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Yun Zhi Li – VP of Engineering APAC at continoHQ – wrote this article as a reaction to comparison of lambdas done in previous year by Yan Cui. He noticed that despite AWS adding more languages to lambda runtime, old languages were not neglected. In the article he reviewed and updated runtime performance benchmark of all five programming languages supported by AWS Lambda.

Similar to the original performance tests, author ignored the initial cold start time – and focused only on the duration metric to compare runtime performance between the different languages.

To manage the performance load test, he created a script that calls artillery.io. The script executes a load test across all twelve APIs over a one-hour period:

Some observations:

• Observation 1 – .Net Core 2.0 significantly outperforms
• Observation 2 – Go performance is comparable to Java
• Observation 3 – Consistent performance of compiled vs dynamic

With Go and .Net Core 2.0 support, AWS continues to lead the FaaS race as the most mature provider – with the widest range of supported languages. Good read!

Bruno Pedro detailed blog post focusing on secure storage of your API keys in the cloud. Many people store sensitive information in private git repositories. If you do this, please think about it twice.

Storing API Keys, or any other sensitive information, on a git repository is something to be avoided at all costs. Whenever you integrate a third-party application with one of the services like GitHub, GitLab, Bitbucket, you might be opening your private repositories to those third parties.

He then describes how to use various tools to encrypt keys:

• git-remote-gcrypt lets you encrypt a whole git repository
• git-secret is a tool that works on your local machine and encrypts specific files
• git-crypt is a binary executable to encrypt your files
• BlackBox from Stak Overflow supports the encryption of small strings and not just entire files
• Heroku configuration and config vars
• Docker secrets
• AWS Parameter Store

This article will help you become aware of the dangers of storing sensitive information such as API keys and secrets on public and also private git repositories. Click on the link to learn how to mitigate the risks. Great!

In his article Stefan Thorpe focuses on Theory of Constrains and DevOps. “Theory of Constraints” was originally conceived by Israeli business management educator and philosopher, Dr. Eliyahu M. Goldratt. Theory of Constraints inspired the development of new business management concepts and systems to revolutionize production procedures in manufacturing.

These practices of systems management all seek to improve on or, where possible, remove bottlenecks through process analysis.

Theory of Constraints has become a reputed model for eliminating waste, recognizing opportunities for better collaboration, and streamlining the flow of work down the value stream.

Author then identifies five steps to improving your development pipeline:

• Identify the constraint
• Exploit the constraint
• Subordinate everything else
• Elevate the constraint
• Repeat the process

Diagrams and charts explain these five points. Please read to learn how Lean influences within the DevOps methodology actually provide a great defense strategy to follow on a daily basis. Very good!

Bill Sourour from DevMastery.com wrote this article to introduce the pattern he has been using. He claims he did not invent it and came across it in other people’s code and eventually adopted it himself. The pattern is Receive an object, return an object (RORO).

Receive an object, return an object (RORO) Most of author’s functions now accept a single parameter of type object and many of them return or resolve to a value of type object as well. This patterns uses:

• Named parameters
• Cleaner default parameters
• Richer return values
• Easy function composition

RORO relies on destructuring feature introduced in ES2015. An added benefit of using destructuring for our parameter object is that it promotes immutability.

See function definition example bellow, with all parameters optional:

function findUsersByRole ({
  role,
  withContactInfo,
  includeInactive
} = {}) {...}

To learn more, read this article. Excellent!

Tadeu Zagallo announcment and introduction into NEAL. To make code reviews easier, Uber engineers built Not Exactly a Linter (NEAL), an open source language-agnostic tool that allows engineers to write custom syntax-based rules, thereby automating sections of the code review process.

NEAL lets engineers write their own set of rules to cover any part of the codebase, taking the code review process one step closer to full automation. In fact, to make this process easier, NEAL uses its own domain-specific language.

NEAL is extensively used for:

• Improve the reliability of our tests by checking for patterns
• Control the growth of our binary size
• Enforce high-level restrictions on executable code

NEAL is designed to be completely extensible across three dimensions. To learn how please read whole article. Exciting!

Sebastian Muller wrote this article / tutorial about AWS AppSync, a serverless GraphQL with support for custom data sources using AWS Lambda. To enable easy access to his RSS feed, author created a simple GraphQL API using AWS AppSync.

Tricky part was the deployment of the API due to lack of CloudFormation support for AWS AppSync. In the tutorial, you will find:

• AWS Lambda function to fetch and parse RSS feed
• Serverless Application Model to deploy Lambda function
• AppSync GraphQL API setup using AWS CLI

Tutorial then describes in detail what dependencies are, how to install Golang packages, configure environment and deploy using AWS Serverless Application Model. And finally you will learn how to use the GraphQL API. Great article!

John Tucker addresses important question how to create documentation for open source project. He takes us through example and will demonstrate a compelling documentation organization for an open source project.

Author pieced together the project’s documentation organization. Documentation entry point is in 3 places:

• Web site of HTML pages (including a search feature) generated with GitBook
• README.md markup file in the root folder of the master branch
• README.md markup file in the docs folder of the master branch

The HTML pages are generated from source markup files from the master branch of the repository. Author also offered solution for automation of the documentation updates using Travis CI (via travis.yml configuration filke). You will also find code examples for this article in the GitHub repository together with explanation how to use GitHub Pages. Interesting.

Guys from The Linux Foundation produced this Open Source Guide which is designed to offer advice about how your enterprise and your development team can plan for the day when you are ready to end or move away from an unneeded open source project.

They touch on many interesting points of open source project, including:

• Why life cycle planning is important
• How to protect your company’s reputation
• Seek a diverse contributor base
• How to end an open source project
• The importance of clear communications

They suggest that once you’ve decided to make the move, you must determine whether to end it, transfer it to another organization, or just pull out and end your direct involvement.

This is excellent guide, well worth your time!

Frans van Buul another look at event-driven architecture for a perspective you might not have seen to learn about messaging patterns, coupling, and more.

Gartner has identified this as one of the top 10 technology trends for 2018. “Events” occur very naturally in many business domains, which by itself is a good reason to make them an explicit part of software systems. They can be processed asynchronously.

Two anti-patterns considered:

• Messaging pattern
• Coupling

As per messaging anti-pattern he points out that messages between systems are not just that: they may also be things like instructions to do something. To represent a command (“post a new blog entry”) like an event (“there has been a request to post this new blog entry”) is unnatural.

A command represents a desire by the sender to change or do something. It should be handled exactly once, and the sender often expects a confirmation, since a command may fail. This is a totally different case from sending an event.

Learn about coupling problems in the article. Great read!

Patrick Michelberger created this tutorial in which we deploy a machine learning microservice using AWS Lambda, AWS API Gateway and scikit-learn.

Author starts with basic 3-class gradient boosted decision tree logistic regression model on iris data. This is not about quality of model, as for the purpose of the article it just needs to make predictions.

In this article author considers:

• How to train a basic model
• How to upload your model to AWS S3
• How to create a Flask API
• How to configure AWS Lambda & API Gateway
• How to test the API locally
• and how to deploy everything

Short and straight to the point tutorial for everybody starting with machine learning. Great!