Gergo Debreczeni gergo-dryrun
| a4b.amazonaws.com | |
| access-analyzer.amazonaws.com | |
| account.amazonaws.com | |
| acm-pca.amazonaws.com | |
| acm.amazonaws.com | |
| airflow-env.amazonaws.com | |
| airflow.amazonaws.com | |
| alexa-appkit.amazon.com | |
| alexa-connectedhome.amazon.com | |
| amazonmq.amazonaws.com |
| Title | Description
| 'Update or create a stack given a name and template + params' | |
| from __future__ import division, print_function, unicode_literals | |
| from datetime import datetime | |
| import logging | |
| import json | |
| import sys | |
| import boto3 | |
| import botocore |
| Code | Title | Duration | Link |
|---|---|---|---|
| Keynote | Andy Jassy Keynote Announcement Recap | 0:01 | https://www.youtube.com/watch?v=TZCxKAM2GtQ |
| Keynote | AWS re:Invent 2016 Keynote: Andy Jassy | 2:22 | https://www.youtube.com/watch?v=8RrbUyw9uSg |
| Keynote | AWS re:Invent 2016 Keynote: Werner Vogels | 2:16 | https://www.youtube.com/watch?v=ZDScBNahsL4 |
| Keynote | [Tuesday Night Live with Jame |
Code is clean if it can be understood easily – by everyone on the team. Clean code can be read and enhanced by a developer other than its original author. With understandability comes readability, changeability, extensibility and maintainability.
- Follow standard conventions.
- Keep it simple stupid. Simpler is always better. Reduce complexity as much as possible.
- Boy scout rule. Leave the campground cleaner than you found it.
- Always find root cause. Always look for the root cause of a problem.
A curated list of AWS resources to prepare for the AWS Certifications
A curated list of awesome AWS resources you need to prepare for the all 5 AWS Certifications. This gist will include: open source repos, blogs & blogposts, ebooks, PDF, whitepapers, video courses, free lecture, slides, sample test and many other resources.
Here is the raw output from examining the Python LambdaContext context object in a AWS Lambda function when called from a CloudFormation stack. More information on the context object can be found here : http://docs.aws.amazon.com/lambda/latest/dg/python-context-object.html
<__main__.LambdaContext object at 0x7fd706780710>
| STACK:=myapp-dev | |
| TEMPLATE:=cloudformation-template_vpc-iam.json | |
| PARAMETERS:=cloudformation-parameters_myapp-dev.json | |
| AWS_REGION:=us-east-1 | |
| AWS_PROFILE:=aws-dev | |
| all: | |
| @which aws || pip install awscli | |
| aws cloudformation create-stack --stack-name $(STACK) --template-body file://`pwd`/$(TEMPLATE) --parameters file://`pwd`/$(PARAMETERS) --capabilities CAPABILITY_IAM --profile $(AWS_PROFILE) --region $(AWS_REGION) |
I was at Amazon for about six and a half years, and now I've been at Google for that long. One thing that struck me immediately about the two companies -- an impression that has been reinforced almost daily -- is that Amazon does everything wrong, and Google does everything right. Sure, it's a sweeping generalization, but a surprisingly accurate one. It's pretty crazy. There are probably a hundred or even two hundred different ways you can compare the two companies, and Google is superior in all but three of them, if I recall correctly. I actually did a spreadsheet at one point but Legal wouldn't let me show it to anyone, even though recruiting loved it.
I mean, just to give you a very brief taste: Amazon's recruiting process is fundamentally flawed by having teams hire for themselves, so their hiring bar is incredibly inconsistent across teams, despite various efforts they've made to level it out. And their operations are a mess; they don't real