Roy is the creative lead behind and owner of Make Mistakes
In this episode, we cover the following topics: A common feature for web apps is image upload. And we all know the "best practices" for how to build this feature. But getting it right can be tricky. We start off by discussing the problem space, and what we want to solve. A key goal is to have a solution that is massively scalable while being cost-effective. We outline the general architecture of the solution, with separate techniques for handling image uploading and downloading. We then dive deep into how to handle image uploading, highlighting various techniques for controlling access over who can perform uploads. Two common techniques for securing uploads when using AWS are presigned URLs and presigned POSTs. We discuss how each works and when to use one over the other. We finish up by putting everything together and detailing the steps involved with uploading an image. Detailed Show NotesWant the complete episode outline with detailed notes? Sign up here: https://mobycast.fm/show-notes/Support Mobycasthttps://glow.fm/mobycastEnd SongLazy Sunday by Roy EnglandMore InfoFor a full transcription of this episode, please visit the episode webpage.We'd love to hear from you! You can reach us at: Web: https://mobycast.fm Voicemail: 844-818-0993 Email: ask@mobycast.fm Twitter: https://twitter.com/hashtag/mobycast Reddit: https://reddit.com/r/mobycast
In this episode, we cover the following topics: A common feature for web apps is image upload. And we all know the "best practices" for how to build this feature. But getting it right can be tricky. We start off by discussing the problem space, and what we want to solve. A key goal is to have a solution that is massively scalable while being cost-effective. We outline the general architecture of the solution, with separate techniques for handling image uploading and downloading. We then dive deep into how to handle image uploading, highlighting various techniques for controlling access over who can perform uploads. Two common techniques for securing uploads when using AWS are presigned URLs and presigned POSTs. We discuss how each works and when to use one over the other. We finish up by putting everything together and detailing the steps involved with uploading an image. Detailed Show NotesWant the complete episode outline with detailed notes? Sign up here: https://mobycast.fm/show-notes/Support Mobycasthttps://glow.fm/mobycastEnd SongLazy Sunday by Roy EnglandMore InfoFor a full transcription of this episode, please visit the episode webpage.We'd love to hear from you! You can reach us at: Web: https://mobycast.fm Voicemail: 844-818-0993 Email: ask@mobycast.fm Twitter: https://twitter.com/hashtag/mobycast Reddit: https://reddit.com/r/mobycast
Show DetailsJon Christensen and Chris Hickman of Kelsus and Rich Staats of Secret Stache conclude their series on the birth of NoSQL and DynamoDB. They compare the NoSQL database, Leviathan, created by Chris’s startup in the late 1990s to today’s DynamoDB. A lot of things haven’t changed, even though technology has evolved. It’s cyclical. There are patterns and problems that continue to dominate.  Some of the highlights of the show include: Reason for Creation of NoSQL Database: How to scale database with Internet-scale applications to have a virtual pool of infinite storage that can be scaled out Main Architecture Components of Leviathan: API client Update distributor (UD) Base server (storage node) Shepherd (housekeeping management system)   Additional core components included smart IP and storage abstraction layer (SAL) Leviathan mostly used C code and minimal Java code to support users Big difference between DynamoDB and Leviathan is request router and partition metadata system living on the server vs. living on the edge Leviathan was a closed system with an instance for every network or data center; not designed to run as a software as a service, like DynamoDB Leviathan was strongly consistent, unlike DynamoDB’s eventually consistent model Definition and Different Types of Transactions Shepherd was used to identify and address consistency, synchronous, and timing issues  Rather than using a file system, Leviathan used relational databases  Links and ResourcesDynamoDBMicrosoft SQLOracle DBAWS IoT GreengrassKelsusSecret Stache Media Quotes:“We had the same kind of problems that DynamoDB had - how do you scale your database dealing with Internet-scale applications and have this virtual pool of infinite storage that can be scaled out.” Chris Hickman “This system and this technology went through many iterations.” Chris Hickman “You can’t have a 100% consistent state across everything. It’s just impossible. How do you do the right thing?” Chris Hickman “The big difference between DynamoDB and Leviathan...is the request router and partition metadata system living on the server vs. living out at the edge.” Jon Christen
Show DetailsJon Christensen and Chris Hickman of Kelsus and Rich Staats of Secret Stache conclude their series on the birth of NoSQL and DynamoDB. They compare the NoSQL database, Leviathan, created by Chris’s startup in the late 1990s to today’s DynamoDB. A lot of things haven’t changed, even though technology has evolved. It’s cyclical. There are patterns and problems that continue to dominate.  Some of the highlights of the show include: Reason for Creation of NoSQL Database: How to scale database with Internet-scale applications to have a virtual pool of infinite storage that can be scaled out Main Architecture Components of Leviathan: API client Update distributor (UD) Base server (storage node) Shepherd (housekeeping management system)   Additional core components included smart IP and storage abstraction layer (SAL) Leviathan mostly used C code and minimal Java code to support users Big difference between DynamoDB and Leviathan is request router and partition metadata system living on the server vs. living on the edge Leviathan was a closed system with an instance for every network or data center; not designed to run as a software as a service, like DynamoDB Leviathan was strongly consistent, unlike DynamoDB’s eventually consistent model Definition and Different Types of Transactions Shepherd was used to identify and address consistency, synchronous, and timing issues  Rather than using a file system, Leviathan used relational databases  Links and ResourcesDynamoDBMicrosoft SQLOracle DBAWS IoT GreengrassKelsusSecret Stache Media Quotes:“We had the same kind of problems that DynamoDB had - how do you scale your database dealing with Internet-scale applications and have this virtual pool of infinite storage that can be scaled out.” Chris Hickman “This system and this technology went through many iterations.” Chris Hickman “You can’t have a 100% consistent state across everything. It’s just impossible. How do you do the right thing?” Chris Hickman “The big difference between DynamoDB and Leviathan...is the request router and partition metadata system living on the server vs. living out at the edge.” Jon Christen 
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Creator Details

Episode Count
73
Podcast Count
1
Total Airtime
2 days, 12 hours
PCID
Podchaser Creator ID logo 459575