Monthly DevOps News #3

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Monthly DevOps Track #3 – 17/09/2018

Some great posts this month on important topics, including the benchmarks of serverless computing in different cloud providers, YAML files, Multi-Cloud governance and automation.


1 -) If you wrote YAML file before, you know the pain of your Pipeline saying that your YAML’s syntax is broken. These tools will help you spot syntax errors beforehand.

2 -) Detailed performance comparison of different cloud providers’ serverless computing services. Concurrency and overhead are the main criteria.

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The Ultimate DevOps Explanation

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Dream Has Come True!

I am a person who believes that if someone wants to do a successful job, they first need to understand what the job is fundamentally. I love how Albert Einstein put it as he states:

If you can’t explain it simply, you don’t understand it well enough.
– Albert Einstein

With that being said, I consider Amazon’s DevOps definition as a simple yet amazing definition. It describes DevOps in a rough way but also covers nearly everything. Although, it needs some elaboration.

From what I’ve seen, ~99% of the definitions on the internet don’t cover up everything related to DevOps. Let’s be ~1%.

If you know what DevOps actually is, you will start seeing things from a different, constructive, rewarding and top-view perspective and contribute even more to your team.

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Monthly DevOps News #2

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Monthly DevOps Track #2 – 30/08/2018

Some great posts this month on important topics, including the economics of serverless, serverless strategies with organisations, and the importance of sustaining quality.


1 -) An excellent, detailed post about EU Commission’s new cloud strategy.

2 -) A post about sustaining high mainframe code quality while improving velocity efficieny.

3 -) Finding a correct approach to assess organizational readiness.

4 -) Cost-cutting is one of the most important concerns of cloud computing. This post gives some advices on reducing costs.

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Creating Cloudwatch Dashboards per Environment with Python

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Show Me The Code Already

After installing Cloudwatch Agent to the machines you want to monitor, it’s time to create dashboards to view real-time metrics.

There are some ways to create Cloudwatch Dashboards such as creating them manually by selecting widgets from AWS Console, with Cloudformation etc.

I’ve decided to create them with Python because in DevOps literature, there is no such a thing as manually creating something. I also didn’t want to use Cloudformation because I like scripting and we have many applications to monitor in our company, thus, I needed something to iterate over our environments and create dashboards for each of them.

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