more active learning. Ultimately, this supports CampusIL’s broader vision of reducing educational gaps across diverse populations.”

Shachar Prizat | CTO at CampusIL of Israel National Digital Agency

Key Success Factors

For CampusIL, three factors were critical to realizing the full value of Aspects at scale:

Strategic Deployment: Leveraging MidLink’s expertise to ensure a smooth, optimized implementation on AWS.
Continuous Data Utilization: Actively using real-time insights to drive ongoing improvements in course delivery and learner support.
Scalability Planning: Designing with future growth in mind, ensuring the solution seamlessly scales with demand.

Future Directions

With production-ready analytics in place, CampusIL is well-positioned to expand capabilities further

GenAI Integration: Leveraging AWS Bedrock to develop generative AI components (e.g., personal tutors).
Advanced Analytics: Extending reporting and predictive analytics to support deeper educational research and policy-making.
Continuous Improvement: Institutionalizing feedback loops where analytics directly inform and refine course design and learner support.

Conclusion

This collaboration between Open edX (innovation), MidLink (production expertise), and CampusIL (national vision) demonstrates the power of combining open-source with cloud-native modernization.
By making Open edX Aspects production-ready, CampusIL has unlocked a scalable, cost-effective, and observable analytics platform that directly improves learner outcomes and strengthens national digital education strategy.

This case highlights how open-source, when implemented with the right expertise, can be elevated into an enterprise-grade solution serving millions of learners daily.

The post CampusIL and MidLink Making Open edX Aspects Production-Ready appeared first on peax cloud.

Case Study – Vibrant Gastro

info@sela-style.co.il — Wed, 05 Nov 2025 09:20:48 +0000

About the Customer

Vibrant® Gastro is the pioneer behind the Synchronized Activation Method, a first-in-class, drug-free technology powering the Vibrant System. This state-of-the-art system utilizes micro-vibrations to mechanically stimulate the colon, enhancing natural colonic motility and offering a groundbreaking alternative for patients suffering from chronic idiopathic constipation (CIC).

Vibrant Gastro’s mission is to enable millions of people to live more enjoyable lives through innovative, drug-free treatments that synchronize and activate the gut-brain connection. The company’s approach not only addresses immediate patient needs but also opens the door to data-driven therapies leveraging the enteric nervous system (ENS) pathway for future gastrointestinal and systemic health solutions.

Customer Challenge

As a rapidly growing medical technology innovator, Vibrant Gastro recognized the strategic value of its expanding data assets – real world data collected from medical devices, patients feedback collected via companion app and other sources of information. In order to generate value from the collected data, expedite its analysis and draw accurate conclusions, Vibrant Gastro sought to:

Leverage artificial intelligence (AI) and advanced analytics to extract deeper insights from customer and clinical data under strict security and HIPAA compliance and analyse consumer behaviour to allow Vibrant Gastro to increase customer satisfaction and continually adjust the product to meet consumer needs.
Accelerate data analysis, in order to provide insights and improve value for patients more rapidly and efficiently.
Implement a secure, compliant integration of AI models with existing databases to accelerate research and improve outcomes for patients.

Partner Solution

Vibrant Gastro partnered with MidLink Cloud to design and deploy a comprehensive AI-driven data analytics solution powered by AWS Bedrock and integrated with Amazon RDS.

The implementation included:

AI Model Integration: Utilizing AWS Bedrock’s generative AI capabilities to analyse structured and unstructured data from Vibrant Gastro’s RDS databases, enabling insights on patient outcomes, device usage, and treatment effectiveness.
Data Connectivity & Governance: Establishing secure, role-based access between Bedrock and RDS with compliance-aligned data governance policies ensured HIPAA and PHI protection.
Data Residency & Privacy: Ensuring that all data processing remains within AWS boundaries and that no Protected Health Information (PHI) leaves the environment, maintaining full alignment with healthcare compliance standards.
Automation & Scalability: Streamlining DevOps workflows to support continuous data ingestion and AI-driven analysis at scale.

Results & Benefits

The AI-powered solution delivered transformative results for Vibrant Gastro:

Enhanced Data Insights: Bedrock’s integration with RDS enabled advanced pattern detection and correlation analysis, allowing Vibrant to better understand patient behaviour and treatment efficacy.
Improved Product Innovation: Insights from AI-driven analysis directly informed device optimization and feature development, helping the company continuously improve its drug-free treatments.
Operational Efficiency: Automated data processing reduced manual overhead and empowered internal teams with actionable intelligence.
Data-Driven Care: Vibrant can now better explore future developments based on quick real world data analysis aligned with its mission.
Foundation for Future Growth: The scalable AWS infrastructure and Bedrock integration position Vibrant for future expansion into additional indications and data-driven healthcare solutions.

About the Partner – MidLink Cloud

MidLink Cloud specializes in Cloud Data Management, Big Data & AI Cloud, and Cloud Modernization on AWS. Its customer-centric approach combines technological excellence with tailored managed services and a culture of continuous learning.

By leveraging deep AWS expertise and a focus on data-driven innovation, MidLink Cloud empowers healthcare and technology companies like Vibrant Gastro to unlock the full potential of their data ecosystems and accelerate innovation through the cloud.

The post Case Study – Vibrant Gastro appeared first on peax cloud.

Case Study – CampusIL

info@sela-style.co.il — Mon, 03 Nov 2025 14:14:15 +0000

AI-Powered Analytics with Automated Cloud Operations on AWS

Industry: Education, Public Sector, Data Analytics
Platform: Amazon Web Services (AWS)
Client: CampusIL
Services: Generative AI, Data Analytics, Cloud Operations, DevOps Automation, Security, Application Integration

About the Customer

CampusIL is Israel’s national digital learning platform, led by the Israel National Digital Agency. It provides accessible online education and learning resources to millions of learners, educators, and organizations.
The platform generates significant volumes of educational data, including student engagement, course activity, and content interactions.
CampusIL uses this information to understand learner behavior, evaluate course effectiveness, and support data-driven decisions that improve educational outcomes.

Customer Challenge

CampusIL operated an advanced Business Intelligence environment based on a customized implementation of OpenEdX Aspects, using ClickHouse to store learning events and Apache Superset to provide analytics dashboards and visualizations.
Although the platform offered powerful analytical capabilities, creating new dashboards and queries required specialized SQL and ClickHouse knowledge.
This created ongoing dependency on technical experts for routine data exploration and dashboard development, increasing operational effort and slowing access to insights.
The large volume of educational events also made data exploration and query creation more complex.
CampusIL wanted to simplify the analytics experience by allowing users to request information and generate visualizations through natural language.
However, introducing generative AI created additional operational requirements. The AI system needed accurate, continuously updated knowledge of the underlying database structure, while maintaining secure access to educational data and supporting reliable production operation.
Manual updates to database metadata and AI context would have increased maintenance requirements and created the risk of outdated information being used for query generation.
CampusIL therefore needed a secure, automated, and efficiently operated analytics solution that would reduce dependency on specialized technical resources and simplify the ongoing maintenance of its AI capabilities.

Partner Solution

Peax Cloud designed and deployed an AI-powered analytics solution integrating Amazon Bedrock with CampusIL’s existing Apache Superset and ClickHouse environment.

The solution, deployed to production in July 2025, combines generative AI capabilities with automated data and application operations.
The implementation includes:

AI-Powered Analytics: Amazon Bedrock interprets natural-language requests and generates ClickHouse queries and Apache Superset charts, allowing users to explore data without writing SQL.
Application Integration: A React frontend and Python backend were developed and integrated into Apache Superset, enabling users to interact with the AI assistant directly within the existing BI platform.
Automated RAG Pipeline: A cron-based Retrieval-Augmented Generation process updates the AI knowledge base with the latest ClickHouse schemas and metadata, maintaining relevant context for query generation.
Security and Data Governance: Role-based access controls and secure communication between solution components help protect educational information and maintain appropriate data access.
Data Privacy: The architecture was designed to keep data processing within the AWS environment and protect sensitive educational information.
Operational Automation: Automated schema ingestion and knowledge-base updates reduce the need for manual maintenance and support consistent AI-assisted analytics operations.

Peax Cloud provides the cloud and DevOps expertise supporting the solution’s operation and evolution, with automated processes helping maintain the AI assistant’s awareness of the underlying analytics environment.
The automated RAG pipeline is a central operational capability. As database schemas evolve, the scheduled process updates the AI’s metadata knowledge, reducing the manual effort required to keep the solution aligned with the underlying data platform.
This combination of application integration, secure cloud architecture, and operational automation helps CampusIL operate a sophisticated AI analytics solution with reduced maintenance complexity.

Results and Benefits

Reduced Dependency on Technical Specialists: Users can generate analytics queries and charts through natural language, reducing reliance on BI developers for routine data exploration.
Reduced Operational Maintenance: Automated schema ingestion and RAG updates minimize manual knowledge-base maintenance and help the AI assistant remain aligned with database changes.
Faster Access to Insights: The conversational interface enables non-technical users to request analytics and visualizations without developing SQL queries.
Improved Operational Consistency: Automated processes provide a structured approach to maintaining AI metadata and supporting the continued operation of the analytics solution.
Secure Analytics Access: Role-based access controls and secure AWS integration support educational data governance and privacy requirements.
Improved Business Efficiency: CampusIL’s administrators and educational teams can spend less time on technical query development and more time interpreting insights and improving educational offerings.
Foundation for Future Innovation: The AWS-based architecture supports future enhancements such as multilingual analytics, automated dashboard recommendations, and additional AI-assisted capabilities.
By combining generative AI with automated operational processes, Peax Cloud helps CampusIL maintain an accessible and more efficiently operated analytics environment that supports its mission to improve digital education through data-driven insights.

January, 2025 - Ongoing

The post Case Study – CampusIL appeared first on peax cloud.

Case Study – CampusIL

info@sela-style.co.il — Sun, 08 Sep 2024 14:36:53 +0000

Modernized and Efficiently Operated Learning Platform on AWS

Industry: Education, Public Sector
Platform: Amazon Web Services (AWS)
Client: CampusIL
Services: Application Modernization, Kubernetes Operations, DevOps Automation, Monitoring, Scaling, Cost Optimization

About the Customer

CampusIL is Israel’s national digital learning platform, part of the National Digital Israel Initiative. It provides accessible, high-quality online education to students, teachers, job seekers, professionals, and lifelong learners across Israel.
Its educational platform offers courses, videos, interactive activities, and digital learning tools designed to make education more accessible and support skills development across diverse populations.
To deliver reliable digital learning experiences, CampusIL depends on scalable and efficiently operated cloud infrastructure capable of supporting changing traffic patterns and continuous platform development.

Customer Challenge

CampusIL faced significant operational challenges with its WordPress-based website. The application experienced stability issues, lacked effective scaling capabilities, and consumed excessive infrastructure resources, resulting in high operational costs.
Application management also relied on traditional development processes, with files maintained directly on the file system and no structured version-control mechanism.
This made application changes difficult to track, increased the risk of deployment errors, and complicated troubleshooting and rollback procedures.
As a public digital learning platform, CampusIL also needed to support fluctuating levels of traffic while maintaining consistent application availability and performance.
Without automated scaling and comprehensive monitoring, day-to-day infrastructure operations required additional manual effort, and identifying application or infrastructure issues was more challenging.
CampusIL needed a more modern and operationally efficient AWS environment that would reduce manual infrastructure management, improve application stability, simplify deployments, and provide better visibility into system health.
The organization worked with Peax Cloud to modernize its infrastructure and establish an automated cloud operating model capable of supporting ongoing application delivery, monitoring, and resource optimization.

Partner Solution

Peax Cloud modernized CampusIL’s application infrastructure on AWS and established an automated, observable, and scalable environment designed for efficient cloud operations.
The solution includes:

Application Containerization: Peax Cloud migrated the WordPress application to a container-based architecture running on Kubernetes, improving deployment consistency and application management.
Version Control: The application codebase was migrated to GitHub, introducing structured change tracking, version history, and rollback capabilities.
Automated CI/CD: GitHub Actions and ArgoCD were implemented to automate application deployment and support consistent release processes.
Application Autoscaling: Kubernetes Horizontal Pod Autoscaling was configured to dynamically adjust application capacity based on workload demand.
Infrastructure Autoscaling: Karpenter was deployed to automatically adjust Kubernetes worker-node capacity, improving resource utilization and reducing unnecessary infrastructure consumption.
AWS Graviton Optimization: The application was optimized for ARM architecture and deployed on AWS Graviton-based instances to improve compute efficiency.
Monitoring and Logging: Prometheus, Loki, and Grafana were implemented to provide centralized infrastructure monitoring, application logging, and system performance visibility.

Peax Cloud operates and supports the cloud infrastructure using these automated deployment, scaling, and observability capabilities.
The operational approach focuses on maintaining application stability, supporting infrastructure changes, improving visibility into application and infrastructure health, and optimizing resource utilization.
Through automation and modern DevOps practices, Peax Cloud reduces the manual effort associated with operating the environment and supports more consistent application delivery.

Results and Benefits

Improved Platform Stability: The Kubernetes-based infrastructure and automated scaling mechanisms provide a more reliable foundation for CampusIL’s website.
Reduced Operational Overhead: Automated deployments, infrastructure scaling, and version control reduce manual infrastructure and application management activities.
Improved Monitoring and Troubleshooting: Prometheus, Loki, and Grafana provide centralized visibility into application performance and infrastructure health, supporting faster investigation of operational issues.
More Efficient Resource Utilization: AWS Graviton, Karpenter, and HPA enable more efficient allocation of compute resources and help reduce unnecessary cloud consumption.
Reliable and Consistent Deployments: GitHub Actions and ArgoCD improve application release processes, reducing deployment complexity and supporting rollback when required.
Better Support for Changing Demand: Automated application and infrastructure scaling enable the platform to adapt more efficiently to fluctuating traffic.
More Focus on Educational Services: By simplifying infrastructure operations and improving deployment automation, CampusIL can devote more attention to delivering digital learning experiences rather than managing underlying cloud infrastructure.
The modernization and operational improvements provide CampusIL with a scalable, observable, and efficiently operated AWS environment that supports the continued development of its national learning platform.

June, 2024 - Ongoing

The post Case Study – CampusIL appeared first on peax cloud.

Case Study – SEENITY

info@sela-style.co.il — Tue, 20 Aug 2024 13:00:23 +0000

The customer

Seenity is a dynamic and innovative company, operating in the digital marketing industry. Seenity has established itself as a prominent player in the realm of online advertising and brand promotion.

Seenity specializes in leveraging the power of social media to help businesses enhance their online presence, engage with their customers, and drive meaningful conversions. They offer a comprehensive range of services, including social media marketing, influencer partnerships, content creation, and digital advertising strategies tailored to their clients’ specific needs.

Through their cutting-edge strategies and data-driven approach, Seenity has successfully collaborated with numerous brands across various sectors, from startups to established enterprises.

The goal

Seenity aims to migrate the company’s workload from Azure infrastructure to AWS-based IaaS infrastructure. They seek to achieve better agility in managing their infrastructure and applications, allowing more flexibility and scalability.

Alongside with that, Seenity would like to build a cost optimized and secured environment using native managed AWS services, all in order to reduce operation cost.

The Plan – solution

MidLink conducted a deep assessment process, in which it fully mapped the customer assets and understood which of these will be migrated to AWS. Then, MidLink designed a new AWS based architecture according to the AWS 7Rs principles, seven common migration strategies (7 Rs). These strategies are refactor, replatform, repurchase, rehost, relocate, retain, and retire. The architecture takes into consideration all the customer goals, including:

Easy automated scaling
Resilient
Secured
Cost effective

The implementation

MidLink developed a full IaC (Terraform base) coverage to deploy the AWS-based infrastructure that allows Seenity’s workload to be hosted on the AWS cloud.

By leveraging AWS services and features, such as EKS, RDS and S3 buckets, Seenity managed to reduce the cost and still serve their customers with no need for over provisioning of compute resources.

Moreover, by using AWS services like: AWS WAF/Shield, ALBs and multi-AZ deployments, MidLink ensured improved infrastructure agility and security for Seenity. This enables it to scale resources dynamically and respond quickly to changing business demands.

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Case Study – L1GHT

info@sela-style.co.il — Tue, 20 Aug 2024 12:57:56 +0000

The customer

L1ght is a technology company that specializes in online safety solutions and digital well-being. Their mission is to create a safer and more positive digital environment by addressing the challenges posed by harmful content, cyberbullying, and online toxicity.

As an organization, L1ght is dedicated to developing advanced artificial intelligence (AI) and machine learning (ML) technologies, to detect and prevent harmful online behaviour. They leverage their expertise in data analysis, natural language processing, and image recognition to provide real-time monitoring and protection against harmful content across various digital platforms.

L1ght’s solutions are designed to assist social media platforms, online gaming communities, messaging apps, and other digital platforms in maintaining a safe and inclusive online experience for their users.

The goal

Migration of L1ght’s current on-premises workload to AWS. The migration involves deploying an architecture that initially replicates the on-premises design and later transitions to an AWS serverless architecture.

Because on premises environments are limited in their ability to scale–up and out in an agile way L1ght would like the new AWS based architecture to enable it to scale fast and automatically but use the pay as you grow method and not pay up front and wait for new compute resources.

The environment must be hybrid and connect to data sources on the on-premises environment, it must be extra secured and cost optimized.

The Plan – solution

MidLink has conducted a deep assessment process in which it fully mapped the customer assets, and understood which of these will be migrated to AWS. Then, MidLink designed a new AWS based architecture according to the AWS 7Rs principles, seven common migration strategies (7 Rs). These strategies are refactor, replatform, repurchase, rehost, relocate, retain and retire. The architecture takes into consideration all the customer goals, including:

Easy automated scaling
Resilient
Secured
Cost effectiveness

Since the environment we designed is hybrid (Cloud, On premises), we built a secure strategy to connect the on premises stack to AWS by configuring S2S VPN connection between the workloads.

The implementation

MidLink developed a full IaC (Terraform base) coverage to deploy the AWS-based infrastructure that allows L1ght‘s workload to be hosted both on the AWS cloud and connected to an on-premises database.

By leveraging AWS services and features, such as DMS, RDS and EC2 auto scaling groups L1ght managed to reduce the cost and still serve their customers with no need for over provisioning of compute resources.

More than that by using AWS services like: AWS WAF/Shield, ALBs and multi-AZ deployments, MidLink ensured improved infrastructure agility and security for Seenity. This enables Seenity to scale resources dynamically and respond quickly to changing business demands.

The post Case Study – L1GHT appeared first on peax cloud.

Case Study – Vibrant Gastro

info@sela-style.co.il — Tue, 20 Aug 2024 12:50:12 +0000

Secure and Scalable AWS Operations for Healthcare

Industry: Healthcare, Medical Devices
Platform: Amazon Web Services (AWS)
Client: Vibrant Gastro
Services: AWS Landing Zone, Cloud Modernization, Managed Cloud Operations, Security, Kubernetes, Monitoring and Optimization

About the Customer

Vibrant Gastro develops and manufactures innovative medical devices for the treatment of chronic constipation. Its flagship product, the Vibrant® capsule, uses gentle mechanical stimulation to support bowel movements.
Operating in the healthcare and medical-device industry, Vibrant Gastro requires a secure, reliable, and scalable technology environment to support its connected medical-device platform while protecting sensitive healthcare information.

Customer Challenge

Vibrant Gastro faced several challenges with its existing AWS infrastructure, including limited internal AWS expertise, security and HIPAA-related requirements, scalability limitations, and insufficient monitoring capabilities.
As the company’s operations expanded, managing the AWS environment became increasingly complex. Its internal team lacked the specialized cloud and DevOps expertise required to continuously maintain infrastructure, manage configuration changes, address security requirements, and optimize cloud resources.
Security and compliance were especially important due to the sensitive nature of healthcare information. Vibrant Gastro needed to maintain a secure infrastructure with consistent access controls, appropriate governance, and continuous visibility into its cloud environment.
The existing infrastructure also contained potential single points of failure and lacked effective automated scaling. In addition, limited monitoring and alerting capabilities made it difficult to identify and resolve operational issues proactively.
Vibrant Gastro needed a partner capable of not only modernizing its AWS infrastructure but also operating and supporting the environment on an ongoing basis, reducing dependency on internal AWS expertise and allowing its teams to focus on medical-device innovation.

Partner Solution

Peax Cloud modernized Vibrant Gastro’s AWS infrastructure and provides ongoing cloud operations and DevOps expertise to maintain a secure, scalable, and efficiently managed environment.
The solution includes:

AWS Landing Zone and Security: Peax Cloud implemented a HIPAA-oriented AWS Landing Zone for Healthcare using AWS Landing Zone Accelerator, providing standardized infrastructure, stronger governance, and security controls suitable for healthcare workloads.
Infrastructure as Code: Infrastructure was provisioned through Infrastructure as Code (IaC), improving deployment consistency, repeatability, and control over infrastructure changes.
Kubernetes and Automated Scaling: Amazon Elastic Kubernetes Service (Amazon EKS) was implemented with Karpenter and Horizontal Pod Autoscalers (HPA), enabling infrastructure and application resources to scale dynamically according to actual demand.
Monitoring and Operational Visibility: Amazon Managed Service for Prometheus and Amazon Managed Grafana were deployed to provide centralized infrastructure monitoring, application metrics, and visibility into system performance.
IoT Security: AWS IoT Core was implemented to support secure certificate management for Vibrant Gastro’s connected medical-device environment.

Beyond the initial implementation, Peax Cloud supports the day-to-day operation of Vibrant Gastro’s AWS environment, including infrastructure monitoring, operational troubleshooting, infrastructure changes, security-related requirements, scalability management, and AWS resource optimization.
By combining infrastructure automation, advanced monitoring, and professional AWS operational expertise, Peax Cloud helps Vibrant Gastro maintain an efficient cloud environment while reducing the internal effort required to manage complex AWS workloads.

Results and Benefits

Reduced Operational Burden: Peax Cloud’s ongoing AWS and DevOps support reduces Vibrant Gastro’s dependency on internal cloud expertise and allows its teams to focus on developing and supporting medical-device products.
Improved Security and Governance: The standardized AWS Landing Zone and infrastructure management practices provide a stronger foundation for maintaining consistent security controls and addressing healthcare compliance requirements.
Proactive Monitoring and Troubleshooting: Centralized monitoring through Prometheus and Grafana provides visibility into infrastructure and application health, supporting earlier identification and investigation of operational issues.
Improved Scalability and Reliability: Amazon EKS, Karpenter, and HPA enable the environment to respond automatically to workload fluctuations, reducing manual scaling requirements and improving operational resilience.
Optimized Infrastructure Utilization: Automated resource scaling and infrastructure optimization help align AWS capacity with actual workload demand and reduce unnecessary resource consumption.
Focus on Core Business: With Peax Cloud supporting the AWS environment, Vibrant Gastro can devote more internal resources to its medical-device innovation and business growth.

Together, these improvements provide Vibrant Gastro with a secure, scalable, monitored, and efficiently operated AWS environment capable of supporting its continued growth.

January, 2024 - Ongoing

The post Case Study – Vibrant Gastro appeared first on peax cloud.

Case Study – Ree

info@sela-style.co.il — Tue, 20 Aug 2024 12:39:59 +0000

REE Automotive — Simplifying and Operating a Global AWS Environment

Industry: Automotive Technology, Electric Vehicles
Platform: Amazon Web Services (AWS)
Client: REE Automotive
Services: AWS Landing Zone, Cloud Migration, Managed Cloud Operations, Networking, Security, Backup, Cost Optimization

About the Customer

REE (Nasdaq: REE) is an automotive technology company developing innovative electric and autonomous vehicle platforms.
Its revolutionary REEcorner technology integrates essential vehicle components, including steering, braking, suspension, powertrain, and control, into a compact module positioned between the chassis and the wheel.
Headquartered in Israel and operating internationally, REE requires secure, reliable, and efficiently managed IT infrastructure to support its global engineering, development, and business operations.

Customer Challenge

As REE expanded its international operations, its AWS infrastructure became increasingly complex, containing unnecessary resources, configuration inconsistencies, and opportunities for improved resource utilization.
This complexity increased the operational effort required to manage AWS resources, maintain infrastructure configurations, troubleshoot technical issues, and control cloud costs.
REE also faced challenges due to limited dedicated AWS and DevOps operational expertise. Supporting a growing cloud environment required specialized knowledge of AWS infrastructure, networking, security, data protection, and ongoing resource optimization.
With operations spanning multiple geographic locations, REE needed stable and secure network connectivity between its offices, employees, and AWS workloads. Protecting critical business data and maintaining reliable access to IT resources were additional operational priorities.
The company needed to simplify its cloud environment while ensuring that infrastructure could be efficiently operated, supported, and optimized as business requirements evolved.
REE therefore turned to Peax Cloud for AWS modernization and ongoing cloud operational support, allowing its internal teams to concentrate on automotive research, engineering, and innovation rather than day-to-day infrastructure management.

Partner Solution

Peax Cloud designed and implemented an optimized AWS environment and provides ongoing AWS and DevOps operational expertise to support its management and continuous improvement.
The solution includes:

AWS Landing Zone and Governance: Peax Cloud implemented AWS Landing Zone Accelerator to standardize REE’s AWS environment, reduce configuration complexity, and establish stronger security and governance foundations.
Infrastructure Migration and Optimization: Existing workloads were migrated and optimized to eliminate unnecessary resources, improve resource utilization, and establish a more cost-efficient infrastructure.
Secure Global Connectivity: AWS Transit Gateway, AWS Site-to-Site VPN, and Client VPN capabilities were implemented to provide secure connectivity between AWS resources, company locations, and authorized users.
Compute and Storage: Amazon EC2 and Amazon FSx were deployed to support REE’s computing and file-storage requirements.
Data Protection: AWS Backup was implemented to provide centralized backup capabilities and improve the recoverability of critical workloads.
Virtual Desktop Infrastructure: Amazon WorkSpaces was deployed to provide secure and scalable virtual desktop capabilities for employees.

In addition to the initial infrastructure modernization, Peax Cloud supports REE’s ongoing AWS operations, including infrastructure management, operational troubleshooting, infrastructure changes, resource optimization, and security- and reliability-related requirements.
Peax Cloud’s AWS expertise helps REE maintain a manageable cloud environment, address infrastructure issues, and continuously identify opportunities to improve operational and cost efficiency.
This approach reduces the effort required from REE’s internal IT resources while providing access to specialized AWS and DevOps capabilities.

Results and Benefits

Reduced Operational Complexity: Simplifying the AWS architecture and eliminating unnecessary resources reduced infrastructure management overhead and improved the overall manageability of the cloud environment.
Access to Ongoing AWS Expertise: Peax Cloud’s operational support provides REE with professional AWS and DevOps capabilities for managing infrastructure requirements, troubleshooting issues, and supporting continued improvements.
Improved Cost Visibility and Efficiency: Infrastructure optimization and improved resource management provide better control over AWS consumption and help reduce unnecessary cloud expenditure.
Enhanced Security and Governance: The standardized AWS Landing Zone provides a stronger foundation for maintaining consistent infrastructure configurations and security practices.
Reliable Global Connectivity: AWS Transit Gateway and VPN connectivity support secure communication between REE’s international operations and its AWS environment.
Improved Data Protection and Accessibility: AWS Backup supports workload protection and recovery, while Amazon WorkSpaces provides employees with secure and flexible access to virtual desktop environments.
Greater Focus on Innovation: By relying on Peax Cloud for AWS operational support, REE can dedicate more internal resources to its core automotive technology and business growth.

The resulting AWS environment provides REE with a secure, scalable, and efficiently operated cloud foundation capable of supporting its international operations and future expansion.

March, 2024 - Ongoing

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MidLink Cloud’s Achievement in AWS Graviton Service Delivery

info@sela-style.co.il — Thu, 30 May 2024 14:42:09 +0000

We are happy to announce that MidLink Cloud was recognized by AWS as a certified AWS Graviton Service Delivery Program (SDP) partner. This announcement marks a significant milestone in our journey of cloud optimization and service delivery. Further, this recognition strengthens MidLink Cloud’s position as a leading AWS Consulting Partner, showcasing our expertise and success in leveraging AWS Graviton to deliver outstanding cloud solutions.

The AWS Graviton SDP is designed to help customers transition to AWS Graviton, offering substantial price and performance benefits across a wide range of workloads. As an AWS Graviton Delivery Partner, MidLink Cloud complied with the requirements presented by AWS and passed technical validations to ensure conformation with AWS best practices. Our proven success is further demonstrated through multiple customer success stories, and the shifting of their technology stack to be based on AWS Graviton (see example below).

As an AWS Graviton Service Delivery Partner, MidLink Cloud is offering a robust suite of solutions that allow our clients to operate their applications more efficiently on AWS Graviton-based infrastructure. This initiative not only enhances performance and scalability but also promotes cost-efficiency and sustainability in cloud operations.

Why Consider Switching to AWS Graviton Processors?

Given potential of the processers to reduce cloud service costs significantly alongside with enhancing performance, AWS encourages switching to Graviton processors. However, it is important to evaluate whether this transition is suitable for your organization. To that end, MidLink Cloud’s CTO, Udi Altaratz, has created a guide to help review the benefits and considerations of adopting Graviton processors, while understanding the potential impact thereof on your infrastructure, applications and operations.

Case Study: Real-Time Health Monitoring System

Customer Challenges:

Increase performance and reduce the cost of workloads.
Real-time IoT system running on AWS EKS utilizing hundreds of GPUs, where performance is critical.
Existing cost of $500K MRR, with compute costs at $180K.

Solution:

Re-platformed the solution to AWS Graviton.
Native compilation for EKS.
Scanned Docker images with porting advisor and compiled them for Graviton.
Conducted performance testing, achieving a 25% improvement.
Reduced per-node costs by an average of 17%.
Integrated SPOT node groups into EKS.

Results:

Significant cost reduction in EKS and RDS services
Enhanced performance, as confirmed by performance tests.

MidLink Cloud continues to lead in cloud optimization and service delivery through its participation in the AWS Graviton Service Delivery Program. Our expertise in AWS Graviton not only ensures superior performance and cost savings but also drives sustainability in cloud operations. Whether you are considering a switch to Graviton processors or looking for expert-managed services, MidLink Cloud is your trusted partner for a seamless and efficient transition.

For more details and testing of whether you are ready to transition to Graviton, contact MidLink Cloud’s experts. We will scan your code and containers, at no charge, and suggest a working plan to transition to Graviton.

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