BackupLABS provides an automated way for organizations of all sizes to protect your critical data that is held within popular cloud based applications. The vast majority of these cloud based apps, make it very easy to onboard and import data to start using the app. Such as GitHub, GitLab, Trello, Jira, Asana and Notion.
However, none of them offer a robust backup solution so you can protect your most important asset - your data. Organizations are putting more and more critical data on these platforms and the providers T&Cs always state that the customer needs to backup and protect their own data. This is also known as the "Shared Responsibility Model".
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We backup SaaS apps that the main backup providers do not offer. Such as Trello, GitHub, GitLab, Asana, Jira and Notion.
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BackupLABS is easy to use and can be setup within 5 minutes.
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SME market as well as public sector.
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Amazon Web Services.
BackupLABS's answer
BackupLABS was created after the founder, Rob Stevenson became frustrated with the lack of backup solutions available for SaaS apps. He also runs a traditional backup service with a sister company called BackupVault.
Back in 2017 when Microsoft 365 was created, there was no backup available. He missed the opportunity to create a 365 backup system and saw the same issues occuring now with the explosion of other SaaS based services.
These services all contain critical data, and the app providers themselves all state the data is the customers responsibility.
BackupLABS was founded with two apps supported at first: GitHub and Trello. But many more have been added including: GitLab, Jira and Notion.
Based on our record, Python seems to be more popular. It has been mentiond 282 times since March 2021. 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.
Import aiohttp Import asyncio Async def fetch(session, url): async with session.get(url) as response: return await response.text() Async def main(): async with aiohttp.ClientSession() as session: html = await fetch(session, 'https://python.org') print(html) Asyncio.run(main()). - Source: dev.to / 18 days ago
Flat packages are the most common used packages, but distribution packages are more robust and can contain multiple flat packages. That's enough detail for this article but if you want to know more Armin Briegel of ScriptingOSX has a great book covering a lot of the details of these package types. I highly recommend picking up a copy for reference. One of the benefits of Distribution packages is that you can... - Source: dev.to / about 2 months ago
F-strings, introduced in Python 3.6 and later versions, provide a concise and readable way to embed expressions inside string literals. They are created by prefixing a string with the letter ‘f’ or ‘F’. Unlike traditional formatting methods like %-formatting or str.format(), F-strings offer a more straightforward and Pythonic syntax. - Source: dev.to / 5 months ago
Import aiohttp, asyncio Async def fetch_data(i, url): print('Starting', i, url) async with aiohttp.ClientSession() as session: async with session.get(url): print('Finished', i, url) Async def main(): urls = ["https://dev.to", "https://medium.com", "https://python.org"] async_tasks = [fetch_data(i+1, url) for i, url in enumerate(urls)] await... - Source: dev.to / 6 months ago
Threading involves the execution of multiple threads (smaller units of a process) concurrently, enabling better resource utilization and improved responsiveness. Python‘s threading module facilitates the creation, synchronization, and communication between threads, offering a robust foundation for building concurrent applications. - Source: dev.to / 6 months ago
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