Category Archives: Cloud Computing

Does AWS have a dirty little secret?

tell a secret

I was recently talking with a colleague of mine about where AWS is today. Obviously there companies are migrating to EC2 & the cloud rapidly. The growth rates are staggering.

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The question was…

“What’s good and bad with Amazon today?”

It’s an interesting question. I think there some dirty little secrets here, but also some very surprising bright spots. This is my take.

1. VPC is not well understood  (FAIL)

This is the biggest one in my mind.  Amazon’s security model is all new to traditional ops folks.  Many customers I see deploy in “classic EC2”.  Other’s deploy haphazerdly in their own VPC, without a clear plan.

The best practices is to have one or more VPCs, with private & public subnet.  Put databases in private, webservers in public.  Then create a jump box in the public subnet, and funnel all ssh connections through there, allow any source IP, use users for authentication & auditing (only on this box), then use google-authenticator for 2factor at the command line.  It also provides an easy way to decommission accounts, and lock out users who leave the company.

However most customers have done little of this, or a mixture but not all of it.  So GETTING TO BEST PRACTICES around vpc, would mean deploying a vpc as described, then moving each and every one of your boxes & services over there.  Imagine the risk to production services.  Imagine the chances of error, even if you’re using Chef or your own standardized AMIs.

Also: Are we fast approaching cloud-mageddon?

2. Feature fatigue (FAIL)

Another problem is a sort of “paradox of choice”.  That is that Amazon is releasing so many new offerings so quickly, few engineers know it all.  So you find a lot of shops implementing things wrong because they didn’t understand a feature.  In other words AWS already solved the problem.

OpenRoad comes to mind.  They’ve got media files on the filesystem, when S3 is plainly Amazon’s purpose-built service for this.  

Is AWS too complex for small dev teams & startups?

Related: Does Amazon eat it’s own dogfood? Apparently yes!

3. Required redundancy & automation  (FAIL)

The model here is what Netflix has done with ChaosMonkey.  They literally knock machines offline to test their setup.  The problem is detected, and new hardware brought online automatically.  Deploying across AZs is another example.  As Amazon says, we give you the tools, it’s up to you to implement the resiliency.

But few firms do this.  They’re deployed on Amazon as if it’s a traditional hosting platform.  So they’re at risk in various ways.  Of Amazon outages.  Of hardware problems under the VMs.  Of EBS network issues, of localized outages, etc.

Read: Is Amazon too big to fail?

4. Lambda  (WIN)

I went to the serverless conference a week ago.  It was exiting to see what is happening.  It is truely the *bleeding edge* of cloud.  IBM & Azure & Google all have a serverless offering now.  

The potential here is huge.  Eliminating *ALL* of the server management headaches, from packages to config management & scaling, hiding all of that could have a huge upside.  What’s more it takes the on-demand model even further.  YOu have no compute running idle until you hit an endpoint.  Cost savings could be huge.  Wonder if it has the potential to cannibalize Amazon’s own EC2 …  we’ll see.

Charity Majors wrote a very good critical piece – WTF is Operations? #serverless
WTF is operations? #serverless

Patrick Dubois 

Also: Is the difference between dev & ops a four-letter word?

5. Redshift  (WIN)

Seems like *everybody* is deploying a data warehouse on Redshift these days.  It’s no wonder, because they already have their transactional database, their web backend on RDS of some kind.  So it makes sense that Amazon would build an offering for reporting.

I’ve heard customers rave about reports that took 10 hours on MySQL run in under a minute on Redshift.  It’s not surprising because MySQL wasn’t built for the size servers it’s being deployed on today.  So it doesn’t make good use of all that memory.  Even with SSD drives, query plans can execute badly.

Also: Is there a better way to build a warehouse in 2016?

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Is there a new better way to build a data warehouse in 2016?

redshift warehouse

In the old days… the bygone days of 2005 :) That was when you’d pony up for an Oracle license, get the hardware, and build your warehouse. Somewhere along the way you crossed your fingers.

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Today everybody wants to treat data as a product. And for good reason. Knowing how to better server your customers & iterate more quickly is essential in todays hypercompetitive startup world.

1. Amazon Redshift enters the fray

Recently I’ve been wondering why is everyone suddenly talking about Amazon Redshift?? I ask not because recruiters are experts at database technology & predicting the industry trends, but rather because they have their finger on the pulse of what firms are doing.

Amazon launched Redshift in early 2013 using ParAccel technology. Adoption has been quick. Customers who already have their data in the AWS ecosystem find the offering a perfect match for their data analytics needs. And with stories swirling around of 10 hour MySQL reports running in under 60 seconds on Redshift, it’s no wonder.

Also: Is AWS too complex for small dev teams?

2. Old method – select carefully

Ralph Kimball’s opus having fully digested, you set out to meet with stakeholders, and figure out what you were building.

Of course no one understood your questions, and business units & engineering teams spoke english & french. Months went by, and things devolved. Morale got squashed. Eventually out the other end something would be built, nobody would be happy, and eyeballs would roll over the dollars spent.

This model was known in the data warehousing world by the wonderful acronym ETL which is short for extract, transform & load. The transform part happens before you load it. So that your warehouse is a shining, trimmed & manicured copy of your data, ready for reporting.

Also: Is Amazon too big to fail?

3. Today – mirror everything & then build views

Today you’re more likely to see the ELT model employed. That is Extract, Load & Transform. A subtle change, with big differences. When you load first, you mirror all of your transactional data into your warehouse, then build views or new summary tables to fit your ongoing needs.

Customers are using tools like Looker & Tableau to layer on top of these ELT warehouses which are also have some intelligence around the transform piece. This makes the process more self serve for business units, and requires less back & forth between engineering & product teams. No more waiting a few days for a report to be built, because these non-technical teams can build for themselves.

Also: When hosting data on Amazon turns bloodsport?

Is Data your dirty little secret?

4. Pipeline services

So you’re going down the ELT path, but how do get your data into Redshift? I wrote Five ways to get data into Redshift to answer that question.

There are a number of service based offerings from the point & click Fivetran to the more full featured Alooma. And then RJ Metrics & Flydata also fit the bill. You may also want to build your own with xplenty that also has a lot of ELT ETL logic you can build without code. Pretty spiffy.

Read: Is aws a patient that needs constant medication?

5. Reporting databases

We’ll be covering a lot lot more in this space, so check back.

Related: Does Amazon eat it’s own dogfood?

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Five ways to get your data into Redshift

redshift data pipeline

Everybody is hot under the collar this data over Redshift. I heard one customer say, a query that took 10 Hours before now finishes in under a minute. Without modification. When businesses see 600 times speedup, that can change the way they do business.

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What’s more Redshift is easy to deploy. No complicated licenses like the Oracle days. No hardware, just create your cluster & go.

So you’ve made the decision, and you have data in your transactional database, MySQL RDS or Postgres. Now what?

Here are some systems that will help you synchronize data on the regular. And keep it in sync. Most of these are near real-time, so you can expect reports to be looking at the data your business created today.

1. RJ Metrics Pipeline

One of the simplest options, RJ Metrics Pipeline. Setup a trial account, configure your Redshift credentials in the warehouse section (port, user, password, endpoint) and save. Then configure your data source. For MySQL specify hostname, user, password & port. You get the option to go through an ssh tunnel for security. That’s good. You’ll also be given the grant code to create a user in MySQL for RJM.

rjmetrics table config screen

RJM uses a primary or unique key to figure out which rows have changed. Well that’s not completely true. Only if you’re using incremental refresh. If you’re using complete refresh, then it just selects all the data & replaces it each time.

The user interface is a bit clunky. You have to go in and CONFIGURE EACH TABLE you want to replicate. There’s no REPLICATE-ALL option. This is a pain. If you have 500 tables, it might take hours to configure them all.

Also since RJM isn’t CDC (change data capture) based, it won’t be as close to real-time as some of the other options.

Still RJM works and it’s pretty point-n-click.

Also: Is Amazon too big to fail?

2. xplenty

xplenty is really a lot more than just a sync tool. It’s a full featured ETL system. Want to avoid writing tons of python jobs to convert datatypes, transform 0 to paid & 1 to free, things like that? Well xplenty is made to allow building ETL systems without code.

xplenty main dashboard

It’s a bit complex to setup at first, but very full featured. It is the DIY developer or DBAs tool of the bunch. If you need hardcore functionality, xplenty seems to have it.

Also: When hosting data on Amazon turns bloodsport?

Is Data your dirty little secret?

3. Alooma

Alooma might possibly be the most interesting of the bunch.

After a few stumbles during the setup process, we managed to get this up and running smoothly. Again as with xplenty & Fivetran, it uses CDC to grab changes from the MySQL binlogs. That means you get near realtime.

alooma dashboard

Although it’s a bit more complex to setup than Fivetran, it gives you a lot more. There’s excellent visibility around data errors, which you *will* have. Knowing where they happen, means your data team can be very proactive. This is great for the business.

What’s more there is a python based Code Engine which allows you to write bits of code that transform data in the pipeline. That’s huge! Want to do some simple ETL, this is a way to do that. Also you can send notifications, or requeue events. All this means you get state of the art pipeline, with good configurability & logging.

Read: Is aws a patient that needs constant medication?

4. Fivetran

Fivetran is super point-n-click. It is CDC based like Flydata & Alooma, so you’re gonna get near realtime sync with low overhead. It monitors your binlogs for changed data, and ships it to Redshift. No mess.

The dashboard is simple, the setup is trivial, and it just seems to work. Least pain, best bang.

Related: Does Amazon eat it’s own dogfood?

5. Other options

There are lots of other ways to get data into Redshift.

Flydata

I did manage to get Flydata working at a customer last year. It’s a very viable option. I wrote at length about that solution I’ll leave you to read all about it there.

AWS Data Pipeline

I’ve started to kick the tires of AWS Data Pipeline but haven’t decided if it’s the best option for customers.

Nightly rebuild

The Donors Choose Tech Blog posted about their project which can move data from postgres to redshift. You can find the project here.

This will do a *full* reload each night, so if your db is too big for that, it might need modifications. Also if you’re using MySQL as source db you’ll need to change code. One thing I found in there was Perl & Sed commands to transform your source schema CREATE & ALTER statements into Redshift compatible ones. That in itself is worth a look.

Lambda to the rescue

The awslabs github team has put together a lambda-based redshift loader. This might be just what you need. Remember thought that’ll you’ll need to deliver your source data in CSV files to S3 on the regular. So you’ll need some method to dump it. But if you have that half of the equation, this is ideal.

Data Migration Serve or DMS

This appears to have supported Redshift early on, but does not appear to do so now. I’ve gotten conflicting reports, so I should dig a bit more. Anybody want to comment on this one?

Tungsten

I tried & tried & tried to get Tungsten to work. I did have some success but was still blocked by data problems which remained unresolved. To my mind the project is still broken or at least very buggy.

Also: Is AWS too complex for small dev teams?

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Locking down cloud systems from disgruntled engineers

medieval gate fortified aws

I worked at a customer last year, on a short term assignment. A brilliant engineer had built their infrastructure, automated deployments, and managed all the systems. Sadly despite all the sleepless nights, and dedication, they hadn’t managed to build up good report with management.

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I’ve seen this happen so many times, and I do find it a bit sad. Here’s an engineer who’s working his butt off, really wants the company to succeed. Really cares about the systems. But doesn’t connect well with people, often is dismissive, disrespectful or talks down to people like they’re stupid. All burns bridges, and there’s a lot of bad feelings between all parties.

How to manage the exit process. Here’s a battery of recommendations for changing credentials & logins so that systems can’t be accessed anymore.

1. Lock out API access

You can do this by removing the administrator role or any other role their IAM user might have. That way you keep the account around *just in case*. This will also prevent them from doing anything on the console, but you can see if they attempt any logins.

Also: Is AWS too complex for small dev teams?

2. Lock out of servers

They may have the private keys for various serves in your environment. So to lock them out, scan through all the security groups, and make sure their whitelisted IPs are gone.

Are you using a bastion box for access? That’s ideal because then you only have one accesspoint. Eliminate their login and audit access there. Then you’ve covered your bases.

Related: Does Amazon eat it’s own dogfood?

3. Update deployment keys

At one of my customers the outgoing op had setup many moving parts & automated & orchestrated all the deployment processes beautifully. However he also used his personal github key inside jenkins. So when it went to deploy, it used those credentials to get the code from github. Oops.

We ended up creating a company github account, then updating jenkins with those credentials. There were of course other places in the capistrano bits that also needed to be reviewed.

Read: Is aws a patient that needs constant medication?

4. Dashboard logins

Monitoring with NewRelic or Nagios? Perhaps you have a centralized dashboard for your internal apps? Or you’re using Slack?

Also: Is Amazon too big to fail?

5. Non-key based logins

Have some servers outside of AWS in a traditional datacenter? Or even servers in AWS that are using usernames & passwords? Be sure to audit the full list of systems, and change passwords or disable accounts for the outgoing sysop.

Also: When hosting data on Amazon turns bloodsport?

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Is AWS too complex for small dev teams & startups?

via GIPHY

I was discussing a server outage with a colleague recently. AWS had done some confusing things, and the team was rallying to troublehsoot & fix.

He made an offhand comment that caught my attention…


AWS is too complex for small dev teams. I’d recommend we host in a traditional datacenter.

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It’s an interesting point. For all the fanfare over Amazon, lost in the shuffle is the staggering complexity that we’re taking on. For small firms, this is a cost that’s often forgotten when we smell the on-demand cool-aid that is EC2.

Here are my thoughts…

1. Over 70 services offered

Everytime I login to the AWS console there’s a new service offering. Lambda & serverless computing. CodeDeploy, Redshift, EMR, VPC’s, developer tools, IOT, the list goes on. If you haven’t enabled MFA on your IAM accounts you’re not alone!

Also: Is Amazon too big to fail?

2. Still complex to build high availability

The song I hear out of Amazon is, we offer all the components for a high availability infrastructure. multiple availability zones, regions, load balancers, autoscaling, geo & latency dns routing. What’s more companies like Netflix have open sourced tools to help.

But at a lot of startups that I see, all these components are not in use, nor are they well understood. Many admins are still using Amazon like an old-school datacenter. And that’s not good.

Sometimes it seems that AWS is a patient in need of constant medication.

Related: Are we fast approaching cloud-mageddon?

3. Need a dedicated devops

As AWS becomes more complex, and the offering more robust, so too the need for dedicated ops. If you’re devs are already out of bandwidth, but you don’t quite have so much need for a fulltime resource a consultant may be an option. Round out the team & keep costs manageable.

If you’re looking for an aws solutions architect, we can help!

Check out: Does Amazon eat it’s own dogfood?

4. Orchestration involves many moving parts

Infrastructure as code offers the promise of completely versioning all your servers, configurations and changes. From there we can apply test driven development & bring a more professional level of service to our business. That’s the theory anyway.

In practice it brings an incredible number of new toolsets to master and a more complex stack besides. All those components can have bugs, need troubleshooting. This sometimes just kicks the can down the road, moving the complexity elsewhere.

It’s not clear that for smaller shops, all this complexity is manageable.

Also: 5 things toxic to scalability

5. Troubleshooting failed deployments

I was looking at a problem with a broken deploy recently. Turns out a developer had copy & pasted some code solution off the internet, possibly from a tutorial, and broke deployments to staging.

Yes perhaps this was avoidable, and more checks & balances can fix. But my thought is continuous integration & continuous deployments are not a panacea. More complexity brings a more complex web to unweave.

I sometimes wonder if we aren’t fast approaching cloud-mageddon?

Read: Why Airbnb didn’t have to fail?

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Why is Reddit’s CTO Martin Weiner special?

reddit cto martin weiner

I was reading the New Stack recently, and stumbled on Joab Jackson’s article about Reddit CTO Martin Weiner.

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He had some pretty on point observations about stable applications & predictability.

1. Because he should know

He was technical lead at Pinterest & now he’s CTO at Reddit. Those are pretty serious creds. But why wouldn’t he advocate the coolest new language, or baddest new NoSQL database?

Also: Does Amazon eat it’s own dogfood?

2. Because you can google boring tech

That’s right, picture yourself the ops team or developer who’s gotten paged in the middle of the night. You rub your eyes and look at the computer screen. You’re getting an error on MySQL. You dial up google & find the answer. You fix it & fall back to sleep!

“If it is 3 A.M., and your site is broken, because it will break, whatever the problem is with MySQL, the answer will up on Google”

Related: Did Dropbox have to fail?

3. Because you want predictability

New unproven technologies may solve old problems, but they’re also unpredictable. They break in new ways. They’re still immature. That’s dangerous.

What you really want is predictability & you get that from boring tech.

Read: Is Amazon too big to fail?

4. Because you can hire for it!

There are lots of technologies that have been around for a while, that are stable, reliable & *gasp* you can find people who know them!

“Python is a really mature tech. Everyone knows how to use it, and you can hire for it”

Also: Is Amazon Redshift a game changer?

5. Because everything breaks

While you’re discovering the coolest bleeding edge technology, and imaging the castles you can build, don’t forget that it will break at some point.

“If it breaks in the middle of the night, they wake up and fix it”

With boring tech, the fix is within reach.

Also: Is data your dirty little secret?

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Does Amazon eat it’s own dog food (ahem…) or drink it’s own champagne?

laura grit aws amazon retail champagne

I was flipping through the AWS reddit channel and found this excellent presentation from RE:Invent by Laura Grit. She’s in charge of Amazon Retail, and worked very closely with teams on migrating to AWS. She goes in-depth on what that cost in terms of development, what it saved in terms of unused capacity, and surprisingly operational headaches.

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Laura’s a great speaker. I was surprised to find that Amazon Retails migration was similar to many of the customers I’ve worked with in New York. Often they take a hybrid approach where Direct Connect is key, allowing them to move over in a measured way.

What’s more she talks about how EC2 instances have different performance characteristics & applications typically need to be tuned for that world.

I learned a lot more, here are the highlights…

1. Hybrid cloud was key

Around 11:00 in the video she talks about AWS Direct Connect & VPC. These two technologies allow you to leverage AWS as a hybrid cloud, connecting to your existing datacenter. Scale elastically, but migrate in steps.

For example Amazon Retail did only webserver fleet in isolation.

Also: Is Amazon too big to fail?

2. Excite business & developers both

Around 18:20 …

“Moving the webserver fleet not only got the business excited about the cost savings & our ability to scale linearly, but also got developers excited about the operational load decrease that they had to burden.

Once benefits of this were shown to the rest of the company it actually jump started a wave of migrations to ec2 from inside amazon retail. And we found from a program perspective this is important. To find early migrations that benefit both the business & the developers because then they are both working together to figure out how to move their services to AWS.”

And she also pointed out an interesting bit abaout cultural change…

“You may choose to not migration the simplest service from inside your company, but instead one that will create a cultural change in the company & force more migrations automatically to AWS.”

Related: Are SQL Databases dead?

4. Expect application changes

Flip through to 27:47 and she talks about application changes for the new environment of the cloud.

“Don’t expect migrations to require no changes to your applications…
The webserver fleet was not lift & shift”

Also: Why Dropbox didn’t have to fail

5. Cloud not a panacea

Fast forward over to 37:10 and you’ll hear Laura talk about technical debt. That’s big.

“The cloud is not a universal panacea. It can’t coverup for messy engineering practices.
An example of this is availability. Design for failure is a fundamental design principle of amazon.”

Also: Are generalists better at scaling the web?

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Is demand for aws skills skyrocketing?

aws solutions architect trend

If Google trends is any indication, we’re heading for a serious skills shortage around AWS. If you’re a devops, sysop or systems administrator… don’t walk, run in this direction!

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I’ve pivoted a few times in my career, and knowing which way the wind blows is how I keep up with change. And right now it seems to be blowing into the cloud!

1. AWS datacenter growth is staggering

Also: Is Amazon too big to fail?

2. What I hear from recruiters

I’ve been hearing from more & more recruiters recently. And all they can talk about is redshift & AWS cloud solutions architects.

I think recruiters sit in a unique position & have the pulse of the market like nobody else does.

Related: 8 questions to ask an aws expert

3. Certification bandwagon

AWS is pushing hard to help sysops level up their skills. This can only help push adoption, but it’s also ideal for those who are ready to learn more about the cloud.

Read: When hosting data on Amazon turns bloodsport

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5 ways to level up as cloud expert

aws certified

Cloud computing is blowing up! But don’t take my word for it, read this recent NY Times piece: Tech companies clamor to entice cloud computing experts.

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Still don’t believe me? Get on the phone with a recruiter or two. They’ll convince you because they’ve got companies banging down the door looking for talent that is plainly in SHORT SUPPLY. And that’s the supply *you* want to be. :)

Check Gary’s Guide Jobs, or the ever popular Angel List Jobs. There’s also Stack Overflow jobs and many more.

1. Become a book reviewer

You’ve already got a technical background, and want to hone those skills. Take a look at technical book reviewing.

Manning is putting out some excellent technical books these days. Apply here to be a reviewer.

Also take a look at Pragmatic Bookshelf. They are are looking for reviewers too.

In either case you can expect to spend time reading a book chapter by chapter, as it’s written, offer strategic or layout advice, feedback on presentation, comprehension, and edits.

Also: When hosting data on Amazon turns bloodsport

2. Join an Open Source project

There are millions. Flip through github to some that you’re interested in. Contribute a bug fix or comment, reach out to the project leaders.

Afraid to dive in? Join one of the forums or google discussion groups, and lurk for a while. Ask questions, offer a helping hand!

Related: Is Amazon too big to fail?

3. Self-paced labs

Online education is blowing up, and for good reason. They get the job done & for the right price!

One of my favorites for AWS Certification is the A Cloud Guru courses. These offer lecture style introduction to all levels of AWS from Sysops Administration, Developer & Solutions Architect to Devops, Lambda & CodeDeploy.

The courses are priced right, and geared directly towards Amazon’s certifications. That helps you focus on the right things.

Amazon also partners with qwiklabs to offer courses geared towards getting certified. There are specific ones for the associate & professional certification, and many others besides.

You’ll need to signup for AWS Activate first, before you can use these qwiklabs. They offer you 80 credits right out of the gate.

For the next two weeks many of the courses are free! One thing I really like is they include a free temporary aws login for the students. That way there’s no risk of deploying infrastructure, and accidentally getting a big bill at the end of the month.

The labs though are more like reading documentation versus a nice video course lecture. So you the student have to do a lot more to get through it.

Read: Are we fast approaching cloud-mageddon?

4. Coursera, Khanacademy & Udemy

There’s a free class on Coursera called Startup Engineering by Balaji Srinivasan & Vijay Pande. Some pretty amazon material & lectures in here, and if you’re determined, it’s 12 weeks that will get you going on the right foot!

KhanAcademy has a great many courses on computer programming. Awesome and free stuff here. One particularly interesting is their hour of code. For those hesitant, that’s an easy way to jump in!

There is also udemy, which offers some great material on cloud computing. Notice that the certification courses are the same ones from A-Cloud Guru!

Also: Are SQL databases dead?

5. Interview tests

Apply to jobs. Even if you’re unsure if that is your dream job. Why? Because they often include a test to find out about your technical chops. Diving into these tests is a great way to push your own edge. You may do well, you may not. Learn where your weaknesses are.

I especially like the ones where you’re asked to login to a server, configure some things, write some code, and solve a real problem. Nothing beats a real-world example!

Also: Why dropbox didn’t have to fail?

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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.

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

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?

Get more. Grab our exclusive monthly Scalable Startups. We share tips and special content. Our latest Why I don’t work with recruiters