Note to self:

When developing new feature for Node.js native module and using node-pre-gyp, make sure you pump version higher so that node-pre-gyp will not pull the prebuilt binary.

A better man page. This is insanely useful 👍

tar

Archiving utility.
Often combined with a compression method, such as gzip or bzip.

- Create an archive from files:
tar cf target.tar file1 file2 file3

- Create a gzipped archive:
tar czf target.tar.gz file1 file2 file3

- Extract an archive in a target folder:
tar xf source.tar -C folder

- Extract a gzipped archive in the current directory:
tar xzf source.tar.gz

- Extract a bzipped archive in the current directory:
tar xjf source.tar.bz2

- Create a compressed archive, using archive suffix to determine the compression program:
tar caf target.tar.xz file1 file2 file3

- List the contents of a tar file:
tar tvf source.tar

• Birthday paradox

• The Power of Two Random Choices: A Survey of Techniques and Results by Mitzenmacher, Richa, and Sitaraman

• Cache eviction: when are randomized algorithms better than LRU?

• WebAssembly Binary Toolkit - Easiest way to setup WebAssembly binary toolkit. Or if you prefer to manually install it.

• wat2js - Compile WebAssembly .wat files to a common js module

• WebAssembly spec - WebAssembly Specification

Some examples modules

• siphash24 - SipHash (2-4) implemented in pure Javascript and WebAssembly.

• blake2b - Blake2b implemented in WASM

• xsalsa20 - XSalsa20 implemented in Javascript and WebAssembly

Follow Mathias Buus on GitHub. He’s has published quite a few interesting things about WebAssembly.

Successor to xpath-object-transform

camaro is an utility to transform XML to JSON, using Node.js binding to native XML parser pugixml, one of the fastest XML parser around.

• Faster. A lot faster.
• Building time is also faster.
• Mostly backward compatible with xpath-object-transform. I haven’t cover all the cases though.
• pre-built binaries included for some distro. Will include more in the future.

Featured on NodeWeekly #192 and npm addict

This chapter describes various performance tricks that allowed the author to write a very high-performing parser in C++: pugixml. While the techniques were used for an XML parser, most of them can be applied to parsers of other formats or even unrelated software (e.g., memory management algorithms are widely applicable beyond parsers).

Found out about this gem, recommended by the author of “Writing a Really, Really Fast JSON Parser”. This is a really good post as well.

Very young but interesting project.

Might save you from introducing something new your project just for full text search (chances are you probably already have Redis in your tech stack)

Here’s a dockerfile for Redis 4.0 RC3 and Redisearch 0.16 for you to fiddle with.

Selling points:

• Small
• The image is based on glibc for wide compatibility
• Using apt package manager for access to large number of packages
• Quicker security updates

Even though there are many complaints about glibc, it’s still very widely-adopted. I would hate to debug building libraries with musl-libc. It’s just not worth it.

I recently updated all of my personal Dockerfiles that I have for multiple purposes to use alpine as base image.

Prior this, I just use ubuntu as the base image and don’t have much care about built-images size. However, using Kubernetes, having small images size can make rolling out update speed much faster.

Some tips for reducing Docker image size that I found during my research:

• Using smaller base image (alpine, busybox, etc..)
• Remove unnecessary dependencies that you use for compiling stuff after done. (Also remove cache)
• Use few layers as possible. However, I don’t think you should do it blindly just for the shake of small image size and destroy readability. I prefer to keep it simple and clean. Optimize it later for building only.

How to setup twemproxy running on kubernetes.

TODO:

• Convert this into helm chart.