News and announcements
- Flutter now supports the web. Open source, repo on GitHub.
- Flutter 1.5 ships to the stable channel (release notes). Includes preliminary support for targeting Windows, Mac and Linux operating systems. New plug-ins for in-app payment, state management. New samples for ML Kit-based image classification.
- Support for developing on Chrome OS and publishing apps to Chrome OS.
- Dart 2.3 released with new support for UI-as-code features including the spread operator, collection if and collection for; website and package siteoverhauled.
- New reference customers for Flutter announced: eBay, Sonos, and New York Times. The Assistant team is using Flutter for their smart display platform with Flutter, powering the UI of devices such as Google Nest Hub.
- Updates for the Visual Studio Code and Android Studio tooling extensions.
- Flutter training course published by App Brewery, in collaboration with Google. Thirty hours of videos and labs, at a subsidized price of just $10.
- Flutter Create award winners announced, along with demo reel.
- International community-organized Flutter hackathon on June 1st.
AWS just announced the release of S3 Batch Operations. This is a hotly-anticpated release that was originally announced at re:Invent 2018. With S3 Batch, you can run tasks on existing S3 objects. This will make it much easier to run previously difficult tasks like retagging S3 objects, copying objects to another bucket, or processing large numbers of objects in bulk.
In this post, we’ll do a deep dive into S3 Batch. You will learn when, why, and how to use S3 Batch. First, we’ll do an overview of the key elements involved in an S3 Batch job. Then, we’ll walkthrough an example by doing sentiment analysis on a group of existing objects with AWS Lambda and Amazon Comprehend.
On March 2, 1959, a group of Australians gathered to celebrate a groundbreaking ceremony at Bennelong Point in central Sydney, unknowingly watching the start of one of the most disastrous construction projects in human history.
I have tried a few different ways of reporting Lambda errors to Slack, but haven’t found a reusable solution that gave all of the information I desired. I decided to solve that problem by creating my own Lambda layer. This solution doesn’t highlight the use of error logging, but is dynamic enough that you can just pass an error message into the layer.
For this to be useful to you, make sure you are familiar with the following:
1. AWS Lambda
2. Node JS
Events and serverless go together like baked beans and barbecue. The serverless mindset says to focus on code and configuration that provide business value. It turns out that much of the time, this means working with events: structured data corresponding to things that happen in the outside world. Rather than maintaining long-running server tasks that chew up resources while polling, I can create serverless applications that do work only in response to event triggers.
I have lots of options when working with events in AWS: Amazon Kinesis Data Streams, Amazon Simple Notification Service (SNS), Amazon Simple Queue Service (SQS), and more, depending on my requirements. Lately, I’ve been using a service more often that has the word ‘event’ right in the name: Amazon CloudWatch Events.
AWS introduced Lambda Layers at re:invent 2018 as a way to share code and data between functions within and across different accounts. It’s a useful tool and something many AWS customers have been asking for. However, since we already have numerous ways of sharing code, including package managers such as NPM, when should we use Layers instead?
In this post, we will look at how Lambda Layers works, the problem it solves and the new challenges it introduces. And we will finish off with some recommendations on when to use it.