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Amazon Web Services github.com

An opinionated full-stack boilerplate for production AWS apps

The primary objective of this boilerplate is to give you a production ready code that reduces the amount of time you would normally have to spend on system infrastructure’s configuration. It contains a number of services that a typical web application has (frontend, backend api, admin panel, workers) as well as their continuous deployment. Using this boilerplate you can deploy multiple environments, each representing a different stage in your pipeline.

An opinionated full-stack boilerplate for production AWS apps

Amazon Web Services adayinthelifeof.nl

AWS services explained in one line each

there are a lot of AWS services available. And I do mean: a LOT. Currently, there are 163 (!) different services that are available from the Amazon Dashboard, each with their own way of working, difficulties, catches and best practises.

What follows is one-line descriptions of all 163 AWS services. MSK? Kafka as a service. Amazon Connect? AWS call center platform. And so on.

Amazon Web Services github.com

The missing cron CLI for AWS Cloudwatch and Lambda

Do you have an AWS account? Great. Do you want to run cron jobs in the cloud?

Cronyo provides A simple CLI to manage your cron jobs on AWS.

In addition, Cronyo can instantly deploy a couple of super-simple, helpful and secure lambda functions to perform HTTP GET/POST requests for you. So if you need to trigger any webhooks on schedule, an AWS account and Cronyo is all you need :)

Amazon Web Services github.com

A serverless email server on AWS using S3 and SES

This stack was created out of frustration due to the fact that to this day there’s no easy way to have a full email server without the overhead of installing and configuring all servers needed to handle incoming and outgoing messages. We wanted something simple, with no interface and no server management, so we came up with S3-Email. This included AWS SES as our email server (receive and send) and S3 as our database and interface. Then we tied everything together with a bit of code via AWS Lambda.

All of this functionality and the repo is just some JSON, Yaml, and text files. Maybe 2020 really is the year of #nocode… 😉

Amazon Web Services aws.amazon.com

Announcing PartiQL: one query language for all your data

Today we are happy to announce PartiQL, a SQL-compatible query language that makes it easy to efficiently query data, regardless of where or in what format it is stored. As long as your query engine supports PartiQL, you can process structured data from relational databases (both transactional and analytical), semi-structured and nested data in open data formats (such as an Amazon S3 data lake), and even schema-less data in NoSQL or document databases that allow different attributes for different rows.

Announcing PartiQL: one query language for all your data

Ev Kontsevoy gravitational.com

Rolling your own servers with Kubernetes (goodbye AWS)

Why Kubernetes? Should you roll your own servers? Should you go off the cloud?

If you’ve listened to The Changelog #344 — where we cover the details of Changelog.com’s 2019 infrastructure with special guest Gerhard Lazu — then you’ll know the answer to these questions. But if not, as you might assume, I recommend listening to that episode and reading this post from Ev, in that order.

In this three-part blog series, we’ll try to address some of the fears and uncertainties faced by organizations who had successfully started their projects on public clouds, like AWS, but for one reason or another found themselves needing to replicate their cloud environment from scratch, starting with an empty rack in their own enterprise server room or a colocation facility.

Julian Tellez github.com

Lambcycle – a declarative lambda middleware with life cycle hooks

Lambcycle is a middleware for lambda functions. It defines a configurable life-cycle and allows you to focus on your application’s logic. It has a “Feature as Plugin” approach, so you can easily create your own plugins or reuse your favorite packages with very little effort 🐑 🛵.

The author goes deep on why Lambcycle solves a serious problem over on Medium.

Amazon Web Services enterprisedb.com

Is Amazon’s new MongoDB-compatible DBMS really PostgreSQL under the covers?

This is a nice rundown of the technical clues indicating that DocumentDB might be powered by Postgres.

PostgreSQL isn’t the only DBMS that scales writes vertically and reads horizontally via replication, but when you add this all up, especially some of the specific limitations, I think it makes a pretty compelling argument that PostgreSQL is the engine powering AWS DocumentDB.

John Demian dashbird.io

AWS Lambda limitations explained

John Demian lays out Lambda’s runtime environment limitations for your consideration.

I gave Lambda a chance to impress me after Pam Selle gave us the hard sell, but I hit up against the 5-minute function execution timeout. Needless to say I was not impressed.

It’s nice to see they’ve increased that to 15 minutes, but there are other constraints to consider as well.

Amazon Web Services awslabs.github.io

Find CloudFormation difficult to work with? Ditch YAML/JSON with AWS Cloud Development Kit (CDK)

The AWS CDK is an infrastructure modeling framework that allows you to define your cloud resources using an imperative programming interface. The CDK is currently in developer preview. We look forward to community feedback and collaboration.

If you’re developing for AWS and using CloudFormation, and you feel that YAML and/or JSON templates are too restrictive, CDK will allow you to programmatically define your stack. CDK provides strong typed resources for Java, .Net, and TypeScript, as well as JavaScript support. You can even augment it by creating your own constructs and create your own DSL on top of CloudFormation!

Cristian Magherusan-Stanciu github.com

Lower your AWS costs (up to 90%!) by automating the use of spot instances

If you’re using EC2 and paying big bucks to do so, you owe it to yourself to check out AutoSpotting:

Once installed and enabled by tagging existing on-demand AutoScaling groups, AutoSpotting gradually replaces their on-demand instances with spot instances that are usually much cheaper, at least as large and identically configured to the group’s members, without changing the group configuration in any way. For your peace of mind, you can also keep running a configurable number of on-demand instances given as percentage or absolute number.

Lower your AWS costs (up to 90%!) by automating the use of spot instances
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