A year of RackN – 9 lessons from the front lines of evangalizing open physical ops

Let’s avoid this > “We’re heading right at the ground, sir!  Excellent, all engines full power!

another scale? oars & motors. WWF managing small scale fisheries

RackN is refining our from “start to scale” message and it’s also our 1 year anniversary so it’s natural time for reflection. While it’s been a year since our founders made RackN a full time obsession, the team has been working together for over 5 years now with the same vision: improve scale datacenter operations.

As a backdrop, IT-Ops is under tremendous pressure to increase agility and reduce spending.  Even worse, there’s a building pipeline of container driven change that we are still learning how to operate.

Over the year, we learned that:

  1. no one has time to improve ops
  2. everyone thinks their uniqueness is unique
  3. most sites have much more in common than is different
  4. the differences between sites are small
  5. small differences really do break automation
  6. once it breaks, it’s much harder to fix
  7. everyone plans to simplify once they stop changing everything
  8. the pace of change is accelerating
  9. apply, rinse, repeat with lesson #1

Where does that leave us besides stressed out?  Ops is not keeping up.  The solution is not to going faster: we have to improve first and then accelerate.

What makes general purpose datacenter automation so difficult?  The obvious answer, variation, does not sufficiently explain the problem. What we have been learning is that the real challenge is ordering of interdependencies.  This is especially true on physical systems where you have to really grok* networking.

The problem would be smaller if we were trying to build something for a bespoke site; however, I see ops snowflaking as one of the most significant barriers for new technologies. At RackN, we are determined to make physical ops repeatable and portable across sites.

What does that heterogeneous-first automation look like? First, we’ve learned that to adapt to customer datacenters. That means using the DNS, DHCP and other services that you already have in place. And dealing with heterogeneous hardware types and a mix of devops tools. It also means coping with arbitrary layer 2 and layer 3 networking topologies.

This was hard and tested both our patience and architecture pattern. It would be much easier to enforce a strict hardware guideline, but we knew that was not practical at scale. Instead, we “declared defeat” about forcing uniformity and built software that accepts variation.

So what did we do with a year?  We had to spend a lot of time listening and learning what “real operations” need.   Then we had to create software that accommodated variation without breaking downstream automation.  Now we’ve made it small enough to run on a desktop or cloud for sandboxing and a new learning cycle begins.

We’d love to have you try it out: rebar.digital.

* Grok is the correct work here.  Thinking that you “understand networking” is often more dangerous when it comes to automation.

Introducing Digital Rebar. Building strong foundations for New Stack infrastructure

digital_rebarThis week, I have the privilege to showcase the emergence of RackN’s updated approach to data center infrastructure automation that is container-ready and drives “cloud-style” DevOps on physical metal.  While it works at scale, we’ve also ensured it’s light enough to run a production-fidelity deployment on a laptop.

You grow to cloud scale with a ready-state foundation that scales up at every step.  That’s exactly what we’re providing with Digital Rebar.

Over the past two years, the RackN team has been working on microservices operations orchestration in the OpenCrowbar code base.  By embracing these new tools and architecture, Digital Rebar takes that base into a new directions.  Yet, we also get to leverage a scalable heterogeneous provisioner and integrations for all major devops tools.  We began with critical data center automation already working.

Why Digital Rebar? Traditional data center ops is being disrupted by container and service architectures and legacy data centers are challenged with gracefully integrating this new way of managing containers at scale: we felt it was time to start a dialog the new foundational layer of scale ops.

Both our code and vision has substantially diverged from the groundbreaking “OpenStack Installer” MVP the RackN team members launched in 2011 from inside Dell and is still winning prizes for SUSE.

We have not regressed our leading vendor-neutral hardware discovery and configuration features; however, today, our discussions are about service wrappers, heterogeneous tooling, immutable container deployments and next generation platforms.

Over the next few days, I’ll be posting more about how Digital Rebar works (plus video demos).

Deploy to Metal? No sweat with RackN new Ansible Dynamic Inventory API

Content originally posted by Ansibile & RackN so I added a video demo.  Also, see Ansible’s original post for more details about the multi-vendor “Simple OpenStack Initiative.”

The RackN team takes our already super easy Ansible integration to a new level with added SSH Key control and dynamic inventory with the recent OpenCrowbar v2.3 (Drill) release.  These two items make full metal control more accessible than ever for Ansible users.

The platform offers full key management.  You can add keys at the system. deployment (group of machines) and machine levels.  These keys are operator settable and can be added and removed after provisioning has been completed.  If you want to control access to groups on a servers or group of server basis, OpenCrowbar provides that control via our API, CLI and UI.

We also provide a API path for Ansible dynamic inventory.  Using the simple Python client script (reference example), you can instantly a complete upgraded node inventory of your system.  The inventory data includes items like number of disks, cpus and amount of RAM.  If you’ve grouped machines in OpenCrowbar, those groups are passed to Ansible.  Even better, the metadata schema includes the networking configuration and machine status.

With no added configuration, you can immediately use Ansible as your multi-server CLI for ad hoc actions and installation using playbooks.

Of course, the OpenCrowbar tools are also available if you need remote power control or want a quick reimage of the system.

RackN respects that data centers are heterogenous.  Our vision is that your choice of hardware, operating system and network topology should not break devops deployments!  That’s why we work hard to provide useful abstracted information.  We want to work with you to help make sure that OpenCrowbar provides the right details to create best practice installations.

For working with bare metal, there’s no simpler way to deliver consistent repeatable results

OpenCrowbar 2.3 (Drill) Overview Videos

Last week, Scott Jensen, RackN COO, uploaded a batch of OpenCrowbar install and demo videos.  I’ve presented them in reverse chronological order so you can see what OpenCrowbar looks like before you run the installation process.

But…If you want to start downloading while you watch, here are the docs.

Please reach out on chat, email or irc (Freenode #crowbar) channels during your install and let us know how it’s going!

OpenCrowbar Basics & Provisioning (recommended start)

OpenCrowbar Install

OpenCrowbar Setup the Environment (install prep)

DNS is critical – getting physical ops integrations right matters

Why DNS? Maintaining DNS is essential to scale ops.  It’s not as simple as naming servers because each server will have multiple addresses (IPv4, IPv6, teams, bridges, etc) on multiple NICs depending on the systems function and applications. Plus, Errors in DNS are hard to diagnose.

Names MatterI love talking about the small Ops things that make a huge impact in quality of automation.  Things like automatically building a squid proxy cache infrastructure.

Today, I get to rave about the DNS integration that just surfaced in the OpenCrowbar code base. RackN CTO, Greg Althaus, just completed work that incrementally updates DNS entries as new IPs are added into the system.

Why is that a big deal?  There are a lot of names & IPs to manage.

In physical ops, every time you bring up a physical or virtual network interface, you are assigning at least one IP to that interface. For OpenCrowbar, we are assigning two addresses: IPv4 and IPv6.  Servers generally have 3 or more active interfaces (e.g.: BMC, admin, internal, public and storage) so that’s a lot of references.  It gets even more complex when you factor in DNS round robin or other common practices.

Plus mistakes are expensive.  Name resolution is an essential service for operations.

I know we all love memorizing IPv4 addresses (just wait for IPv6!) so accurate naming is essential.  OpenCrowbar already aligns the address 4th octet (Admin .106 goes to the same server as BMC .106) but that’s not always practical or useful.  This is not just a Day 1 problem – DNS drift or staleness becomes an increasing challenging problem when you have to reallocate IP addresses.  The simple fact is that registering IPs is not the hard part of this integration – it’s the flexible and dynamic updates.

What DNS automation did we enable in OpenCrowbar?  Here’s a partial list:

  1. recovery of names and IPs when interfaces and systems are decommissioned
  2. use of flexible naming patterns so that you can control how the systems are registered
  3. ability to register names in multiple DNS infrastructures
  4. ability to understand sub-domains so that you can map DNS by region
  5. ability to register the same system under multiple names
  6. wild card support for C-Names
  7. ability to create a DNS round-robin group and keep it updated

But there’s more! The integration includes both BIND and PowerDNS integrations. Since BIND does not have an API that allows incremental additions, Greg added a Golang service to wrap BIND and provide incremental updates and deletes.

When we talk about infrastructure ops automation and ready state, this is the type of deep integration that makes a difference and is the hallmark of the RackN team’s ops focus with RackN Enterprise and OpenCrowbar.

Hidden costs of Cloud? No surprises, it’s still about complexity = people cost

Last week, Forbes and ZDnet posted articles discussing the cost of various cloud (451 source material behind wall) full of dollar per hour costs analysis.  Their analysis talks about private infrastructure being an order of magnitude cheaper (yes, cheaper) to own than public cloud; however, the open source price advantages offered by OpenStack are swallowed by added cost of finding skilled operators and its lack of maturity.

At the end of the day, operational concerns are the differential factor.

The Magic 8 Cube

The Magic 8 Cube

These articles get tied down into trying to normalize clouds to $/vm/hour analysis and buried the lead that the operational decisions about what contributes to cloud operational costs.   I explored this a while back in my “magic 8 cube” series about six added management variations between public and private clouds.

In most cases, operations decisions is not just about cost – they factor in flexibility, stability and organizational readiness.  From that perspective, the additional costs of public clouds and well-known stacks (VMware) are easily justified for smaller operations.  Using alternatives means paying higher salaries and finding talent that requires larger scale to justify.

Operational complexity is a material cost that strongly detracts from new platforms (yes, OpenStack – we need to address this!)

Unfortunately, it’s hard for people building platforms to perceive the complexity experienced by people outside their community.  We need to make sure that stability and operability are top line features because complexity adds a very real cost because it comes directly back to cost of operation.

In my thinking, the winners will be solutions that reduce BOTH cost and complexity.  I’ve talked about that in the past and see the trend accelerating as more and more companies invest in ops automation.

Are VMs becoming El Caminos? Containers & Metal provide new choices for DevOps

I released “VMS ARE DEAD” this post two weeks ago on DevOps.com.  My point here is that Ops Automation (aka DevOps) is FINALLY growing beyond Cloud APIs and VMs.  This creates a much richer ecosystem of deployment targets instead of having to shoehorn every workload into the same platform.

In 2010, it looked as if visualization had won. We expected all servers to virtualize workloads and the primary question was which cloud infrastructure manager would dominate. Now in 2015, the picture is not as clear. I’m seeing a trend that threatens the “virtualize all things” battle cry.

IMG_20150301_170558985Really, it’s two intersecting trends: metal is getting cheaper and easier while container orchestration is advancing on rockets. If metal can truck around the heavy stable workloads while containers zip around like sports cars, that leaves VMs as a strange hybrid in the middle.

What’s the middle? It’s the El Camino, that notorious discontinued half car, half pick-up truck.

The explosion of interest in containerized workloads (I know, they’ve been around for a long time but Docker made them sexy somehow) has been creating secondary wave of container orchestration. Five years ago, I called that Platform as a Service (PaaS) but this new generation looks more like a CI/CD pipeline plus DevOps platform than our original PaaS concepts. These emerging pipelines obfuscate the operational environment differently than virtualized infrastructure (let’s call it IaaS). The platforms do not care about servers or application tiers, their semantic is about connecting services together. It’s a different deployment paradigm that’s more about SOA than resource reservation.

On the other side, we’ve been working hard to make physical ops more automated using the same DevOps tool chains. To complicate matters, the physics of silicon has meant that we’ve gone from scale up to scale out. Modern applications are so massive that they are going to exceed any single system so economics drives us to lots and lots of small, inexpensive servers. If you factor in the operational complexity and cost of hypervisors/clouds, an small actual dedicated server is a cost-effective substitute for a comparable virtual machine.

I’ll repeat that: a small dedicated server is a cost-effective substitute for a comparable virtual machine.

I am not speaking against virtualize servers or clouds. They have a critical role in data center operations; however, I hear from operators who are rethinking the idea that all servers will be virtualized and moving towards a more heterogeneous view of their data center. Once where they have a fleet of trucks, sports cars and El Caminos.

Of course, I’d be disingenuous if I neglected to point out that trucks are used to transport cars too. At some point, everything is metal.

Want more metal friendly reading?  See Packet CEO Zac Smith’s thinking on this topic.