Tag Archives: expert

Why would I help a customer that’s not paying? The reason might surprise you


I just received an email. It was from a woman building a website, and wanted help with AWS. She wondered if I might be able to provide any assistance.

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Having a popular publicly facing blog, I get a lot of leads that seem to come out of thin air. This is the good problem of publicity. ๐Ÿ™‚

I followed up with her and asked what she was building. “Nothing” she explained, I just want to learn about AWS. I was a little confused at first, but as we talked further, it seemed she was just beginning to branch out onto the wild world of the internet, and didn’t know where to start.

I explained that to build an e-commerce site, she could use a service like Shopify, and would likely not need to use AWS directly, and certainly wouldn’t have to learn it. That might take five to ten years learning computing first!

I realized I was telling her she didn’t need the services of someone like me, and further giving her half of a solution. Though I couldn’t help her build a product, the information could surely help her sell it.

Then I thought to myself, why would I do that? Why give away your time & advice for free?

1. Find time to followup

LESSON: a quick call is always worthwhile networking

Yep it’s true, I’ve learned over the years it’s always worth your time for a quick call. I even talk to recruiters on occasion though I don’t work with them.

You’d be surprised how often you learn from someone, especially when they don’t work in your domain. You learn from the way they frame questions, how others might view or search for you. You learn how better to explain & sell your services to future customers too.

Also: When clients don’t pay

2. Be helpful

LESSON: Provide some real help or value

In a call like this one, it costs me very little to “drop some knowledge” as the cool kids like to say. ๐Ÿ™‚ Sure my time is worth something, and yes I’m giving something away for free. But in this case it was someone who currently doesn’t have the budget for my services so isn’t my target audience anyway.

Read: When you have to take the fall

3. Pay forward

LESSON: Always be networking

Be patient. As Keith Ferrazzi likes to say “Never Eat Alone”! I’ve taken hundreds of calls like this one over the years, and some later get funded & call me back. They’re eager to put me to work, already sold on my integrity & personality.

What’s more she may run in different circles than I do, bump into a colleague or recommend me at some point. If your openness really stands out, it’ll leave a memorable impression long into the future.

In a place like New York where we’re often singularly focused on profit & personal gain, it’s easy to stand out by a small act of kindness.

Related: A look at the serverless hype cycle

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How to interview an amazon database expert


Amazon releases a new database offering every other day. It sure isn’t easy to keep up.

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Let’s say you’re hiring a devops & you want to suss out their database knowledge? Or you’re hiring a professional services firm or freelance consultant. Whatever the case you’ll need to sift through for the best people. Here’s how.

Also: How to interview an AWS expert

What database does Amazon support for caching?

Caching is a popular way to speed up access to your backend database. Put Amazon’s elasticache behind your webserver, and you can reduce load on your database by 90%. Nice!

The two types that amazon supports are Memcache & Redis. Memcache is historically more popular. These days Redis seems a clear winner. It’s faster, and can maintain your cached data between restarts. That will save you I promise!

Also: Is AWS too complex for small dev teams?

How can I store big data in AWS?

Amazon’s data warehouse offering is called Redshift. I wrote Why is everyone suddenly talking about Redshift?. Why indeed!

When you’re doing large reports for your business intelligence team, you don’t want to bog down your backend relational database. Redshift is purpose built for this use case.

I’ve see a report that took over 8 hours in MySQL return in under 60 seconds in Redshift!

A new offering is Amazon Spectrum. This tech is super cool. Load up all your data into S3, in standard CSV format. Then without even loading it into Redshift, you can query the S3 data directly. This is super useful. Firstly because S3 is 1/10th the price. But also because it allows you to stage your data before loading into Redshift itself. Goodbye Google Big Query! I talked about spectrum here.

Related: Which engineering roles are in greatest demand?

What relational database options are there on Amazon?

Amazon supports a number of options through it’s Relational Database Service or RDS. This is managed databases, which means less work on your DBAs shoulders. It also may make upgrades slower and harder with more downtime, but you get what you pay for.

There are a lot of platforms available. As you might guess MySQL & Postgres are there. Great! Even better you can use MariaDB if that’s your favorite. You can also go with Aurora which is Amazon’s own home-brew drop in replacement for MySQL that promises greater durability and some speedups.

If you’re a glutton for punishment, you can even get Oracle & SQL Server working on RDS. Very nice!

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

Does AWS have a NoSQL database solution?

If NoSQL is to your taste, Amazon has DynamoDB. According to . I haven’t seen a lot of large production applications using it, but what he describes makes a lot of sense. The way Amazon scales nodes & data I/O is bound to run into real performance problems.

That said it can be a great way to get you up and running quickly.

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

How do I do ETL & migrate data to AWS?

Let’s be honest, Amazon wants to make this really easy. The quicker & simpler it is to get your data there, that more you’ll buy!

Amazon’s Database Migration Service or DMS allows you to configure your old database as a data source, then choose a Amazon db solution as destination, then just turn on the spigot and pump your data in!

ETL is extract transform and load, data warehouse terminology for slicing and dicing data before you load it into your warehouse. Many of todays warehouses are being built with the data lake model, because databases like Redshift have gotten so damn fast. That model means you stage all your source data as-is in your warehouse, then build views & summary tables as needed to speed up queries & reports. Even better you might look a tool like xplenty.

Amazon’s new offering is called Glue. Five ways to get data into Amazon Redshift. This solution is purpose build for creating a powerful data pipeline, complete with python code to do transformations.

Read: Is data your dirty little secret?

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Top Amazon Lambda questions for hiring a serverless expert


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.

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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?

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Why is everyone suddenly talking about Amazon Redshift?

par accel redshift

It seems like all I hear these days is Redshift, Redshift, Redshift!

I met up with a recruiter today. We talked about this & that. The usual. Then when he came to the topic of technology he said,

“yeah it seems as though suddenly everybody is looking for Redshift & Snowflake”

As I blogged about before, I don’t work with recruiters, I learn a lot from them.

Join 32,000 others and follow Sean Hull on twitter @hullsean.

Luckily I got to cut my teeth on Redshift about a year ago. I was senior database engineer managing Amazon & MySQL RDS, and they wanted to build a data warehouse. Bingo!

Here’s the big takeaway from my discussion today. Recruiters have their fingers on the pulse!

1. We need an Amazon expert

Here’s what else I’m hearing everywhere. “We’re migrating to AWS, can you help?” Complexity & confusion around the new virtual networking, moving into the cloud, and tuning applications & components to get the same performance as before. All of these are real & present needs for firms.

Related: Is data your dirty little secret?

2. We need a Redshift expert

Amazon bought Par Accel, a bleedingly fast warehouse. It uses SQL. It looks like Postgres, and handles petabytes. You read that petabytes! It’s so good in fact that it seems a lot of folks are now dumping Hadoop.

Incredible as that sounds, Redshift is delivering *that* kind of speed on that kind of big data. Wow! What’s more you skip the whole Hadoop cycle of write, test, debug, schedule job, fix bugs, and stir. With SQL you bring back the iterative agile process!

Read: 5 cloud challenges I’m thinking about today

3. We need a Hadoop expert

Ok, for those enterprises who aren’t sold on Redshift yet, there is still a ton of Hadoop out there. And for good reason.

Apache Spark is also getting really big now too. It’s an easier to manage successor to Hadoop, based around much of the same concepts.

Also: 5 core pieces of the Amazon cloud puzzle to get your project off the ground

4. We need strong Python skills

Python is everywhere. Amazon’s command line interface is python based. You see it everywhere. If it’s not in your wheelhouse get it there!

Also: Why Dropbox didn’t have to fail

5. We need communicators

Another interesting thing the recruiter said

“I was surprised & a little shocked that you suggested we meet for coffee. Most developers are hard to get out to have a conversation with.”

Good communicators are as in-demand as ever! Being able to and happy to talk with people who aren’t deeply technical, and distill complex technical jargon into plain english. And do that with a smile too & enjoy it?

That’s special!

Also: Should we be muddying the waters? Use cases for MySQL & Mongodb

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