Why we can’t move past installers to talk about operations – the underlay gap

20 minutes.  That’s the amount of time most developers are willing to spend installing a tool or platform that could become the foundation for their software.  I’ve watched our industry obsess on the “out of box” experience which usually translates into a single CLI command to get started (and then fails to scale up).

Secure, scalable and robust production operations is complex.  In fact, most of these platforms are specifically designed to hide that fact from developers.  

That means that these platforms intentionally hide the very complexity that they themselves need to run effectively.  Adding that complexity, at best, undermines the utility of the platform and, at worst, causes distractions that keep us forever looping on “day 1” installation issues.

I believe that systems designed to manage ops process and underlay are different than the platforms designed to manage developer life-cycle.  This is different than the fidelity gap which is about portability. Accepting that allows us to focus on delivering secure, scalable and robust infrastructure for both users.

In a pair of DevOps.com posts, I lay out my arguments about the harm being caused by trying to blend these concepts in much more detail:

  1. It’s Time to Slay the Universal Installer Unicorn
  2. How the Lure of an ‘Easy Button’ Installer Traps Projects

Three reasons why Ops Composition works: Cluster Linking, Services and Configuration (pt 2)

In part pt 1, we reviewed the RackN team’s hard won insights from previous deployment automation. We feel strongly that prioritizing portability in provisioning automation is important. Individual sites may initially succeed building just for their own needs; however, these divergences limit future collaboration and ultimately make it more expensive to maintain operations.

aid1165255-728px-install-pergo-flooring-step-5-version-2If it’s more expensive isolate then why have we failed to create shared underlay? Very simply, it’s hard to encapsulate differences between sites in a consistent way.

What makes cluster construction so hard?

There are a three key things we have to solve together: cross-node dependencies (linking), a lack of service configuration (services) and isolating attribute chains (configuration).  While they all come back to thinking of the whole system as a cluster instead of individual nodes. let’s break them down:

Cross Dependencies (Cluster Linking) – The reason for building a multi-node system, is to create an interconnected system. For example, we want a database cluster with automated fail-over or we want a storage system that predictably distributes redundant copies of our data. Most critically and most overlooked, we also want to make sure that we can trust cluster members before we share secrets with them.

These cluster building actions require that we synchronize configuration so that each step has the information it requires. While it’s possible to repeatedly bang on the configure until it converges, that approach is frustrating to watch, hard to troubleshoot and fraught with timing issues.  Taking this to the next logical steps, doing upgrades, require sequence control with circuit breakers – that’s exactly what Digital Rebar was built to provide.

Service Configuration (Cluster Services) – We’ve been so captivated with node configuration tools (like Ansible) that we overlook the reality that real deployments are intertwined mix of service, node and cross-node configuration.  Even after interacting with a cloud service to get nodes, we still need to configure services for network access, load balancers and certificates.  Once the platform is installed, then we use the platform as a services.  On physical, there are even more including DNS, IPAM and Provisioning.

The challenge with service configurations is that they are not static and generally impossible to predict in advance.  Using a load balancer?  You can’t configure it until you’ve got the node addresses allocated.  And then it needs to be updated as you manage your cluster.  This is what makes platforms awesome – they handle the housekeeping for the apps once they are installed.

Digital Rebar decomposition solves this problem because it is able to mix service and node configuration.  The orchestration engine can use node specific information to update services in the middle of a node configuration workflow sequence.  For example, bringing a NIC online with a new IP address requires multiple trusted DNS entries.  The same applies for PKI, Load Balancer and Networking.

Isolating Attribute Chains (Cluster Configuration) – Clusters have a difficult duality: they are managed as both a single entity and a collection of parts. That means that our configuration attributes are coupled together and often iterative. Typically, we solve this problem by front loading all the configuration. This leads to several problems: first, clusters must be configured in stages and, second, configuration attributes are predetermined and then statically passed into each component making variation and substitution difficult.

Our solution to this problem is to treat configuration more like functional programming where configuration steps are treated as isolated units with fully contained inputs and outputs. This approach allows us to accommodate variation between sites or cluster needs without tightly coupling steps. If we need to change container engines or networking layers then we can insert or remove modules without rewriting or complicating the majority of the chain.

This approach is a critical consideration because it allows us to accommodate both site and time changes. Even if a single site remains consistent, the software being installed will not. We must be resilient both site to site and version to version on a component basis. Any other pattern forces us to into an unmaintainable lock step provisioning model.

To avoid solving these three hard issues in the past, we’ve built provisioning monoliths. Even worse, we’ve seen projects try to solve these cluster building problems within their own context. That leads to confusing boot-strap architectures that distract from making the platforms easy for their intended audiences. It is OK for running a platform to be a different problem than using the platform.
In summary, we want composition because we are totally against ops magic.  No unicorns, no rainbows, no hidden anything.

Basically, we want to avoid all magic in a deployment. For scale operations, there should never be a “push and prey” step where we are counting on timing or unknown configuration for it to succeed. Those systems are impossible to maintain, share and scale.

I hope that this helps you look at the Digital Rebar underlay approach in a holistic why and see how it can help create a more portable and sustainable IT foundation.

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

too easy to bare metal? Ansible just works with OpenCrowbar

2012-01-15_10-21-12_716I’ve talked before about how OpenCrowbar distributes SSH keys automatically as part of its deployment process.  Now, it’s time to unleash some of the subsequent magic!

[5/21 Update: We added the “crowbar-access” role to the Drill release that allows you to inject/remove keys on a per node basis from the API or CLI at any point in the node life-cycle]

If you provision servers with your keys in place, then Ansible will just work with truly minimal configuration (one line in a file!).

Video Demo (steps bellow):

Here are my steps:

  1. Install OpenCrowbar and run some nodes to ready state [videos]
  2. Install Ansible [simple steps]
  3. Add hosts range “192.168.124.[81:83]  ansible_ssh_user=root” to the
    “/etc/ansible/hosts” file
  4. If you are really lazy, add “[Default] // host_key_checking = False” to your “~/.ansible.cfg” file
  5. now ping the hosts, “ansible all -m ping”
  6. pat yourself on the back, you’re done.
  7. to show off:
    1. touch all machines “ansible all -a “/bin/echo hello”
    2. look at types of Linux “ansible all -a “uname -a”

Further integration work can make this even more powerful.  

I’d like to see OpenCrowbar generate the Ansible inventory file from the discovery data and to map Ansible groups from deployments.  Crowbar could also call Ansible directly to use playbooks or even do a direct hand-off to Tower to complete an install without user intervention.

Wow, that would be pretty handy!   If you think so too, please join us in the OpenCrowbar community.

OpenCrowbar v2.1 Video Tour from Metal to OpenStack and beyond

With the OpenCrowbar v2.1 out, I’ve been asked to update the video library of Crowbar demos.  Since a complete tour is about 3 hours, I decided to cut it down into focused demos that would allow you to start at an area of interest and work backwards.

I’ve linked all the videos below by title.  Here’s a visual table on contents:

Video Progression

Crowbar v2.1 demo: Visual Table of Contents [click for playlist]

The heart of the demo series is the Annealer and Ready State (video #3).

  1. Prepare Environment
  2. Bootstrap Crowbar
  3. Add Nodes ♥ Ready State (good starting point)
  4. Boot Hardware
  5. Install OpenStack (Juno using PackStack on CentOS 7)
  6. Integrate with Chef & Chef Provisioning
  7. Integrate with SaltStack

I’ve tried to do some post-production so limit dead air and focus on key areas.  As always, I value content over production values so feedback is very welcome!

Delicious 7 Layer DIP (DevOps Infrastructure Provisioning) model with graphic!

Applying architecture and computer science principles to infrastructure automation helps us build better controls.  In this post, we create an OSI-like model that helps decompose the ops environment.

The RackN team discussions about “what is Ready State” have led to some interesting realizations about physical ops.  One of the most critical has been splitting the operational configuration (DNS, NTP, SSH Keys, Monitoring, Security, etc) from the application configuration.

Interactions between these layers is much more dynamic than developers and operators expect.  

In cloud deployments, you can use ask for the virtual infrastructure to be configured in advance via the IaaS and/or golden base images.  In hardware, the environment build up needs to be more incremental because that variations in physical infrastructure and operations have to be accommodated.

Greg Althaus, Crowbar co-founder, and I put together this 7 layer model (it started as 3 and grew) because we needed to be more specific in discussion about provisioning and upgrade activity.  The system view helps explain how layer 5 and 6 operate at the system layer.

7 Layer DIP

The Seven Layers of our DIP:

  1. shared infrastructure – the base layer is about the interconnects between the nodes.  In this model, we care about the specific linkage to the node: VLAN tags on the switch port, which switch is connected, which PDU ID controls turns it on.
  2. firmware and management – nodes have substantial driver (RAID/BIOS/IPMI) software below the operating system that must be configured correctly.   In some cases, these configurations have external interfaces (BMC) that require out-of-band access while others can only be configured in pre-install environments (I call that side-band).
  3. operating system – while the operating system is critical, operators are striving to keep this layer as thin to avoid overhead.  Even so, there are critical security, networking and device mapping functions that must be configured.  Critical local resource management items like mapping media or building network teams and bridges are level 2 functions.
  4. operations clients – this layer connects the node to the logical data center infrastructure is basic ways like time synch (NTP) and name resolution (DNS).  It’s also where more sophisticated operators configure things like distributed cache, centralized logging and system health monitoring.  CMDB agents like Chef, Puppet or Saltstack are installed at the “top” of this layer to complete ready state.
  5. applications – once all the baseline is setup, this is the unique workload.  It can range from platforms for other applications (like OpenStack or Kubernetes) or the software itself like Ceph, Hadoop or anything.
  6. operations management – the external system references for layer 3 must be factored into the operations model because they often require synchronized configuration.  For example, registering a server name and IP addresses in a DNS, updating an inventory database or adding it’s thresholds to a monitoring infrastructure.  For scale and security, it is critical to keep the node configuration (layer 3) constantly synchronized with the central management systems.
  7. cluster coordination – no application stands alone; consequently, actions from layer 4 nodes must be coordinated with other nodes.  This ranges from database registration and load balancing to complex upgrades with live data migration. Working in layer 4 without layer 6 coordination creates unmanageable infrastructure.

This seven layer operations model helps us discuss which actions are required when provisioning a scale infrastructure.  In my experience, many developers want to work exclusively in layer 4 and overlook the need to have a consistent and managed infrastructure in all the other layers.  We enable this thinking in cloud and platform as a service (PaaS) and that helps improve developer productivity.

We cannot overlook the other layers in physical ops; however, working to ready state helps us create more cloud-like boundaries.  Those boundaries are a natural segue my upcoming post about functional operations (older efforts here).