Dissecting Serverless Stacks (I) This post establishes the base for a small series on how to create Serverless based Lambdas which can be deployed in environments without IAM privileges or where the sls command cannot be used at all.
Ruby Layers with Serverless After showing how easy it is to write AWS Lambda functions in Ruby, we will work on a way to build Layers with external dependencies or shared data in this post.
Ruby Lambdas with Serverless Support for Ruby was added on AWS Lambda end of November 2018, with support via the Serverless Framework landing on the same day.
Automating ACM Certificate creation with the Serverless Framework Encryption is the basis for secure communication in our modern world. For most web applications this boils down to using HTTPS to encrypt traffic between the client and server. HTTPS or the underlying protocols TLS/SSL rely on Public Key Infrastructure and Encryption to establish the Authenticity of the communication partner. Authenticity in this context means that the client can be sure he is communicating with Google if they access https://google.
Amazon Connect und die kleine Mailbox… Amazon Connect ist als veröffentlichter Service zwar noch relativ jung, aber definitiv nicht mehr in den Kinderschuhen. Das cloudbasierte Contact Center von Amazon etabliert sich zunehmend, was auch wir - nicht zuletzt über steigende Projektzahlen - feststellen können. Dabei besticht es unter anderem durch seine offene Plattform und hohe Integrierbarkeit. Was fehlt - ist eine Mailbox!
How to: CloudFormation Makro CloudFormation vermisst gegenüber Terraform einige Funktionen, die das Erstellen von Infrastruktur vereinfachen können. Das ist grundsätzlich korrekt, allerdings gibt es in CloudFormation die Möglichkeit, sich selber um den Einbau solcher Funktionen zu kümmern. Das geht mithilfe sogenannter CloudFormation Makros. CloudFormation Makros sind Funktionen, die wir per CloudFormation erstellen können und dann in weiteren CloudFormation Templates einbauen und verwenden können. Wir zeigen dies am Beispiel einer Count Funktion.
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.
The AWS CDK has been presented on reInvent 2018. Its mission is to simplify develop infrastructure as code. There are several other frameworks, as discussed here on the blog in tRick. So there are some competitors… Can you use shiny new CDK also for serverless lambda applications? Big “Yes” from my side, but read for yourself…
