Tag Archives: docker

Top questions to ask a devops expert when hiring or preparing for job & interview

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Strip by Randall Munroe; xkcd.com

Whether your a hiring manager, head of HR or recruiter, you are probably looking for a devops expert. These days good ones are not easy to find. The spectrum of tools & technologies is broad. To manage today’s cloud you need a generalist.

Join 33,000 others and follow Sean Hull on twitter @hullsean.

If you’re a devops expert and looking for a job, these are also some essential questions you should have in your pocket. Be able to elaborate on these high level concepts as they’re crucial in todays agile startups.

Check out: 8 questions to ask an aws ec2 expert

Also new: Top questions to ask on a devops expert interview

And: How to hire a developer that doesn’t suck

1. How do you automate deployments?

A. Get your code in version control (git)

Believe it or not there are small 1 person teams that haven’t done this. But even with those, there’s real benefit. Get on it!

B. Evolve to one script push-button deploy (script)

If deploying new code involves a lot of manual steps, move file here, set config there, set variable, setup S3 bucket, etc, then start scripting. That midnight deploy process should be one master script which includes all the logic.

It’s a process to get there, but keep the goal in sight.

C. Build confidence over many iterations (team process & agile)

As you continue to deploy manually with a master script, you’ll iron out more details, contingencies, and problems. Over time You’ll gain confidence that the script does the job.

D. Employ continuous integration Tools to formalize process (CircleCI, Jenkins)

Now that you’ve formalized your deploy in code, putting these CI tools to use becomes easier. Because they’re custom built for you at this stage!

E. 10 deploys per day (long term goal)

Your longer term goal is 10 deploys a day. After you’ve automated tests, team confidence will grow around developers being able to deploy to production. On smaller teams of 1-5 people this may still be only 10 deploys per week, but still a useful benchmark.

Also: Top serverless interview questions for hiring aws lambda experts

2. What is microservices?

Microservices is about two-pizza teams. Small enough that there’s little beaurocracy. Able to be agile, focus on one business function. Iterate quickly without logjams with other business teams & functions.

Microservices interact with each other through APIs, deploy their own components, and use their own isolated data stores.

Function as a service, Amazon Lambda, or serverless computing enables microservices in a huge way.

Related: Which engineering roles are in greatest demand?

3. What is serverless computing?

Serverless computing is a model where servers & infrastructure do not need to be formalized. Only the code is deployed, and the platform, AWS Lambda for example, takes care of instant provisioning of containers & VMs when the code gets called.

Events within the cloud environment, such a file added to S3 bucket, trigger the serverless functions. API Gateway endpoints can also trigger the functions to run.

Authentication services are used for user login & identity management such as Auth0 or Amazon Cognito. The backend data store could be Dynamodb or Google’s Firebase for example.

Read: Can on-demand consulting save startups time & money?

4. What is containerization?

Containers are like faster deploying VMs. They have all the advantages of an image or snapshot of a server. Why is this useful? Because you can containerize your microservices, so each one does one thing. One has a webserver, with specific version of xyz.

Containers can also help with legacy applications, as you isolate older versions & dependencies that those applications still rely on.

Containers enable developers to setup environments quickly, and be more agile.

Also: 30 questions to ask a serverless fanboy

5. What is CloudFormation?

CloudFormation, formalizes all of your cloud infrastructure into json files. Want to add an IAM user, S3 bucket, rds database, or EC2 server? Want to configure a VPC, subnet or access control list? All these things can be formalized into cloudformation files.

Once you’ve started down this road, you can checkin your infrastructure definitions into version control, and manage them just like you manage all your other code. Want to do unit tests? Have at it. Now you can test & deploy with more confidence.

Terraform is an extension of CloudFormation with even more power built in.

Also: What can startups learn from the DYN DNS outage?

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Sean Hull interviewed on the Doppler Cloud podcast

I recently got a chance to talk with Mike Kavis over at Cloud Technology Partners. It was fun to get away from the keyboard, and in front of the microphone for a change.

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1. Docker

Docker is making deployments easier & easier. But as the pace accelerates, are we introducing vulnerabilities & scalability problems faster than we can fix them?

Also: Are generalists better at scaling the web?

2. Redshift

I’ve blogged that I don’t work with recruiters but I do chat with them regularly.

In a recent conversation a recruiter asked me:

“Why is it that suddenly everyone is looking for Redshift?”

I’m seeing the same trend. And if you look at Hadoop you might see why. Writing SQL queries against Redshift data is wildly simpler than writing EMR jobs for Hadoop.

Related: Why Dropbox didn’t have to fail?

3. Devops automation

These days I hear a lot of talk that all operations is software development. Are you still SSHing into boxes. You’re doing it wrong!

Read: When hosting data on Amazon turns bloodsport

4. Hardware solves all speed problems

Having performance problems? Scale out! Database slow, scale up! These days it seems the old short sighted way of thinking is back with a vengence. Throw hardware at the problem and kick the can down the road.

Also: How to hire a developer that doesn’t suck?

5. Amazon disrupting VC

During dot-com version one-point-oh, you’d need hundreds of thousands to buy hardware & software licenses to get an idea off the ground. That necessarily meant real VC money to get off the ground.

Amazon web services & on-demand computing has brought world class infrastructure to even the smallest startups. For just dollars, they can get started.

Now we’re seeing startups get going with micro investments from the likes of Angel List syndicates. Cutting traditional VCs right out of the equation.

Also: Is Amazon too big to fail?

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Which tech do startups use most?

MySQL on Amazon Cloud AWS

Leo Polovets of Susa Ventures publishes an excellent blog called Coding VC. There you can find some excellent posts, such as pitches by analogy, and an algorithm for seed round valuations and analyzing product hunt data.

He recently wrote a blog post about a topic near and dear to my heart, Which Technologies do Startups Use. It’s worth a look.

One thing to keep in mind looking over the data, is that these are AngelList startups. So that’s not a cross section of all startups, nor does it cover more mature companies either.

In my experience startups can get it right by starting fresh, evaluating the spectrum of new technologies out there, balancing sheer solution power with a bit of prudence and long term thinking.

I like to ask these questions:

o Which technologies are fast & high performance?
o Which technologies have a big, vibrant & robust community?
o Which technologies can I find plenty of engineers to support?
o Which technologies have low operational overhead?
o Which technologies have low development overhead?

1. Database: MySQL

MySQL holds a slight lead according to the AngelList data. In my experience its not overly complex to setup and there are some experienced DBAs out there. That said database expertise can still be hard to find .

We hear a lot about MongoDB these days, and it is surely growing in popularity. Although it doesn’t support joins and arbitrary slicing and dicing of data, it is a very powerful database engine. If your application needs more straightforward data access, it can bring you amazing speed improvements.

Postgres is a close third. It’s a very sophisticated database engine. Although it may have a smaller community than MySQL, overall it’s a more full featured database. I’d have no reservations recommending it.

Also: Top MySQL DBA Interview questions

2. Hosting: Amazon

Amazon Web Services is obviously the giant in the room. They’re big, they’re cheap, they’re nimble. You have a lot of options for server types, they’ve fixed many of the problems around disk I/O and so forth. Although you may still experience latency around multi-tenant related problems, you’ll benefit from a truly global reach, and huge cost savings from the volume of customers they support.

Heroku is included although they’re a different type of service. In some sense their offering is one part operations team & one part automation. Yes ultimately you are getting hosting & virtualization, but some things are tied down. Amazon RDS provides some parallels here. I wrote Is Amazon RDS hard to manage?. Long term you’re likely going to switch to an AWS, Joyent or Rackspace for real scale.

I was surprised to see Azure on the list at all here, as I rarely see startups build on microsoft technologies. It may work for the desktop & office, but it’s not the right choice for the datacenter.

Read: Are generalists better at scaling the web?

3. Languages: Javascript

Javascript & Node.js are clearly very popular. They are also highly scalable.

In my experience I see a lot of PHP & of course Ruby too. Java although there is a lot out there, can tend to be a bear as a web dev language, and provide some additional complication, weight and overhead.

Related: Is Hunter Walk right about operations & startups?

4. Search: Elastic Search

I like that they broke apart search technology as a separate category. It is a key component of most web applications, and I do see a lot of Elastic Search & Solr.

That said I think this may be a bit skewed. I think by far the number one solution would be NO SPECIFIC SEARCH technology. That’s right, many times devs choose a database centric approach, like FULLTEXT or others that perform painfully bad.

If this is you, consider these search solutions. They will bring you huge performance gains.

Check this: Are SQL Databases Dead?

5. Automation: Chef

As with search above, I’d argue there is a far more prevalent trend, that is #1 to use none of these automation technologies.

Although I do think chef, docker & puppet can bring you real benefits, it’s a matter of having them in the right hands. Do you have an operations team that is comfortable with using them? When they leave in a years time, will your new devops also know the technology you’re using? Can you find a good balance between automation & manual configuration, and document accordingly?

Read: Why are database & operations experts so hard to find?

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