AWS Lambda Power Tuning

Step Functions state machine generator for AWS Lambda Power Tuning.

The state machine is designed to be quick and language agnostic. You can provide any Lambda Function as input and the state machine will estimate the best power configuration to minimize cost. Your Lambda Function will be executed in your AWS account (i.e. real HTTP calls, SDK calls, cold starts, etc.) and you can enable parallel execution to generate results in just a few seconds.

https://github.com/alexcasalboni/aws-lambda-power-tuning

AWS X-Ray Update – General Availability, Including Lambda Integration

I first told you about AWS X-Ray at AWS re:Invent in my post, AWS X-Ray – See Inside Your Distributed Application. X-Ray allows you to trace requests made to your application as execution traverses Amazon EC2 instances, Amazon ECS containers, microservices, AWS database services, and AWS messaging services. It is designed for development and production use, and can handle simple three-tier applications as well as applications composed of thousands of microservices. As I showed you last year, X-Ray helps you to perform end-to-end tracing of requests, record a representative sample of the traces, see a map of the services and the trace data, and to analyze performance issues and errors. This helps you understand how your application and its underlying services are performing so you can identify and address the root cause of issues.

You can take a look at the full X-Ray walk-through in my earlier post to learn more.

https://aws.amazon.com/blogs/aws/aws-x-ray-update-general-availability-including-lambda-integration

Amazon DynamoDB Accelerator (DAX) – In-Memory Caching for Read-Intensive Workloads

I’m fairly sure that you already know about Amazon DynamoDB. As you probably know, it is a managed NoSQL database that scales to accommodate as much table space, read capacity, and write capacity as you need. With response times measured in single-digit milliseconds, our customers are using DynamoDB for many types of applications including adtech, IoT, gaming, media, online learning, travel, e-commerce, and finance. Some of these customers store more than 100 terabytes in a single DynamoDB table and make millions of read or write requests per second. The Amazon retail site relies on DynamoDB and uses it to withstand the traffic surges associated with brief, high-intensity events such as Black Friday, Cyber Monday, and Prime Day.

While DynamoDB’s ability to deliver fast, consistent performance benefits just about any application and workload, there’s always room to do even better. The business value of some workloads (gaming and adtech come to mind, but there are many others) is driven by low-latency, high-performance database reads. The ability to pull data from DynamoDB as quickly as possible leads to faster & more responsive games or ads that drive the highest click-through rates.

 https://aws.amazon.com/blogs/aws/amazon-dynamodb-accelerator-dax-in-memory-caching-for-read-intensive-workloads

Litho: A declarative UI framework for Android

Litho is a declarative framework for building efficient user interfaces (UI) on Android. It allows you to write highly-optimized Android views through a simple functional API based on Java annotations. It was primarily built to implement complex scrollable UIs based on RecyclerView.

With Litho, you build your UI in terms of components instead of interacting directly with traditional Android views. A component is essentially a function that takes immutable inputs, called props, and returns a component hierarchy describing your user interface.

@LayoutSpec
class HelloComponentSpec {

  @OnCreateLayout
  static ComponentLayout onCreateLayout(
      ComponentContext c,
      @Prop String name) {

    return Text.create(c)
        .text("Hello, " + name)
        .textSizeRes(R.dimen.my_text_size)
        .textColor(Color.BLACK)
        .withLayout()
        .paddingDip(ALL, 10)
        .build();
  }
}

You simply declare what you want to display and Litho takes care of rendering it in the most efficient way by computing layout in a background thread, automatically flattening your view hierarchy, and incrementally rendering complex components.

Have a look at our Tutorial for a step-by-step guide on using Litho in your app. You can also read the quick start guide on how to write and use your own Litho components.

http://fblitho.com/

Cache eviction: when are randomized algorithms better than LRU?

Once upon a time, my computer architecture professor mentioned that using a random eviction policy for caches really isn’t so bad. That random eviction isn’t bad can be surprising – if your cache fills up and you have to get rid of something, choosing the least recently used (LRU) is an obvious choice, since you’re more likely to use something if you’ve used it recently. If you have a tight loop, LRU is going to be perfect as long as the loop fits in cache, but it’s going to cause a miss every time if the loop doesn’t fit. A random eviction policy degrades gracefully as the loop gets too big.

In practice, on real workloads, random tends to do worse than other algorithms. But what if we take two random choices and just use LRU between those two choices?

http://danluu.com/2choices-eviction/

Drawing lessons from the “ Bezos Way”

Amazon’s CEO annual letter to his shareholders is a must-read. Customer focus, decision-making or the importance of writing down important things… Here are my takeaways from Jeff’s latest.

Whatever we think of its founder and CEO, Amazon remains a remarkable example of great management. Since its 1994 start, the company enjoyed steady growth, relentlessly conquering new markets and sectors, coupled to exceptional resilience shown when the company weathered two market crashes (2000 and 2008). In addition, Bezos has demonstrated a consistent ability to convince his board and shareholders to let expansion take precedence over profits and dividends. (No one can complain: thousand dollars invested in Amazon’s 1997 IPO are now worth more than half a million, a 500x multiple).

This didn’t happen without damage. By some measures, Amazon isn’t an enviable place to work and the pressure it applies to its suppliers rivals the iron fist of Walmart’s purchasing department. All things considered, Amazon’s level of corporate toxicity remains reasonable compared to Uber, as an example.

Jeff Bezos is also able to project an ultra-long term vision with his space exploration project for which he personally invests about a billion dollars per year.

Closer to our concerns, he has boosted a respected but doomed news institution — The Washington Post — thanks to a combined investment in journalistic excellence and in technology, two areas left fallow by most publishers.

That is why I thought Bezos’ written addresses to his shareholders (here) are worth some exegesis.

Let start with last week’s letter. (Emphasis mine, and while quotes are lifted from the original documents, some paragraphs have been rearranged for clarity and brevity).

Bezos starts his 2016 missive with a question asked by staffers at all-hands meetings:

“Jeff, what does Day 2 look like? (…) [Bezos reply:] Day 2 is stasis. Followed by irrelevance. Followed by excruciating, painful decline. Followed by death. And that is why it is always Day 1.”

Then he enumerates the three obsessions that make Amazon what it is today:…

https://mondaynote.com/drawing-lessons-from-the-bezos-way-dd0e950ade68