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.
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https://github.com/so-fancy/diff-so-fancy- Source: Hacker News / 3 months ago[alias].
The diff itself is impressive, but in terms of styling I still prefer diff-so-fancy[1]. It's easier to read at a glance. [1]: https://github.com/so-fancy/diff-so-fancy/. - Source: Hacker News / about 1 year ago
This is actually one that's really easy to write and remember but I hate typing and I run it all the time, so I've aliased it down to gd for git-diff. Also I use diff-so-fancy to make the output of my diffs look frickin sweet and I suggest you do the same. - Source: dev.to / about 2 years ago
I recommend a tool like diff-so-fancy with some custom colors. You will never want to go back to vanilla diffs. Source: over 2 years ago
Ok, thanks, diff-so-fancy is a good solution for me. Source: over 2 years ago
Takeaway: S3 is feature-rich and great for complex workflows. Cloud Storage is simpler and faster for global access. Explore S3 documentation. - Source: dev.to / about 17 hours ago
To address this, the team introduced a conditional frontend build mechanism. Using git diff with the three-dot notation, it detects whether a PR includes frontend changes compared to the main branch. If no changes are detected, the frontend build step is skipped, reusing a prebuilt version stored in AWS S3 and served via an internal Content Delivery Network (CDN). - Source: dev.to / 23 days ago
In this article, we present an architecture that demonstrates how to collect application logs from Amazon Elastic Kubernetes Service (Amazon EKS) via Vector, store them in Amazon Simple Storage Service (Amazon S3) for long-term retention, and finally query these logs using AWS Glue and Amazon Athena. - Source: dev.to / 29 days ago
Iceberg has quietly become the foundation of the modern data lakehouse. More and more engineering teams are adopting it to store and manage analytical data in cloud storage — like Amazon S3, Google Cloud Storage, or Azure Data Lake Storage — while freeing themselves from the limitations of closed systems. - Source: dev.to / about 2 months ago
AWS Lambda is perfect for applications that process images due to its integration with AWS S3, an object storage service. A good example is an e-commerce application that renders images in different sizes. Here are the top features:. - Source: dev.to / about 2 months ago
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