GitDuck
Floobits
CodeTogether
GitLive
Visual Studio Live Share
Tuple
CodeStream
CodeAlly
Amazon S3
AWS Lambda
Google Cloud Storage
Amazon CloudFront
Amazon EC2
Amazon AWS
DynamoDB
Google App Engine
Amazon S3 (Amazon Simple Storage Service) is the storage platform by Amazon Web Services (AWS) that provides an object storage with high availability, low latency and high durability. S3 can store any type of object and can serve as storage for internet applications, backups, disaster recovery, data archives, big data sets and multimedia.
GitDuck Amazon S3Based on our record, Amazon S3 seems to be a lot more popular than GitDuck. While we know about 214 links to Amazon S3, we've tracked only 2 mentions of GitDuck. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I think that there is something like this already, it have most the thing you have in your app, also I don't see paid plans https://gitduck.com/. Source: over 5 years ago
First you need to have a GitDuck account and be part of a team so you can talk there. If you don't have one, just go to gitduck.com and create an account. - Source: dev.to / over 5 years ago
TLS at the API boundary encrypts the payload in transit, but your application is responsible for what happens to the document after the response arrives. If you're writing the rendered PDF to disk, a message queue, or cloud storage, that persistence layer needs its own encryption at rest. An unencrypted file sitting in an Amazon S3 bucket with overly permissive ACLs falls outside what the API provider's TLS covers. - Source: dev.to / 3 months ago
SAM CLI generates the SAMCodeUriServices mapping so that each collection value resolves to its own build artifact. At package time, those paths become Amazon S3 URIs. I don't need to manage any of this. - Source: dev.to / 3 months ago
Fine-tuning adapts an FM to a specific use case with proprietary training data. Titan, Cohere, and Meta models support fine-tuning via Amazon Bedrock. Text models need labelled prompt-completion pairs; image models need Amazon Simple Storage Service (Amazon S3) paths linked to descriptions. Secure training data with Amazon Virtual Private Cloud (Amazon VPC) + AWS PrivateLink. - Source: dev.to / 4 months ago
You need to understand vector stores for semantic and hybrid search using Amazon OpenSearch Service and Amazon Simple Storage Service (Amazon S3). Prompt caching helps reduce costs by reusing previously processed prompts. Amazon Bedrock Prompt Management simplifies the creation, evaluation, versioning, and sharing of prompts to help you get the best responses from foundation models. Flow orchestration with Amazon... - Source: dev.to / 4 months ago
All fine-tuning used Amazon SageMaker Training Jobs โ no instance provisioning, no SSH, no manual teardown. You provide a training script and an S3 dataset path, specify the instance type, and SageMaker handles the rest. - Source: dev.to / 6 months ago
Floobits - Floobits brings real-time collaborative editing to text editors, IDEs, and now Atom.
AWS Lambda - Automatic, event-driven compute service
CodeTogether - Live share IDEs and coding sessions. See changes in real time.
Google Cloud Storage - Google Cloud Storage offers developers and IT organizations durable and highly available object storage.
GitLive - Extend Git with real-time collaborative superpowers
Amazon CloudFront - Amazon CloudFront is a content delivery web service.