Any performance comparisons across compute engines in use in a datacenter are always valid for a point in time since new CPUs, GPUs, FPGAs, and other ASICs are always coming into the market at different times. …
Intel Pits Its “Sapphire Rapids” Xeon SP Against AMD “Genoa” Epycs was written by Timothy Prickett Morgan at The Next Platform.
Uncollected outbursts and Mind Farts on Vision Pro
Starting today, Cloudflare’s API Gateway can protect GraphQL APIs against malicious requests that may cause a denial of service to the origin. In particular, API Gateway will now protect against two of the most common GraphQL abuse vectors: deeply nested queries and queries that request more information than they should.
Typical RESTful HTTP APIs contain tens or hundreds of endpoints. GraphQL APIs differ by typically only providing a single endpoint for clients to communicate with and offering highly flexible queries that can return variable amounts of data. While GraphQL’s power and usefulness rests on the flexibility to query an API about only the specific data you need, that same flexibility adds an increased risk of abuse. Abusive requests to a single GraphQL API can place disproportional load on the origin, abuse the N+1 problem, or exploit a recursive relationship between data dimensions. In order to add GraphQL security features to API Gateway, we needed to obtain visibility inside the requests so that we could apply different security settings based on request parameters. To achieve that visibility, we built our own GraphQL query parser. Read on to learn about how we built the parser and the security features it enabled.
Take a Network Break: Drew is on holiday (again) and Ethan shows up. Who knew he was still around ? We start with FU, Cisco Live was underwhelming announcing a new focus simplicity and that customers hate their licensing, Bluecat spends again, Hashicorp gets a financial slapping, Itential ships a new version and Quantum Space Networking.
The post Network Break 434: Cisco Licensing To Get Simpler, Bluecat Buys Again, Hashicorp Money Problems, and Itential Pops A Release appeared first on Packet Pushers.
Stefano Sasso added two new Junos platforms in netlab release 1.5.4:
There are also the usual bug fixes, and we moved the documentation to netlab.tools.
Stefano Sasso added two new Junos platforms in netlab release 1.5.4:
There are also the usual bug fixes, and we moved the documentation to netlab.tools.
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| CanaKit Raspberry Pi 4 EXTREME Kit - Aluminum |
Next, follow instruction for installing Docker Engine (Raspberry Pi OS Lite is based on Debian 11).
Note: One of the important tips for lab environments is to set an auto-shutdown timer, below is one such setting in GCP
I have been working on a few hosted environments which include AWS Sagemaker Notebook instances, Google Cloud Colab, Gradient (Paperspace) etc and all of them are really good and needed monthly subscriptions, I decided to have my own GPU server instance which can be personalized and I get charged on a granular basis.
Installing it is not easy, first, you need to find a cloud-computing instance which has GPU support enabled, AWS and GCP are straightforward in this section as the selection is really easy.
Let’s break this into 3 stages
For a change, I will be using GCP in this case from my usual choice of AWS here.
Choose GPU alongside the Instance
Generic Guidelines — https://cloud.google.com/deep-learning-vm/docs/cloud-marketplace
rakesh@instance-1:~$ sudo apt install jupyter-notebook # Step1: generate the file by typing this line in console jupyter notebook Continue reading
Large language models (LLM) – ChatGPT and friends – are one of those technologies with a crazy learning curve. They look simple and friendly (resulting in plenty of useless demoware) but become devilishly hard to work with once you try to squeeze consistent value out of them.
Most people don’t want to talk about the hard stuff (sexy demoware results in more page views), but there’s an occasional exception, for example All the Hard Stuff Nobody Talks About when Building Products with LLMs describing all the gotchas Honeycomb engineers discovered when creating a LLM-based user interface.
Large language models (LLM) – ChatGPT and friends – are one of those technologies with a crazy learning curve. They look simple and friendly (resulting in plenty of useless demoware) but become devilishly hard to work with once you try to squeeze consistent value out of them.
Most people don’t want to talk about the hard stuff (sexy demoware results in more page views), but there’s an occasional exception, for example All the Hard Stuff Nobody Talks About when Building Products with LLMs describing all the gotchas Honeycomb engineers discovered when creating a LLM-based user interface.
Security researches found another ICMP redirect SNAFU: a malicious wireless client can send redirects on behalf of the access point redirecting another client’s traffic to itself.
I’m pretty sure the same trick works on any layer-2 technology; the sad part of this particular story is that the spoofed ICMP packet traverses the access point, which could figure out what’s going on and drop the packet. Unfortunately, most of the access points the researchers tested were unable to do that due to limitations in the NPUs (a fancier word for SmartNIC) they were using.
Security researches found another ICMP redirect SNAFU: a malicious wireless client can send redirects on behalf of the access point redirecting another client’s traffic to itself.
I’m pretty sure the same trick works on any layer-2 technology; the sad part of this particular story is that the spoofed ICMP packet traverses the access point, which could figure out what’s going on and drop the packet. Unfortunately, most of the access points the researchers tested were unable to do that due to limitations in the NPUs (a fancier word for SmartNIC) they were using.
The following sponsored blog post was written by Anupam Upadhyaya at Palo Alto Networks. We thank Palo Alto Networks for being a sponsor. Palo Alto Networks is the leading vendor in preventing Cobalt Strike C2 communication and blocked 99.2% of tested attacks, with the next leading vendor blocking only 17% of attacks, as cited in a […]
The post Prisma Access Outperforms Against Cobalt Strike Attacks appeared first on Packet Pushers.
We think that server spending is a leading indicator of economic growth or decline, and we are tracking the public companies that peddle systems to try to get a sense of how they are doing to get a better sense of what enterprises, governments, academic institutions, and other organizations separate from the hyperscalers and cloud builders, the latter of which comprise around half of server shipments and slightly less than half of server spending. …
No Server Recession At Lenovo And Supermicro So Far was written by Timothy Prickett Morgan at The Next Platform.
