Hello Edge Enthusiasts ! 😎

Keeping you ahead in the world of Edge Computing!

Lets dive right away into it. We will begin with key questions related to data management requirements and processing latency sensitive workloads locally:

• Why send critical patient data to the cloud when you can bring the cloud closer to the patient?

• Latency kills. Literally. Can AWS Outposts save lives in critical healthcare environments?

• Be it hospitals or research facilities, why is it critical to manage data processing locally?

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The Key Challenges in Healthcare & Life Sciences

Hospitals and life sciences organizations face two major challenges Speed & Compliance

• 🕒 Speed & Latency: Real-time healthcare applications like medical imaging, patient monitoring, and genomics analysis need ultra-low latency to make critical, life-saving decisions.

• 🛡️ Compliance & Data Residency: Sensitive healthcare data must stay on-premises to meet strict regulations and ensure security. E.g HIPAA or

• 🌐 The Solution – AWS Outposts: Brings cloud capabilities on-premises, solving both latency and compliance challenges by keeping the cloud close to where the data lives.

• Quick Peak into AWS Outposts : Overview & How it Works

Use Cases: HealthCare Applications Highlights

Below are few examples we can look at, but there is surely an ever increasing use cases:

1. Medical Imaging (CT, MRI, X-Ray)

• The Problem: Medical imaging requires processing massive files in real-time for faster diagnosis.

• How AWS Outposts Solves It: Keeps compute and storage local for minimal latency while still using AWS services like EC2, S3, and Sage Maker.

Imagine reducing diagnosis time from hours to minutes—how would you architect the storage pipeline for massive DICOM files locally with AWS Outposts?

2. Real-Time Patient Monitoring

• The Problem: Monitoring ICU patients requires ultra-low latency for life-saving decisions.

• Solution: Deploy machine learning models locally to process patient data and trigger alerts instantly.

For patient monitoring, milliseconds matter. Would you integrate AWS IoT Greengrass alongside AWS Outposts to process edge data in real time?

3. Genomics & Drug Discovery 🔬

• The Problem: Life sciences companies need to train massive ML models for genomics and research. Centralized cloud transfers can slow progress.

• How AWS Outposts Solves It: Brings compute closer to research labs for faster analysis and secure data residency.

For genomics data processing, would you favor Outposts to combine S3 storage with on-prem SageMaker training pipelines? Curious to hear your thoughts!

Insights & Considerations for Solution’s Architects

AWS Outposts is more than a solution—it’s the bridge between cloud innovation and on-prem reality for healthcare and life sciences. It’s fast, compliant, and purpose-built for industries where every second counts

If you found this helpful, share it with a colleague tackling hybrid cloud challenges. And let me know your thoughts—what’s the most exciting AWS Outposts use case you’ve seen?

That’s it for today! ☀️

Let’s push the boundaries of technology together. Until next week, stay curious and stay on the Edge!

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Thanks for spending part of your day with JambuSpace.

Your AWS Edge Explorer,

Sharat Sami (Let’s connect on LinkedIn)