My Interview with Google

While not an original post by far, I’d like to share my experience interviewing with Google. Since Google is constantly changing their interview process, this was conducted in Spring 2019. This is a bit of a ramble so I’ll highlight key points as I go.

The Summoning

Ever since I interviewed for Google back in my college days for an internship, I get calls from them once or twice a year asking if I’m interested in applying. Sometimes I tell them yes, sometimes no, and sometimes “never call me again”. They still call. Unfortunately, this means I can’t help you get a call from their recruiters because I’ve been stuck on their radar for years, whether I want to be or not.

Key Point: If you don’t think you can get a job at Google yet, apply anyway and they will stay in touch with you as your experience starts to match what they need. It’s not creepy: it’s Google.

Anyway, one day I was checking my Gmail inbox and was inspired to go through my spam to see if the filters were too aggressive. Ironically, there was a recruiter email from Google asking to schedule a call. In their defense, it was being forwarded from my college email address (as per history above) so I guess they weren’t flagging themselves so much as my university.

I almost always agree to do a call, mostly because I one day hope to hear they’ve embraced fully remote work. I don’t think this will ever happen. Still, who knows how long I’ll be stuck on their recruiting radar?

During the call I get the usual spiel about what teams are in my area and which offices I can apply for, immigration questions, and when I’d like to interview. Normally, I’ll ask about working from home or flexible hours but this time I had another motive to interview: I was coaching people in technical interviews and figured putting myself in their place would be a good way to help them. See how altruistic I am by making the great sacrifice of interviewing for one of the top tech companies? My motives aside, I figured I’d get them to send me their list of study materials, I’d go over them with my mentees, do a phone screen, and share my notes.

Surprise! You get to skip the phone screen because your friends at Google recommended you. Ugh. I didn’t really want to do the full 6 hours of walking over algorithmic coals but fine Retrospectively, I think I need to find better hobbies than interviewing at tech companies.

Key Point: If you have former classmates or colleagues at Google, their recommendation will not only get you an interview but can also decide whether you get the job. 

“The Usual Spiel”

As mentioned above, recruiters tend to follow a script and Google is no exception. Below are the points covered:

  • Locations of new and existing offices in your area as well as questions about where you would like to work. Key Point: An interview anywhere for Google is good for any location at Google, including any country or continent.
  • A list of teams hiring in your area along with their current projects.
  • New company initiatives around benefits, diversity, etc.
  • What the interview process looks like:
    • (Usually) a phone screen
    • An on-site interview for 6 hours with 5 hours of technical interviews and 1 hour of lunch with a Googler
    • Judgement – tentative offer or rejection
    • Requests for references, preferably internal to Google but also external
    • Selection of a start date
    • Team rotations/team shopping: you spend 1 – 2 weeks on a team to decide whether you want to work with them or not
    • Team selection and assimilation into the Borg
  • Promises to send follow up emails and interview materials

Key Point: I was told after Spring 2019 there would be 4 technical interviews and 1 ‘soft skills’ interview. 

When and What

First Email: Study Materials

The first email sent after the call was to thank me for my interest and provide an impossible amount of material to review. Oh, but don’t worry, this is probably stuff that you already deal with day to day. Right. When was the last time I not only used but implemented a priority queue backed by a min/max heap? Never. This is the same deal with Facebook, Microsoft, and Amazon interviews so I didn’t worry about it too much. It’s just a matter of prioritizing topics against time.

For System Design, this is a great example of prioritization based on time:

How To Prioritize?

If I don’t have much time, I’ll jump right into practice problems and do 50/50 problems and reviewing concepts. If I have some time, I’ll review all data structures and algorithms first then do as many practice problems as possible. With extra time, I will review all operating systems and system design concepts. I almost always skip discrete math and the whole NP-complete business. This time around I had extra time so when I wasn’t doing problems I was reading through system design books.

Key Point: If you feel you cannot achieve “excellence” or “proficiency” in at least the data structures and algorithms concepts, I recommend requesting a follow up in 3 – 6 months to allow for more study time. There’s no harm in failing but if you definitely want the job this time around then set yourself up to be as successful as possible.

The Materials: Copy Pasted From The Email


This is a non-exhaustive list of topics that may or may not be covered during your interviews. Its intent is to guide your study and preparation.



  • The interviews focus on coding, data structures, algorithms, computer science theory, and systems design (systems design questions normally reserved for applicants with 5+ years of industry experience)

  • Likely additional topics include: hash tables, heaps, binary trees, linked lists, depth-first search, recursion (think CS 101 – concepts that everyone knows but doesn’t always quickly come-to-mind).More information on Algorithms

  • Many questions are open-ended and are deliberately underspecified to see how you engage the problem. Verbalize your thought process as you work to understand, approach, and solve the problem. Interviewers want to see which areas you find most important to the problem’s solution. Think about ways to improve the solution you’ll present. In many cases, the first answer that springs to mind will need refining. Verbalize your initial thoughts to the question. Ask clarifying questions if you don’t understand the problem or need more information. As a rule: efficient solution > brute force solution

  • For in-depth study – 3 highly recommended reads from Sr. Engineers: (1) “Programming Interviews Exposed: Secrets to Landing Your Next Job” (2) “Programming Pearls” and (3) “Cormen/Leiserson/Rivest/Stein: Introduction to Algorithms”


  • Coding: construct / traverse data structures, implement system routines, distill large data sets to single values, transform one data set to another

  • Algorithm Design / Analysis: big-O analysis, sorting and hashing, handling obscenely large amounts of data. Also see topics listed under ‘Coding’

  • System Design: features sets, interfaces, class hierarchies, designing a system under certain constraints, simplicity and robustness, trade-offs

  • Open-Ended Discussion: biggest challenges faced, best/worst designs seen, performance analysis and optimization, testing, ideas for improving existing product


  • We believe in collaboration and sharing ideas. Most importantly, you’ll need more information from the interviewer to analyze & answer the question to its full extent

  • If you don’t understand something or are stuck, please question your interviewer and ask for clarification and/or a hint

  • When asked to provide a solution, first define and frame the problem as you see it

  • If you need to assume something, verbally check it’s a correct assumption

  • Describe how you want to tackle solving each part of the question

  • Always let your interviewer know what you are thinking as they are just as interested in your thought process as the final solution

  • Finally, listen – don’t miss a hint if your interviewer is trying to assist you

TECHNICAL DOMAINS (understanding these concepts is necessary to succeed in a Google Interview)

  • Algorithm Complexity: Understand big-O complexity analysis and Big-O notations (aka – “the run time characteristic of an algorithm.”) Working through practice problems is key

  • Sorting: Know how to sort. Don’t do bubble-sort. Know the details of at least one n*log(n) sorting algorithm, preferably two (say, quicksort and merge sort). Merge sort can be highly useful in situations where quicksort is impractical

  • Hashtables: The single most important data structure. Be able to implement one using only arrays in your favorite language with time limitations

  • Trees: Know about trees; basic tree construction, traversal and manipulation algorithms. Familiarize yourself with binary trees, n-ary trees, and trie-trees. Know at least one type of balanced binary tree, whether it’s a red/black tree, a splay tree or an AVL tree, and know how it’s implemented. Understand tree traversal algorithms: BFS and DFS, and know the difference between inorder, postorder and preorder

  • Graphs: There are 3 basic ways to represent a graph in memory (objects and pointers, matrix, and adjacency list); know each representation and its pros & cons. Know the basic graph traversal algorithms: breadth-first search & depth-first search. Know their computational complexity, their tradeoffs, and how to implement them in real code. Time permitting, study fancier algorithms such as Dijkstra and A*.

  • Other Data Structures: Know as many other data structures and algorithms as possible. Start with the famous classes of NP-complete problems, such as traveling salesman and the knapsack problem. Must recognize them when an interviewer asks you them in disguise. Find out what NP-complete means

  • Mathematics: Some interviewers ask basic discrete math questions. At Google we are surrounded by counting problems, probability problems, and other Discrete Math 101 situations. Know the essentials of combinatorics and probability. Be familiar with n-choose-k problems and their ilk – the more the better

  • Operating Systems: Concepts to know: (1) processes, threads and concurrency issues. (2) locks, mutexes, semaphores, and monitors (3) deadlock & livelock and how to avoid them (4) resources processes needs, and thread needs, and how context switching works, and how it’s initiated by the OS and underlying hardware (5) scheduling (6) multi-core: the fundamentals of “modern” concurrency constructs

Second Email: Time and Place

For scheduling, you are going to have to take a day off work (if you are currently working). You are asked to provide 3+ days in the next 4 weeks when you can interview. You will get an email confirming the time as one of those days you selected. I usually see 9 am or 10 am start times with 3 pm or 4 pm end times. The email includes instructions on parking, time to arrive, where to arrive, who to ask for, etc. This will vary based on which office you’ve selected for your interview location but read the whole email. The location I went to had a very strange parking situation so I needed to show up 30 min early. Finally, upon confirmation of the date, you need to file a formal application with Google using one of their tools.

Key Point: Read the whole interview confirmation email.

Interview Day

Key Point: Bring what makes you comfortable. As below, I like having physical pen and paper to take notes during the interviews.

As they say in the email, wear what you are comfortable with. Bring whatever you think you might need. I recommend bringing a notebook and a pen. I like to write down the names of my interviewers, which team they worked on, how long they’ve worked at Google, and notes on the questions they asked. I also bring chocolate and Tylenol because interviews are stressful.

Why write down that information? One or more of your interviewers might be a future teammate. Also, if you are not extended an offer, you can keep the questions to understand where your gaps are. Finally, if all your interviewers have been at the company 2 years or less, maybe that’s something you want to ask your recruiter about – what happens to employees after 2 years?

Things you might not expect:

  • Interview rooms can be really hot, like “I hope they don’t notice how much I’m sweating” hot or cold enough to feel like you’re directly in the path of the industrial air conditioner
  • You’re not going to be in the same room all day so make sure you don’t bring so much stuff that you’ll be uncomfortable carrying it around from room to room
  • You’ll be waiting for up to 30 mins from the scheduled “start time” of your interview – bring something to read or do
  • You will be given the opportunity to code on a computer or whiteboard. You can choose what you’re most comfortable with at each interview.

Impressions and Amenities

DISCLAIMER: I have pre-existing negative feelings about large tech companies. Have your salt at the ready.

The good things about Google corporate offices are fairly well known: free food, gyms, nap nooks, laundry, commuting cars/buses, etc. I found all my interviewers easy to talk to. In past Google interview, there were a few “hard to deal with” interviewers and I was happy not repeating that experience. The amenities were clearly well kept and organized.

The negatives are similar to other large tech companies (Amazon, Facebook, and sometimes Microsoft). All these things are what I heard from my interviewers:

  • There are too many people in the offices so you need to come in earlier and earlier to find parking
  • You have to avoid the cafeterias during lunch time because of how crowded they are
  • Organizations are constantly being moved under new leaders and moved to new buildings, sometimes in other cities
  • The offices are being shifted around to support the high populations so often that you always get lost

A few additional things stood out. First, there was a nap nook. Nap nooks are meant as small rooms or enclosures where you could take a nap during work. I’m used to seeing them as very small rooms about the size of a walk-in closet with a light, maybe a recliner or a cot, and enough room for prayer mats. This is similar to what I encountered:

via-we-heart-it_rect540 alcove bed
Credit to

Kudos for making the decor look, ah, “homey” but this makes me just a little bit uncomfortable. Can you imagine sitting next to your manager on that couch for a quick chat? Ew.

The second thing that stood out was how one interviewer described the difference between this location and Mountain View.

People here are a lot more interested in work-life balance and family rather than getting work done quickly.

I see. I guess it’s good that I’m not applying to work in Mountain View. Or maybe I want to burn out like a supernova: a high energy, crazy-bright star, with a short life on its way to complete destruction. But a rich supernova.

Coding Questions

As a friendly reminder, our interview questions are confidential, so please keep things under wraps.


I won’t tell you the questions but I will share the areas you would need to study to answer them.

Question 1: Card Game

  • Object-oriented design
  • Multi-dimensional arrays
  • Randomness
  • Multi-threaded access to shared objects (I used the word “semaphore” at some point)

Question 2: Merge K Lists

  • Greedy algorithms
  • The merge k lists problem – this wasn’t the question but I really kicked myself for skipping it during my practice after this interview

Question 3: Empire Building Board Game

  • Binary trees
  • Graph search
  • Linked Lists vs. Arrays

Question 4: I Heard You Like Trees

Question 5: Design a Cache

  • This was actually the question

The Result

As of writing this post, I do not have the result of the interview and I suspect I won’t for another few weeks. Google is infamous for long deliberation on candidates. I’ll update this post with the result when it makes it to me.

Very delayed update almost 6 months later…

As expected, I didn’t get the job. Why? When given a technical interview question, it is expected that you have the correct answer right away. Out of a pool of hundreds of questions, this is really a matter of luck. However, I was told I had excellent communication skills. Too bad Google doesn’t like good communicators.

While this may seem like a bad outcome, I came out with stronger interview skills, further conviction that I don’t want to work at Google, and a boost in my confidence as a communicator. It also helps that a Googler I met after the interview described the team in interviewed for as “a massive dumpster fire” and handed in his resignation shortly after.

System Design Interviews

As I network through tech I frequently hear newcomers ask how to answer system design questions. I’ll try to clear that up in this post.

Why am I being asked to design a parking lot?

If you’re comfortable writing code and work on multi-component projects, then you might be familiar with maximizing reuse without high coupling. In an interview, they will test this with an object oriented design questions. In a service-oriented world, we are now being asked to do this with systems.

These concepts are inconsistently taught across all programs. Unlike a for loop, interviewers can’t always expect a candidate to be familiar with systems and services. Unfortunately, the interviewers are given a checklist and if it contains system design, they ask it. More bad news: the recruiters aren’t told what’s on the list. As a result, you and your interviewer have different ideas about what’s going to be asked.

How To Learn This

Question and Answer Format


Questions will be phrased as: “design a system to XYZ”, “design a pre-existing software system”, “draw the architecture for XYZ”. Examples:

  • Existing software: Uber, Lyft, Facebook Messenger, Amazon retail website, Google Search, DNS, Expedia, Docker, GitHub, WordPress, any website you can think of.
  • Interview problems: Parking garage, generic search engine, inventory management system, hotel guest management system, log aggregation

Anything can come up here depending on how prepared or creative the interviewer is.

Boxes and Lines

The answer is going to be boxes and lines.


Approaching the Question

Clarifying Questions and Requirements

If you’ve done any preparation or any interviews, you will know you need to ask clarifying questions and get the requirements. Treat your unimplemented solution as a black box and try to describe the inputs and the outputs. Take Twitter for example:

  • Are tweets text only?
  • How will customers get data out of the system? Browser, phone, REST API?
  • Can a customer send one tweet at a time or many?
  • Do users have accounts or is this anonymous?
  • Is user following enabled?
  • Are there multiple feeds or one giant aggregated feed of tweets?

You might be thinking “Do you even know how Twitter works?” If you are, good. You need to make sure you and the interviewer are on the same page. You can’t come up with a design that has every current Twitter feature so make sure to scope it down to a few specific features. Saying “I’m going to implement user accounts, tweeting text only, and retrieving messages without the follower system as my first round” is extremely helpful. The interviewer will know that you are aware that there are more features and are choosing to defer than rather than forgetting them. This also makes the problem easier. If you don’t specify which aspects you are implementing, you and your interviewer will have different ideas about a good answer.

Note: These interviews are 45 to 60 min. It’s better to start small and then discuss enlarging the scope with the interviewer than the other way around.

Always identify the data.

The data tells you a lot about the design. What data is being sent? What data is being stored? Does the data need to be sorted? How quickly does the data need to be available? This provides another way to get requirements. Example:

  • How will data be searched? Maybe we start with hashtag search only.
  • Can anyone see all tweets or are some tweets restricted viewing? We can start with all public.
  • When we search for tweets, do we return all of them that match or only the top 100 most recent? Let’s do all of them at first for simplicity.

The Boxes

What are the boxes? Don’t be thrifty on the boxes. Boxes are more easily grouped than separated. You can do a “discovery” style and follow a single piece of data through the system.

For example, a customer hits the “Tweet” button from their browser. This goes to some server, the TweetManager. The tweet needs to be stored and show up in the user’s page and the global feed (as per requirements of no custom feeds). The tweet also needs to be searched later by hashtags (as per requirement of hashtag search only). This tells us we need a place to store the whole tweet, TweetStore. We might also need to store user information that can reference their tweets, UserStore and maybe UserManager. Somewhere else, we need to support hashtag searches, SearchTagManager and/or HashTagStore. Finally, we can throw in notifications for fun and have  NotificationManager. Here’s what that looks like:


  1. The user tweets and the tweet is sent to the TweetManager (here we assume that the user is logged in and is who their cookies or headers say they are).
  2. The TweetManager stores the Tweet in the TweetStore. At this point it is linked to the user that posted it.
  3. The TweetManager sends the hashtags in the tweet along with a reference to the tweet in the TweetStore.
  4. The HashtagManager adds the tweet reference to the list of all tweets related to that hashtag in the hashtag store (this creates a link to the tweet store).
  5. The TweetManager sends a completed message to the notifier which then shows everyone logged in that a new tweet has been posted.

We also have Login and ‘A’ which is searching by hashtag.

Note: This is a simplified example. I would strongly discourage using this answer in an interview because it doesn’t scale, has high latency, and will likely result in data inconsistency.

Hey, Where Are My Tables?

You may be tempted to say one of your boxes will be a SQL database and start describing your schema in detail. Don’t. Don’t do this unless the interviewer asks you to go into details. If you focus on details, you won’t have time to answer the whole question. However, having them at the ready doesn’t hurt in follow up questions.


It turns out I have 3 storage boxes and 3 service boxes. Do they all need to be separate or can some be together? There are many driving factors for doing this:

  • Minimize coupling: you should minimize lines between two boxes for a single “trip” through the system
  • Follow the K.I.S.S. rule: you should not have to fan out to turn one tweet into 5 calls to other boxes
  • Asynchronous vs. Synchronous: know which lines need to be blocking and which can be done asynchronously. In some systems, the different types of calls go to different boxes (not always).

A simple grouping might be all the logic in one box and all the data in another:



Scalability is challenging. In these questions, you can either predict how to scale the system or you can do this exercise repeatedly:

  1. A significant political event is happening. A few key individuals are sending out tweets through the event. Everyone on the planet is trying to search for tweets with the event hashtag at the same time.
  2. Identify what will break first and how it will break. If it breaks, does it break only the overloaded part of the system or other parts too? In this case, the hashtag manager can actually be scaled to tolerate the number of requests. However, the data store (no matter what store you use) will be in trouble.
  3. Discuss or draw a way to solve this. The most common answers to this are asynchronous communication with queuesreplicas, and some form of sharding.

Often you need to do one or two examples to show you understand what scaling is and how to alter a system to support more traffic.

New Features

You’re feeling great because you drew boxes and lines. You came up with your own scaling answers before the interviewer asked. Then the interviewer throws a giant wrench into your answer: I want you to implement followers, identity verification, and malicious account detection.

If you only have 5 minutes left, feel free to verbally explain while waving your hands at your diagram. Throw a quick machine learning trained fraud box and a service that requests identity verification through a third party vendor. Usually when these features are requested near the end of the interview it isn’t about implementing them but about discussing how you can grow your solution. If you can’t discuss the solution, it might look like you copied it from a book.

Follow Up Questions

  • Why is this data here and who can access it?
  • How long does it take to complete one customer request?
  • Why are these two components separate or together?
  • Can you make this more generic or into a platform? How would you covert this into a Software as a Service product?

I Did All The Right Things And All I Got Was This T-Shirt

I’ve had too many interviews where the interviewer was stubborn, critical, condescending, dismissive, and basically an asshole. It’s almost impossible to succeed in these cases unless you fit their mold perfectly and even then it’s not a guarantee. Here are some signs that it might not be your answer that’s at fault:

  • Your interviewer is flipping between high level criteria and specific technologies (i.e. we need a customer service but please use AWS lambda)
  • Your interviewer is telling you where to draw your lines without explaining why
  • Your interviewer is repeatedly cutting you off when you try to ask clarifying questions and replies with “just implement it the way it is”
  • Your interviewer says “uhhh” a lot and doesn’t seem to know where he or she is going with the question
  • Your interviewer changes the question halfway through: did I say architecture? I meant library
  • You were incorrectly leveled by your recruiter (surprise!) and you feel deeply in over your head.


All companies put their applicants into buckets that are highly variable but sort of follow this structure:

  • 0 to 2 years of experience: entry level
  • 2 to 5 years of experience: mid level
  • 5+ years of experience: senior level
  • 12+ years of experience: principle or CTO level

Highly variable by company, geographic area, job role, and how the recruiter feels that day.

I think it’s unreasonable to ask an entry level applicant a design question because they may or may not have encountered them. If an applicant is on a border of experience levels, they may ask this question to see which bucket they fit in. Finally, as above, recruiters and interviewers don’t talk.

In Conclusion

Just don’t draw a single box with a SQL database schema as your answer. Good luck!


Defensive Interviewing

If you’ve interviewed anywhere in tech, you’ll hear the advice or instructions to have questions ready for your interviewers. Which questions do you ask though?

Hopes and Fears

Everything boils down to what you want to happen and what you don’t want to happen.


  • Belonging
  • Achievement
  • Trust
  • Growth
  • Variety
  • Money – this one is salary negotiation so I’ll skip it


  • Exploitation
  • Rejection and isolation
  • Boredom
  • Stress

Now that we’ve got the heavy stuff out of the way, how does that translate into interview questions?

Belonging / Rejection and Isolation

A sense of belonging contributes to happiness. A sense of happiness contributes to productivity. Thus, you will be more successful if you feel like you belong. Even when your job is really bad, if you feel like “you’re all in it together”, it’s easier to pull through.


  • What is the diversity of your team?
  • Are there people like me on the team?
  • Who will be my mentor when I join?
  • What are some social activities we will do as a team?
  • What communities for technical and non-technical topics exist at the company?
  • Do you feel like you could be friends with some of the people you work with if they weren’t your coworkers?
  • How often will I have 1 on 1s with my manager?

Scenario one: a diverse group of people who welcome new members with an automatic support network of a mentor and bond through shared interests. Scenario two: a monochromatic team of humorless people you can’t identify with that leave you to struggle alone and generally don’t talk to each other. Take your pick.

Achievement, Growth, and Variety / Boredom

Boredom is bad. Boredom is similar to stress. You disassociate and (eventually) become depressed or destructive. Work that slightly exceeds your skill set is ideal for maximum engagement and learning (according to Emotional Intelligence by Daniel Goleman). You can keep things interesting through promotions, new skills, or role changes. Additionally, if you want to climb the ladder, make sure there are at least a few rungs.


  • What does promotion look like here?
  • How long does someone like me stay in this role before being considered for promotion?
  • Do you support 20% time or time to grow professionally via hackathons, conferences, or tech talks?
  • Does this company encourage moving between teams if there are other opportunities available?
  • Does this company support role changes and what does a successful role change look like?

Trust / Exploitation

People typically know when something they are going to say will put people off. The managers and recruiters of the world know this and choose to omit or mislead when it comes to that information. Instead of trying to catch them in a lie, probe to fill out the truthiness of their answers. This was taught to me as “peeling the onion”. In this metaphor, the more you peel the onion, you might get more onion or, I don’t know, a radish.


  • What tasks are you working on right now? Ask for specifics.
  • What would you say is the key success criteria for your job? Why?
  • What is an example of the first project (not task) I will be working on? How is this important to our customer?
  • How involved will I be in designing new features and choosing team priorities? How often will I get a chance to influence project direction?
  • How many people with my role are on the team? (the more there are, the more reliable their answers)
  • If I am interested in working on something in particular, how would I go about getting assigned to the project? Give me an example of when you did this.
  • When something goes wrong, what is the recovery? Maybe a bug is pushed or a customer says the feature was done wrongly or a service goes down. Is there a retrospective? Does it get fixed right away?
  • Who is responsible for operations, customer contact, and project planning?

This is probably the hardest one to detect. Often, teams want to hire someone to do the housekeeping, like bug fixes, legacy maintenance, mindless migration, and minor management activities. You need to ask questions to confirm there is enough “meaty” work for you and housekeeping is spread evenly or kept to a minimum.

General Red Flags

  • Your manager has been in the company or sub-org for less than 6 months. This usually means they haven’t been through a performance cycle and there is a risk that they aren’t sure what it looks like for you to do a good job. If you don’t know how to do a good job, you might not be rewarded for the work you do. However, after about a year to a year and a half, most managers figure it out.
  • You are being hired for a “generic” position. This is basically job roulette. It’s worked out well for me in the past but it’s also opportunity for you to be placed where no one else wants to be.
  • There are a lot of buzzwords. If something sounds good but doesn’t tell you anything specific, they might be trying to hide something. “We do machine learning” is the equivalent of saying “we develop software”. It generates excitement but doesn’t tell you that you’ll actually be a code monkey for the scientists who do the “real” machine learning.
  • “We have no operations.” This is very job dependent. I’m talking about services, cloud, and larger software applications. If you have no ops, you have no usage or no customers. On the other side, you might have a lot of ops but someone else deals with it. This is an organizational anti-pattern and guarantees someone will strongly dislike you on that ops team. Not fun.
  • “We are a rapidly growing team.” This can genuinely be exciting if you are joining a team of smart and capable people coming together to create a new great thing. Or this could mean the managers are throwing bodies at a problem in such a way that creates stress, confusion, and general unhappiness.

It’s Too Late

If you’ve found yourself in a job where it didn’t live up to your expectation, first, figure out which questions to ask next time you interview. Second, tell someone it wasn’t what you expected and firmly ask to be placed somewhere that meets those expectations. Third, as soon as you can, decide whether you want to stay or go. Be intentional about what job you are choosing to do. By taking responsibility, you give yourself control over your situation and who doesn’t like control?

Good luck interviewing!

Dot Your I’s, Cross Your T’s, And Get Paid

An independent professional in my network recommended I watch a talk by Mike Monteiro called “F*ck You, Pay Me” when I asked for advice on contracts and client relations. Whether you’re freelancing, consulting, part-time, or full-time, the advice given applies to any contract you sign related to your professional skills. Below is a summary of the video and I’ll also cover how this can apply to a full-time position.

Read More »

Course Review: Docker for Java Developers

This post will go over a course (company owned by LinkedIn and by extension Microsoft) to learn about Docker for Java Developers. Course



Usefulness And Overview

Currently, the course topic is relevant. The paradigm of “containerization” or releasing your software as self-contained collections of related packages and dependencies called “containers” is catching on quickly across services in the industry. Even though this says it’s for Java developers, it’s not really Java specific. All the concepts and commands used are language independent to a certain extent. The part that the course missed out on was Kubernetes, a fast growing solution from Google related to container management.

Is this particular course a good use of your time to learn about Docker? Maybe. A lot of the content was easily found in documentation or by searching online. If you like information presented in sequence with context, yes, this is a good choice. Otherwise, it may be tedious or too shallow in topic coverage.

The course follows a mini-lecture with demo format. You can copy the course materials and follow along with the demo. The course starts off assuming you don’t have Docker set up. The content begins with installation and follows a simple web app through containerization, deployment, release and scaling. It further goes through monitoring options and maintenance commands.

Course Details

  • The instructor introduces Docker by showing you the download websites and how to install on various operating systems.
  • He introduces the course material by showing how to use git to clone the course materials and use them.
  • The first use of Docker is to create a container with the sample application and use the start and stop commands along with options. List running containers as well.
  • Next, the website is deployed using the container and various health checks are shown. An important not here was how container health is different than application health.
  • The lecture shows how to automate the use of containers in a build and release flow.
  • Container sharing, tagging, and maintenance in a container store are shown along with best practices for tagging.
  • Next was a more complex application with multiple services with a container that needed to be started up in a particular order (application and database).
  • He went over the use of container contexts to allow running multiple instances of a container on the same host.
  • This then moved into more advanced use of containers including swarm mode with rolling updates, certificate rotation, auto-scaling, and fail over.
  • He went over container maintenance and use of the master node to manage other nodes in the cluster including the use of drain and pause commands.
  • Another advanced topic covered was storage nodes and how to use container independent storage or distributed storage solutions with containers.
  • As the last topic, he went over tools and other plugins for monitoring including the stats CLI tool, Prometheus and C Advisor.
  • He did not go over Kubernetes but recommended it as a future topic.

What Doesn’t Kill You Slowly Grinds Away Your Sanity: Psychological Burnout

Often you will hear people say that someone is “burnt out” or “I was really burnt out on [project/team/company].” Casually, this means you are exhausted or temporarily stressed on a team. This often is thought of as a passing condition. Unfortunately, there is a more formal type of burnout called “psychological burnout” or “occupational burnout.” Here I’ll talk about what this is, how it can ruin your life, and how to fix it.

Top: this is your brain. Bottom: this is your brain crushed by burnout.

What Is It?

Burnout is a pathologic syndrome in which prolonged occupational stress leads to emotional and physical depletion and ultimately to the development of maladaptive behaviors (e.g., cynicism, depersonalization, hostility, detachment).

This is a fairly formal definition and doesn’t include a few key points:

  • This type of burnout can last years
  • You may develop long lasting mental health problems such as depression, alcoholism, and eating disorders
  • It can take months or years to recover
  • By the time you notice your “maladaptive behaviors”, it’s already happened to you

You May Have Psychological Burnout If…

We are all different and the signs of this type of condition are different per person too. On top of that, we have such poor mental health support (in North America) that we don’t recognize these problems as repeated exposure to stressful situations. Remember, these “symptoms” are a stress reaction, not a personality trait.

What To Look For:

  • No matter how hard you try to stay optimistic, you can’t see anything going well and you constantly fall into cynicism and criticism at work or elsewhere.
  • You take a lot of breaks at work to get away from work with activities like eating, drinking, or over-exercising.
  • Your week follows a pattern like this: work Monday to Friday, sleep Saturday to Sunday.
  • You become more resentful of people asking you do to things even if they are simple.
  • You start blaming yourself for not working hard enough, not being tough enough, or not being smart enough to overcome the challenges you have at work.
  • You enter a protective combat mode: you are argumentative and defensive about any changes or comments related to your work. When you look back on what caused it, these are usually no attacks on you but you can’t stop yourself from reacting that way.
  • You feel isolated. This can be emotional isolation: no one is there to help you, you need to fix this all on your own, your coworkers or boss don’t have your back. Or physical isolation: you start working from home more, you don’t want to participate in any team activities, you stop responding to emails or chats messages.
  • And much, much more…

The worst part is the slow creep: you won’t notice a big, sudden change. Instead, you’ll find yourself here without knowing how and you’re not sure how to get out.


When we talk about burn out in the casual sense, it’s usually caused by a tight deadline, late nights, or the frenzied kind of work we associate with “crunch time”. Interestingly, this isn’t the same as what causes psychological burnout.

This is how I sum up the cause of psychological burnout:

You put effort into something and you got no result (or not the one you expected).

Here are some examples of how that shows up:

  • You are asked to write a design or build a feature and just as you are halfway through, it’s cancelled
  • You put up a code review and no one reviews it for days or weeks
  • You prepare a proposal for a new feature, project, initiative, anything and it’s brushed aside by your manager or team
  • You write a masterpiece of an email reporting some fabulous result or finding and no one responds
  • You ask questions or make comments in team meetings and they are ignored

Some other causes you’ll see listed on medical websites call out other things like dysfunctional teams, lack of control, or boredom. To me, these fall into work that’s not getting the result you expect. If you are trying to talk to your team and they don’t respond, that’s effort wasted. If you find out your project was cut because you have no say in your team road map, more effort wasted. I find that any action by the team or company that sends the message of “you did all this work and we don’t care” is hugely damaging. It makes sense that people withdraw, start thinking nothing they do matters, and, of course, “develop maladaptive coping behaviors.”

When It’s Too Late

Too late to me means you’ve gone so far into your emotional hell that you start to see your relationships, productivity, and physical health suffer. “Too late” doesn’t mean you can’t get better, it just means that you will need to make a significant change in your lifestyle to recover from your new and horrible condition. Here are a few examples of what too late looks like:

  • You a few beers after work to get rid of the unhappiness built up during the day
  • You can’t remember the last time you slept well and find yourself self medicating with pot, alcohol, sleep medication or other substances to get to sleep at night
  • You’re are late to work because you can’t get yourself out of bed anymore
  • Your coworkers and managers tell you you’re angry and critical
  • Your friends are telling you to quit or they’re not talking with you as much because they’re tired of your work rants
  • You’ve been to visit your doctor to either get anti-depressants or increase doses
  • You have other minor physical problems building up: regular indigestion, random aches and pains, sprains, headaches, frequent colds or flues

These signs differ for each person. Some choose to drink while others over-exercise. Some will get angry and others consider self-harm. Either way, substance abuse, uncontrolled emotion, mood altering prescriptions, and a decline in personal relationships mean this is now taking over your life and something needs to change.

How To Recover

How did this happen? It’s complicated. A lot of different pieces came together at the same time to create this situation. To solve it, it’s also going to take a lot of different pieces coming together to work to get you better. Here are a few of the bigger things you can do to find your path to recovery:

  • Go to therapist or counselor: this person will help you identify the situations leading to burnout and track your improvement or lack thereof over time
  • See a doctor for mental health evaluation: you may have stress induced depression, anxiety, ulcers, or insomnia that needs medications and management with a physician
  • Take a break: take time off for as long as you can. By taking time off, you will see how unhealthy your life has become and seek better opportunities.
  • Change jobs: consider changing teams, managers, or companies depending on what you learn from introspection and counseling
  • Change careers: many people choose to change careers to escape the damage of burnout. Going back to school, choosing to invest in family, or becoming a travel blogger are common escape routes.

Make sure you do something. If you choose inaction, you’re damaging yourself physically, mentally, and potentially financially (medical bills, being fired).

Finally, find things that counteract the cause of burnout:

Do things that turn your efforts into rewards.

It’s Not That Bad Yet

If you’re reading through these signs and think “I’m putting effort and not seeing results but I’m just frustrated, not a depressed alcoholic” then you’re in luck! You can avoid the worst by getting away from your situation early. When you start to see people ignoring, cancelling, brushing off, or otherwise not returning anything on your effort, evaluate whether or not it’s worth staying where you are. It’s not just about wasting your time, it’s about damaging your motivation and joy in working. You can use mindfulness to identify what is going well and what isn’t to get yourself moving in a better direction.

Event Review: GeekWire Cloud Tech Summit 2018

Screen Shot 2018-06-27 at 9.10.06 AM.png

Event Info

Event Location: Maydenbauer Center, Bellevue, WA

Event Cost: $350 (early bird + group) to $500 (late bird solo) USD. PyLadies and Stripe were generous enough to sponsor my attendance.

Approximate number of attendees: 300 – 500

Event Duration: 9 hours (8am to 5pm) + after party

Slides and videos


  • Talks were short and manageable in length (30 min each) so I could move around
  • All topics were relevant and understandable
  • I learned about cloud-edge computing and more about Kubernetes
  • This was my favorite swag: Tech Tarot Cards
  • Great dedication to diversity by giving out gender pronoun pins, providing diversity activities and events
  • Excellent venue: lots of space, tables, electric outlets, and Wi-Fi


  • Nothing. I fully enjoyed this event.

Would I go again?

Definitely. I recommend this to anyone wanting to get breadth on current cloud topics in the Seattle area.


Caution: This is a long one.

Fireside Chat with Mark Russinovich, CTO Microsoft Azure

  • New Azure features announced recently: Azure IoT Edge, Data Lake integration, New China regions
  • Azure IoT edge: a lot of computing will move out to the “edge” to optimize for bandwidth consumption and responsiveness of computed results.
  • Github: Microsoft will not change what’s already there and fully invests in and supports the open source community
  • How are people using blockchain in non cryptocurrency applications? Non-centralized security where multiple parties can see and verify a set of actions in a distributed networks.
  • What is Quantum? It is a type of computer that can solve intractable problems in computer science that cannot be solved by a traditional computer.
  • Is Microsoft planning to invest in quantum computing? Yes, Microsoft is getting ready for it along with an SDK and Q#, a language for quantum computing.
  • Where do you think the best space to invest in technologically is? AI and ML – we’re at a breakthrough point where it’s still unknown how much we can do with it.
  • Live poll: People are very unsure about what to think of Microsoft acquiring GitHub.

Did I like the talk?

No. This seemed like a giant advertisement for Microsoft and I could have done without. The comments on block-chain and quantum compute were interesting but very much sidelines.

3 Back-to-the-Future Trends in AI Systems – Carlos Guestrin, Apple and Amazon Professor Of Machine Learning at University of Washington

  • We are in a period of resurgence in AI. Previously we saw a dip in its popularity.
  • In the 80s, AI was primarily rule based systems that were not as useful or correct.
  • Now, we are using machine learned models we are able to go into applications where we cannot enumerate all rules in spaces where there are a lot of possibilities. For example, we previously could beat humans in chess and now we are able to move to use Go without needing to describe the full space of the game.
  • Spark uses large amounts of data with low compute per datum and massively scales out. We are moving towards Deep Learning where we have huge amounts of data (where huge > large) and there is high compute per datum that requires compute grids and node scalability.
  • We moved from specialized hardware to specialized with Spark. Now with deep learning we need to move to more specialized hardware once again.
  • AutoTVM: How do you make sure you choose the right coding patterns to optimize for your hardware when training models using a tensor language over different hardware? This project is meant to learn the right parameters to maximize use of hardware and optimize efficiency.
  • We are trying to move to simpler adoption of machine learning. Currently you need a lot of expertise in order to understand data, use the tools, and manage the hardware needed for training.
  • Two trends: pre-trained models where generic data is sufficient and the need for developers to create models for their specific scenario.
  • Turi Create: allow developers to create their own domain specific data to easily train models via transfer learning from existing generic model training.
  • Another trend is moving towards making the internal workings of machine learning and AI available to everyone instead of being a black box.
  • Providing transparency into how a result was reached helps understand what features of the input are affecting the output as well as understanding where error might be coming from.
  • The data you choose to use with define the user experience.
  • Example: initially when film was being developed, they created chemical exposure guides that optimized for only light skinned models. As a result, dark skin colored people in photos were not visible due to over exposure. We need to think about the culture and values the data we select to train on shows.

Did I like this talk?

Yes, I enjoyed the examples provided and the organization of the talk. I may have already know the content but it was phrased in a organized and easily understood way.

Rook: Portable Storage on Kubernetes – Bassam Tabbara, Founder and CEO of Upbound, Inc.

  • Kubernetes can be thought of as the cluster operating system or the container orchestrator. It also does life-cycle management, scaling, load balancing, scheduling, etc.
  • It exposes a portable cloud API and thus supports the “write once, run everywhere”. You can for the most part containerize and deploy using Kubernetes and run in AWS, Azure, or other places fairly easily.
  • When we start to manage storage beyond the lifecycle of a container (or other unit), we have to look outside of Kubernetes. Similarly, different forms of storage also need to be managed: blocks, volumes, queues, key-value stores, time-series, etc.
  • Kubernetes allows portable volume extraction that is independent of pods. This is currently the only stateful workload abstraction.
  • You need to interact with storage services that exist outside of your Kubernetes managed cluster for the most part.
  • Rook is a cloud native storage orchestrator. It is an extension to Kubernetes hosted by the Cloud Native Foundation.
  • It helps storage systems run like a service on top of a Kubernetes cluster by encapsulating storage system management logic.
  • Can create a configuration that specifies size, monitors, and scaling that will create all components within the cluster that is needed using the operator pattern via Kubernetes operators.
  • Rook operator defines a desired state and loops through state activating different components until the desired state is achieved and continues to do so to maintain desired state.
  • This is an open source project looking for contributors!

Did I like the talk?

No. I understood what the problem and solution were but somehow I felt like I was missing something when he was explaining the examples. Most of them were “here is the configuration and then it just happens”.

Serverless and Kubernetes: The best of both worlds by Aparna Sinha, Google

  • They key to a serverless platform is such that not many people are needed to maintain the servers and more time can be spent on developing the application.
  • A lot of time in application development is spent on understanding monitoring, logging, orchestration, etc. that the application developer needs to spend time on.
  • What is serverless at Google? Zero ops, auto-scaling, managed security; event-driven programming model, horizontally scaling with microservices; pay for usage.
  • Serverless can be applied to more than compute including data storage and other components.
  • Two main ideas: decouple applications and automate infrastructure
  • This translates to: containerize the application + automate deployment + build in metering
  • Kubernetes is container infrastructure as a service:
    • It contains load balancing, networking, DNS and server discovery
    • Environment agnostic management
    • Has flexible, composable primitives that can be built together to craft your application. Ex. application + storage + deployments
  • Kubernetes is a platform for automating management
    • Can provide a desired number of replicas and Kubernetes will make this happen
    • Provides auto-scaling based on system state like queue length or traffic rate
  • Kubernetes is a declarative extensible API
    • You can define different components or controllers you want to use in your own application
    • Example: you could create a custom Spark controller that will allow you to treat Kubernetes as a Spark orchestrator
  • Demo: the demo goes through creating an extension deploy a function via Kubernetes in such a way that makes the extension appear as part of the Kubernetes API. Using that function, write a function and deploy it via Kubernetes.

Did I like the talk?

Yes. I finally know what Kubernetes does (you’d think I would have looked it up by now). However, having worked with these types of orchestrators before it wasn’t too hard to figure out.

From Infra Ops to Platform Development: T-Mobile‘s Approach to Cloud – Nicholas Criss, Sr. Manager, Cloud Center of Excellence, T-Mobile

  • Background: T-Mobile aims to be a market disrupting mobile carrier that strongly favors magenta the color
  • Moving from waterfall development to agile development
  • In 6 months moved up from last to first in JD Power survey
  • Moved to the cloud and didn’t just follow “lift and shift” but tried to adopt the new philosophy of cloud development to make sure they didn’t fall behind competition
  • Having already moved to the cloud, the company was seeing that they were able to adjust very quickly to sudden demands from business needs. Example: They were able to spin up tons of video processing servers very quickly and scale down as needed. Without being on the cloud it wouldn’t have been possible.
  • Migrated through different stages:
    • Before cloud: no cloud integration
    • AWS console management: Manual management of cloud infrastructure
    • Some automation of cloud infrastructure
    • Managing infrastructure as code: all infrastructure was automated in code
    • Software Developers: The software developers can easily (with minimal error) leverage fully automated infrastructure and eliminate the need for infrastructure teams
    • Platforms: We got tired of having to relearn through repeating the same mistakes on different teams – make all these learnings a part of the platform. For example: scaling, fault tolerance, and general operational readiness.
  • We moved from “we’re mostly security, compliance, and operations” to “we are software developers”
  • Build our compliance and operations into code rather than Sharepoint docs that no one will ever read
  • If you can’t implement something as code, it won’t happen or will happen incorrectly
  • No more projects, only products – focus on building customer focused value instead of meeting deadlines and completing tasks
  • Moved from being a telecom company that sometimes has interesting technology to a software company that happens to build telecommunications software
  • Platforms that T-Mobile built internally to make software development better: Security management, policy enforcement platform, enhanced Hashicorp Vault service that optimizes for T-Mobile integration, enhanced container management platform, deployment platform
  • Building out platforms to take away the painful parts of developing makes people more excited to develop and come to work
  • They see these growth points as ways to interact with and give back to the community by open sourcing their projects
  • Question: How did T-Mobile make this happen instead of just talk and no management support?
    • From top level, management is supporting training and education
    • From the bottom, there is the ability to innovate and remove pain by moving to a continuous improvement culture. There is a push to adopt new things to make old pain go away.
    • There are still some holdovers of the old model with devops teams continuing to do deployments but there is progress and benefits being seen.
  • Question: How do you get started by targeting small things to start building interest?
    • Break off small pieces and build up the great infrastructure
    • However, speaker encourages moving directly to going fully to containers and platform and don’t waste time through the in betweens
  • Question: How do you migrate people to your platforms without the additional cost of making it work?
    • We don’t force people to use a particular solution but instead we encourage them to use our solutions where they make sense
    • It’s a continuous journey to make this work

Did I like the talk?

Yes. It was a rough start with some of the disjointed examples but it improved a lot by highlighting the journey steps and the growth that happened each time.

Diversity and Inclusion Panel Sponsored by Stripe

  • Panel:
    • Uma from Stripe Infrastructure Team manager
    • Amy is a system software engineer at a local startup
    • Dana is a manager at Google
  • Q: How did you choose your field?
    • Uma: I was one of the “accidental tech people”. In India, my grades were not high enough for medicine and the only other option was engineering. Software was chosen because it was less intense than the hard engineering. I found that I enjoyed it and continued.
    • Amy: Tried to do pre-med and didn’t like it. Through a chat roulette interaction via Omegle, decided to try computer science!
    • Dana: Father introduced her to computers and started playing with programming and got into that way.
  • Q: What’s a problem in your field that you are excited about?
    • Uma: Since we are growing to be global we are solving a lot of problems of scale and growth.
    • Amy: Working on Kubernetes, we want to enable larger companies to be able to migrate easily to new technology.
    • Dana: We focus on talking about how many 9s we want to support. We need to push harder to have better quality because with millions of users, even 0.01% is a lot of people.
  • Q: Amy, what are some ways you can demonstrate leadership without being in a formal leadership role?
    • Amy: I am not a manager and I don’t want to be one. I still want the ability to influence others. I achieve that through deep understanding and making my knowledge available through youtube or automating and sharing.
  • Q: Dana, as you started moving into your tech lead role, what kinds of pros and cons were you thinking about? What advice was helpful?
    • Dana: Tech lead can mean a lot of things and in silicon valley it can mean a tech manager. What I considered before moving into this position was to talk to other women in a tech lead manager position at Google. I recommend you make sure to talk to other women in these positions before making this move. What I got was: the hybrid tech manager role is a challenging one at Google. You won’t be able to do everything you want to do and you need to learn to let go of some things. However, you get a broad impact. You need to be comfortable not coding and still having an impact.
  • Uma: You moved from being an engineer to manager and then from manager of engineers to manager of managers. What motivated you to do this switch?
    • Uma: First, I didn’t plan to be a manager and was offered the opportunity to try being a manager after coming back from maternity leave. My manager supported me trying it out and would keep the IC option open if it didn’t work. I found that I really liked it and wanted to keep mentoring and growing other developers. Moving to the manager of managers position was due to seeking a new challenge with a level of abstraction. However, people don’t tell you how lonely it is being a manager since you lose the casual chat of other ICs.
  • Q: When you were earlier on in your career was there support that you wished you had and how would you recommend people find it?
    • Uma: Women need to ask more for access to things. Try to share what you learn with others to help them be aware of what it out there.
    • Amy: The money that people are willing to offer you is a measure of how much they value you. Having a diverse group of people you can talk to to understand the potential range of values and opportunities that could exist. Try to find mentors or sponsors in different demographics and in different pay levels.
    • Dana: I was lucky enough to get interesting products until I moved to Google. You need to find the thing you want to work on and make a difference on your own. Look for opportunities to do something you haven’t done before.
  • Q: When it comes to negotiating, what advice do you have to figure out what to ask for?
    • Dana: I was underpaid at my last job. Checked Glassdoor at a point where I was ready to potentially leave and asked them to pay me competitively or I would go. And they paid me more. Use recruiters as an opportunity to reassess you value and gain leverage.
    • Uma: Continually research and update your data on what you should be paid. Don’t base your targets on your emotional response to the money. A lot of things are negotiable like working from home and you can negotiate for what is important for you.
    • Amy: Always be on the job market to keep collecting data on what you are valued at. Make sure to try to get a pay band so that you are aware of how much you can negotiate for and where the lower end of tradeoffs might be. If you can, be on social media and get yourself out there.
  • Q: Do you notice any behaviors that you wish under-represented groups would display more?
    • Dana: If you haven’t noticed, I’m trans and had spent some of my career as a different gender. I have been socialized to have some of that other gender’s traits and as a result I don’t back down even though I have a feminine communication style. I will call people out and stand up for myself. I would like to see more women doing that. The way people behaved towards me when I changed to female. It was harder and I had to adapt. I encourage everyone to stand up for themselves.
    • Amy: Ask to be treated equally and have the same as what your peers. Don’t change your communication style because other people don’t like it.
    • Uma: Risk-taking in a more calculated way is something I’d like to see more people doing. Build a support network so that you can take risks.
  • Audience Question: Do you think that offering training to help people learn these skills that would allow them to get an even footing culturally would help?
    • Uma: Yes, at Stripe we had a training around negotiating that really helped understand that everything can be negotiable. Further, in backgrounds where saying no to managers is hard, building 1:1 relationships that helps understand the new ways interact with peers and manager.
    • Amy: Managers should constantly be emphasizing that they are equals and not superior so that directs are comfortable say no or constructive discussion. It is really helpful that my managers communicates that I’m allowed to challenge them.
  • Audience Question: How do you thank people for treating you like an equal?
    • Dana: Thank them. It’s okay to tell them and explain to them why it matters to you.

Did I like this Panel?

Not particularly but that’s only because I’ve already heard this advice a number of times.

Fireside Panel with CIO of Providence Health Janice Newell and Charu Jain CIO at Alaska Airlines

  • Q: Can you tell us about a service story that went horribly wrong?
    • Charu: a lot of our cloud providers are on their own journey as well and even though you do everything right on your end, one day you find out that something isn’t there when you expect it to. We’ve learned to trust but verify even with some of the large providers?
    • Q: How do you verify?
    • Charu: Work with them to prove that it is working and pair on testing.
    • Q: What about a great thing?
    • Charu: We were building a cloud infrastructure to support more bookings. After moving to a cloud based solution we found that we were able to do things instantly that weren’t possible before.
    • Janice: I have a horror story from us. During the Wannacry virus, we found out that one of our cloud providers that had advertised high security and a whole bunch of other features. It turns out they didn’t actually have those features. The virus then took down voice transcription for doctors for over a month. This created a huge problem for the customers. We ended up moving all of our physicians off of the SaaS based solution to an on-prem solution. We then went back to verify and inspect all the features and fault tolerance the company said they offered and were horrified to see how terrible it was. We pushed back and had to get them to improve their systems. This is an example of the trust but verify example is similar to what Alaska had to do.
  • Q: We’ve seen a trend of a shift from Hybrid (on-prem + cloud) to an idea of multi-cloud where you use multiple cloud solutions (Azure + AWS). Are you thinking of multi-cloud and how would you use it?
    • Charu: Our strategy is stated as multi-cloud. We are currently on Azure and have multiple SaaS providers. We are trying to get better at one thing before maturing into a multi-cloud environment.
    • Janice: We are using containers to try to adopt that flexibility.
  • Q: How has cloud adoption impacted things organizationally and culturally? Devops? Team makeup between specialist, generalist, or devops?
    • Charu: We are working on a phased plan where we move one team and then take the learnings and roll that out to more teams. We are choosing teams first that have the most legacy technology that needs to be moved further. Developers feel empowered to drive these changes. We stood up automation teams to help start up the infrastructure and that has migrated to a cloud center where we help teams understand developing for the cloud.
    • Q: Has there been resistance along the way?
    • Charu: Change has always met resistance. People who have embraced it are setting the example.
  • Q: What is your approach to monitoring?
    • Charu: We are still in early stages. We are trying to make our monitoring complete but also not too noisy.
    • We need to measure to know how our services are doing.

Did I like this panel?

No, it seems more managerial/business level than technical. There was a lot of repetitive back and forth so it was hard to pull out relevant information.

Machine Learning At Scale On Microsoft Azure, Paige Bailey, Microsoft

  • Artificial Intelligence: any technique that allows computers to mimic human behavior
  • This means anything that is coded to behave as a human which started off as rule based systems
  • As the behavior becomes more complex and can’t be enumerated, you can use machine learning to let the computer learn a large space than the rules defined by a human

Types of Machine learning:

  • Do you have labelled data?
      • Yes – Cluster Analysis – Example: K-means
        • These problems are harder
        • Do you want to Group Data?
          • Yes – Cluster Analysis – Example: K-means
          • Categories: classification – determine what type of thing and object is. Example: KNN.
          • Quantities: regression – estimate an output based on input. Example – linear regression.
  • No – Unsupervised Learning
  • These problems are harder
  • Do you want to Group Data?
    • Yes – Cluster Analysis – Example: K-means
    • No – Dimensionality reduction – Example: PCA


  • Example walkthrough: you are given a CSV with age, credit history, and employment; determine if you should give someone a loan
  • You can make a decision tree to classify this person into yes or no buckets
  • Aside: Jupyter notebooks are excellent for machine learning
  • Feature: think of this as a column in a CSV
  • Record: think of this as a row in a CSV
  • Demo: showing a simple training example in a Jupyter notebook. (Author’s note: many tutorials are available online that will walk you through this)
  • Machine learning is helping us learn without explicit rules; deep learning is now helping us identify features to learn on and extrapolate huge amounts of potential cases. Example: Magenta
  • After this there were more examples and a discussion of how you can save your company money by learning to do machine learning on your own and also bump your salary due to the additional skills
  • GPUs are very good for training neural networks
  • Data science virtual machine using X2Go: if you don’t want to have to worry about managing your own machine learning environment, this will maintain all versions of libraries and languages to help you move faster with tons of educational Jupyter notebooks out of the box including topics like TensorFlow. They are ready, waiting, and free!

Did I like this talk?

Yes and no. I already knew all of this so it wasn’t super helpful but the presenter did a great job starting from 0 and showing people good examples in the time given.

Container and Serverless at Edge Connected to Cloud – Ying Xiong, Chief Architect, Cloud Platform, Huawei

  • What is edge cloud? Computing resources at the edge managed by the cloud owned by provider or customers with bidirectional communication between both.
  • Example scenario: security cameras where processing can be done on the camera itself and send data back to cloud
  • Challenges: resource constraints and frequent network partitioning with no public access; we also need to support edge to edge communication
  • Kubernetes on the Edge: what happens when and edge node loses the network connection? We can’t update it or support serverless on it.
  • To solve these problems:
    • We need to create robust communication between edge and cloud with high reliability and scalability
    • Build an edge resource controller that manages the edge from cloud
    • Support asynchronous metadata syncing and local storage to allow edge to operate on it’s own until connectivity is available
    • Similarly, build a component called KubeEdge that will manage the edge applications and listen to events to allow self maintenance on edge nodes
    • Use an event hub as a centralized listener to aggregate and queue events locally on the edge
  • Created a custom TCP/IP to optimize for edge-cloud communication for reliable bi-directional multiplex channels that can scale
  • Needs to support AuthN with certificates
  • This provides a Kubernetes plugin to manage and maintain edge nodes and also provides Kubernetes on the node to support app status syncing
  • KubeEdge is an optimized version of kubelet on edge for managing the edge node lifecycle and maintenance. It can work offline.
  • Not yet open source but that is the plan.

Did I like this talk?

Yes. Before going to this conference I hadn’t hear the term “edge cloud” and it turns out it is very aligned with my technical interests.

Fireside Chat with Matthew Prince, Co-founder & CEO, Cloudflare

  • When Cloudflare started we were competing with companies that were trying to find newer and better hardware to accomplish their goals; we did the opposite: we searched for ways of making the commodity hardware scale cheaply and linearly.
  • Over 150 datacenters for Cloudflare with fully owned hardware in rented spaces; ISPs are interested in moving Cloudflare closer to them since it creates a faster internet and better customer experience.
  • We have a world-wide infrastructure and we are suffering from low performance that isn’t improving from existing DNS providers due to lack of competition. We were able to create a secure and performant competitor in response.
  • Discussion on opening business to public offering, costs and profits, competitive advantages, customer successes, various marketing and business data
  • Insider threats are a big security challenge going forward
  • “Our scale is so large that attackers can’t DDOS attack”
  • Question: You made a decision to stop supporting a Neo-Nazi customer. How have you dealt with this internally?
    • “I never thought I’d know so much about Neo-Nazis”
    • “It’s lots of fun to kick Neo-Nazis off your service”
    • There’s no way for consumers to understand when they are using CloudFlare. It seems creepy if we curate what users can or cannot see.
    • We had to decide what the role of deep cloud infrastructure companies is
    • The point at which we decided to do this is when the customer started to attribute their political view to the company
    • There is still no clear answer on how to handle these cases

Did I like this talk?

No. This appeared to be a very long advertisement for Cloudflare. There were tidbits of interesting notes about network structure. Some really great quotes came out of this one.

Power Talk by Peter DeSantis Vice President, AWS Global Infrastructure and Customer Support followed by a Fireside Chat

  • At a large scale you are able to invest in things that wouldn’t be cost efficient at lower scale
  • AWS has expanded to many region and at an accelerating rate
  • What is a region? A set of availability zones?
  • What is an AZ (availability zone)? A fully isolated infrastructure with one or more datacenters, a unique power center, and a meaningful distance from each other
  • Every region has at least 3 and up to 6 AZs
  • Connectivity:
    • Between datacenters within the AZ
    • Between AZs within the region
    • Between AZs and the public internet across the region
  • Built on top of a dense fibre backbone with high redundancy than Amazon manages
  • Also creating inter-region Direct Connect that allows customer to get a fast lane between regions
  • Compute with AWS EC2: Security, Performance, and Familiarity (look and feel is like any other server)
  • Going over the history of EC2 architecture
    • First started off with customer instances on top of a hypervisor that managed security, network, and hardware
    • In the next big iteration, they moved over to Nitro infrastructure
    • Through these moves they were able to improve network latency by 20%
    • This also enabled moving to commodity hardware – except for security and some other core features
    • Could continue to look for hardware solution, use FPGA chips, or go with a custom ASIC – eventually acquired Annapurna labs to realize the last option
    • Thus equipped, security improved and allowed nearly 100% of compute resources to be available to customers on the instance. This achieved the familiarity goal.
  • Now have also opened offerings for bare metal instances as well as Nitro VMs

Did I like this talk?

Yes. Despite knowing a lot of this information at a high level, I hadn’t seen in presented in this particular nutshell. I liked how it was phrased and the progression through the topics.

Event Infrastructure

  • The event used a phone app to support planning your agenda, quick connect with other attendees, integration with for live polls
  • Regular video on projectors but also a live keyword note taking screen which was actually very helpful
  • The breakfast was great: hot toasted bagels and a hot oatmeal bar for breakfast
  • Event support for developers is great: they provide desks and tables with a high density of plugs available
  • The sponsors presented before, between, and after each talk. It was a little overwhelming and felt like I was watching Youtube with ads turned on. However, the comfort of the event was worth it. Similarly, all “ads” were relevant so it wasn’t too bad.

Networking Notes

  • Very easy to network at this event: all I needed to do was sit down at a table and people would start up conversations about technical topics
  • Despite trying to avoid doing so, people are very interested in hearing the terrible things about the company I currently work for
  • I encountered some discussion because I perhaps foolishly brought my motorcycle gear with me (I did ride the motorcycle to the event) and started some conversations about whether or not to lock your helmet to your bike. This then lead to discussions about companies that let you work from home and some nice connections. If you learn one thing from this: bring or wear an item that will inspire people to talk to you.