Passing the AZ-300

Hello all!

Over the past year I’ve been buried in Amazon Web Services (AWS), learning the platform, and working through the certification paths.  As part of my new role at Microsoft, I’ve been given the opportunity to pursue the Microsoft Certified: Azure Solutions Architect Expert.  In the world of multi-cloud who doesn’t want to learn multiple platforms? 🙂

The Microsoft Certified: Azure Solutions Architect Expert certification is part of Microsoft’s new set of certifications.  If you’re already familiar with the AWS Certification track, the new Microsoft track is very similar in that it has three paths.  These paths are Developer, Administrator, and Architect.  Each path consists of two exams, again similar to AWS’s structure of Associate and Professional.

Even though the paths are similar the focus and structure of the first tier of exams for the Microsoft exams differ greatly from the AWS Associate exams.  The AWS exams are primarily multiple choice while the Microsoft first level of exams consists of multiple choice, drag and drop, fill in the blank, case studies, and emulated labs.  Another difference between the two is the AWS exams focus greatly on how the products work and when and where to use each product.  The Microsoft first level exams focus on those topics too, but additionally test your ability to implement the technologies.

When I started studying for the AZ-300 – Microsoft Azure Architect Technologies two weeks I had a difficult time finding good study materials because the exam is so new and has changed a few times since Microsoft released it last year.  Google searches brought up a lot of illegitimate study materials (brain dumps) but not much in the way of helpful materials beyond the official Azure documentation.  After passing the exam this week, I wanted to give back to the community and provide some tips, links, and the study guide I put together to help prepare for the exam.

To prepare for an exam I have a standard routine.

  1. I first start with referencing the official exam requirements.
  2. From there, I take one or two on-demand training classes.  I watch each lesson in a module at 1.2x speed (1x always seems to slow which I think is largely due to living in Boston where we tend to talk very quickly).  I then go back through each module at 1.5x to 2.0x taking notes on paper.  I then type up the notes and organize them into topics.
  3. Once I’m done with the training I’ll usually dive deep into the official documentation on the subjects I’m weak on or that I find interesting.
  4. During the entirety of the learning process I will build out labs to get a feel for implementation and operation of the products.
  5. I wrap it up by adding the additional learnings from the public documentation and labs into my digital notes.  I then pull out the key concepts from the digital notes and write up flash cards to study.
  6. Practice makes perfect and for that I will leverage legitimate practice exams (braindumps make the entire exercise a pointless waste of time and degrade the value of the certification) like those offered from MeasureUp.

Yes, I’m a bit nuts about my studying process but I can assure you it works and you will really learn the content and not just memorize it.

From a baseline perspective, my experience with Microsoft’s cloud services were primarily in Azure Active Directory and Azure Information Protection.  For Azure I had built some virtual networks with virtual machines in the past, but nothing more than that.  I have a pretty solid foundation in AWS and cloud architectural patterns which definitely came in handy since the base offerings of each of the cloud providers are fairly similar.

For on-demand training A Cloud Guru has always been my go to.  Unfortunately, their Azure training options aren’t as robust as the AWS offerings, but Nick Coyler’s AZ-300 course is solid.  It CANNOT be your sole source of material but as with most training from the site, it will give you the 10,000 ft view.  Once I finished with A Cloud Guru, I moved on to UdemyScott Duffy’s AZ-300 course does not have close to the detail of Nick’s course, but provides a lot more hands-on activities that will get you working with the platform via the GUI and the CLI.  Add both courses together and you’ll cover a good chunk of the exam.

The courses themselves are not sufficient to pass the exam.  They will give you the framework, but docs.microsoft.com is your best friend.  There is the risk you can dive more deep into the product than you need to, but reference back to the exam outline to keep yourself honest.  Hell, worst case scenario is you learn more than you need to learn. 🙂  Gregor Suttie put together a wonderful course outline with links to the official documentation that will help you target key areas of the public documentation.

Perhaps most importantly, you need to lab.  Then lab again.  Lab once more, and then another time.  Run through the Quickstarts and Tutorials on docs.microsoft.com.  Get your hands dirty with the CLI, PowerShell, and the Portal.  You don’t have to be an expert, but you’ll want to understand the basics and the general syntax of both the CLI and PowerShell.  You will have fully interactive labs where you’ll need to implement the products given a set of requirements.

Finally, I’ve added the study guides I put together to my github.  I make no guarantees that the data is up to date or even that there aren’t mistakes in some of the content.  Use it as an artifact to supplement your studies as you prepare your own study guide.

Summing it up, don’t just look at the exam as a piece of virtual paper.  Look at it as an opportunity to learn and grow your skill set.  Take the time to not just memorize, but understand and apply what you learn.  Be thankful you work an industry where things change and provides you with the opportunity to learn something new and exercise that big brain of yours.

I wish you the best of luck in your studies and if you have additional materials or a website you’ve found helpful, please comment below.

Thanks!

 

 

 

 

 

 

 

Some updates…

Hello folks!  Life has been busy with some wonderful work and some big career changes.  As some of you may know, I moved on from my role at the Federal Reserve last summer.  While I loved the job, the people, and the organization, I wanted to try something new and different.

I was lucky enough to have the opportunity to work for one of the big three cloud providers in a security-focused professional services role supporting public sector customers.  The role was amazing, I learned a TON about a cloud platform I had never worked with, interacted with some of the smartest people I’ve ever met, and had the chance to help architect and implement some really awesome environments for some stellar customers.

Unfortunately the travel started taking a toll on my personal life and family time.  I made the tough decision to move on and find something that was a bit more regional and less travel.  I struck the lottery once more and in April started as a Cloud Solution Architect at Microsoft focusing on Infrastructure and Security in Azure.  I’ve once again been drinking from multiple firehoses and learning my second cloud platform.  It’s been a ball so far and I’m extremely excited learn and contribute to Microsoft’s mission to empower every person and every organization on the planet to achieve more!

Expect a lot more activity on this blog as I share my experiences and my learnings with the wider tech community.  It’s going to be a fun ride!

Capturing and Visualizing Office 365 Security Logs – Part 1

Welcome back again my fellow geeks!

I’ve been busy over the past month nerding out on some pet projects.  I thought it would be fun to share one of those pet projects with you.  If you had a chance to check out my last series, I walked through my first Python experiment which was to write a re-usable tool that could be used to pull data from Microsoft’s Graph API (Microsoft Graph).

For those of you unfamiliar with Microsoft Graph, it’s the Restful API (application programming interface) that is used to interact with Microsoft cloud offerings such as Office 365 and Azure.  You’ve probably been interacting with it without even knowing it if through the many PowerShell modules Microsoft has released to programmatically interact with those services.

One of the many resources which can be accessed through Microsoft Graph are Azure AD (Active Directory) security and audit reports.  If you’re using Office 365, Microsoft Azure, or simply Azure AD as an identity platform for SSO (single sign-on) to third-party applications like SalesForce, these reports provide critical security data.  You’re going to want to capture them, store them, and analyze them.  You’re also going to have to account for the window that Microsoft makes these logs available.

The challenge is they are not available via the means logs have traditionally been captured on-premises by using syslogd, installing an SIEM agent, or even Windows Event Log Forwarding.  Instead you’ll need to take a step forward in evolving the way you’re used to doing things. This is what moving to the cloud is all about.

Microsoft allows you to download the logs manually via the Azure Portal GUI (graphical user interface) or capture them by programmatically interacting with Microsoft Graph.  While the former option may work for ad-hoc use cases, it doesn’t scale.  Instead we’ll explore the latter method.

If you have an existing enterprise-class SIEM (Security Information and Event Management) solution such as Splunk, you’ll have an out of box integration.  However, what if you don’t have such a platform, your organization isn’t yet ready to let that platform reach out over the Internet, or you’re interested in doing this for a personal Office 365 subscription?  I fell into the last category and decided it would be an excellent use case to get some experience with Python, Microsoft Graph, and take advantage of some of the data services offered by AWS (Amazon Web Services).   This is the use case and solution I’m going to cover in this post.

Last year I had a great opportunity to dig into operational and security logs to extract useful data to address some business problems.  It was my first real opportunity to examine large amounts of data and to create different visualizations of that data to extract useful trends about user and application behavior.  I enjoyed the hell out of it and thought it would be fun to experiment with my own data.

I decided that my first use case would be Office 365 security logs.  As I covered in my last series my wife’s Office 365 account was hacked.  The damage was minor as she doesn’t use the account for much beyond some crafting sites (she’s a master crocheter as you can see from the crazy awesome Pennywise The Clown she made me for Christmas).

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The first step in the process was determining an architecture for the solution.  I gave myself a few requirements:

  1. The solution must not be dependent on my home lab infrastructure
  2. Storage for the logs must be cheap and readily available
  3. The credentials used in my Python code needs to be properly secured
  4. The solution must be automated and notify me of failures
  5. The data needs to be available in a form that it can be examined with an analytics solution

Based upon the requirements I decided to go the serverless (don’t hate me for using that tech buzzword 🙂 ) route.  My decisions were:

  • AWS Lambda would run my code
  • Amazon CloudWatch Events would be used to trigger the Lambda once a day to download the last 24 hours of logs
  • Amazon S3 (Simple Storage Service) would store the logs
  • AWS Systems Manager Parameter Store would store the parameters my code used leveraging AWS KMS (Key Management Service) to encrypt the credentials used to interact with Microsoft Graph
  • Amazon Athena would hold the schema for the logs and make the data queryable via SQL
  • Amazon QuickSight would be used to visualize the data by querying Amazon Athena

The high level architecture is pictured below.

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I had never done a Lambda before so I spent a few days looking at some examples and doing the typical Hello World that we all do when we’re learning something new.  From there I took the framework of Python code I put together for general purpose queries to the Microsoft Graph, and adapted it into two Lambdas.  One Lambda would pull Sign-In logs while the other would pull Audit Logs.  I also wanted a repeatable way to provision the Lambdas to share with others and get some CloudFormation practice and brush up on my very dusty Bash scripting.   The results are located here in one of my Github repos.

I’m going to stop here for this post because we’ve covered a fair amount of material.  Hopefully after reading this post you understand that you have to take a new tact with getting logs for cloud-based services such as Azure AD.  Thankfully the cloud has brought us a whole new toolset we can use to automate the extraction and storage of those logs in a simple and secure manner.

In my next post I’ll walk through how I used Athena and QuickSight to put together some neat dashboards to satisfy my nerdy interests and get better insight into what’s happening on a daily basis with my Office 365 subscription.

See you next post and go Pats!

Using Python to Pull Data from MS Graph API – Part 1

Welcome to 2019 fellow geeks! I hope each of you had a wonderful holiday with friends and family.

It’s been a few months since my last post. As some of you may be aware I made a career move last September and took on a new role with a different organization. The first few months have been like drinking from multiple fire hoses at once and I’ve learned a ton. It’s been an amazing experience that I’m excited to continue in 2019.

One area I’ve been putting some focus in is learning the basics of Python. I’ve been a PowerShell guy (with a bit of C# thrown in there) for the past six years so diving into a new language was a welcome change. I picked up a few books on the language, watched a few videos, and it wasn’t clicking. At that point I decided it was time to jump into the deep end and come up with a use case to build out a script for. Thankfully I had one queued up that I had started in PowerShell.

Early last year my wife’s Office 365 account was hacked. Thankfully no real damage was done minus some spam email that was sent out. I went through the wonderful process of changing her passwords across her accounts, improving the complexity and length, getting her on-boarded with a password management service, and enabling Azure MFA (Multi-factor Authentication) on her Office 365 account and any additional services she was using that supported MFA options.  It was not fun.

Curious of what the logs would have shown, I had begun putting together a PowerShell script that was going to pull down the logs from Azure AD (Active Directory), extract the relevant data, and export it CSV (comma-separate values) where I could play around with it in whatever analytics tool I could get my hands on. Unfortunately life happened and I never had a chance to finish the script or play with the data. This would be my use case for my first Python script.

Azure AD offers a few different types of logs which Microsoft divides into a security pillar and an activity pillar. For my use case I was interested in looking at the reports in the Activity pillar, specifically the Sign-ins report. This report is available for tenants with an Azure AD Premium P1 or P2 subscription (I added P2 subscriptions to our family accounts last year).  The sign-in logs have a retention period of 30 days and are available either through the Azure Portal or programmatically through the MS Graph API (Application Programming Interface).

My primary goals were to create as much reusable code as possible and experiment with as many APIs/SDKs (Software Development Kits) as I could.  This was accomplished by breaking the code into various reusable modules and leveraging AWS (Amazon Web Services) services for secure storage of Azure AD application credentials and cloud-based storage of the exported data.  Going this route forced me to use the MS Graph API, Microsoft’s Azure Active Directory Library for Python (or ADAL for short), and Amazon’s Boto3 Python SDK.

On the AWS side I used AWS Systems Manager Parameter Store to store the Azure AD credentials as secure strings encrypted with a AWS KMS (Key Management Service) customer-managed customer master key (CMK).  For cloud storage of the log files I used Amazon S3.

Lastly I needed a development environment and source control.  For about a day I simply used Sublime Text on my Mac and saved the file to a personal cloud storage account.  This was obviously not a great idea so I decided to finally get my GitHub repository up and running.  Additionally I moved over to using AWS’s Cloud9 for my IDE (integrated development environment).   Cloud9 has the wonderful perk of being web based and has the capability of creating temporary credentials that can do most of what my AWS IAM user can do.  This made it simple to handle permissions to the various resources I was using.

Once the instance of Cloud9 was spun up I needed to set the environment up for Python 3 and add the necessary libraries.  The AMI (Amazon Machine Image) used by the Cloud9 service to provision new instances includes both Python 2.7 and Python 3.6.  This fact matters when adding the ADAL and Boto3 modules via pip because if you simply run a pip install module_name it will be installed for Python 2.7.  Instead you’ll want to execute the command python3 -m pip install module_name which ensures that the two modules are installed in the appropriate location.

In my next post I’ll walk through and demonstrate the script.

Have a great week!