Evolution or Rebellion? The rise of Site Reliability Engineers (SRE)

What is a Google SRE?  Charity Majors gave a great overview on Datanauts #65, Susan Fowler from Uber talks about “no ops” tensions and Patrick Hill from Atlassian wrote up a good review too.  This is not new: Ben Treynor defined it back in 2014.

DevOps is under attack.

Well, not DevOps exactly but the common misconception that DevOps is about Developers doing Ops (it’s really about lean process, system thinking, and positive culture).  It turns out the Ops is hard and, as I recently discussed with John Furrier, developers really really don’t want be that focused on infrastructure.

In fact, I see containers and serverless as a “developers won’t waste time on ops revolt.”  (I discuss this more in my 2016 retrospective).

The tension between Ops and Dev goes way back and has been a source of confusion for me and my RackN co-founders.  We believe we are developers, except that we spend our whole time focused on writing code for operations.  With the rise of Site Reliability Engineers (SRE) as a job classification, our type of black swan engineer is being embraced as a critical skill.  It’s recognized as the only way to stay ahead of our ravenous appetite for  computing infrastructure.

I’ve been writing about Site Reliability Engineering (SRE) tasks for nearly 5 years under a lot of different names such as DevOps, Ready State, Open Operations and Underlay Operations. SRE is a term popularized by Google (there’s a book!) for the operators who build and automate their infrastructure. Their role is not administration, it is redefining how infrastructure is used and managed within Google.

Using infrastructure effectively is a competitive advantage for Google and their SREs carry tremendous authority and respect for executing on that mission.

ManagersMeanwhile, we’re in the midst of an Enterprise revolt against running infrastructure. Companies, for very good reasons, are shutting down internal IT efforts in favor of using outsourced infrastructure. Operations has simply not been able to complete with the capability, flexibility and breadth of infrastructure services offered by Amazon.

SRE is about operational excellence and we keep up with the increasingly rapid pace of IT.  It’s a recognition that we cannot scale people quickly as we add infrastructure.  And, critically, it is not infrastructure specific.

Over the next year, I’ll continue to dig deeply into the skills, tools and processes around operations.  I think that SRE may be the right banner for these thoughts and I’d like to hear your thoughts about that.

MORE?  Here’s the next post in the series about Spiraling Ops Debt.  Or Skip to Podcasts with Eric Wright and Stephen Spector.

2016 Infrastructure Revolt makes 2017 the “year of the IT Escape Clause”

Software development technology is so frothy that we’re developing collective immunity to constant churn and hype cycles. Lately, every time someone tells me that they have hot “picked technology Foo” they also explain how they are also planning contingencies for when Foo fails. Not if, when.

13633961301245401193crawfish20boil204-mdRequired contingency? That’s why I believe 2017 is the year of the IT Escape Clause, or, more colorfully, the IT Crawfish.

When I lived in New Orleans, I learned that crawfish are anxious creatures (basically tiny lobsters) with powerful (and delicious) tails that propel them backward at any hint of any danger. Their ability to instantly back out of any situation has turned their name into a common use verb: crawfish means to back out or quickly retreat.

In IT terms, it means that your go-forward plans always include a quick escape hatch if there’s some problem. I like Subbu Allamaraju’s description of this as Change Agility.  I’ve also seen this called lock-in prevention or contingency planning. Both are important; however, we’re reaching new levels for 2017 because we can’t predict which technology stacks are robust and complete.

The fact is the none of them are robust or complete compared to historical platforms. So we go forward with an eye on alternatives.

How did we get to this state? I blame the 2016 Infrastructure Revolt.

Way, way, way back in 2010 (that’s about bronze age in the Cloud era), we started talking about developers helping automate infrastructure as part of deploying their code. We created some great tools for this and co-opted the term DevOps to describe provisioning automation. Compared to the part, it was glorious with glittering self-service rebellions and API-driven enlightenment.

In reality, DevOps was really painful because most developers felt that time fixing infrastructure was a distraction from coding features.

In 2016, we finally reached a sufficient platform capability set in tools like CI/CD pipelines, Docker Containers, Kubernetes, Serverless/Lambda and others that Developers had real alternatives to dealing with infrastructure directly. Once we reached this tipping point, the idea of coding against infrastructure directly become unattractive. In fact, the world’s largest infrastructure company, Amazon, is actively repositioning as a platform services company. Their re:Invent message was very clear: if you want to get the most from AWS, use our services instead of the servers.

For most users, using platform services instead of infrastructure is excellent advice to save cost and time.

The dilemma is that platforms are still evolving rapidly. So rapidly that adopters cannot count of the services to exist in their current form for multiple generations. However, the real benefits drive aggressive adoption. They also drive the rise of Crawfish IT.

As they say in N’Awlins, laissez les bon temps rouler!

Related Reading on the Doppler: Your Cloud Strategy Must Include No-Cloud Options


Please stop the turtles! Underlay is it’s own thing.

DISCLAIMER: “Abstractions are helpful till they are not” rant about using the right tools for the job follows…


Turtle Stacking From Dr Seuss’ Yertle The Turtle

I’ve been hearing the Hindu phrase “turtles all the way down” very often lately to describe the practice of using products to try and install themselves (my original posting attributed this to Dr Seuss) .  This seems especially true of the container platforms that use containers to install containers that manage the containers.  Yes, really – I don’t make this stuff up.


While I’m a HUGE fan of containers (RackN uses them like crazy with Digital Rebar), they do not magically solve operational issues like security, upgrade or networking.  In fact, they actually complicate operational concerns by creating additional segmentation.

Solving these issues requires building a robust, repeatable, and automated underlay.  That is a fundamentally different problem than managing containers or virtual machines.  Asking container or VM abstraction APIs to do underlay work breaks the purpose of the abstraction which is to hide complexity.

The lure of a universal abstraction, the proverbial “single pane of glass,” is the ultimate siren song that breeds turtle recursion. 

I’ve written about that on DevOps.com in a pair of articles: It’s Time to Slay the Universal Installer Unicorn and How the Lure of an ‘Easy Button’ Installer Traps Projects.  It seems obvious to me that universal abstraction is a oxymoron.

Another form of this pattern emerges from the square peg / round hole syndrome when we take a great tool and apply it to every job.  For example, I was in a meeting when I heard “If you don’t think Kubernetes is greatest way to deploy software then go away [because we’re using it to install Kubernetes].”  It may be the greatest way to deploy software for applications that fit its model, but it’s certainly not the only way.

What’s the solution?  We should accept that there are multiple right ways to manage platforms depending on the level of abstraction that we want to expose.

Using an abstraction in the wrong place, hides information that we need to make good decisions.  That makes it harder to automate, monitor and manage.  It’s always faster, easier and safer when you’ve got the right tool for the job.

Can we control Hype & Over-Vendoring?

Q: Is over-vendoring when you’ve had to much to drink?
A: Yes, too much Kool Aid.

There’s a lot of information here – skip to the bottom if you want to see my recommendation.

Last week on TheNewStack, I offered eight ways to keep Kubernetes on the right track (abridged list here) and felt that item #6 needed more explanation and some concrete solutions.

  1. DO: Focus on a Tight Core
  2. DO: Build a Diverse Community
  3. DO: Multi-cloud and Hybrid
  4. DO: Be Humble and Honest
  5. AVOID: “The One Ring” Universal Solution Hubris
  6. AVOID: Over-Vendoring (discussed here)
  7. AVOID: Coupling Installers, Brokers and Providers to the core
  8. AVOID: Fast Release Cycles without LTS Releases

kool-aid-manWhat is Over-Vendoring?  It’s when vendors’ drive their companies’ brands ahead of the health of the project.  Generally by driving an aggressive hype cycle where vendors are trying to jump on the hype bandwagon.

Hype can be very dangerous for projects (David Cassel’s TNS article) because it is easy to bypass the user needs and boring scale/stabilization processes to focus on vendor differentiation.  Unfortunately, common use-cases do not drive differentiation and are invisible when it comes to company marketing budgets.  That boring common core has the effect creating tragedy of the commons which undermines collaboration on shared code bases.

The solution is to aggressively keep the project core small so that vendors have specific and limited areas of coopetition.  

A small core means we do not compel collaboration in many areas of project.  This drives competition and diversity that can be confusing.  The temptation to endorse or nominate companion projects is risky due to the hype cycle.  Endorsements can create a bias that actually hurts innovation because early or loud vendors do not generally create the best long term approaches.  I’ve heard this described as “people doing the real work don’t necessarily have time to brag about it.”

Keeping a small core mantra drives a healthy plug-in model where vendors can differentiate.  It also ensures that projects can succeed with a bounded set of core contributors and support infrastructure.  That means that we should not measure success by commits, committers or lines of code because these will drop as projects successfully modularize.  My recommendation for a key success metric is to the ratio of committers to ecosystem members and users.

Tracking improving ratio of core to ecosystem shows that improving efficiency of investment.  That’s a better sign of health than project growth.

It’s important to note that there is also a serious risk of under-vendoring too!  

We must recognize and support vendors in open source communities because they sustain the project via direct contributions and bringing users.  For a healthy ecosystem, we need to ensure that vendors can fairly profit.  That means they must be able to use their brand in combination with the project’s brand.  Apache Project is the anti-pattern because they have very strict “no vendor” trademark marketing guidelines that can strand projects without good corporate support.

I’ve come to believe that it’s important to allow vendors to market open source projects brands; however, they also need to have some limits on how they position the project.

How should this co-branding work?  My thinking is that vendor claims about a project should be managed in a consistent and common way.  Since we’re keeping the project core small, that should help limit the scope of the claims.  Vendors that want to make ecosystem claims should be given clear spaces for marketing their own brand in participation with the project brand.

I don’t pretend that this is easy!  Vendor marketing is planned quarters ahead of when open source projects are ready for them: that’s part of what feeds the hype cycle. That means that projects will be saying no to some free marketing from their ecosystem.  Ideally, we’re saying yes to the right parts at the same time.

Ultimately, hype control means saying no to free marketing.  For an open source project, that’s a hard but essential decision.


Cloudcast.net gem about Cluster Ops Gap

15967Podcast juxtaposition can be magical.  In this case, I heard back-to-back sessions with pragmatic for cluster operations and then how developers are rebelling against infrastructure.

Last week, I was listening to Brian Gracely’s “Automatic DevOps” discussion with  John Troyer (CEO at TechReckoning, a community for IT pros) followed by his confusingly titled “operators” talk with Brandon Phillips (CTO at CoreOS).

John’s mid-recording comments really resonated with me:

At 16 minutes: “IT is going to be the master of many environments… If you have an environment is hybrid & multi-cloud, then you still need to care about infrastructure… we are going to be living with that for at least 10 years.”

At 18 minutes: “We need a layer that is cloud-like, devops-like and agile-like that can still be deployed in multiple places.  This middle layer, Cluster Ops, is really important because it’s the layer between the infrastructure and the app.”

The conversation with Brandon felt very different where the goal was to package everything “operator” into Kubernetes semantics including Kubernetes running itself.  This inception approach to running the cluster is irresistible within the community because the goal of the community is to stop having to worry about infrastructure.  [Brian – call me if you want to a do podcast of the counter point to self-hosted].

Infrastructure is hard and complex.  There’s good reason to limit how many people have to deal with that, but someone still has to deal with it.

I’m a big fan of container workloads generally and Kubernetes specifically as a way to help isolate application developers from infrastructure; consequently, it’s not designed to handle the messy infrastructure requirements that make Cluster Ops a challenge.  This is a good thing because complexity explodes when platforms expose infrastructure details.

For Kubernetes and similar, I believe that injecting too much infrastructure mess undermines the simplicity of the platform.

There’s a different type of platform needed for infrastructure aware cluster operations where automation needs to address complexity via composability.  That’s what RackN is building with open Digital Rebar: a the hybrid management layer that can consistently automate around infrastructure variation.

If you want to work with us to create system focused, infrastructure agnostic automation then take a look at the work we’ve been doing on underlay and cluster operations.


DevOps vs Cloud Native: Damn, where did all this platform complexity come from?

Complexity has always part of IT and it’s increasing as we embrace microservices and highly abstracted platforms.  Making everyone cope with this challenge is unsustainable.

We’re just more aware of infrastructure complexity now that DevOps is exposing this cluster configuration to developers and automation tooling. We are also building platforms from more loosely connected open components. The benefit of customization and rapid development has the unfortunate side-effect of adding integration points. Even worse, those integrations generally require operations in a specific sequence.

The result is a developer rebellion against DevOps on low level (IaaS) platforms towards ones with higher level abstractions (PaaS) like Kubernetes.
11-11-16-hirschfeld-1080x675This rebellion is taking the form of “cloud native” being in opposition to “devops” processes. I discussed exactly that point with John Furrier on theCUBE at Kubecon and again in my Messy Underlay presentation Defrag Conf.

It is very clear that DevOps mission to share ownership of messy production operations requirements is not widely welcomed. Unfortunately, there is no magic cure for production complexity because systems are inherently complex.

There is a (re)growing expectation that operations will remain operations instead of becoming a shared team responsibility.  While this thinking apparently rolls back core principles of the DevOps movement, we must respect the perceived productivity impact of making operations responsibility overly broad.

What is the right way to share production responsibility between teams?  We can start to leverage platforms like Kubernetes to hide underlay complexity and allow DevOps shared ownership in the right places.  That means that operations still owns the complex underlay and platform jobs.  Overall, I think that’s a workable diversion.

Provisioned Secure By Default with Integrated PKI & TLS Automation

Today, I’m presenting this topic (PKI automation & rotation) at Defragcon  so I wanted to share this background more broadly as a companion for that presentation.  I know this is a long post – hang with me, PKI is complex.

Building automation that creates a secure infrastructure is as critical as it is hard to accomplish. For all the we talk about repeatable automation, actually doing it securely is a challenge. Why? Because we cannot simply encode passwords, security tokens or trust into our scripts. Even more critically, secure configuration is antithetical to general immutable automation: it requires that each unit is different and unique.

Over the summer, the RackN team expanded open source Digital Rebar to include roles that build a service-by-service internal public key infrastructure (PKI).

untitled-drawingThis is a significant advance in provisioning infrastructure because it allows bootstrapping transport layer security (TLS) encryption without having to assume trust at the edges.  This is not general PKI: the goal is for internal trust zones that have no external trust anchors.

Before I explain the details, it’s important to understand that RackN did not build a new encryption model!  We leveraged the ones that exist and automated them.  The challenge has been automating PKI local certificate authorities (CA) and tightly scoped certificates with standard configuration tools.  Digital Rebar solves this by merging service management, node configuration and orchestration.

I’ll try and break this down into the key elements of encryption, keys and trust.

The goal is simple: we want to be able to create secure communications (that’s TLS) between networked services. To do that, they need to be able to agree on encryption keys for dialog (that’s PKI). These keys are managed in public and private pairs: one side uses the public key to encrypt a message that can only be decoded with the receiver’s private key.

To stand up a secure REST API service, we need to create a private key held by the server and a public key that is given to each client that wants secure communication with the server.

Now the parties can create secure communications (TLS) between networked services. To do that, they need to be able to agree on encryption keys for dialog. These keys are managed in public and private pairs: one side uses the public key to encrypt a message that can only be decoded with the receiver’s private key.

Unfortunately, point-to-point key exchange is not enough to establish secure communications.  It too easy to impersonate a service or intercept traffic.  

Part of the solution is to include holder identity information into the key itself such as the name or IP address of the server.  The more specific the information, the harder it is to break the trust.  Unfortunately, many automation patterns simply use wildcard (or unspecific) identity because it is very difficult for them to predict the IP address or name of a server.   To address that problem, we only generate certificates once the system details are known.  Even better, it’s then possible to regenerate certificates (known as key rotation) after initial deployment.

While identity improves things, it’s still not sufficient.  We need to have a trusted third party who can validate that the keys are legitimate to make the system truly robust.  In this case, the certificate authority (CA) that issues the keys signs them so that both parties are able to trust each other.  There’s no practical way to intercept communications between the trusted end points without signed keys from the central CA.  The system requires that we can build and maintain these three way relationships.  For public websites, we can rely on root certificates; however, that’s not practical or desirable for dynamic internal encryption needs.

So what did we do with Digital Rebar?  We’ve embedded a certificate authority (CA) service into the core orchestration engine (called “trust me”).  

The Digital Rebar CA can be told to generate a root certificate on a per service basis.  When we add a server for that service, the CA issues a unique signed certificate matching the server identity.  When we add a client for that service, the CA issues a unique signed public key for the client matching the client’s identity.  The server will reject communication from unknown public keys.  In this way, each service is able to ensure that it is only communicating with trusted end points.

Wow, that’s a lot of information!  Getting security right is complex and often neglected.  Our focus is provisioning automation, so these efforts do not cover all PKI lifecycle issues or challenges.  We’ve got a long list of integrations, tools and next steps that we’d like to accomplish.

Our goal was to automate building secure communication as a default.  We think these enhancements to Digital Rebar are a step in that direction.  Please let us know if you think this approach is helpful.