Using SOPS with Pulumi

I was first introduced to SOPS at a platform engineering event hosted in Denver last year. SOPS, which is an acronym for Secrets OPerationS, describes itself as “an editor of encrypted files that supports YAML, JSON, ENV, INI and BINARY formats and encrypts with AWS KMS, GCP KMS, Azure Key Vault, age, and PGP” (taken directly from the project’s GitHub repository). In this post, I’ll explore using Pulumi with SOPS—and I’ll also touch upon whether this combination of tools offers value or users or not.

SOPS is a command-line tool written primarily in Go; users can download binaries from the SOPS GitHub repository or, for Linux users, install it via their distribution’s package manager. Depending upon the encryption mechanism you’re going to use, you may also need to install other tools (for example, if you’re going to use AWS KMS then you’ll need the appropriate AWS tools installed and configured). I chose to use Rage, a Rust-based implementation of Age, as my encryption mechanism.

One of the things I find really interesting about SOPS is the fact that it supports data formats like YAML and JSON. What does this mean, exactly? When you Continue reading

Paris 2024 Olympics recap: Internet trends, cyber threats, and popular moments

The Paris 2024 Summer Olympics wrapped up on August 11, 2024, with the Olympic flag being lowered in the Stade de France after 16 days of competitions. With 329 events across 32 sports, over 10,000 athletes from 204 nations participated in the pursuit of medals and glory, creating some viral online moments along the way. In this post, we turn our attention to the closing ceremony, the impact of various Olympic moments on Internet traffic, and the cyber attacks faced by sponsors. We also examine email trends related to the Olympics, including mentions of Simone Biles, Snoop Dogg, and Imane Khelif.

Cloudflare has a global presence with data centers in over 330 cities, supporting millions of customers with different tools and products, which provides a global view of what’s happening on the Internet. This is helpful for improving security, privacy, efficiency, and speed, but also for observing Internet disruptions and traffic trends.

In our previous blog post about the opening ceremony and the early days of the event, we showed how France was impacted by the Olympics, with clear drops in traffic during the main events. The opening ceremony caused the most significant drop—traffic decreased by as much as 20% Continue reading

Paris 2024 Olympics recap: Internet trends, cyber threats, and popular moments

The Paris 2024 Summer Olympics wrapped up on August 11, 2024, with the Olympic flag being lowered in the Stade de France after 16 days of competitions. With 329 events across 32 sports, over 10,000 athletes from 204 nations participated in the pursuit of medals and glory, creating some viral online moments along the way. In this post, we turn our attention to the closing ceremony, the impact of various Olympic moments on Internet traffic, and the cyber attacks faced by sponsors. We also examine email trends related to the Olympics, including mentions of Simone Biles, Snoop Dogg, and Imane Khelif.

Cloudflare has a global presence with data centers in over 330 cities, supporting millions of customers with different tools and products, which provides a global view of what’s happening on the Internet. This is helpful for improving security, privacy, efficiency, and speed, but also for observing Internet disruptions and traffic trends.

In our previous blog post about the opening ceremony and the early days of the event, we showed how France was impacted by the Olympics, with clear drops in traffic during the main events. The opening ceremony caused the most significant drop—traffic decreased by as much as 20% Continue reading

Arista cEOS Got Working MPLS Data Plane

Urs Baumann brought me a nice surprise last weekend. He opened a GitHub issue saying, “MPLS works on Arista cEOS containers in release 4.31.2F” and asking whether we could enable netlab to configure MPLS on cEOS containers.

netlab already had MPLS configuration templates for Arista EOS but reported an error message if you tried to use MPLS with the cEOS containers because the containers did not have a working MPLS data plane.

After a few configuration tweaks and a batch of integration tests later, I had the results: everything worked. You can use MPLS on Arista cEOS with netlab release 1.9.0 (right now @ 1.9.0-dev2), and I’ll be able to create MPLS labs running in GitHub Codespaces in the not-too-distant future.

Huawei’s HiSilicon Can Compete With Nvidia GPUs In China

Each time that the United States has figured out that it needed to do export controls on massively parallel compute engines to try to discourage China from buying such gear and building supercomputers with them, it has already been too late to have much of a long term effect on China’s ability to run the advanced HPC simulations and AI training workloads that we were worried would be enabled by such computing oomph. …

Huawei’s HiSilicon Can Compete With Nvidia GPUs In China was written by Timothy Prickett Morgan at The Next Platform.

HS080: Top Mistakes In Developing and Executing Technology Strategies

To borrow a phrase first used in a military context, no tech strategy survives its first contact with real users. Today’s Heavy Strategy explores common mistakes executives make when developing and executing a technology plan. They include poor communication, making assumptions, not understanding a system’s architecture or dependencies, and more. Co-hosts Johna and Jerry draw... Read more »

Introducing HTTP request traffic insights on Cloudflare Radar

Historically, traffic graphs on Cloudflare Radar have displayed two metrics: total traffic and HTTP traffic. These graphs show normalized traffic volumes measured in bytes, derived from aggregated NetFlow data. (NetFlow is a protocol used to collect metadata about IP traffic flows traversing network devices.) Today, we’re adding an additional metric that reflects the number of HTTP requests, normalized over the same time period. By comparing bytes with requests, readers can gain additional insights into traffic patterns and user behavior. Below, we review how this new data has been incorporated into Radar, and explore HTTP request traffic in more detail.

Note that while we refer to “HTTP request traffic” in this post and on Radar, the term encompasses requests made in the clear over HTTP and over encrypted connections using HTTPS – the latter accounts for ~95% of all requests to Cloudflare during July 2024.

New and updated graphs

Graphs including HTTP request-based traffic data have been added to the Overview and Traffic sections on Cloudflare Radar. On the Overview page, the “Traffic trends” graph now includes a drop-down selector at the upper right, where you can choose between “Total & HTTP bytes” and “HTTP requests & bytes”. We explore Continue reading

Introducing HTTP request traffic insights on Cloudflare Radar

Historically, traffic graphs on Cloudflare Radar have displayed two metrics: total traffic and HTTP traffic. These graphs show normalized traffic volumes measured in bytes, derived from aggregated NetFlow data. (NetFlow is a protocol used to collect metadata about IP traffic flows traversing network devices.) Today, we’re adding another metric that reflects the number of HTTP requests, normalized over the same time period. By comparing bytes with requests, readers can gain additional insights into traffic patterns and user behavior. Below, we review how this new data has been incorporated into Radar, and explore HTTP request traffic in more detail.  

Note that while we refer to “HTTP request traffic” in this post and on Radar, the term encompasses requests made in the clear over HTTP and over encrypted connections using HTTPS – the latter accounts for ~95% of all requests to Cloudflare during July 2024.

New and updated graphs

Graphs including HTTP request-based traffic data have been added to the Overview and Traffic sections on Cloudflare Radar. On the Overview page, the “Traffic trends” graph now includes a drop-down selector at the upper right, where you can choose between “Total & HTTP bytes” and “HTTP requests & bytes”. We explore Continue reading

Layer-3-Only EVPN: Behind the Scenes

In the previous blog post, I described how to build a lab to explore the layer-3-only EVPN design and asked you to do that and figure out what’s going on behind the scenes. If you didn’t find time for that, let’s do it together in this blog post. To keep it reasonably short, we’ll focus on the EVPN control plane and leave the exploration of the data-plane data structures for another blog post.

The most important thing to understand when analyzing a layer-3-only EVPN/VXLAN network is that the data plane looks like a VRF-lite design: each VRF uses a hidden VLAN (implemented with VXLAN) as the transport VLAN between the PE devices.

Read more …

Rising together: honoring Cloudflare’s outstanding partners

We’re thrilled to announce Cloudflare’s worldwide 2023 Channel Partner Award winners! Partners are crucial to Cloudflare’s success, extending the solutions and support that customers need to control application complexity, reduce cyber risk, and cut costs, all with a high level of customer satisfaction.

PowerUP Partners First

This year, we again received CRN’s highest accolade of a 5-star ranking for our Partner Program. Through our expanded Cloudflare PowerUP Partner Program, we’re ensuring Cloudflare’s partnerships and alliances continue delivering strong results to joint customers across sectors worldwide. We’re focused on making it easier for our partners to work with us and grow their business with us. The Cloudflare team is all about helping partners:

  • Be innovative by transforming how customers connect, protect, and build with Cloudflare security, speed, programmability, and resilience.

  • Increase profitability by growing revenue and delivering more value at scale to rapidly grow business and expand reach.

  • Accelerate GTM by benefiting from sales and marketing support, streamlined processes, and transparent pricing to close deals quickly.

From comprehensive training through Cloudflare University to expert support across departments, partners are equipped to drive digital transformation and modernize IT infrastructures for their customers in a competitive market.

Leaders Who Understand the Power Continue reading

Rising together: honoring Cloudflare’s outstanding partners

This post is also available in Deutsch, Español, 简体中文, 繁體中文, 日本語 and 한국어.

We’re thrilled to announce Cloudflare’s worldwide 2023 Channel Partner Award winners! Partners are crucial to Cloudflare’s success, extending the solutions and support that customers need to control application complexity, reduce cyber risk, and cut costs, all with a high level of customer satisfaction.

PowerUP partners first

This year, we again received CRN’s highest accolade of a 5-star ranking for our Partner Program. Through our expanded Cloudflare PowerUP Partner Program, we’re ensuring Cloudflare’s partnerships and alliances continue delivering strong results to joint customers across sectors worldwide. We’re focused on making it easier for our partners to work with us and grow their business with us. The Cloudflare team is all about helping partners:

  • Be innovative by transforming how customers connect, protect, and build with Cloudflare security, speed, programmability, and resilience.
  • Increase profitability by growing revenue and delivering more value at scale to rapidly grow business and expand reach.
  • Accelerate GTM by benefiting from sales and marketing support, streamlined processes, and transparent pricing to close deals quickly.

From comprehensive training through Cloudflare University to expert support across departments, partners are equipped to drive digital Continue reading

The Sugar Daddy Boomerang Effect: How AI Investments Puff Up The Clouds

Here’s a question for you: How much of the growth in cloud spending at Microsoft Azure, Amazon Web Services, and Google Cloud in the second quarter came from OpenAI and Anthropic spending money they got as investments out of the treasure chests of Microsoft, Amazon, and Google? …

The Sugar Daddy Boomerang Effect: How AI Investments Puff Up The Clouds was written by Timothy Prickett Morgan at The Next Platform.

NB490: Google’s Post-Monopoly Options; Microsoft Flips Delta’s Legal Threats the Bird

Take a Network Break! This week we cover a judge’s ruling that Google is monopolist and potential outcomes, the HPE/Juniper acquisition clearing regulatory hurdles, and Microsoft flipping the bird at Delta’s legal threats. HPE Aruba Networking adds NDR for IoT devices, Fortinet fortifies its DLP capabilities via acquisition, Azure lets you stack logs in different... Read more »

Advancing Threat Intelligence: JA4 fingerprints and inter-request signals

For many years, Cloudflare has used advanced fingerprinting techniques to help block online threats, in products like our DDoS engine, our WAF, and Bot Management. For the purposes of Bot Management, fingerprinting characteristic elements of client software help us quickly identify what kind of software is making an HTTP request. It’s an efficient and accurate way to differentiate a browser from a Python script, while preserving user privacy. These fingerprints are used on their own for simple rules, and they underpin complex machine learning models as well. 

Making sure our fingerprints keep pace with the pace of change on the Internet is a constant and critical task. Bots will always adapt to try and look more browser-like. Less frequently, browsers will introduce major changes to their behavior and affect the entire Internet landscape. Last year, Google did exactly that, making older TLS fingerprints almost useless for identifying the latest version of Chrome.

JA3 Fingerprint 

JA3 fingerprint introduced by Salesforce researchers in 2017 and later adopted by Cloudflare, involves creating a hash of the TLS ClientHello message. This hash includes the ordered list of TLS cipher suites, extensions, and other parameters, providing a unique identifier for each Continue reading

Advancing Threat Intelligence: JA4 fingerprints and inter-request signals

For many years, Cloudflare has used advanced fingerprinting techniques to help block online threats, in products like our DDoS engine, our WAF, and Bot Management. For the purposes of Bot Management, fingerprinting characteristic elements of client software help us quickly identify what kind of software is making an HTTP request. It’s an efficient and accurate way to differentiate a browser from a Python script, while preserving user privacy. These fingerprints are used on their own for simple rules, and they underpin complex machine learning models as well.

Making sure our fingerprints keep pace with the pace of change on the Internet is a constant and critical task. Bots will always adapt to try and look more browser-like. Less frequently, browsers will introduce major changes to their behavior and affect the entire Internet landscape. Last year, Google did exactly that, making older TLS fingerprints almost useless for identifying the latest version of Chrome.

Cloudflare network fingerprinting techniques

These methods are instrumental in accurately scoring and classifying bots, enhancing security measures, and enriching data analytics capabilities. Below are some examples of the fingerprinting techniques we have implemented over the years:

HTTP Signature: The HTTP Signature technique involves analyzing HTTP Continue reading

Response: The Usability of VXLAN

Wes made an interesting comment to the Migrating a Data Center Fabric to VXLAN blog post:

The benefit of VXLAN is mostly scalability, so if your enterprise network is not scaling… just don’t. The migration path from VLANs is to just keep using VLANs. The (vendor-driven) networking industry has a huge blind spot about this.

Paraphrasing the famous Dinesh Dutt’s Autocon1 remark: I couldn’t disagree with you more.

Read more …

How Walking Improved My Daily Productivity?

How Walking Improved My Daily Productivity?

Recently, walking has become a habit for me, and I absolutely love taking short walks while listening to music or podcasts. It helps me rest and recover mentally, emotionally, and physically. Walking clears my mind and helps me process my emotions and thoughts. In this post, I will cover the benefits I experience from walking and how it improves my productivity.

Taking a Break with a Walk

Every time I feel stressed or need a break from everything around me, I go for a walk. It's a simple act, but it refreshes me more than anything else. These quiet moments alone with my thoughts are important for recharging and gaining a new perspective on whatever is bothering me. Walking not only gives me the physical exercise I need but also eases my mind and allows me to return to my tasks with renewed energy and focus.

AI/ML Networking: Part-IV: Convolutional Neural Network (CNN) Introduction

Feed-forward Neural Networks are suitable for simple tasks like basic time series prediction without long-term relationships. However, FNNs is not a one-size-fits-all solution. For instance, digital image training process uses pixel values of image as input data. Consider training a model to recognize a high resolution (600 dpi), 3.937 x 3.937 inches digital RGB (red, green, blue) image. The number of input parameters can be calculated as follows:

Width: 3.937 in x 600 ≈ 2362 pixels
Height: 3.937 in x 600 ≈ 2362 pixels
Pixels in image: 2362 x 2362 = 5,579,044 pixels
RGB (3 channels): 5,579,044 pxls x 3 channels = 16 737 132
Total input parameters: 16 737 132
Memory consumption: ≈ 16 MB

FNNs are not ideal for digital image training. If we use FNN for training in our example, we fed 16,737,132 input parameters to the first hidden layer, each having unique weight. For image training, there might be thousands of images, handling millions of parameters demands significant computation cycles and is a memory-intensive process. Besides, FNNs treat each pixel as an independent unit. Therefore, FNN algorithm does not understand dependencies between pixels and cannot recognize the same image if it shifts within the frame. Besides, FNN does not detect edges and other crucial details. 

A better model for training digital images is Convolutional Neural Networks (CNNs). Unlike in FFN neural networks where each neuron has a unique set of weights, CNNs use the same set of weights (Kernel/Filter) across different regions of the image, which reduces the number of parameters. Besides, CNN algorithm understands the pixel dependencies and can recognize patterns and objects regardless of their position in the image. 

The input data processing in CNNs is hierarchical. The first layer, convolutional layers, focuses on low-level features such as textures and edges. The second layer, pooling layer, captures higher-level features like shapes and objects. These two layers significantly reduce the input data parameters before they are fed into the neurons in the first hidden layer, the fully connected layer, where each neuron has unique weights (like FNNs).



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