This post's content
- Google Developers: Machine Learning Crash Course
- The SaaS CTO Security Checklist
- AI-based Database Expert for PostgreSQL/MySQL
- Amazon Web Services In Plain English
- NoSQL Databases: a Survey and Decision Guidance
- Comparing Git Workflows: What You Should Know
- A reference guide for fintech & small-data engineering
- What Is DevOps?
- Evolutionary Database Design
- Awesome CTO repository on GitHub
Guest post by Etai Stein
As a CTO you constantly have a lot of spinning plates to handle. Whether it’s implementing new technologies or going to the office at night when the CPU is at 100%, one of the key factors of being a successful CTO is having a good grasp on the varieties of technologies you’re dealing with. Here are a few resources I wish I had when I started my position as CTO:
For all you CTOs looking to get into ML, Google offers a great crash course on Machine Learning. It consists of 25 lessons, 30+ exercises, real case studies, and lectures from google experts.
The course itself is about 15 hours, relatively short for getting into this expansive field, but it just about covers the basics you need to know.
This edition of the SaaS CTO Security Checklist provides actionable security best practices CTOs (or anyone for that matter) can use to harden their security.
It sections into several categories such as employees, code, infrastructure, users, and more.
Each item on the checklist contains a paragraph about what should you do to increase security, and offers additional resources.
These days, it is hard to find PostgreSQL or MySQL specialists due to high salaries and a lack of experience. Additionally, you don't have to wait several days for someone to analyze what went wrong when PostgreSQL has 100% CPU usage.
With automated solutions like EverSQL, you can analyze and apply a solution to speed up your production environment.
This one is basic - a simple dictionary for AWS jargon - app and web developer services, Ops and code deployment services, enterprise, big data, and more. It even offers a better name for each service and compares it to a familiar replacement.
This article by Felix Gessert gives a top-down overview of the field of NoSQL: It presents the need for NoSQL databases, or “big data”, and explores its benefits and shortcomings over traditional rational databases. The piece goes in-depth into High-Level System Classification, and techniques such as sharding, replication, storage management, and query processing.
For every CTO considering NoSQL over PostgreSQL or MySQL, this is a must-read.
This piece serves as an introduction, comparison, and guide for the most common Git workflow, such as centralized workflow, Feature branching, and Forking Workflow. It mainly focuses on the centralized workflow, as it shows how it works and gives a step-by-step guide to implementing it.
Jack Danger has a different approach to data engineering than the common big-data approach many companies take. His article tackles 3 challenges faced by companies with small amounts of critical data in complex domains.
Jack’s article offers a guide to small-data, product-led data engineering.
You’re all probably familiar with DevOps, but as one department under the CTO’s responsibility, it’s important to know exactly what DevOps means, what are their areas of expertise, and how to manage a functioning DevOps team. This Atlassian space gives you several articles and even tutorials for DevOps practices.
Pramod Sadalage and Martin Fowler wrote this thorough piece about innovative database design and development, as agile development changed the demands for database design.
The piece offers an introduction to this agile-driven design methodology, and then dives into its practices:
DBAs collaborations with devs, version-controlled database artifacts, database changes as migrations, and more.
A lot of the resources I just shared with you came from this awesome repo on GitHub that was created by the talented Dima Kuchin. Its description - A curated and opinionated list of resources for Chief Technology Officers and VP R&D, with an emphasis on startups and hyper-growth companies.
It covers anything from technologies, people management, finance, and marketing. A must read for any technical manager.