AWS SAA Certification Prep – 2018

I’m getting ready to take the AWS Solutions Architect Associate 2018 test.  Below are some final items I need to review before the exam.

AWS FAQ’s:

Specific Items:

  • Spot vs Spot Block
  • Application ELB vs Classic ELB
  • Convertible vs. Standard Reserved Instances
  • EBS Cost vs Performance
  • EC2 reverse proxy (link) (link)
  • Glacier Retrieval Options
  • Beanstalk vs. NGINX
  • Cross-region snapshots for databases

SSDT 2017 and Backwards Compatibility

If you are working with SSDT 2017 and creating reports for earlier versions of SSRS, please read the following article!

I really think MS did a great job here with the “TargetServerVersion” property functionality, which allows reports to convert to previous SSRS formats during deployment.

aplusd.png

AWS Developer Certification – My Plan

Below is my plan to obtain the AWS Developer Certification.

For each of the following areas listed further down, I am trying to do the following:

  • Read the FAQ’s
  • Practice in the console
  • Practice with the CLI and understand the functions\parameters
  • Review all HTTP codes
  • Review all defaults and limits
  • Review uniqueness of each area

Here are the areas I am covering in preparation for the exam.

  • EC2
  • S3
  • DynamoDB
  • SNS
  • SQS
  • VPC
  • ELB
  • Lambda
  • Route 53
  • RDS
  • SWF
  • Cloudformation
  • Elastic Beanstalk
  • API Gateway
  • Storage Gateway
  • EFS
  • CloudWatch
  • CloudTrail
  • IAM

The exam is only 55 questions, so i’m not sure how in depth the exam will go on each of these.  Regardless, its a good to review all of the areas!

Python – Tesseract – OCR – IMAGE

You can do some pretty cool things with tesseract-ocr.  Using PyOCR, which is a wrapper for Tesseract, you can generate text from an image using Tesseract.

Example Image:

aws_.jpg

Example Output:

Tesseract.png

Example Code:

from wand.image import Image
from PIL import Image as PI
import pyocr
import pyocr.builders
import io
import sys

reload(sys) 
sys.setdefaultencoding('utf8')
 
tool = pyocr.get_available_tools()[0]
lang = tool.get_available_languages()[1]
 
txt_list = tool.image_to_string(
 PI.open('/home/build/aws.jpg'),
 lang=lang,
 builder=pyocr.builders.TextBuilder())

outputFile = open('output.txt', 'w')
for item in txt_list:
 outputFile.write("%s" % item)
outputFile.close()

Another use case I was working on today was rendering the text in a PDF file using Tesseract.  I was converting the PDF to an image file first, then performing the above actions to read the text from the new image.

Here are a couple valuable resources I used to complete this little test.

  • Installing Tesseract on a RHEL system – http://www.keienberg.com/install-tesseract-3-04-centos-7/ (link)
  • Installing PyOCR and other image conversion tools – https://pythontips.com/2016/02/25/ocr-on-pdf-files-using-python/ (link)

Getting all the prerequisites installed was by far the hardest part on this effort.

AWS Consistency Models

S3 Consistency Model

  • Puts (New record) = Read-after-write consistency model
  • Updates and Deletes = Eventual consistency model

DynamoDB Consistency Model

  • Write = Eventual consistency model
  • Read = Eventual consistency model
  • Read  = Optional – Strong consistency model

Definitions

  • Read-after-write consistency model = New objects should be available with out delays to clients.
  • Eventual consistency model = “Eventually” all access attempts to a particular item will return the last updated value.  There is potential here for stale or old data reads while data replication occurs.
  • Strong consistency model = All access attempts (e.g. parallel) to a particular item return the same unique state.  Old\stale data reads are avoided, but it will cost you more.

Good information to know for any AWS certification tests…. 🙂

AmazonWebservices_Logo.svg_

Docker Hub – Build Hooks

I tried out the Docker Hub post_push hook script today with my automated build and it works great.  This link has all the details around more advanced Docker Hub build scripting.

What I tried using the post_push script for was to tag my mainline build (latest) with another specific tag (release).

Steps to implement:

  1. Create a hooks folder in my GitHub repo.
  2. Create a script called “post_push” under the hooks folder that will tag the latest image with my release number.

    #!/bin/bash
    set -e
    tagStart=$(expr index “$IMAGE_NAME” 🙂
    repoName=${IMAGE_NAME:0:tagStart-1}
    docker tag $IMAGE_NAME ${repoName}:18.3.1
    docker push ${repoName}:18.3.1

The end results is the following:

postpushdocker.png

So a possible use-case would be to have a Jenkins job that gets triggered when your Dockerfile changes in GitHub and updates the release version in the “post_push” script, then triggers the Docker Hub job.

docker.png

Docker Goodies – Frequent Commands

Noting some of the usual Docker commands I run for future reference…

  • Start Docker daemon = systemctl start docker
  • View running Docker images = docker ps
  • View all images on the server = docker images or docker image ls
  • Remove all images on the server (dangling and unused) = docker images prune -a
  • Build my image = docker build -f <dockerfile_path> .
  • Run my Docker image and check Ansible version = docker run –rm -it <image_id> –version
  • Tag new image = docker tag <image> devopsunleashed/ansible:3.31.1
  • Login to Docker Hub = docker login -u <user> -p <pw>
  • Push image to Docker Hub = docker push devopsunleashed/ansible:3.31.1

Awesome Docker command cheat-sheet (link)

dockericon