Building a Fargate-based container app with Cognito Authentication

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In this post I’m going to show you how to use Cognito User Authentication in combination with a Docker app running in Fargate behind an Application Load Balancer and we’re going to build all this with the Cloud Development Kit (CDK).

Why would you want to use this? You’re running your web application inside a docker container and don’t want to deal with user authentication.

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In this post I’m going to show you how to use Cognito User Authentication in combination with a Docker app running in Fargate behind an Application Load Balancer and we’re going to build all this with the Cloud Development Kit (CDK).

Why would you want to use this? You’re running your web application inside a docker container and don’t want to deal with user authentication.

Read more →

Machine to Machine Authentication with Cognito and Serverless

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Introduction Authentication is a problem almost every IT professional has had to deal with at some point in time. Doing it right isn’t easy. What I mean by right is balancing usability and security. AWS attempts to solve this problem with AWS Cognito, which is quite nice of them, because Authentication is exactly the undifferentiated heavy lifting most customers don’t want to deal with themselves. Unfortunately authentication is still a complex topic and Cognito is an abstraction layer for it, which makes it easier, but it’s a fairly low level abstraction conceptually in that you still need to understand most of the concepts involved in order configure it correctly.
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Introduction Authentication is a problem almost every IT professional has had to deal with at some point in time. Doing it right isn’t easy. What I mean by right is balancing usability and security. AWS attempts to solve this problem with AWS Cognito, which is quite nice of them, because Authentication is exactly the undifferentiated heavy lifting most customers don’t want to deal with themselves. Unfortunately authentication is still a complex topic and Cognito is an abstraction layer for it, which makes it easier, but it’s a fairly low level abstraction conceptually in that you still need to understand most of the concepts involved in order configure it correctly.
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Automating Athena Queries with Python

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Automating Athena Queries with Python Introduction Over the last few weeks I’ve been using Amazon Athena quite heavily. For those of you who haven’t encountered it, Athena basically lets you query data stored in various formats on S3 using SQL (under the hood it’s a managed Presto/Hive Cluster). Pricing for Athena is pretty nice as well, you pay only for the amount of data you process and that’s relatively cheap at $5 per TB when you consider the effort to set up EMR Clusters for one-time or very infrequent queries and transformations.
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Automating Athena Queries with Python Introduction Over the last few weeks I’ve been using Amazon Athena quite heavily. For those of you who haven’t encountered it, Athena basically lets you query data stored in various formats on S3 using SQL (under the hood it’s a managed Presto/Hive Cluster). Pricing for Athena is pretty nice as well, you pay only for the amount of data you process and that’s relatively cheap at $5 per TB when you consider the effort to set up EMR Clusters for one-time or very infrequent queries and transformations.
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Wer ist der Schnellste? Überblick über AWS Ressourcen mit Polyglot Programming.

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tl;dr - asynchrone Programmierung ist sehr viel schneller als sequentielle Aufrufe. Insofern stimmt das Pferdebild gar nicht, aber ein einzelnes Pferd sieht halt nicht so spannend aus… Außerdem bin ich selber über die Unterschiede in der Ausführungszeit überrascht… Eine Analyse am Anwendungsfall “wie bekomme ich den Überblick über AWS Resourcen über alle Regionen mit minimaler Ausführungszeit. Am Rennen nehmen teil: node, python und go. Und - um die Aufschreie der jeweiligen Fans vorwegzunehmen - es geht mehr um das Paradigma asynchron als um die Sprache. Ganz nebenbei seht ihr die AWS SDKs im Vergleich! Aber lest selbst  

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tl;dr - asynchrone Programmierung ist sehr viel schneller als sequentielle Aufrufe. Insofern stimmt das Pferdebild gar nicht, aber ein einzelnes Pferd sieht halt nicht so spannend aus… Außerdem bin ich selber über die Unterschiede in der Ausführungszeit überrascht… Eine Analyse am Anwendungsfall “wie bekomme ich den Überblick über AWS Resourcen über alle Regionen mit minimaler Ausführungszeit. Am Rennen nehmen teil: node, python und go. Und - um die Aufschreie der jeweiligen Fans vorwegzunehmen - es geht mehr um das Paradigma asynchron als um die Sprache. Ganz nebenbei seht ihr die AWS SDKs im Vergleich! Aber lest selbst  

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