This is the third of a twelve-part series covering the sessions from Calibrate, an engineering leadership conference held September, 2015 in San Francisco.
This is the second of a twelve-part series covering the sessions from Calibrate, an engineering leadership conference held September, 2015 in San Francisco.
Today we’re featuring Rands’ keynote: “Leadership. By the Numbers.”
This is the first of a twelve-part series covering the sessions from Calibrate, an engineering leadership conference held September, 2015 in San Francisco. Content will be posted at a regular cadence throughout the month of November.
After creating a few Scala projects, we noticed that we repeated a good chunk of SBT configuration across projects. This caused issues, the kind that occur any time there’s repeated code. In some cases, developers were resolving version and dependency incompatibilities over and over. In others, improvements...
Most of Sharethrough’s infrastructure runs on AWS. For a long time we’ve relied on chef and knife ec2 to maintain resources, but as we grew, we searched for tools that would continue to improve operation efficiency. Recently we started using two tools from Hashicorp, Packer and Terraform, that appear...
Updated 9/1/2015: We have updated our SlackErrorService to use Sidekiq’s global error handlers feature.
Back in 2013 when we began our platform rewrite, there were many Ruby-based queuing options available. The following three stood out as the best choices: Delayed Job, Resque
My career at Sharethrough began in the Solutions Architect role. My publisher operations experience from the last company helped me develop empathy with the processes and tools the team at Sharethrough was employing, and learn about the external business stakeholders. I sat in on internal operations...
For those of you not familiar with Spark, it is a cluster computing framework developed in AMPLab at UC Berkeley. Unlike MapReduce, which writes its data to disk between steps, Spark attempts to perform all of its computations in memory which can yield significant performance improvements. It is...
It’s a best practice to bypass logging during unit tests. Since the tests will be run by a computer, the output is wasted I/O, and if you needed log output to understand why a test failed, that should be a sign that a new test needs to be written. Logging tests can even make debugging harder by hiding...
One of Scala’s strengths is its support for multiple programming paradigms. In practice, however, Scala reminds the developer how each paradigm evolved separately, and carried with it lexicons and perspectives for concepts that turn out to have a lot in common.
Type Classes were a concept I had difficulty...
