In "Redefining Roles in Application Security," Darren House, CTO of NXT1, explores the need for a shift in responsibility away from end users in securing commercial technologies. He emphasizes the importance of adopting a long-term perspective, integrating GenAI into the development process, and fostering a culture of shared responsibility among educators, industries, and users. Dive into the full article to discover how we can build a safer future together.

https://nxt1.cloud/cybersecurity/redefining-roles-in-application-security/?utm_medium=blog&utm_source=communities&utm_term=Reddit

First load test today for the Moirai Programming Language.

The test was performed using the free tier of Oracle Cloud Infrastructure, a single VM.Standard.E2.1.Micro host with the Spring Boot service deployed, and the K6 load testing framework.

Four scripts were tested,

1. A single loop with 25 units of cost supporting 800 TPS
2. Two nested loops with 153 units of cost supporting 800 TPS
3. Three nested loops with 1,177 units of cost supporting 500 TPS
4. Four nested loops at the very limit of 9,369 units of cost (the service allows up to 10,000 units) supporting 146 TPS.

Because the single host is free, I do not have a cost estimate for an 800 TPS service. However, (conservatively) using the cost of an E5 server at $34 a month, 800 TPS would allow for 1.6 cents per 1 million requests. Note that AWS Lambda costs 20 cents per 1 million requests in addition to the price of CPU and memory fees, which might be much higher. Using the example on the AWS Lambda website, with 1 million requests costing $2.73, the Moirai service would be 170 times cheaper using pessimistic measures.

I am concerned about the low TPS of the most expensive case. This indicates to me that nested loops need to explode in cost at a faster rate than they do in the interpreter. This is just one of many areas in the language that need to be refined. The cost of a unit of computation in Moirai code needs to better reflect actual CPU and memory usage.

I’m working on serverless computing I should do a thesis propsal after tomorrow about the problem that I should work on 😄, frankly I’m welling to work on performance enhancement but, but using which approach or approaching which issue in serveless I’m not sure, can somebody help 🫶

Quantum computers may not be here yet, but we still need to prepare for them.

Read more…

Hello everyone,

I recently faced challenges while automating AWS Lambda function updates directly from GitHub pushes. The main hurdles included managing secrets and dealing with timeouts during updates. After some effort, I've successfully streamlined the process.

For those interested, I've created a detailed guide and included a YAML configuration in a GitHub gist. This might help if you're encountering similar issues. Here's the link to the gist:

https://gist.github.com/DominiquePaul/15be5f5da95b2c30684ecdfd4a151f27

I'm open to feedback and suggestions for further improvement. Feel free to share your thoughts or ask questions if you need more details.

Asher Sterkin, a technical researcher explores the concept of middleware within the context of the new programming language, Winglang.

Sterkin discusses the evolution and importance of middleware in modern software development, particularly how it integrates with cloud platforms.

The article marks the beginning of a series aimed at addressing the complexities of developing middleware solutions in Winglang, highlighting ongoing research and development in this area.

You can check out the article here.

Suppose you want to call the OpenAI API, and you expect a very big response. How would you approach that, trying to optimize execution costs?

I recently made an example service that demonstrates the Moirai Programming Language. It is a scripting language (not an infra generator, not a JSON generator) which is designed for multi-tenant microservices and serverless applications.

In the original example, raw Moirai code could be sent over a network and executed directly. This is generally safe to do because the language was designed exactly for that use case. The Worst-Case Execution Time (WCET) is calculated by the interpreter before executing any script.

Early adopters might not like executing arbitrary code sent over a network, so I added a new example endpoint to the service that allows JSON requests to be sent over the network instead. Given the name of a function and the name of a library script, a Moirai type is used to walk the JSON parse tree and generate Moirai code.

As an example, given the following Moirai script stored/deployed on the server:

script my.library

record R(val x: Int, val l: List<Int, 5>)

def f(r: R): Int {
    mutable res = 0
    for(r.l) {
        res = res + (r.x * it)
    }
    res
}

With the new endpoint, jsonExecuteScript, scriptName = my.library and functionName = f with a JSON request that looks like this:

{ "x": 5, "l": [3, 4, 5] }

The following Moirai code gets generated and then invoked:

transient script my.library
            
f(R(5, List(3, 4, 5)))

The result of this computation is 60.

Note that no changes were made to the Moirai interpreter itself. As far as Moirai is concerned, JSON does not exist. The webservice simply maps one format to another before invoking the interpreter. Data conversions can be as sophisticated as desired in this process.

As an experienced developer working to monetize my desktop app, I was initially drawn to Azure's serverless functions. The free tier and scalability promises seemed perfect for handling payment processing and license verification without major infrastructure costs. The initial setup integrating PayPal, load balancing with NGINX, and using Cosmos DB as a NoSQL database went smoothly.

However, I soon ran into performance issues as users reported sluggish startup times. Upon looking into it, I discovered the "cold start" problem with serverless functions, where they can take up to 30 seconds to start on the free tier. For a desktop app demanding fast responsiveness, this delay was unacceptable.

I tried potential fixes like using Azure Logic Apps to keep the functions running, but the delays continued. Ultimately, I made the difficult choice to move the backend API and NGINX components to a dedicated Azure Linux instance to eliminate cold starts entirely.

While this move required some code changes, it allowed me to keep most of my existing work, including the Cosmos DB integration. The experience taught me an important lesson - thoroughly evaluating tech solutions for specific needs before fully committing. Even cutting-edge offerings may have limitations for certain use cases. While providers have since improved cold start performance, a proof-of-concept is still advisable before production deployment.

https://danielhofman.com/how-serverless-almost-killed-my-app

Hey!

Agenda: Interview + live coding!

• AWS Serverless Hero: Filip Pyrek interview
• Ex-AWS and the mind behind the CDK: Elad Ben-Israel will be coding live on a step function integration with Wing.

Join live on YouTube or Twitch at 2 PM EST.

Question (Need Help):
Hi all,
We are using serverless framework for our application. For local testing , we use serverless offline command to start the local server. Is there any way to attach a python debugger to lambdas? Ability to visualise variables and add breakpoints is a key for us. Please let me know if there is any way.

Thanks!

Hey AWS lambda experts

I am a Lambda Python newbie and I am struggling with structuring my application to run correctly on AWS Lambda. So, I am reaching out to the experts as my last resort.

Issue summary

I am attempting to run my code, which imports the pyathena package, but it still is failing to run due to the following error:

[ERROR] Runtime.ImportModuleError: Unable to import module 'app': No module named 'pyathena'

Current application's structure.

app.py
organization_name_folder
├── configs
│   └── mysql_db_configs.py
├── db
│   └── query_executor.py
├── enums
│   └── mysql_config_prop.py
├── libs
│   └── pymysql

How the code is packaged.

The code is packaged into a zip file.

zip -r function_name.zip __init__.py \
app.py \
dotfiles \
libs \
organization_name_folder

Handler’s configuration

Here is how the function’s handler is configured: app.handler_name

3rd-party installation

Here is how I installed my 3rd party packages: pip3 install -r requirements.txt --target ./libs, which installs the packages into a libs folder.

Imports

import pyathena
from organization_name.folder_path_to_python_file.python_file import ClassName

What I have attempted so far:

1. I have attempted to change the directory structure
2. Update the imports

without any luck

My questions are:

1. How should I import my dependencies into my app.py file?
2. I included 3rd party libraries in libs folder, but still AWS is not correctly importing them.
3. If my handler is located in app.py, what handler value be?

The guide explores how CodiumAI AI coding assistant simplifies automated testing for AWS Serverless, offering improved code quality, increased test coverage, and time savings through automated test case generation for a comprehensive set of test cases, covering various scenarios and edge cases, enhancing overall test coverage.

Salut, communauté

Je m'aventure dans le développement d'applications fullstack et serverless, et j'ai décidé d'utiliser Firebase pour mon projet. C'est un outil incroyable avec tant de potentiel, mais je sais qu'il y a beaucoup à apprendre pour vraiment en tirer le meilleur parti.

J'ai récemment découvert une formation gratuite qui semble offrir une excellente introduction à la création d'applications fullstack et serverless avec Firebase. Elle couvre tout, de la configuration initiale à la sécurisation et l'optimisation de l'application. Je pense que cela pourrait être une excellente ressource pour quiconque cherche à se lancer ou à approfondir ses connaissances dans ce domaine.

Voici ce que j'aimerais savoir de vous :

​

• Vos expériences : Avez-vous déjà développé des applications avec Firebase ? Quels défis avez-vous rencontrés et comment les avez-vous surmontés ?
• Conseils pour les débutants : Quels sont les pièges à éviter ? Avez-vous des astuces spécifiques pour travailler avec Firebase dans un contexte fullstack et serverless ?
• Ressources supplémentaires : Connaissez-vous d'autres formations, tutoriels ou outils qui pourraient aider ceux qui débutent avec Firebase ?

Si vous êtes intéressés par la formation que j'ai trouvée et souhaitez en savoir plus, je serais ravi de partager le lien ou plus de détails dans les comentaires. N'hésitez pas à me contacter !

J'espère que nous pourrons apprendre les uns des autres et partager nos réussites (et nos échecs) pour mieux naviguer dans le monde fascinant du développement serverless avec Firebase.

The guide explores how CodiumAI AI coding assistant simplifies automated testing for AWS Serverless, offering improved code quality, increased test coverage, and time savings through automated test case generation for a comprehensive set of test cases, covering various scenarios and edge cases, enhancing overall test coverage.

🚀 Excited to share the first installment of our series on real-time serverless chat applications!
In this blog, I dive into the essentials of setting up the Serverless Framework and integrating it seamlessly with Amazon Web Services (AWS). Whether you're a seasoned developer or just starting out, this guide is tailored to provide clear, step-by-step instructions to get you up and running with serverless technologies.

🔗 Check out the full post here : Setting Up Serverless Framework with AWS