architect
aws-lambda-power-tuning
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architect | aws-lambda-power-tuning | |
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13 | 36 | |
2,492 | 5,134 | |
0.6% | - | |
8.7 | 8.7 | |
5 days ago | 10 days ago | |
JavaScript | JavaScript | |
Apache License 2.0 | Apache License 2.0 |
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Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
architect
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Cloudflare Sippy: Incrementally Migrate Data from AWS S3 to Reduce Egress Fees
I had been running dockeri.co with https://arc.codes/ for pennies a month.
Then, one month, I got a ~$500 bill out of no where.
Docker had changed an api causing my service to return 5xx errors all month. Each error was individually logged to CloudWatch - which racked up a ~$500 bill.
I moved to Cloudflare Workers that day and haven’t moved back.
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Show HN: Formula8.ai – A formula-based approach to AI prompts
We use https://github.com/architect/architect to test, provision and deploy the functional web app via GitHub Actions (…whenever they work ;). For the UI/UX we work with https://tailwindui.com and paid them for their great work.
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Tools like Architect (arc.codes) for AWS serverless apps?
I use https://arc.codes/ for deploying to AWS Lambda/API Gateway. It does a really good job with Remix and NestJS and is easy enough. I like that all I have to do is give a very simple config, and it builds the apps, zips the function code, uploads all my static assets, and then generates and deploys the CloudFormation. I am curious to migrate off as I do have to do some workarounds and it doesn't seem to have a ton of traction.
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Node.js 20 is now available
Not sure why this is downvoted, Fastify is quite popular and the 'generator for everything' approach of Koa didn't really take off.
Architect serverless (https://arc.codes) is pretty good for serverless.
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⚡️Serverless Frameworks for 2023
Architect is a heavily opinionated framework for building FWA's, Functional Web Apps. It uses AWS SAM under the hood but provides a layer on top with simplified abstractions that lets developers define and use AWS infrastructure without necessarily knowing what service is backing their "events" construct.
- What’s your favorite backend framework and why?
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Managed Server for NodeJS?
I work for vercel but I highly recommend a host like us because we make it a lot easier to manage a lambda environment and being a lot more to the table (cdn, edge functions, etc). If you want to go your own I really like architect https://arc.codes too. It really depends on your traffic and application patterns but cold starts can be virtually nil.
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I made a "game" to find words that are not repos on NPM, yet. It's harder than you think and surprisingly addictive.
It uses: - Remix for the frontend - Architect for the backend
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How to Use Source Maps in TypeScript Lambda Functions (with Benchmarks)
Alternately, use Architect. Architect is a 3rd party developer experience that builds on top of AWS SAM. Architect includes a TypeScript plugin.
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Tools for testing Functional Web Apps
For us at Begin and Architect, tape has been in use for several years. tape has a stable and straightforward API, routine maintenance updates, and outputs TAP, making it really versatile. While TAP is legible, it's not the most human-readable format. Fortunately, several TAP reporters can help display results for developers. Until recently, Begin's TAP reporter of choice was tap-spec. Sadly tap-spec wasn't kept up to date and npm began reporting vulnerabilities.
aws-lambda-power-tuning
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Optimizing Costs in the Cloud: Embracing a FinOps Mindset
Sometimes, changing services, like opting for HTTP over REST API Gateway, leveraging tools like Lambda Powertuning to optimize functions, or reducing a CloudWatch log retention and changing log level, can lead to significant savings.
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AWS SnapStart - Part 13 Measuring warm starts with Java 21 using different Lambda memory settings
In case of not enabling SnapStart for the Lambda function we observed that increasing memory reduces the warm execution time for our use case especially for p>90. As adding more memory to the Lambda function is also a cost factor, the sweet spot between cold and warm start time and cost is somewhere between 768 and 1204 MB memory setting for the Lambda function for our use case. You can use AWS Lambda Power Tuning for very nice visualisations.
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How to enhance your Lambda function performance with memory configuration?
The aws lambda power tuning tool helps optimise the Lambda performance and cost in a data-driven manner. Let's try it out:
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Controlling Cloud Costs: Strategies for keeping on top of your AWS cloud spend
For Lambda, a very useful tool to help optimise is the AWS Lambda Power Tuning tool, released by Alex Casalboni, Developer Advocate at AWS: https://github.com/alexcasalboni/aws-lambda-power-tuning
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Best way to decrease latency (API <-> Lambda <-> Dynamodb)
Lambda memory affects not only the CPU performance and and host execution priority, but also network performance. Be wary though as the price scales linearly. You can use a tool like Lambda Power Tuning to find the sweet spot for your application. https://github.com/alexcasalboni/aws-lambda-power-tuning
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How to optimize your lambda functions with AWS Lambda power tuning
This tool, which is open source and available here, takes the form of a Step Function that is deployed on your AWS account. The purpose of this Step Function is to run your lambda with different memory configurations several times and output a comparison in the form of a graph (or JSON) to try to find the optimal balance between cost and execution time. There are three possible optimization modes: cost, execution time, or a "balanced" mode where it tries to find a balance between the two.
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Developers Journey to AWS Lambda
The AWS Documentation's Memory and Computing Power page is a good starting point. To avoid configuring it manually, it's worth checking out AWS Lambda Power Tuning, which will help you find the sweet spot.
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Guide to Serverless & Lambda Testing — Part 2 — Testing Pyramid
Utilizing tools such as AWS X-Ray, AWS Lambda Power Tuning, and AWS Lambda Powertools tracer utility is recommended. Read more about it here.
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Tunea tus funciones Lambda
Install the AWS SAM CLI in your local environment. Configure your AWS credentials (requires AWS CLI installed): $ aws configure Clone this git repository: $ git clone https://github.com/alexcasalboni/aws-lambda-power-tuning.git Build the Lambda layer and any other dependencies (Docker is required): $ cd ./aws-lambda-power-tuning $ sam build -u sam build -u will run SAM build using a Docker container image that provides an environment similar to that which your function would run in. SAM build in-turn looks at your AWS SAM template file for information about Lambda functions and layers in this project. Once the build has completed you should see output that states Build Succeeded. If not there will be error messages providing guidance on what went wrong. Deploy the application using the SAM deploy "guided" mode: $ sam deploy -g
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AWS Serverless Production Readiness Checklist
Use AWS Lambda Power Tuning to balance cost and performance.
What are some alternatives?
htmx - </> htmx - high power tools for HTML
json-schema-to-ts - Infer TS types from JSON schemas 📝
ARC-Game - The Abstraction and Reasoning Corpus made into a web game
dynamodb-toolbox - A simple set of tools for working with Amazon DynamoDB and the DocumentClient
node-source-map-support - Adds source map support to node.js (for stack traces)
middy - 🛵 The stylish Node.js middleware engine for AWS Lambda 🛵
aws-sam-cli - CLI tool to build, test, debug, and deploy Serverless applications using AWS SAM
deno-mixed-runtimes - Begin app
aws-graviton-getting-started - Helping developers to use AWS Graviton2 and Graviton3 processors which power the 6th and 7th generation of Amazon EC2 instances (C6g[d], M6g[d], R6g[d], T4g, X2gd, C6gn, I4g, Im4gn, Is4gen, G5g, C7g[d][n], M7g[d], R7g[d]).
aws-lambda-builders - Python library to compile, build & package AWS Lambda functions for several runtimes & framework
failure-lambda - Module for fault injection into AWS Lambda