Category Archives: Devops

What’s the *real* way to deploy on Google Cloud?

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I was talking to a customer recently and they asked about deployments. They wanted to do things the real way. Here’s a snippet…

I’m helping out a company called Blue Marble and they are getting ready to deploy a new POS system. The app has been built using a Node.js back-end and Google Cloud Datastore for storage. The current dev build is hosted on AWS and connects to Google for the data bits.

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For prod launch, they are interested in migrating to the “real” way of deployment on Google for everything.

They are pressed on time and looking for someone who can jump in quickly. Are you available? Do you have Google Cloud expertise?

Here’s what I said.

Cultural hurdles


Yep, I’ve have used Bigquery & GCE.

What are they looking for specifically? Full deployment automation? Multiple deploys per day?

I’ve found that sometimes the biggest hurdle to fully automated deploys can be cultural issues.

In other words yes you can automate your deployment so it is push button, get all the artifacts & moving parts automated. Then deploy without much intervention. But to go from that to the team having *faith* in the system, that is a challenge.

Also: Why would I help a customer that’s not paying?

Unit testing


Once the process has been streamlined, a lot often still needs to happen around unit & smoke tests.

If the team isn’t already in the habit of building tests for each bit of code, this may take some time. Also building tests can be an art in itself. What are the edge cases? What values are out of bounds?

Consider for example odd vulnerabilities that show up when hackers type SQL code into fields that devs were expecting. Sanity checking anyone?

Read: Is AWS too complex for small dev teams? The growing demand for Cloud SRE

Integraton testing

What makes this all even more complicated is integration testing. Today many application use various third party APIs, service-based authentication, and even web-based databases like Firebase. So these things can complicate testing.

Related: How to build an operational datastore on Amazon Redshift with S3

Getting there

Although your project, startup or business may be pressed for time, that may not change the realities of development. Your team has to become culturally ready to be completely agile. Many teams choose a middle ground of automating much of the deployment process, but still having a person in the loop just in case.

Same with testing. Sure automating can make you more agile & more efficient. But you’ll never automate out creative thinking, problem solving & ownership of the product.

Related: Why did Flatiron School fail?

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Is maintenance as sexy as innovation?

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A recent NYT piece on our aging american infrastructure got me thinking. It seems that roads, bridges, airports & city sewer systems are all in need of repair. Sadly as budgets to maintain these systems in good repair are often short, they become larger problems to fix as their status becomes critical.

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“Americans have an impoverished and immature conception of technology, one that fetishizes innovation as a kind of art and demeans upkeep as a mere drudgery.”

I’m not sure this is an American-only phenomenon. However I do see it a lot with technology companies & startups.

1. Do we have to manage ops in the cloud?

The cloud has enabled infrastructure automation in some pretty phenomenal ways. Code pipelines can deliver changes to a repo, through automated unit testing, and out to customers all without human intervention. This makes teams more agile, and ultimately businesses faster & more profitable.

We might be distracted enough to stop worrying about operations altogether. After all Amazon knows how to manage broken servers & alert us right? I write do we have to manage operations in the cloud previously, as this sentiment seems to be growing.

Modern applications have a ton of interdependencies. Even with decent integration testing, the full stack is complex, and requires monitoring. Co-tenancy can complicate your performance tuning efforts as neighboring customers may directly affect your application. Third party services may be delivered from smaller or less experienced companies, whose SLA may be limiting besides. And hey if Amazon goes down, I can just tell my customers it was their fault, right?

Also: Is Amazon too big to fail?

2. Do you know Dustin Moskovitz?

Chances are I’m guessing you’ll say no. He was part of the original Facebook team alongside Zuckerberg. You don’t know his name? He had the sexy job of, you guessed it maintenance! He was the operations guy. Did he write the application code? More than likely he knew that code very well as he had to fix & maintain it. Along with the infrastructure to scale & support Facebook’s massive growth.

Read: Is AWS too complex for small dev teams? The growing demand for Cloud SRE

3. Is a little technical debt ok?

Ward Cunningham has an excellent interview about technical debt. Is a little bit ok? Maybe. But each amount is kicking the can down the road. As the NYT article on maintenance makes clear, you can move the responsibility on to the next administration, the next term, or someone else, but eventually you’ll have a critical problem on your hands, which will be much more expensive to fix.

Related: How to build an operational datastore on Amazon Redshift with S3

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Do we have to manage ops in the cloud?

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One of the things that is exciting about the cloud is the reduced need for operations staff. There seem to be two drivers of this trend. One is devops, and all the automation that comes with it. As we formalize configurations, things become repeatable, and fewer people can manage greater armies of servers.

The second is by moving to a cloud hosting provider, we essentially outsource the operations to their team.

1. Pretty abstractions? still hardware buried somewhere

That’s right, beneath all the virtual EC2 instances & VPCs there is physical hardware. Huge datacenters sit in North Virginia, Oregon, Ireland, London and many other cities. Within them there are racks upon racks of servers. The hypervisor layer, the abstraction built on top of that, orchestrates everything.

Although we outsource the management of those datacenters to Amazon, there are still responsibilities we carry. Let’s dig into those more.

Also: Top serverless interview questions to ask an expert

2. Full-stack dev – demand for generalists?

These days we see the demand for a full stack developer. That is someone who does not only front end dev, but also backend. In turn, they are often asked to wear the had of ops. Spinup EC2 instance, decide on the capacity & size, choose proper disk I/O, place it within the right subnet & vpc & then configure the security groups properly.

All of these tasks would previously been managed by a dedicated ops team, but now those responsibilities are being put on developers shoulders. In some cases, such as with microservices, devs also carry the on-call duties of their applications.

Lastly there is likely ops to handle automation. Devops will formalize configurations, into ansible playbooks or chef recipes, so they can be checked into version control. At this point infrastructure can even be unit tested.

Read: Build an operational datastore on aws S3 with Spectrum

3. Design, resiliency, instrumentation, debugging

In previous eras, ops teams would be heavily involved with design of applications & architecture to support that. Now that may be handed to devs, but it still needs to happen.

Furthermore resiliency is said to be the customers responsibility. In the pre-cloud days, hardware was more reliable. It had a slower failure rate. With virtual machines, they’re expected to fail, and all the components to make your applications resilient are given to you. But it’s your job to architect them together.

That means your applications need to be self-healing. Failures need to be detected, taken out of autoscaling groups, and replaced. All automatically. Code or not, that is certainly operations.

Check this: Which engineering roles are in top demand?

4. It’s amazon’s fault we’re down!

I’ve seen quite a few outages in the past year, from Dropbox to Airbnb, and DYN themselves. Ultimately these outages could be tied back to a failure with Amazon. But when your business customers are relying on your service, it is *YOUR* business that answers to it’s own SLA.

In the news we see many of these firms pointing the finger at Amazon, “hey it’s not our fault, our cloud provider went down!”. Ultimately your customers don’t care. They don’t want excuses. If using multiple regions in AWS is not sufficient, you’ll need to build your application to be multi-cloud.

Also: 30 questions to ask a serverless fanboy

5. It’s hard to outsource your expertise

Remember, while you outsource your operations to Amazon, you’re getting very professional management of those systems. However they will optimize for their many customers. Your particular problems are less of a concern.

Read this: What can startups learn from the DYN DNS outage?

6. Only you can thinking holistically about interdependancies

Your application more than likely uses a number of APIs to capture data, perhaps do single sign on or even a third party database like Firebase. It’s your responsibility to do integration testing. All that becomes more complex in the cloud.

Also: How to lock down systems from outgoing employees

7. How do services complicate things?

SaaS solutions are everywhere now. auth0, firebase and an infinite variety of third party apis complicate reliability, security, storage, performance, integration testing & debugging?

Security is a traditional responsibility held by the operations hat. Much of that becomes more complex in the cloud. With serverless applications for example you may use a few APIs, plus an authentication broker, and a backend database. As this list of services grows, the code you write may decrease. But testing & securing it all becomes much more complex.

With more services like this, the attack vector or surface area becomes greater. Each of those services, can and will have bugs. What if a zero day is found in the authentication broker, allowing a hacker to break into a broad cross section of applications across the internet? How do you discover this? What if your vendor hasn’t found out yet?

Read: Is Amazon cloud too complex for small dev teams?

8. How does co-tenancy impact performance tuning?

Back to point #1 above, all these virtual servers sit on real physical servers. That affects customers in two ways. One you may be sharing the same host. That is if you use a very small vm, it may sit along side another customer with a small vm. If those eat up CPU cycles or network on that box, neighbors or co-tenants will suffer.

There are many other instance types where you get your own dedicated hardware. With those you have your own nic as well, so no competition. Except wait there’s network storage! That’s right all the machines in the AWS environment use EBS now, which is all co-tenant. So your data is sitting alongside other customers, and you are all fighting for usage of the same disk read heads.

One way to mitigate this is to configure specific provisioned IOPS for your servers. But that costs more. It’s normally reserved for database instances where disk I/O is really crucial.

Granted the NewRelics of the world will certainly help us with this process. But they’re not giving us a hypervisor or global view of those servers, network or storage. So we can’t see how the overall systems performance may be impacted.

Related: Is AWS a patient that needs constant medication?

9. Operations can be invisible

When security is done well, you don’t have breakins, you don’t have data stolen, everything just runs smoothly. Operations is like that too. When it is done well it can be invisible.

It can also be invisible in a different way. When you deploy your application on serverless, all the servers & autoscaling is completely abstracted away. So when you get some weird outage because the farm of servers is offline, or because you hit some account limit in the number of functions you can run at once, then it quickly comes into focus.

Beware of invisible operations, because it’s harder to see what to monitor, and know how to stay ahead of outages.

Read: Is amazon too big to fail?

10. We can’t oursource true ownership

At the end of the day you can’t outsource ownership of your application or your business. The holistic view of your application in totality can only be understood by your engineers.

And that in the end is what operations is all about, no matter who’s wearing the hat!

Also: 5 reasons to move data to amazon redshift

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A roughneck walk down database alley

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I was just responding to some Disqus comments on a recent blog post. Admittedly it had a provocative title Will SQL databases just die already. What do you think?

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A reader pointed out that some No-SQL databases do support joins. Huh? My face contorts in total confusion. How? Why?

For years SQL was misunderstood & unloved

Relational databases have been around for decades. 43 years according to the StackExchange article. That’s a lot of years. I’ve spent a few years as a dba, aka database administrator. The role can be distilled down as a herder of sorts. Keep all the data bits in the right boxes with the right labels. A digital librarian, that makes sure the books don’t get lost.

Of course patrons don’t always put books back where they should, and strict rules get put in place to avoid losing that one volume of shakespear in miles of shelves.

In the fast moving world of web + mobile, product is king, and agile rules the day. And anything that can make us more agile also wins. SQL, much maligned & misunderstood, was not one of those things.

Also: Top serverless interview questions for hiring aws lambda experts

NoSQL burst on the scene with much fanfare

With all that pressure, it was no wonder engineers thought, there must be a better way. Then along comes the No SQL database. I mean just the name speaks volumes about the design goal.

We’ll sacrifice anything, just please don’t make me write SQL!

The promises…

1. Never have to deal with pesky SQL that we don’t understand!
2. Interact with the database like any other data structure in our code!
3. Be schemaless! Crotchety Database Administrators be damned!
4. Be distributed. Be everywhere consistent! Be indistinguishable from magic!
5. Always be fast.

In that rush into the abyss, we lost track of durability. And down the rabbithole we went!

Related: Which engineering roles are in greatest demand?

Relational databases tried to be key-value

Then I started hearing about crazy things, like MySQL providing a memcache plugin, so you could use it albeit lightening fast, as a key-value store. You could sidestep that pesky SQL engine, and get right down to the bare metal. But why? Memcache & Redis were already doing that & purpose built. Why indeed?

I started to argue maybe we shouldn’t be muddying the waters. I mean stick with what you know!

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

War was won, success declared

Around this I think was when Mongodb was declaring the war won. We had finally left SQL databases in the dustheap of history. It may or may not have inspired this popular youtube skit…

Also: 30 questions to ask a serverless fanboy

Meanwhile hadoop is losing ground. Bigquery & Redshift both speak SQL

But then something funny started to happen. It seemed there was a backlash against Mongodb. A lot of customers were losing data. (Yep that’s what durability means guys…) And the hype started reversing. Even the mighty hadoop has been losing popularity of late. How long does it take to write an EMR job versus an SQL query. Let’s be honest?

I asked myself, Is Hadoop losing ground to SQL warehouses like Redshift & Bigquery?. I wonder.

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

NoSQL databases are looking for JOINs?

Recently I bumped into some interesting blog comments & discussions about how Orientdb was trying to add joins to their product.

As certain relational databases try to become No SQL databases, other No SQL databases are trying to add more complex SQL, because well somehow their product is missing something.

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

Engineering truth versus fashion

43 years is a lot of years. And when we drop all the fashion trends in tech, and the new database du jour, what do we find?

There is room for No SQL databases. Yep. And the do certain things, and solve certain types of problems well. But their not general workhorses, nor can they slice and dice your data however you like. And when you get to that point in your project, you’re going to want to ask interesting questions of your data.

And surely that’s where SQL excels. It ain’t going anywhere, folks!

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

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Top Amazon Lambda questions for hiring a serverless expert

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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.

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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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Key lessons from the Devops Handbook

I picked up a copy of the DevOps Handbook.

This is not a book about how to setup Amazon servers, how to use git, codePipeline or Jenkins. It’s not about Chef or Ansible or other tools.

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This is a book about processes & people. It’s about how & why automation & world-class infrastructure will make your business more agile, raise quality & increase productivity.

1. Infrastructure in version control

With technologies like Terraform and CloudFormation, the entire state of your infrastructure can be captured. That means you can manage it just like any other code.

Also: Myth of five nines – Why high availability is overrated

2. Pushbutton builds

You’ve heard it before. Automate your builds. That means putting everything in version control, from environment building scripts, to configs, artifacts & reference data. Once you can do that, you’re on your way to automating production deploys completely.

Related: 5 ways to move data to amazon redshift

3. Devs & Ops comingled

In the devops world, devs should learn about operations, infrastructure, performance & more. What’s more operations teams should work closely with devs.

Read: Why were dev & ops siloed job roles?

4. Servers as cattle not pets

In the old days, we logged into servers & provided personal care & feeding. We treated them like pets.

In the new world of devops, we should treat servers like cattle. When it begins to fail, take it out back and shoot it. (tbh i don’t love the analogy, but it carries some meaning…)

Also: Are SQL databases dead?

5. Open to learnings & failures

Organizations that are open to failures, without playing the blame game, learn quicker & recover from problems faster.

Also: Is Amazon too big to fail?

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30 questions to ask a serverless fanboy

Everyone is hot under the collar again. So-called serverless or no-ops services are popping up everywhere allowing you to deploy “just code” into the cloud. Not only won’t you have to login to a server, you won’t even have to know they’re there.

As your code is called, but cloud events such a file upload, or hitting an http endpoint, your code runs. Behind the scene through the magic of containers & autoscaling, Amazon & others are able to provision in milliseconds.

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Pretty cool. Yes even as it outsources the operations role to invisible teams behind Amazon Lambda, Google Cloud Functions or Webtask it’s also making companies more agile, and allowing startup innovation to happen even faster.

Believe it or not I’m a fan too.

That said I thought it would be fun to poke a hole in the bubble, and throw some criticisms at the technology. I mean going serverless today is still bleeding edge, and everyone isn’t cut out to be a pioneer!

With that, here’s 30 questions to throw on the serverless fanboys (and ladies!)…

1. Security

o Are you comfortable removing the barrier around your database?
o With more services, there is more surface area. How do you prevent malicious code?
o How do you know your vendor is doing security right?
o How transparent is your vendor about vulnerabilities?

Also: Myth of five nines – Why high availability is overrated

2. Testing

o How do you do integration testing with multiple vendor service components?
o How do you test your API Gateway configurations?
o Is there a way to version control changes to API Gateway configs?
o Can Terraform or CloudFormation help with this?
o How do you do load testing with a third party db backend?
o Are your QA tests hitting the prod backend db?
o Can you easily create & destroy test dbs?

Related: 5 ways to move data to amazon redshift

3. Management

o How do you do zero downtime deployments with Lambda?
o Is there a way to deploy functions in groups, all at once?
o How do you manage vendor lock-in at the monitoring & tools level but also code & services?
o How do you mitigate your vendors maintenance? Downtime? Upgrades?
o How do you plan for move to alternate vendor? Database import & export may not be ideal, plus code & infrastructure would need to be duplicated.
o How do you manage a third party service for authentication? What are the pros & cons there?
o What are the pros & cons of using a service-based backend database?
o How do you manage redundancy of code when every client needs to talk to backend db?

Read: Why were dev & ops siloed job roles?

4. Monitoring & debugging

o How do you build a third-party monitoring tool? Where are the APIs?
o When you’re down, is it your app or a system-wide problem?
o Where is the New Relic for Lambda?
o How do you degrade gracefully when using multiple vendors?
o How do you monitor execution duration so your function doesn’t fail unexpectedly?
o How do you monitor your account wide limits so dev deploy doesn’t take down production?

Also: Are SQL databases dead?

5. Performance

o How do you handle startup latency?
o How do you optimize code for mobile?
o Does battery life preclude a large codebase on client?
o How do you do caching on server when each invocation resets everything?
o How do you do database connection pooling?

Also: Is Amazon too big to fail?

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Some irresistible reading for March – outages, code, databases, legacy & hiring

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I decided this week to write a different type of blog post. Because some of my favorite newsletters are lists of articles on topics of the day.

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Here’s what I’m reading right now.

1. On Outages

While everyone is scrambling to figure out why part of the internet went down … wait is S3 is part of the internet, really? While I’m figuring out if it is a service of Amazon, or if Amazon is so big that Amazon *is* the internet now…

Let’s look at s3 architectural flaws in depth.

Meanwhile Gitlab had an outage too in which they *gasp* lost data. Seriously? An outage is one thing, losing data though. Hmmm…

And this article is brilliant on so many levels. No least because Matthew knows that “post truth” is a trending topic now, and uses it his title. So here we go, AWS Service status truth in a post truth world. Wow!

And meanwhile the Atlantic tries to track down where exactly are those Amazon datacenters?

Also: Is Amazon too big to fail?

2. On Code

Project wise I’m fiddling around with a few fun things.

Take a look at Guy Geerling’s Ansible on a Mac playbooks. Nice!

And meanwhile a very nice deep dive on Amazon Lambda serverless best practices.

Brandur Leach explains how to build awesome APIs aka ones that are robust & idempotent

Meanwhile Frans Rosen explains how to 0wn slack. And no you don’t want this. 🙂

Related: 5 surprising features in Amazon’s serverless Lambda offering

3. On Hiring & Talent

Are you a rock star dev or a digital nomad? Take a look at the 12 best international cities to live in for software devs.

And if you’re wondering who’s hiring? Well just about everyone!

Devs are you blogging? You should be.

Looking to learn or teach… check out codementor.

Also: why did dev & ops used to be separate job roles?

4. On Legacy Systems

I loved Drew Bell’s story of stumbling into home ownership, attempting to fix a doorbell, and falling down a familiar rabbit hole. With parallels to legacy software systems… aka any older then oh say five years?

Ian Bogost ruminates why nothing works anymore… and I don’t think an hour goes by where I don’t ask myself the same question!

Also: Are we fast approaching cloud-mageddon?

5. On Databases

If you grew up on the virtual world of the cloud, you may have never touched hardware besides your own laptop. Developing in this world may completely remove us from understanding those pesky underlying physical layers. Yes indeed folks containers do run in “virtual” machines, but those themselves are running on metal, somewhere down the stack.

With that let’s not forget that No, databases are not for containers… but a healthy reminder ain’t bad..

Meanwhile Larry’s mothership is sinking…(hint: Oracle) Does anybody really care? Now’s the time to revisit Mike Wilson’s classic The difference between god and Larry Ellison.

Read: Are SQL Databases Dead?

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5 surprising features in Amazon’s Lambda serverless offering

Amazon is building out it’s serverless offering at a rapid clip. Lambda makes a great solution for a lot of different use cases including:

o a hybrid approach, building lambda functions for small pieces of your application, sitting along side your full application, working in concert with it

o working with Kinesis firehose to add ETL functionality into your pipeline. Extract Transform & Load is a method of transforming data from a relational or backend transactional databases, into one better fit for reporting & analytics.

o retrofitting your API? Layer Lambda functions in front, to allow you to rebuild in a managed way.

o a natural way to build microservices, with each function as it’s own little universe

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Great, tons of ways to put serverless to use. What’s Amazon doing to make it even better? Here are some of the features you’ll find indispensible in building with Lambda.

1. Versioned functions

As your serverless functions get more sophisticated, you’ll want to control & deploy different versions. Lambda supports this, allowing you to upload multiple copies of the same function. Coupled with Aliases below, this becomes a very powerful feature.

Also: When hosting data on Amazon turns bloodsport

2. Aliases

As you deploy multiple versions of your functions in AWS, you don’t want to recreate the API endpoints each time. That’s where aliases come in. Create one alias for dev, another for test, and a third for production. That way when new versions of those are deployed, all you have to do is change the alias & QA or customers will be hitting the new code. Cool!

Related: Are you getting errors building lambda functions?

3. Caching & throttling

Using the API gateway, we can do some fancy footwork with Lambda. First we can enabling caching to speedup access to our endpoint. Control the time-to-live, capacity of the cache easily. We’ll also need to invalidate the cache when we make changes & redeploy our functions.

Throttling is another useful feature, allowing you to control the maximum number of times your function can be called per second on average (the rate) and maximum number of times (burst limit). These can be set at both the stage & method levels.

Read: Is Amazon too big to fail?

4. Stage variables

Creating multiple stages, for dev, test & production means you can separate out and control environment variables with more granular control. For example suppose you have access & secret keys to reach S3. You can set environment variables for these to avoid committing any credentials or secrets in your code. Definitely don’t do that!

Allowing multiple copies of stage variables, means you can set them separately for dev, test & production.

Also: How to deploy on Amazon EC2 with Vagrant?

5. Logging

You can enable logging in your Lambda function configuration. This will send error and/or info warning messages out to CloudWatch.

You may also choose the log all of the request & response data. This is controlled in the API Gateway settings for individual stages.

Also: Is Amazon RDS hard to manage?

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How can startups learn from the Dyn DNS outage?

storm coming

As most have heard by now, last Friday saw a serious DDOS attack against one of the major US DNS providers, Dyn.

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

DNS being such a critical dependency, this affected many businesses across the board. We’re talking twitter, etsy, github, Airbnb & Reddit to name just a few. In fact Amazon Web Services itself was severely affected. And with so many companies hosting on the Amazon cloud, it’s no wonder this took down so much of the internet.

1. What happened?

According to Brian Krebs, a Mirai botnet was responsible for the attack. What’s even scarier, those requests originated for IOT devices. You know, baby monitors, webcams & DVRs. You’ve secured those right? 🙂

Brian has posted a list of IOT device makers that have backdoors & default passwords and are involved. Interesting indeed.

Also: Is a dangerous anti-ops movement gaining momentum?

2. What can be done?

Companies like Dyn & Cloudflare among others spend plenty of energy & engineering resources studying attacks like this one, and figuring out how to reduce risk exposure.

But what about your startup in particular? How can we learn from these types of outages? There are a number of ways that I outline below.

Also: How do we lock down systems from disgruntled engineers?

3. What are your dependencies?

After an outage like the Dyn one, it’s an opportunity to survey your systems. Take stock of what technologies, software & services you rely on. This is something your ops team can & likely wants to do.

What components does your stack rely on? Which versions are hardest to upgrade? What hardware or services do you rely on? Which APIs do you call out to? Which steps or processes are still manual?

Related: The myth of five nines

4. Put your eggs in many baskets

Awareness around your dependencies, helps you see where you may need to build in redundancy. Can you setup a second cloud provider for DR? Can you use an alternate API to get data, when your primary is out? For which dependencies are your hands tied? Where are your weaknesses?

Read: Is AWS too complex for small dev teams?

5. Don’t assume five nines

The gold standard in technology & startup land has been 5 nines availability. This is the SLA we’re expected to shoot for. I’ve argued before (see: myth of five nines) that it’s rarely ever achieved. Outages like this one, bringing hours long downtime, kill hour 5 nines promise for years. That’s because 5 nines means only 5 ½ minutes downtime per year!

Better to be realistic that outages can & will happen, manage & mitigate, and be realistic with your team & your customers.

Also: Is AWS a patient that needs constant medication?

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