An elephant graveyard, when applied to a corporate setting, is a team, company, or some other set of conditions in which otherwise bright engineers are forced into positions or assignments where there is no hope for future career growth. In this post, I hope to define the conditions that must be present for an elephant graveyard to form, how to detect them, and how to navigate them.
I am a software engineer and technology architect in New York City / New Jersey area. All opinions expressed here are mine and do not represent opinions of my employers and customers, nor should my opinions be construed as opinions about my employers and customers.
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Now that Peloton filed for IPO, there is a whole lot of opinions in the media from people who don’t own the product or subscribe to the digital service. I don’t intend to offer an investment opinion in this post. I do, however, want to dispel some of the FUD (Fear, Uncertainty, and Doubt) being spread around by so-called “experts” and “journalists.”
I am a big fan of data-driven fitness. I’ve been using some sort of a fitness tracking ecosystem for almost five years. Nothing motivates me more than a correctly recorded workout.
I have no idea what the cold caller was trying to sell as I did not have the brain power to process it. My mind was preoccupied with something else. What cold callers from vendors don’t seem to grasp is that they are asking the person to switch context from what they are doing and focus on the conversation.
I am not a fan of apps encouraging users to sign up using their social network credentials. The other popular alternative is creating individual accounts on each service, but it has its own pitfalls. There are emerging techniques like password-less authenticators that help simplify and secure the process. This post reviews some of them.
While I have long moved on from PostgreSQL, I continue to follow its development. I am glad to see Citus grow from a small startup with growing pains into an important part of Microsoft.
AWS offers a number of messaging and queuing services, each one with its own pros and cons. This post describes each service and when to use it.