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If you’re looking to fill a job roll that says microservices or find an expert that knows all about serverless computing, you’ll want to have a battery of questions to ask them.
Join 33,000 others and follow Sean Hull on twitter @hullsean.
For technical interviews, I like to focus on concepts & the big picture. Which rules out coding exercises or other puzzles which I think are distracting from the process. I really like what what the guys at 37 Signals say…
“Hire for attitude. Train for skill.”
So let’s get started.
1. How do you automate deployment?
Programming lambda functions is much like programming in other areas, with some particular challenges. When you first dive in, you’ll use the Amazon dashboard to upload a zipfile with your code. But as you become more proficient, you’ll want to create a deployment pipeline.
o What features in Amazon facilitate automatic deployments?
AWS Lambda supports environment variables. Use these for credentials & other data you don’t want in your deployment package.
Amazon’s serverless offering, also supports aliases. You can have a dev, stage & production alias. That way you can deploy functions for testing, without interrupting production code. What’s more when you are ready to push to production, the endpoint doesn’t change.
o What frameworks are available for serverless?
Serverless Framework is the most full featured option. It fully supports Amazon Lambda & as of 1.0 provides support for other platforms such as IBM Openwhisk, Google Cloud Functions & Azure functions. There is also something called SAM or Serverless Application Model which extends CloudFormation. With this, you can script changes to API Gateway, Dynamo DB & Cognos authentication stuff.
If you’re using Auth0 instead of Cognito or Firebase instead of Dynamodb, you’ll have to come up with your own way to automate changes there.
Also: Is the difference between dev & ops a four-letter word?
2. What are the pros of serverless?
Why are we moving to a serverless computing model? What are the advantages & benefits of it?
o easier operations means faster time to market
o large application components become managed
o reduced costs, only pay while code is running
o faster deploy means more experimentation, more agile
o no more worry about which servers will this code run on?
o reduced people costs & less infrastructure
o no chef playbooks to manage, no deploy keys or IAM roles
Related: Is automation killing old-school operations?
3. What are the cons of serverless?
There are a lot of fanboys of serverless, because of the promise & hope of this new paradigm. But what about healthy criticism? A little dose of reality can identify a critical & active mind.
o With Lambda you have less vendor control which could mean… more downtime, system limits, sudden cost changes, loss of functionality or features and possible forced API upgrades. Remember that Amazon will choose the needs of the many over your specific application idiosyncracies.
o There’s no dedicated hardware option with serverless. So you have the multi-tenant challenges of security & performance problems of other customers code. You may even bump into problems because of other customers errors!
o Vendor lock-in is a real obvious issue. Changing to Google Cloud Functions or Azure Functions would mean new deployment & monitoring tools, a code rewrite & rearchitect, and new infrastructure too. You would also have to export & import your data. How easy does Amazon make this process?
o You can no longer store application & state data in local server memory. Because each instantiation of a function will effectively be a new “server”. So everything must be stored in the database. This may affect performance.
o Testing is more complicated. With multiple vendors, integration testing becomes more crucial. Also how do you create dev db instance? How do you fully test offline on a laptop?
o You could hit system wide limits. For example a big dev deploy could take out production functions by hitting an AWS account limit. You would thus have DDoS yourself! You can also hit the 5 minute execution time limit. And code will get aborted!
o How do you do zero downtime deployments? Since Amazon currently deploys function-by-function, if you have a group of 10 or 20 that act as a unit, they will get deployed in pieces. So your app would need to be taken offline during that period or it would be executing some from old version & some from new version together. With unpredictable results.
Read: Do managers underestimate operational cost?
4. How does security change?
o In serverless you may use multiple vendors, such as Auth0 for authentication, and perhaps Firebase for your data. With Lambda as your serverless platform you now have three vendors to work with. More vendors means a larger area across which hackers may attack your application.
o With the function as a service application model, you lose the protective wall around your database. It is no longer safely deployed & hidden behind a private subnet. Is this sufficient protection of your key data assets?
Also: Is the difference between dev & ops a four-letter word?
5. How do you troubleshoot & debug microservices?
o Monitoring & debugging is still very limited. This becomes a more complex process in the serverless world. You can log error & warning messages to CloudWatch.
o Currently Lambda doesn’t have any open API for third party tooling. This will probably come with time, but again it’s hard to see & examine a serverless function “server” while it is running.
o For example there is no New Relic for serverless.
o Performance tuning may be a bit of a guessing game in the serverless space right now. Amazon will surely be expanding it’s offering, and this is one area that will need attention.
Also: Is the difference between dev & ops a four-letter word?
