Introducing NRE Labs by James Kelly


“The 80s called and they want their CLI back.” Until recently, that was basically the beckoning call of the network automation and programmability plot. Like a broken record, the replayed attention on tools and APIs talked of new NetOps technology, but it didn’t paint a picture of the promised land. It didn’t provide a map and it didn’t prepare anyone professionally.

Today, as Network Reliability Engineering (NREs) roles pave the way from CLIs to SLIs and other higher-order SRE-inspired methods and metrics, the picture of automated NetOps is crystalizing. Juniper Networks has elaborated the 5-step map of the journey. And now, with the launch of NRE Labs, Juniper is introducing the virtual training camp to support the trip to the promised land. It’s open—open source and open for use—and it’s by and for network engineers.

People are the greatest asset or predicament to any transformation like automating NetOps, so this is where the focus was on democratizing NRE learning for all.

An Automation Dojo in the Browser

For most network engineers, automating has either been an ad hoc adventure, or the barrier to entry has stopped engineers from starting. And without the right roots, asking for automation from network engineers is like asking for pears from a pine tree. Hands-on time is needed to form the software engineering skills and experience needed to architect and automate.

Providing a cheap, quick and easy solution, NRE Labs is free and easily accessible. It includes live terminal access to one’s own network devices and linux systems, right in the browser. Each learning lab topic is pieced apart into lessons that are, in turn, comprised of short lab steps that each take only a couple minutes. This is important because it eliminates those overwhelming obstacles to getting started with hands-on learning.

  • It removes the risk of learning by trial and error in production

  • It doesn’t require a sign-up and doesn’t have a classroom or a teacher

  • It doesn't require a long download or physical or virtual lab setup times

  • It doesn’t demand expertise or painful piecing together of all the background infrastructure

  • It demands zero prerequisite knowledge of tools and programming

Without any major impediments, anybody can jump right in and click through a few lessons right in their web browser.

The main NRE Labs runtime sponsored by Juniper Networks is available at:

Learn by Doing

Education that isn’t applied is quickly forgotten. That’s why the topics and lessons in NRE Labs are organized into real-life NetOps contexts and workflows. NRE Labs is also built with useful systems and tools that are widely available and applicable to network engineers today.

NRE Labs was created to be accessible to anyone, so it starts from scratch with a learning topic for basics, but users can move around lessons as they see fit. Other topics include troubleshooting, configuration, testing and verification. In the future, additional lessons will take these topics deeper and additional topics will take learning broader. This includes covering the spectrum of NetOps workflows; structuring automation and infrastructure as code with gitOps rigor; evolving troubleshooting into proactive testing; orchestrating testing, delivery and deployment with a pipeline; and using telemetry and analytics for monitoring and measuring service-level indicators and automating network remediation and regulation.

Open for Contributions

NRE Labs needs to be open to democratize learning across different networking environments, but it’s also open to keep up with the rate of and scale it to all kinds of innovators broadly automating their networks that have something to share.

The NRE Labs back-end infrastructure and front-end lessons are all open source as the NRE Learning Antidote project and code repository on GitHub. The project’s documentation explores some background on the Kubernetes-based Antidote infrastructure and explains how to run a standalone instance of NRE Labs to develop, test and contribute improvements and lessons.

For the express documentation, Juniper has open sourced the NRE Labs project summary as a poster.

While NRE Labs is live today, it’s in tech preview and we’re looking for quick iterative progress over delayed perfection. We welcome contributions! Other than curriculum development, some of the back-end work revolves around hardening and scaling the infrastructure and shortening start times of network nodes. We’d also greatly appreciate front-end work such as mobile optimizations. Suggestions are welcome and are already flowing in. Use the project’s issues tracker on GitHub to find work or share feedback.

To be Continued

Notice that NRE is learning created by and for network engineers and free of external marketing. You can use it anonymously, but we hope you’ll tell us what you think. 

Beyond learning new NRE and automation skills, NRE Labs aims to spark new, open conversations to listen to or chime in. Follow @nrelabs for updates on new content, improvements and more. We also created an #nre_labs channel in the Slack spaces for the Juniper Engineering Network (EngNet) (Join here) and the vendor-neutral space run by Network2Code (Join here).

Please spread this day-one news and follow the blogs as lessons continue to roll out.

See you in the community,

@mierdin@cloudtoad and @jameskellynet from the NRE Learning Team

This blog was originally published at

5 Steps to Automated NetOps by James Kelly


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In Juniper Networks anthology of 5-step frameworks, we take a different turn. Instead of focusing on a network domain vertical like the 5-steps for data center, campus, WAN and branch, we are focused horizontally across all domains on network automation. This 5-step can apply to any place in network, and be overlaid like a transparency, for example, over the data center 5-step.

5-step automated netops.png

Not 5 Steps to Network Automation

Sometimes you climb the ladder only to find it's standing against the wrong wall. 

In the pursuit of network automation, a multi-decade long affair, the narrative and advancements mostly revolved around programmability which gave way to NFV and SDN. Despite those developments, network automation seems to have ricocheted back to center. We’ve realized that the average NetOps job has practically been sealed in a time capsule compared to the evolution of software engineering and related DevOps and SRE movements.

That’s not to say network automation hasn’t gone anywhere, but progress has largely been technological in the inner-workings of products: we have slightly more autonomous systems; we have abstracted and elevated systems across more network surface area; and we’ve created more APIs, making systems more automatable. Alas, all this one-sided network automation does not an automated network make.

What has failed to change? The forlorn customer and NetOps opportunity for automation.

The handoff from vendor to customer is still, on average, very siloed and impetuous. NetOps catch what comes over the proverbial Dev-Ops wall and then has to run it. Then starts the same old crucible of some inaugural architecting, some less-agreeable administration and then hapless eons of daily toil and troubleshooting, trying to uphold availability. And we cannot forget our “friend,” IT gravity: pulling down issue triaging and blame fastest to the lowest common denominator, the network.

In brooding over that experience, surely NetOps itself is where the emphasis on automation is needed most, to evolve from automatable to automated. And the metamorphosis process cannot consider automation in the vacuum of technology alone, but rather must pay particular attention to ameliorating people and processes.

Where to Begin? 

Transforming people and process, it turns out, is hard, but luckily there are bright spots to replicate. The DevOps movement copied the lessons of the manufacturing industry to change the way software engineering was done, and now the most successful NetOps teams are essentially copying DevOps.

It also turns out that network engineers don’t fancy being called developers because developers and associated app teams are often the ones dropping the headaches, falling with that IT gravity, down upon network engineers’ heads. While most don’t mind the term DevOps or DevNetOps, implying “developer” may induce ire and make network engineers want to duck for cover. Moreover, DevOps is a fairly amorphous set of principles, so the leading NetOps teams have drawn inspiration from site reliability engineering (SRE), a prescriptive implementation of DevOps and dubbed their transformational job: network reliability engineering (NRE).

This 5-step framework to automating NetOps is a journey to a more self-driving network, but most of all, a journey of engineering reliability and simplicity. The journey stars upskilled network reliability engineers capable of some coding and wielding the tools of automation to manage the service-level goals and indicators of reliability.

Think of the framework as a map. As you orient yourself and direct your path, you’ll see progress is seldom a straight line, and it won’t begin in the same place for everyone. In all likelihood, most networkers are at Step 1, manual ops, riding the pine in the automation game and gingerly operating their networks by the ITIL book. But we’re convinced that engineers are dedicated lifelong learners and their stagnation at Step 1 is not so much from hesitation, but rather because they’re busy firefighting and the network automation narrative has not addressed them directly until the rise of NRE.

The importance of taking the first step cannot be overstated, yet it has also historically been daunting and difficult for engineers without a software engineering background. This is why Juniper has just launched EngNet, NRE Labs, ATOM, free trials, hosted trials, labs, training and services to ease the first small steps to automating. 

Reaching for Step 2, once you scientifically dissects some NetOps workflows then re-engineer what were manual tasks with some coding and tools, it’s a virtual gateway and virtuous cycle to more automating. Finding, sharing and using these tools, you also buy yourself more time to automate, partaking in less toil.


Step 1 - Manual Ops

Manual ops are actually very useful for teaching how things work and fit together, but for tasks that are arduous, lengthy and especially repetitive, network engineers need to begin to document their tribal knowledge and workflows and assess the ROI of automating them.

To move to Step 2:

  • Adopt an automator’s mindset. Be a builder and a technologist, not a technician

  • Take documented workflows and automate them. At this stage it can be any ad hoc workflow to cut one’s teeth coding and using new tools for speed, scale and consistency

  • In addition to using the CLI documentation, explore the API documentation for systems

  • Find tools that already exist and dissect them. And build those that are customized and contextual to NetOps workflows.

  • Realize the value of abstractions and SDN so that the re-creation of automation at the box-to-box or lower levels does not have to occur unnecessarily where proven systems exist. Automate on top of them.

Step 2 - Automate Workflows

In Step 2, you take documented workflows or their pseudocode and start automating small wins. The biggest pay off is in repetitive troubleshooting workflows, which are in fact an early form of testing and verification that will be useful in Step 3. Troubleshooting read-only workflows are a safer bet than re-configuration, re-deploy or read-write workflows. Automating changes during maintenance windows mitigates risk. But ultimately maintenance windows are an IT anti-pattern to avoid and changes are best handled with the reliability of a pipeline introduced in later steps.

To move to Step 3:

  • Progress beyond ad hoc automating. Begin to practice as-code and “GitOps” developer-like behaviors. Code means codifying, not necessarily programming. Use SCM workflows and a versioned source of truth for all artifacts, configurations and creations.

  • Configuration is not distributed and perpetually drifting, but declarative and codified and its changes are reviewed, as are programmed automated workflows.

  • Begin to think proactively of how to eliminate mistakes and manual triggers with both testing and sensors.

  • Connect the “then that” Step-2 automated and aggregate tasks that were manually triggered to now start getting automatically triggered. Thus, begin automating the “if this” to trigger the “then that.”

  • Use APIs and data from systems like Juniper AppFormix or other telemetry collectors and analytics systems in: 1. observability and decision making, moving to NRE service-level indicator tooling; 2. proactive testing instead of relying solely on reactive troubleshooting; and 3. automating “if this” sensors.

Step 3 - Automated Triggers and Networks as Code

Beyond provisioning, scripting and programming languages, at Step 3 you’re learning GitOps, version control and code reviewing. You’re embracing infrastructure as code and thinking about automating troubleshooting as testing and proactive verification. Test-driven network automation is inspired from test-driven development (TDD). It’s not sufficient to simply run scripts and fix problems later; but instead must build holistic tests that protect from failures.

Beyond proactive tests, we can be proactive about triggering some automated actions where event-driven frameworks will help. And proactive triggering requires building or using sensors. Sensors are sometimes based on telemetry and analytics systems that are also useful for providing or building service-levels indicators.

To move to Step 4:

  • Adopt a QA and testing mindset in making all changes, automating not only consistency, but accuracy as well.

  • Testing processes are inserted in between “as-code” and deployment on a pipeline. Congruent to software engineers using a DevOps pipeline, we could optionally call this a DevNetOps pipeline or networking CICD pipeline, like Juniper’s NITA framework.

  • Move toward expediting more frequent deployments without maintenance-window woes because of higher confidence in automated change testing.

Step 4 - Continuous Processes and Pipeline

Here, the technology and automation runtime takes on a new axis of pre-production instead of only in-production. Step 4 adds a CICD pipeline for running automated testing.

Continuous integration (CI) allows being able to integrate code changes at any time. For example, these could include programming changes or a configuration change. Reliable changes are made possible thanks to automated testing. The automated merging of sometimes concurrent changes into a safely tested main line and building the artifacts necessary for deployment is continuous delivery (CD).

Automating the deployment itself is also wise (here’s a customer example) and reaches toward continuous deployment (also CD). And even actual continuous deployment still involves manual judgements. Truly deploying any time, especially following the immutable infrastructure pattern, can cause controlled, isolated outages that require architecting and automating around the outage to preserve availability and not drop traffic. In microservice-crafted software, deployment patterns like blue-green, canary or rolling upgrades are more readily possible, but networks are not traditionally designed and architected for such things, although today some SDN systems are, and redundant or sliced hardware systems are closer to enabling it. 

Beyond CICD, continuous response (CR) extends the event-driven if-this then-that from Step 3. Also CR acts mostly in production instead of in the phases of pre-production and deployment. CR with machine learning, deep learning and big-data analytics can be used for observability and automated regulation of networking systems to achieve optimization and efficiency far closer to the edge of the envelope than what a human would manage. See the Juniper blogs on self-driving networks for more on this concept.

To move to Step 5:

  • Evolve tooling and thinking to NRE / SRE concepts

  • Operations culture, observability and planning is data driven

  • Seek to understand system efficiency, effectiveness and satisfaction to customers (e.g. the up-stack IT organization or an SP’s actual customers)

  • Use chaos engineering and experimentation to understand system boundaries, limits and dependencies to optimize and plan for capacity and what-if scenarios.

Step 5 - Engineering Outcomes

While Step 5 is the last step, it’s still one of continual learning and growth. This allows quick and safe iteration on the network and fine tuning of processes to focus on higher-order reliability metrics and other goals. Don’t stop at network uptime—dive deeper and continuously improve the ability to respond to issues and change.

The network ceases to be the center of the universe in this step and an NRE specialized in networking will manage reliability with error budgets, toil budgets and service-level indicators (SLIs) like any other SRE. They do this for themselves with service-level objectives (SLOs) and for their dependents with service-level agreements (SLAs). They consider their reliability dependencies; for example, they may have reliability dependencies on software running on infrastructure outside of their control.  

An NRE in this step has a world view in layers of separate concerns and understands their place in the stack.

With agreements, automation and tradeoffs, reliability is a goal to be managed, not necessarily maximized. Speed, agility, efficiency and other successes are incidental for the NRE meter that holds reliability and availability prerequisites to other useful economies.

Flip through our 5-step framework slides to learn more. Technologists seem mostly gripped by the 5-step tool landscape slide, but progress is less about what you use and more about how you use it.

Please leave a comment below about your journey and lessons, and finally, thanks for sharing these ideas—long been missing in the automation discourse.

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The Wisdom of the Giants in SD-WAN by James Kelly


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When it comes to your branch how can SD-WAN upgrade without also uprooting? Tall trees may tell.

A Branch’s Reach Should Not Exceed Its Grasp

They are the showy exterior of your organization: your branches, your stores, your schools, your sites. But insofar as networking domains, these are the humblest of locations with little or no networking expertise and sophistication. In the past, your networking grasp was feeble in the far reaches of the branch.

Now the story goes that SD-WAN is changing that. It’s putting the prowess of your brightest networking pros and the autopilot  automation of SDN steadily into these network extremities. But this is only the beginning of the story. So allow me to disabuse you from the enrapture of the shining fruits and perfumed flowers of the branch that is SD-WAN today.

You have been tricked. This was not the story, merely the first act.

Focusing on SD-WAN, my friends, we see the fruits. Take a step back and look wider. Now we see the tree. Now we see the roots.

One Tree: Everything Is Connected

The levity with which some people and vendors approach branch networking with SD-WAN quickly fades when they realize the simple truth that, beyond the branch, everything is connected. It is one tree.

Ungrounded SD-WAN solutions ignore what’s below the branches and clouds at tree tops. But approaching enterprise networking grounded in reality, you see the whole picture: your wide-area is not only your remote and branch connectivity. Everything is connected between branch sites, campuses, headquarters, data centers, and certainly today, multicloud—SaaS and your own cloud-based applications.

You would never be so credulous as to protect a tree’s exterior, believing it’s safe from harm. And no one would mistake strung-up ornaments for the tree itself. How about vines overlaying the tree? Yes, they could reach the branches. But they still aren’t your tree, nor its species, and they cannot be grafted on. This is SD-WAN for dummies and by decoration, but it parallels some SD-WAN propaganda.

SD-WAN savvy would never use proprietary control and data plane protocols that won’t graft and interoperate with your wider network. Security would not be secondary and sheath, but foremost in the immune system of the network first. Add-on network functions like VNFs would be symbiotic and seamless with network design and management. And other virtualized branch services would felicitously fold into the SD-Branch canopy or NFV-centers in nearby limbs.

This is multicloud and multi-site thinking, end to end and top to bottom. While its natural given Juniper’s portfolio, it’s quite different than the thinking of some other SD-WAN vendors whose niche interests, I leave to be addressed with the words of a fine woodsman. “When we try to pick out anything by itself, we find it hitched to everything else in the universe.” -John Muir

Layer Upon Layer

Just under the bark are the newest layers of a tree. Pushing out and up, a tree’s trunk core and deep roots nourish new growth and give it strength to endure the tests of time.

Drawing a parallel to networking growth and longevity, you may have observed this strategy at Juniper, where investment is steadfast in Junos and our platforms. Customers enjoy the benefit of this continuity, as investment protection and the ability to simply extend and build on base systems with SDN, like SD-WAN, employing our NFX, SRX, and MX Series systems and interoperating with the routing of all Junos-powered platforms.

You may observe another approach in the industry too. Vendors that continually force rip and replacement of systems. There are sales motivations for this, but another cause runs deeper...

When you engineer something anew, you usually architect for a minimum viable product and getting to market quickly. Take a tech startup for example: it’s faster to build software as a monolith or a mesh of purely cloud services, than to construct a devops pipeline, platform architecture, and microservices that scale. Taking that MVP route, eventually they will throw away their early work, to redo it at scale, with extensibility, with reliability and economically. This is invisible to customers of SaaS companies, but when translated to packaged-and-sold hardware and software systems, this architecture fetters customers with technical debt and forces rip and replacement inefficiency.

In networking, it’s wiser to sow scale and flexibility into the seeds of your base networking technologies and topologies. Architecting for growth in layers, allows you to scale your rootstock and your core so to speak, evolving today’s investments tomorrow.

Evolvable architecture is how the cloud giants design their software, and happens to be how Juniper designs our portfolio. This is why we did not acquire an SD-WAN solution. And this is why we built SD-WAN backward: we tackled the hard problems first (multi-tenancy, scale, reliability, NFV, etc.), so we could design once and for all, and offer the simplicity of one solution.

Reach for the Clouds

With so many SD-WAN solutions in the market, and mostly built with haste, as you might imagine, the winds of technology change will cause many to snap and topple. They weren’t designed beyond SD-WAN connections for the branch and cloud endpoints.

The wisdom of giant trees would suggest that as you reach for the multicloud, strength lies in swaying and adapting with the winds of change, and evolving and using the strength of the whole.

About Juniper Contrail SD-WAN

Juniper’s newly dubbed Contrail SD-WAN solution and its component parts were designed to inherently secure from within and to scale to support thousands of tenants each with thousands of sites. It was designed where SD-WAN is merely the first act of your transformation story. So it will grow with you to SD-Branch for site virtualization and consolidation, and even incorporate NFV-cloud services into your network service. Of course it’s multicloud-ready, connecting up to the likes of AWS, but just as importantly, it ties right into your core WAN routing today from your campuses and data centers.

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