Cloudflare launched fifteen years ago with a mission to help build a better Internet. Over that time the Internet has changed and so has what it needs from teams like ours.  In this year’s Founder’s Letter, Matthew and Michelle discussed the role we have played in the evolution of the Internet, from helping encryption grow from 10% to 95% of Internet traffic to more recent challenges like how people consume content. 

We spend Birthday Week every year releasing the products and capabilities we believe the Internet needs at this moment and around the corner. Previous Birthday Weeks saw the launch of IPv6 gateway in 2011,  Universal SSL in 2014, Cloudflare Workers and unmetered DDoS protection in 2017, Cloudflare Radar in 2020, R2 Object Storage with zero egress fees in 2021,  post-quantum upgrades for Cloudflare Tunnel in 2022, Workers AI and Encrypted Client Hello in 2023. And those are just a sample of the launches.

This year’s themes focused on helping prepare the Internet for a new model of monetization that encourages great content to be published, fostering more opportunities to build community both inside and outside of Cloudflare, and evergreen missions like making more features available to everyone and constantly improving the speed and security of what we offer.

We shipped a lot of new things this year. In case you missed the dozens of blog posts, here is a breakdown of everything we announced during Birthday Week 2025. 

Monday, September 22

Tuesday, September 23

Wednesday, September 24

Thursday, September 25

Friday, September 26

Helping build a better Internet has always been about more than just technology. Like the announcements about interns or working together in our offices, the community of people behind helping build a better Internet matters to its future. This week, we rolled out our most ambitious set of initiatives ever to support the builders, founders, and students who are creating the future.

For founders and startups, we are thrilled to welcome Cohort #6 to the Workers Launchpad, our accelerator program that gives early-stage companies the resources they need to scale. But we’re not stopping there. We’re opening our doors, literally, by launching new physical hubs for startups in our San Francisco, Austin, London, and Lisbon offices. These spaces will provide access to mentorship, resources, and a community of fellow builders.

We’re also investing in the next generation of talent. We announced free access to the Cloudflare developer platform for all students, giving them the tools to learn and experiment without limits. To provide a path from the classroom to the industry, we also announced our goal to hire 1,111 interns in 2026 — our biggest commitment yet to fostering future tech leaders.

And because a better Internet is for everyone, we’re extending our support to non-profits and public-interest organizations, offering them free access to our production-grade developer tools, so they can focus on their missions.

Whether you’re a founder with a big idea, a student just getting started, or a team working for a cause you believe in, we want to help you succeed.

Thank you to our customers, our community, and the millions of developers who trust us to help them build, secure, and accelerate the Internet. Your curiosity and feedback drive our innovation.

It’s been an incredible 15 years. And as always, we’re just getting started!

(Watch the full conversation on our show ThisWeekinNET.com about what we launched during Birthday Week 2025 here.)

Read more here: https://blog.cloudflare.com/birthday-week-2025-wrap-up/

The post 15 years of helping build a better Internet: a look back at Birthday Week 2025 appeared first on IPv6.net.

Just after 11:30 UTC (16:00 local time) on Monday, September 29, 2025, subscribers of wired Internet providers in Afghanistan experienced a brief service interruption, lasting until just before 12:00 UTC (16:30 local time). Cloudflare traffic data for AS38472 (Afghan Wireless) and AS131284 (Etisalat) shows that traffic from these mobile providers remained available during that period.

However, just after 12:30 UTC (17:00 local time), the Internet was completely shut down, with Afghani news outlet TOLOnews initially reporting in a post on X that “Sources have confirmed to TOLOnews that today (Monday), afternoon, fiber-optic Internet will be shut down across the country.” This shutdown is likely an extension of the regional shutdowns of fiber optic connections that took place earlier in September, and it will reportedly remain in force “until further notice”. (The earlier regional shutdowns are discussed in more detail below.)

While Monday’s first shutdown was only partial, with mobile connectivity apparently remaining available, the graphs below show that the second event took the country completely offline, with web and DNS traffic dropping to zero at a national level, as seen in the graphs below.

While the shutdown will impact subscribers to fixed and mobile Internet services, it also “threatens to paralyze critical services including banking, customs operations and emergency communications” across the country. The X post from TOLOnews also noted that television and radio networks would face disruptions.

HTTP request traffic is traffic coming from web browsers, applications, and automated tools, and is a clear signal of the availability of Internet connectivity. The graph below shows this request volume dropping sharply as the shutdown was implemented.

^{HTTP request traffic from Afghanistan, September 29, 2025}

Cloudflare sends bytes back in response to those HTTP requests (“HTTP bytes”), as well as sending bytes back in response to traffic associated with other services, such as our 1.1.1.1 DNS resolver, authoritative DNS, WARP, etc. (“total bytes”). Cloudflare stopped receiving client traffic from the services when the shutdown began, causing the bytes transferred in response to drop to zero.

^{Internet traffic from Afghanistan, September 29, 2025}

1.1.1.1 is Cloudflare’s privacy-focused DNS resolver, and processes DNS lookup requests from clients. As connectivity was cut, traffic to the service disappeared.

^{DNS query traffic to Cloudflare’s 1.1.1.1 resolver from Afghanistan, September 29, 2025}

At a regional level, it appears that traffic from Kabul fell slightly later than traffic from the other regions, trailing them by approximately a half hour.

^{HTTP request traffic from the top five provinces in Afghanistan, September 29, 2025}

The delay in traffic loss seen in Kabul may be associated with a more gradual loss of traffic seen at AS38742 (Afghan Wireless), which saw traffic approach zero just after 13:00 UTC (17:30 local time). This conjecture is supported by a published report that noted “Residents across Kabul and several provincial cities reported on Monday that fiber-optic services were no longer available, with only limited mobile data functioning briefly before signal towers stopped working altogether.”

Interestingly, it appears that as of 00:00 UTC (04:30 local time) on September 30, we continue to see a very small amount of traffic from this network. (This is in contrast to other networks, whose lines disappeared from the graph around 12:30 UTC (17:00 local time)).

^{HTTP request traffic from the top 10 ASNs in Afghanistan, September 29, 2025}

Network providers announce IP address space that they are responsible for to other networks, enabling the routing of traffic to and from those IP addresses. When these announcements are withdrawn, the resources in that address space, whether clients or servers, can no longer reach, or are no longer reachable from, the rest of the Internet.

In Afghanistan, announced IPv4 address space dropped rapidly as the shutdown was implemented, falling by two-thirds from 604 to 197 announced /24s (blocks of 256 IPv4 addresses) in the first 20 minutes, and then dropping further over the next 90 minutes. Through the end of the day, several networks continued to announce a small amount of IPv4 address space: four /24s from AS38742 (Afghan Wireless), two from AS149024 (Afghan Bawar ICT Services), and one each from AS138322 (Afghan Wireless) and AS136479 (Cyber Telecom).

Afghan Wireless is a mobile connectivity provider, and Afghan Bawar and Cyber Telecom appear to offer wireless/mobile services as well. The prefixes still visible from Afghan Wireless appear to be routed through AS17557 (Pakistan Telecom), while the prefixes from the other two providers (Afghan Bawar, Cyber Telecom) appear to be routed through AS40676 (Psychz Networks), a US-based solutions provider.

^{Announced IPv4 address space from Afghanistan, September 29, 2025}

Announced IPv6 address space fell as well, though not quite as catastrophically, dropping by three-fourths almost immediately, from 262,407 /48s (blocks of over 1.2 septillion IPv6 addresses) to 65,542.

^{Announced IPv6 address space from Afghanistan, September 29, 2025}

In mid-September, the Taliban ordered the shutdown of fiber optic Internet connectivity in multiple provinces across Afghanistan, as part of a drive to “prevent immorality”. It was the first such ban issued since the Taliban took full control of the country in August 2021.

These regional shutdowns blocked Afghani students from attending online classes, impacted commerce and banking, and limited access to government agencies and institutions such as passport and registration offices, customs offices. As many as 15 provinces experienced shutdowns, and we review the observed impacts across several of them below, using the regional traffic data recently made available on Cloudflare Radar.

Balkh appeared to be one of the earliest targeted provinces, with traffic dropping midday (UTC) on September 15. While some nominal recovery occurred on September 23, traffic remained well below pre-shutdown levels.

^{Internet traffic from Balkh, Afghanistan, September 1-28, 2025}

After several days of peak traffic levels double those seen in previous weeks, traffic in Takhar fell on September 16, remaining near zero until September 21, when a small amount of connectivity was apparently restored.

^{Internet traffic from Takhar, Afghanistan, September 1-28, 2025}

In Kandahar, lower peak traffic volumes are visible between September 17 and September 21. The partial restoration of traffic is coincident with the restoration of Internet services highlighted in a published report, though it notes that “The restoration of services is limited to point-to-point connections for key government offices, including banks, customs offices, and the Directorate for National ID Cards.”

^{Internet traffic from Kandahar, Afghanistan, September 1-28, 2025}

Baghlan experienced an anomalous spike in traffic on September 16, with total traffic spiking 3x higher than peaks seen during the previous weeks. However, on September 17, traffic dropped to a fraction of pre-shutdown levels. Except for a return to near-normal levels on September 21 & 22, the disruption remained in place through the end of the month.

^{Internet traffic from Baghlan, Afghanistan, September 1-28, 2025}

Traffic in Nangarhar was disrupted between September 19-22, but quickly recovered to pre-shutdown levels once restored.

^{Internet traffic from Nangarhar, Afghanistan, September 1-28, 2025}

After experiencing an apparent issue at the start of the month, Internet traffic in Oruzgan, again fell on September 19. After an apparent complete shutdown, on September 23, a small amount of traffic was again visible.

^{Internet traffic from Oruzgan, Afghanistan, September 1-28, 2025}

Internet connectivity was also disrupted in the province of Herat, although differently. From September 22-25, partial Internet outages were implemented between 16:30-03:30 UTC (21:00-08:00 local time), with traffic volumes dropping to approximately half of those seen at the same time the prior weeks. The intent of these “Internet curfew” shutdowns is unclear, but Herat residents noted that they “severely disrupted their business and educational activities”.

^{Internet traffic from Herat, Afghanistan, September 16-29, 2025}

While Internet shutdowns remain all too common around the world, most (though not all) are comparatively short-lived, and are generally in response to a local event, such as exams, unrest/riots, elections, etc. Given the broad impact of this shutdown across all facets of daily personal, social, and professional life in Afghanistan, analysts state that it “could deepen Afghanistan’s digital isolation, further damage its struggling economy and drive more Afghans out of work at a time when humanitarian needs are already severe.”

You can follow the latest state of Internet connectivity in Afghanistan on Cloudflare Radar. The Cloudflare Radar team will continue to monitor traffic from Afghanistan as well, sharing our observations on the Cloudflare Radar Outage Center, via social media, and in posts on blog.cloudflare.com. Follow us on social media at @CloudflareRadar (X), noc.social/@cloudflareradar (Mastodon), and radar.cloudflare.com (Bluesky), or contact us via email.

Read more here: https://blog.cloudflare.com/nationwide-internet-shutdown-in-afghanistan/

The post Nationwide Internet shutdown in Afghanistan extends localized disruptions appeared first on IPv6.net.

Read more here: https://cloud.google.com/blog/products/networking/gke-network-interface-from-kubenet-to-ebpfcilium-to-dranet/

The post GKE network interface at 10: From core connectivity to the AI backbone appeared first on IPv6.net.

Read more here: https://cloud.google.com/blog/products/networking/network-performance-whitepapers-on-headers-data-and-bitrates/

The post Network Performance Decoded: Much ado about headers, data and bitrates appeared first on IPv6.net.

Samsung and OpenAI sign a landmark Letter of Intent (LOI) to accelerate advancements in global AI data centre infrastructure. The collaboration unites Samsung’s capabilities across semiconductors, cloud, shipbuilding and engineering with OpenAI’s expertise, aiming to build next-generation AI technologies and support Korea’s ambitions to become one of the top three AI nations globally.

OpenAI and Samsung today announce a new strategic partnership designed to reshape the global landscape of AI infrastructure. Signed at Samsung’s corporate headquarters in Seoul, Korea, the agreement reflects a commitment by both parties to pool their strengths in semiconductors, cloud, shipbuilding and engineering to advance the future of AI data centres and related technologies.

The partnership is formalised through a Letter of Intent (LOI) signed by senior leaders from OpenAI, Samsung Electronics, Samsung SDS, Samsung C&T, and Samsung Heavy Industries. The ceremony is attended by Young Hyun Jun, Vice Chairman & CEO of Samsung Electronics; Sung-an Choi, Vice Chairman & CEO of Samsung Heavy Industries; Sechul Oh, President & CEO of Samsung C&T; and Junehee Lee, President & CEO of Samsung SDS.

Together, these organisations will work on OpenAI’s global Stargate initiative, an ambitious programme to support the growing demand for AI model training and deployment at scale.

Samsung electronics: Strategic semiconductor partner

Samsung Electronics plays a key role in this partnership as OpenAI’s strategic memory partner. With OpenAI’s demand for semiconductors projected to reach up to 900,000 DRAM wafers per month, Samsung will supply advanced semiconductor solutions optimised for AI workloads.

Samsung’s semiconductor technologies span memory, logic and foundry, supporting the entire AI workflow from training to inference. The company’s differentiated packaging capabilities and its expertise in integrating memory with system semiconductors position it uniquely to deliver tailored solutions to OpenAI.

Samsung SDS: Building the Future of AI data centres

Samsung SDS enters a partnership with OpenAI to co-develop advanced AI data centres and provide enterprise AI services. The company brings expertise in data centre design, deployment and operation, and will play a vital role in developing and managing the Stargate AI data centres.

Under the LOI, Samsung SDS is now positioned to deliver consulting, integration and management services for organisations adopting OpenAI’s AI models. Additionally, Samsung SDS signs a reseller agreement for OpenAI services in Korea, supporting businesses in adopting ChatGPT Enterprise solutions and accelerating AI transformation across industries.

Samsung C&T and Samsung heavy industries

Samsung C&T and Samsung Heavy Industries join forces with OpenAI to develop floating data centres, a concept designed to address global land scarcity while improving sustainability. Floating data centres can reduce cooling costs, optimise energy use and lower carbon emissions.

Samsung C&T and Samsung Heavy Industries also explore broader opportunities in floating power plants and floating control centres. Their shipbuilding and engineering expertise, combined with OpenAI’s AI infrastructure needs, create opportunities to pioneer large-scale maritime technology projects that support the next generation of AI systems.

Supporting Korea’s AI Ambitions

Samsung’s partnership with OpenAI aligns with Korea’s national strategy to become one of the world’s top three nations in AI. By advancing semiconductor solutions, next-generation data centres and floating infrastructure, the collaboration strengthens Korea’s position in the global AI ecosystem.

Samsung is also exploring wider use of ChatGPT internally, promoting AI-driven transformation across its businesses.

About OpenAI

OpenAI is an artificial intelligence research and deployment company with a mission to ensure that artificial general intelligence (AGI) benefits all of humanity. Founded in 2015, the company has become one of the world’s leading organisations in developing large-scale AI models.

Its portfolio includes products such as ChatGPT, GPT models, DALL·E for image generation, and Codex for coding assistance, all designed to bring advanced AI capabilities into practical use. OpenAI also partners with enterprises and governments to integrate AI responsibly across industries. The company is guided by its commitment to safety, ethics and transparency in AI deployment, ensuring its technologies create broad social and economic value.

About Samsung Electronics Co., Ltd.

Samsung Electronics inspires the world and shapes the future with transformative ideas and technologies. Established in 1969, the company has grown into one of the world’s largest technology manufacturers, operating across consumer electronics, semiconductors, and communications. Its product portfolio includes televisions, smartphones, tablets, wearable devices, digital appliances and network systems, many of which lead their markets globally.

In semiconductors, Samsung is a world leader in memory chips, logic solutions, and foundry services, supplying advanced components that power cloud computing, artificial intelligence, and next-generation devices. The company is also advancing innovations in AI, 5G, IoT, robotics, automotive electronics, medical imaging technologies, and HVAC systems.

Through the SmartThings ecosystem, Samsung connects millions of devices into a seamless, intelligent network for consumers. It continues to expand its research in sustainable technology and energy-efficient solutions while collaborating with global partners to build future-ready innovations.

About Samsung C&T Corporation

Samsung C&T Corporation, founded in 1938 as the first Samsung company, has evolved into a global enterprise operating in more than 50 countries. The company manages four core business groups: Engineering & Construction, Trading & Investment, Fashion, and Resort.

The Engineering & Construction division is renowned for landmark projects worldwide, including skyscrapers, airports, railways, power plants, and civil infrastructure. The Trading & Investment group covers a wide range of industries, from chemicals and steel to renewable energy and industrial materials, driving sustainable business development. The Fashion group develops and markets leading brands across apparel and lifestyle sectors, while the Resort group manages integrated resorts, leisure facilities, and theme parks.

With a focus on innovation, global partnerships, and sustainability, Samsung C&T contributes to international infrastructure growth and lifestyle industries.

About Samsung Heavy Industries Co., Ltd.

Samsung Heavy Industries Co., Ltd. (SHI), founded in 1974, is one of the world’s largest and most technologically advanced shipbuilding companies. Based in South Korea, SHI specialises in designing and constructing a wide range of high-value ships, including LNG carriers, container vessels, oil tankers, drillships, FPSOs (Floating Production Storage and Offloading units), and FLNGs (Floating Liquefied Natural Gas facilities).

The company operates one of the most sophisticated shipyards in the world, equipped with advanced automation and digital shipbuilding technologies. SHI has pioneered numerous world-first innovations, including the Arctic Shuttle-Tanker and FLNG facilities, and is a recognised leader in developing environmentally friendly and energy-efficient vessels.

Beyond shipbuilding, SHI is expanding into offshore engineering and integrated maritime solutions, positioning itself as a central player in the transition towards sustainable and intelligent marine industries.

About Samsung SDS Co., Ltd.

Samsung SDS, established in 1985, is a leading global provider of digital transformation and IT services. The company delivers advanced solutions that integrate artificial intelligence, cloud computing, cybersecurity, logistics and enterprise applications to help organisations increase productivity and competitiveness.

Through its Samsung Cloud Platform (SCP), the company provides enterprise-grade cloud and AI solutions tailored for diverse industries. Its digital logistics platform, Cello Square, supports globally integrated freight forwarding services, enabling businesses to optimise operations and make data-driven decisions.

Samsung SDS also develops industry-specific SaaS platforms, ranging from finance and manufacturing to healthcare and retail, helping organisations implement hyper-automation. With over 40 years of expertise and operations spanning multiple continents, Samsung SDS remains at the forefront of enterprise AI adoption, digital innovation, and global logistics integration.

The post Samsung and OpenAI Announce Strategic Partnership to Drive Global AI Infrastructure Development appeared first on IntelligentHQ.

Read more here: https://www.intelligenthq.com/samsung-openai-strategic-partnership-global-ai-infrastructure/

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ChannelConnect is ook dit jaar mediapartner van de Fiber Vakdag en de Green Datacenter Conference. Tijdens beide evenementen verschijnt het novembernummer van ChannelConnect, met daarin twee specials die perfect aansluiten op de beide beurzen: Data & Duurzaamheid en Network & Infrastructure. Deze editie wordt voor het eerst verspreid tijdens deze conferenties.

Verder vind je in deze editie een special rond Network & Infrastructure. Digitale innovatie staat of valt met een solide infrastructuur. Deze special onderzoekt de bouwstenen van de digitale economie: glasvezel en PON-technologie, SD-WAN en SASE, edge computing en AI-gestuurde netwerkautomatisering. Duurzaamheid loopt als rode draad mee, met aandacht voor energiezuinige netwerkoplossingen en circular IT.

Voorbeelden van onderwerpen:

• Glasvezel en PON-technologie voor mkb en enterprise
• SD-WAN, SASE en zero trust op netwerkniveau
• Edge-datacenters en latency-kritische toepassingen
• AI en automatisering in netwerkbeheer

Het bericht ChannelConnect verspreid tijdens Fiber Vakdag & Green Datacenter Conference verscheen eerst op ChannelConnect.

Read more here: https://www.channelconnect.nl/datacenter-en-cloud/channelconnect-verspreid-tijdens-fiber-vakdag-green-datacenter-conference/

The post ChannelConnect verspreid tijdens Fiber Vakdag & Green Datacenter Conference appeared first on IPv6.net.

In the rapidly evolving landscape of artificial intelligence and machine learning, organizations continue to seek cost-effective solutions to reduce reliance on expensive third-party tools—not only for development but also for deployment. Recently I was tasked with deploying a predictive machine learning (ML) model at my organization. Our original goal was to bring the ML model in-house to reduce operational costs, but the deployment process presented significant challenges due to expensive infrastructure requirements.

Enter serverless computing, with platforms like AWS Lambda offering a compelling solution for lightweight and on-demand ML inference. The serverless approach is a particularly timely option given the rise in edge computing and machine learning use cases and the need to reduce the excessive costs traditionally associated with ML deployment.

In this article, I will walk you through two ways to deploy an ML model on AWS Lambda. AWS Lambda is a preferred choice because it is simple, automatically scalable, and cost-effective, as we only pay for the requests we make.

Why use AWS Lambda for ML model deployment?

AWS Lambda provides a compelling solution for model deployment that offers a true pay-as-you-go service model. Key advantages include

• Cost efficiency: For organizations processing between 1,000 to 10,000 predictions daily, serverless compute can potentially reduce infrastructure costs by up to 60% compared to maintaining dedicated prediction servers.
• Scalability: AWS Lambda automatically scales computational resources based on incoming prediction requests, without requiring manual intervention.

By eliminating the need for pre-provisioned server capacity, organizations can optimize resource utilization and significantly reduce infrastructure overhead.

While AWS Lambda excels in many scenarios, it is crucial to evaluate its limitations, including cold starts and resource constraints, to determine if it aligns with your specific ML deployment needs.

Approach #1:  Deploying a model stored on Amazon S3

Deploying a ML model as a Python pickle file in an Amazon S3 bucket and using it through a Lambda API makes model deployment simple, scalable, and cost-effective. We set up AWS Lambda to load this model from S3 when needed, enabling quick predictions without requiring a dedicated server. When someone calls the API connected to the Lambda function, the model is fetched, run, and returns predictions based on the input data. This serverless setup ensures high availability, scales automatically, and saves costs because you only pay when the API is used.

Step 1. Create a zip archive for the Lambda layer

A Lambda layer is a zip archive that contains libraries, a custom runtime, and other dependencies. I will demonstrate the creation of a Lambda layer using two Python libraries, Pandas and Scikit-learn, that are often used in ML models. Below is the code for creating a Lambda layer zip archive, containing Pandas and Scikit-learn, using Docker. Create a file, name it createlayer.sh, and copy the code into it.

if [ "$1" != "" ] || [$# -gt 1]; then
echo "Creating layer compatible with python version $1"
docker run -v "$PWD":/var/task "lambci/lambda:build-python$1" /bin/sh -c "pip install -r requirements.txt -t python/lib/python$1/site-packages/; exit"
zip -r sklearn_pandas_layer.zip python > /dev/null
rm -r python
echo "Done creating layer!"
ls -lah sklearn_pandas_layer.zip
else
echo "Enter python version as argument - ./createlayer.sh 3.6"

Now, in the same directory, create a file named requirements.txt to store the names and versions of the libraries in the layer. In this case, our requirements.txt file will list the names and versions of the Pandas and Scikit-learn libraries we’re using.

pandas==0.23.4
scikit-learn==0.20.3

Next, in the terminal, navigate to the directory where you have placed the createlayer.sh and requirements.txt files and run the command below to generate the Lambda layer zip file.

./createlayer.sh 3.6

When the above shell command is executed, the pip install command included in the shell script will automatically download Pandas, Scikit-learn, and their dependencies from the Python Package Index (PyPI) and install them directly into the python/lib/python$1/site-packages/ directory. When the shell script completes, you will find that the generated Lambda layer zip file contains folders for Pandas, Scikit-learn, NumPy, and SciPy, along with some Python files.

Step 2. Store the ML model and Lambda layer files in Amazon S3

Create a new folder in an Amazon S3 bucket and give it the name of your Lambda function for deploying the ML model (such as DeployMlModel). Copy the Python pickle file for your ML model and the zip file for your Lamba layer to the new folder. After you have copied the files, your S3 bucket should show the folder and its contents as shown in Figure 1 below.

Foundry

Step 3. Create the Lambda function

1. Go to the AWS Lambda console and click “Create function.”
2. Choose “Author from scratch.”
3. Enter the function name (e.g., DeployMlModel).
4. Choose the runtime (e.g., Python 3.6).
5. Select or create an appropriate execution role with permission to read from Amazon S3.
6. Click “Create function.”

At this point, you’ll have an empty Lambda function ready to be configured.

Step 4. Add the Lambda layer to the Lambda function

In this step we configure AWS Lambda to use the Lambda layer zip file we created and stored in S3 in Step 2. To add our Lambda layer zip file to AWS Lambda, we click “Layers,” then “Create Layer” in the AWS Lambda UI as shown in Figure 2 below.

Foundry

Next, enter the name, description, S3 URL, and other properties of our Lambda layer as shown in Figure 3 below and click Save.

Foundry

Once the new Lambda layer is created, you should receive a “Successfully created layer” message at the top of the window as shown in Figure 4 below.

Foundry

Some key points about Lambda layers to keep in mind:

1. Lambda layers must be zipped files.
2. You can have at most five Lambda layers for a given Lambda function.
3. The total unzipped size of the Lambda function and its layers cannot be bigger than 250MB.

Now, to add this layer to your Lambda function, go to the Lambda function that you created in Step 3, click on “Layers,” and choose the “Custom layers” option. See Figures 5 and 6 below for reference.

Foundry

Foundry

In the “Custom layers” dropdown menus, select the name and version of the Lambda layer and click on “Add” to add it to the Lambda function.

Step 5. Add the Lambda function code

Next, we will add the Lambda function code that uses the ML model.

1. In the AWS Lambda console, open the Lambda function (DeployMlModel) you created in Step 3.
2. In the left-hand menu, click on “Code.”
3. In the inline editor, replace the default content with the following code:

import json
import pickle
import sklearn
import boto3
import pathlib
import jsons3 = boto3.resource('s3')
filename = 'ml_model.pkl'
file = pathlib.Path('/tmp/'+filename)
if file.exists ():
    print ("File exist")
else :
    s3.Bucket('deployingmlmodel').download_file(filename, '/tmp/ml_model.pkl')
def lambda_handler(event, context):    model = pickle.load(open('/tmp/'+filename, 'rb'))
y    print("provide input here")
    #pred = model.predict(""provide input here"")

Your Lambda function now should include one layer and the code listed above. See Figure 7 below for reference.

Foundry

Hurray! You have successfully deployed your ML model on AWS Lambda. To test your Lambda function, go to the “Test” tab in the AWS Lambda console. Create a new test event by clicking “Configure test event,” provide a simple JSON payload (i.e., an input your model expects), and click “Test.” The function should run, load the model from Amazon S3, and return the output in the console. This allows you to quickly validate that your deployment is working correctly and view the predictions generated by your ML model.

Approach #2: Packaging the model with the AWS Lambda deployment

This approach involves zipping the ML model pickle file together with the Lambda function and uploading the whole package directly to AWS Lambda. Save the Lambda function code in Step 5 above in a file named Predict.py and then zip it together with the ML model pickle file (e.g., ml_model.pkl) to create a zipped archive. See Figure 8 below for the contents of the zip archive.  

Foundry

Now, upload this zipped file to AWS Lambda using the “Upload a .zip file” option highlighted in Figure 9 below.

Foundry

If the size of your zip file is less than 10MB, you can upload it from here. Otherwise, first upload the zip file to Amazon S3 and use the “Upload a file from Amazon S3” option to add it to AWS Lambda from there. This instruction is displayed in small type in the “Upload a .zip file” window as shown in Figure 10 below.

Foundry

Click Save. Once your file is uploaded successfully, view your Lambda function. It should show the .pkl file and the .py file in the archive folder as shown in Figure 11 below.

Foundry

Woohoo! You have successfully deployed the ML model in zip format along with the Lambda function code.

Real-world applications and limitations

Serverless ML deployment is particularly well-suited for low-volume, on-demand use cases, such as customer support chatbots, image recognition APIs, and other lightweight inference tasks at the edge, reducing reliance on central data centers.

TradeIndia.com, a B2B trade portal, uses AWS Lambda to run lightweight ML models for real-time customer data analysis. As a result of their serverless model deployment, they reduced infrastructure costs by 25% to 30%, enabling them to reinvest those savings into expanding their service offerings.

Of course, AWS Lambda also has limitations. For model deployment, the primary limitation is the 250MB package size restriction, which could pose a challenge for complex models. To address this constraint, developers can employ mitigation techniques such as model compression, selective feature engineering, and efficient dependency management. Modularizing model components and implementing hybrid architectures that blend serverless and traditional infrastructure can help overcome size limitations without sacrificing model performance.

Another challenge with AWS Lambda is cold starts, where initial function invocations can experience latency spikes of 10 to 12 seconds, contrasting sharply with the near-instantaneous responses of dedicated server environments. On the first invocation, Lambda must download the container image into its runtime environment, leading to additional response time. This latency is particularly noticeable in scenarios requiring low-latency responses.

To mitigate this, you can configure a CloudWatch-triggered Lambda event to periodically invoke the Lambda function, keeping it “warm” and ready for execution, reducing delays. Additionally, this configuration can be optimized to run only during specific time windows, such as business hours, to balance performance and cost. This approach ensures the ML model remains available without introducing unnecessary runtime costs.

In conclusion, deploying an ML model using AWS Lambda provides a scalable, cost-effective solution that eliminates the need for expensive licensing and deployment tools. The two approaches discussed—reading the ML model from an Amazon S3 bucket, and zipping the model together with the Lambda function code—provide some flexibility in addressing different deployment scenarios.

While the AWS Lambda architecture is efficient, addressing the cold start latency with techniques like warming up the Lambda function will help you ensure optimal performance, even for the first API call. By combining cost efficiency and performance optimization, this deployment method for ML models stands out as a practical choice for organizations aiming to maximize value and reduce expenses.

Read more here: https://www.infoworld.com/article/4064124/how-to-deploy-machine-learning-models-with-aws-lambda.html

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In this new report from Nokia, learn how different CSPs in different regions plan and execute a strategy towards autonomous networks. Explore each region’s unique challenges and how they impact investments

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The major concepts that form the foundation of the Fourth Industrial Revolution (4IR) revolve around digital transformation and its key enabling technologies: Artificial Intelligence (AI), Blockchain, the Internet of Things (IoT), and Fintech.

“The past cannot be changed. The future is yet in your power.” Mary Pickford

We live in a fast, disruptive, technology-driven world where concepts like digital transformation and Industry 4.0 (4IR), AI, Blockchain, IoT, and Fintech influence everything we do as individuals and in the shaping of our cities and countries. This is a world filled with promise and opportunities but also many challenges.

The Fourth Industrial Revolution was defined by Klaus Schwab (2018) as the fourth major industrial era since the initial Industrial Revolution of the 18th century. It is characterised by a fusion of technologies that blur the lines between the physical, digital, and biological spheres, collectively referred to as cyber-physical systems.

What is driving the 4IR are data-driven technologies that have the potential to radically change our economic models, increase productivity, and improve our lives. The 4IR results from an increasingly rapid digital transformation happening worldwide. This digital transformation has brought many evident benefits but is now entering a second stage, one that presents a new set of important challenges. Among these challenges are the growing awareness of how our economic activities impact climate change, as well as the disruption of jobs and the transformation of what we understand as work.

2018 was an annus horribilis in terms of global climate catastrophes. It is irrefutable that the present economic system and human action are triggering changes in the climate. On the other hand, 4IR’s most praised asset is its ability to increase productivity. But what kind of productivity are we talking about? Do we want productivity at all costs, with its implicit externalities, such as its impact on climate change? Or are we able to pursue productivity more sustainably, mindful of the waste it produces? Can the 4IR enable us to shift to more beneficial economic systems, such as the circular economy?

Another important risk of the 4IR is its effect on what we now understand as jobs/work. We have already seen how the way we work and live has changed dramatically over the past few decades, and this will only increase. Initially, 4IR will primarily impact machine operators and food workers, but job loss is expected to extend across various sectors. This development has sparked significant public concern, and governments and nations can no longer ignore this challenge.

A world governed by digits: Digital transformation

Even if we do not think about it, our world is governed by digits. The smartphones we all carry in our pockets are small digital machines packed with powerful chips, coded in ones and zeros. These computational devices have reduced in size incredibly over time, but their capabilities continue to expand exponentially. This journey began with the invention of the first digital calculating machine during the 1940s, followed by the development of subsequent computers and the invention of the internet, which shaped the world as we know it today. The web and its devices became the core instruments around which we govern our lives, impacting the way we live, work, and relate to each other. These technological evolutions have disrupted many of our existing systems and behaviours, while heavily challenging business models, governance processes, and social dynamics.

What is digital transformation?

What we just described is known as “Digital Transformation.” What triggered it was the increasing digitisation of the world. One way to define digital transformation is as “the novel use of digital technology to solve traditional problems” (Lankshear, Colin; Knobel, Michele, 2008). Another definition comes from Shahyan Khan, who analysed the societal effects of digitalisation (Khan, 2017). According to Khan, digitisation (the technical conversion), digitalisation (the business process), and digital transformation (the effect) all contribute to accelerating and illuminating ongoing global processes of societal change. This transformation impacts business models, consumption patterns, socio-economic structures, legal frameworks, organisational patterns, cultural barriers, communication processes, and more.

The spread of digital transformation

The pace at which digital transformation occurs, and the degree to which it is embraced, vary considerably. However, digital transformation seems to have a life of its own. It is happening globally, particularly in Europe and the Western world, with an increasing number of developing countries joining in. Every year, the level of openness and interconnectivity in our economic and social activities grows. This is driven by increasing digitisation and the emergence of technology-intensive sectors shaped by globally hyper-connected marketplaces.

Impact on industries

According to recent research by McKinsey, sectors that will be most affected by digital transformation include Banking, Media and Entertainment, Pharma, Retail, Hospitality, Travel, Insurance, and the Public Sector (Brian Fox, Amit Paley, Michelle Prevost, and Nisha Subramanian, 2017). The impact of digital transformation is not only economic; it also questions our existing culture, communication models, and governance frameworks.

The third industrial revolution

Digital transformation is not a static concept. It has evolved quickly over the years, particularly with improvements in technology, especially the internet, which has fostered increasing digitisation. Jeremy Rifkin, a US economist and sociologist, described this evolution in his book The Third Industrial Revolution: How Lateral Power is Transforming Energy, the Economy, and the World (2011). Rifkin argued that technological shifts occur when new communication technologies, energy supply forms, and transportation mechanisms converge. This confluence of advancements accelerates efficiency, triggering profound societal shifts.

Technological convergence in industrial revolutions

• The first Industrial Revolution (19th century) was driven by steam power, letterpress printing, and railways.
• The second Industrial Revolution (20th century) was driven by electric communication, the combustion engine, and road transportation.
• The third Industrial Revolution is driven by the internet, renewable energies, and sustainable mobility.

Rifkin argued that developed economies could only increase productivity by adopting a connected architecture of data-driven technologies (cloud computing, AI, IoT) that improve energy efficiency in production and distribution. This shift supports a “low carbon economy” and prepares the world for the next industrial revolution.

Since the invention of the iPhone in 2007, the digitisation process has accelerated significantly, especially with the widespread adoption of smartphones. There are now more mobile phones than people, and this expansion in digitisation has resulted in a massive increase in data production. This data comes from sensors, actuators, and the Internet of Things (IoT). As the cost of sensors has decreased and bandwidth has increased, the amount of data being generated has escalated, further fueling developments in AI, Blockchain, IoT, and Fintech, which are now driving the 4IR.

The 4th industrial revolution

Klaus Schwab describes the 4IR as “a range of new technologies that are fusing the physical, digital, and biological worlds, impacting all disciplines, economies, and industries, and even challenging ideas about what it means to be human.” The 4IR is characterized by “velocity, scope, and systems impact,” and is disrupting industries worldwide, leading to the transformation of systems of production, management, and governance.

Key impacts of 4IR:

• A Supercomputer in Your Pocket
• Smart Cities
• AI and Automation
• Blockchain and Cryptocurrencies
• The Sharing Economy
• The Circular Economy

In business, the 4IR is expected to lead to:

• Transformed customer expectations.
• Products enhanced by data, improving asset productivity.
• New partnerships formed based on collaborative innovation.
• New operating models that are more automated and peer-to-peer.

Four most important data-driven technologies shaping the 4IR

I. AI: The powerful search engine at the core of 4IR

AI can imitate intelligent human behaviour and is expanding rapidly across all areas of society. Innovations in AI, such as neurotrophic chips and quantum computing, are accelerating its capabilities, enabling it to handle massive data sets and perform simulations previously thought impossible.

II. Blockchain: The potential architect of the future internet

Blockchain is revolutionising how data is stored, verified, and shared across decentralised networks. Its transparency and security make it an ideal solution for storing large amounts of data, and it is increasingly seen as the future backbone of the internet.

III. IoT: Connecting matter with people

The IoT connects everyday objects and devices, enabling improved efficiency and innovation. The convergence of IoT and blockchain is creating new possibilities for communication and data management between devices.

IV. Fintech: The energy heart of the world

Fintech is transforming the financial sector by providing digital alternatives to traditional financial methods. Mobile phones have made it easier for people, especially in developing countries, to access financial services and participate in global economic activities.

Challenges of the 4IR

While the 4IR presents many opportunities, it also brings significant challenges, especially regarding job loss and security. Automation may lead to fewer new jobs in emerging industries, as studies by Oxford Martin University and McKinsey have shown. Additionally, cybersecurity concerns will escalate as more systems become automated and interconnected.

To navigate these challenges, ideas such as Universal Basic Income (UBI) and Basic Income Guarantee (BIG) have been proposed. These measures could help cushion the effects of job loss and ensure a more equitable transition into the future workforce.

Digital transformation, innovation, and legislation

Digital transformation and the 4IR are here to stay, and their impact will continue to grow. As technologies like AI, Blockchain, IoT, and Fintech converge, they will blur the lines between the physical, digital, and biological spheres. However, to ensure the benefits of these technologies outweigh their risks, careful planning and innovative legislation are required.

Countries like Luxembourg have set examples of balanced regulation that fosters innovation while ensuring safety. The key challenge for governments worldwide is to develop policies that encourage technological advancement while minimising risks such as inequality and environmental degradation.

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The proliferation of poorly secured IoT devices is a major factor behind an increase in hardware vulnerabilities, a new survey has revealed. The latest report from Bugcrowd, a specialist in

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