Vol. 14 No. 3 – May-June 2016


Research for Practice: Distributed Consensus and Implications of NVM on Database Management Systems:
Expert-curated Guides to the Best of CS Research

First, how do large-scale distributed systems mediate access to shared resources, coordinate updates to mutable state, and reliably make decisions in the presence of failures? Second, while consensus concerns distributed shared state, our second selection concerns the impact of hardware trends on single-node shared state.

by Peter Bailis, Camille Fournier, Joy Arulraj, Andy Pavlo

Idle-Time Garbage-Collection Scheduling:
Taking advantage of idleness to reduce dropped frames and memory consumption

Google’s Chrome web browser strives to deliver a smooth user experience. An animation will update the screen at 60 FPS (frames per second), giving Chrome around 16.6 milliseconds to perform the update. Within these 16.6 ms, all input events have to be processed, all animations have to be performed, and finally the frame has to be rendered. A missed deadline will result in dropped frames. These are visible to the user and degrade the user experience. Such sporadic animation artifacts are referred to here as jank. This article describes an approach implemented in the JavaScript engine V8, used by Chrome, to schedule garbage-collection pauses during times when Chrome is idle. This approach can reduce user-visible jank on real-world web pages and results in fewer dropped frames.

by Ulan Degenbaev, Jochen Eisinger, Manfred Ernst, Ross McIlroy, Hannes Payer

Bad Software Architecture is a People Problem:
When people don’t work well together they make bad decisions.

It all started with a bug. Customers were complaining that their information was out of date on the website. They would make an update and for some reason their changes weren’t being reflected. Caching seemed like the obvious problem, but once we started diving into the details, we realized it was a much bigger issue.

by Kate Matsudaira

The Hidden Dividends of Microservices:
Microservices aren’t for every company, and the journey isn’t easy.

Microservices are an approach to building distributed systems in which services are exposed only through hardened APIs; the services themselves have a high degree of internal cohesion around a specific and well-bounded context or area of responsibility, and the coupling between them is loose. Such services are typically simple, yet they can be composed into very rich and elaborate applications. The effort required to adopt a microservices-based approach is considerable, particularly in cases that involve migration from more monolithic architectures. The explicit benefits of microservices are well known and numerous, however, and can include increased agility, resilience, scalability, and developer productivity. This article identifies some of the hidden dividends of microservices that implementers should make a conscious effort to reap.

by Tom Killalea

Dynamics of Change: Why Reactivity Matters:
Tame the dynamics of change by centralizing each concern in its own module.

Professional programming is about dealing with software at scale. Everything is trivial when the problem is small and contained: it can be elegantly solved with imperative programming or functional programming or any other paradigm. Real-world challenges arise when programmers have to deal with large amounts of data, network requests, or intertwined entities, as in UI (user interface) programming.

by Andre Medeiros

The Singular Success of SQL:
SQL has a brilliant future as a major figure in the pantheon of data representations.

SQL has a brilliant past and a brilliant future. That future is not as the singular and ubiquitous holder of data but rather as a major figure in the pantheon of data representations. What the heck happens when data is not kept in SQL?

by Pat Helland

Cluster-level Logging of Containers with Containers:
Logging Challenges of Container-Based Cloud Deployments

This article shows how cluster-level logging infrastructure can be implemented using open source tools and deployed using the very same abstractions that are used to compose and manage the software systems being logged. Collecting and analyzing log information is an essential aspect of running production systems to ensure their reliability and to provide important auditing information. Many tools have been developed to help with the aggregation and collection of logs for specific software components (e.g., an Apache web server) running on specific servers (e.g., Fluentd and Logstash.) They are accompanied by tools such as Elasticsearch for ingesting log information into persistent storage and tools such as Kibana7 for querying log information.

by Satnam Singh

Chilling the Messenger:
Keeping ego out of software-design review

Trying to correct someone who has just done a lot of work, even if, ultimately, that work is not the right work, is a daunting task. The person in question no doubt believes that he has worked very hard to produce something of value to the rest of the team, and walking in and spitting on it, literally or metaphorically, probably crosses your "offense" line--at least I think it does. I’m a bit surprised that since this is the first sprint and there is already so much code written, shouldn’t the software have shown up after the sprints established what was needed, who the stakeholders were, etc.? Or was this a piece of previously existing code that was being brought in to solve a new problem? It probably doesn’t matter, because the crux of your letter is the fact that you and your team do not sufficiently understand the software in question to be comfortable with fielding it.

by George Neville-Neil