If your messaging lurches too far out in front of you, you end up with missed user expectations and disappointment.

In this blog, we explore why, in a world of platform engineering, open source software and flip-a-switch cloud services, missing user expectations could be far more significant than it used to be. With the fashion for story telling, we look at the increased dangers of getting over-imaginative, and then explore some of the emerging technical marketing channels where creativity can be put to better use.

Creating a Fiction 

Tech marketing used to involve a lot more of the worst kind of creativity. Working in media relations over the past two decades, I lost count of the number of times my colleagues and I were asked to officially launch vaporware that was nearly ready, or software or services that (while they were exactly what the market wanted) were still very much in beta. 

Or take the user story, the former source of all success in tech PR and communications: C-suite decision makers were regaled with ‘imaginative’ tales of infamous business challenges and how bold new software solutions made them instamagically vanish. But then came the platform engineer… 

“Superb!” said Debbie DevOps. “Let me spin up your legendary solution and put it to the test.” 

                                                (Queue sad trombone.)

Where spinning was once the preserve of vendor communications teams, suddenly, there is a fresh face in town spinning up test instances across Kube and AWS with happy abandon. These engineers don’t buy into vendors’ tall marketing stories — but C-suite executives increasingly rely on these engineers to inform all of their purchasing decisions. 

The fact is, platform engineers won’t buy much of anything without trying it out first. And so, technology marketing and communications has been brought down to earth with a very heavy thud. Enterprise tech messaging was once built on bold claims laced with hyperbole and superlatives. But today, ‘the leading global providers of…’ now have just a few hours (at most — days) to start backing up their claims with a working demo or a plausible proof of concept (PoC). 

Catfish Marketing is Dead

In branding terms, creating any kind of artificial image has, thankfully, been replaced by a need for developing genuine identity. Ambition and vision are as relevant as ever. Keep reaching for the stars: just don’t leave prospective users relying on your extensive experience as an astronaut. 

We will explore why in the next section, but delighting users by carefully setting and managing expectations has not only replaced creating a more hyped, artificial image, it has become the only real way of attracting new users. 

Devops teams and platform engineers still weigh up the technical solutions to business challenges, and they assess the different options to achieve product/project goals. It would just be very unusual for them to start by looking at user stories in the traditional tech media. More likely, they ask a trusted friend and look for recommendations on developer social channels. 

Delight and disappointment — both get shared

User adoption now happens at the crossroads where tech challenges meet with: search engines, AI Assistants, Stack Overflow, Dev, Reddit or the Discord channel of a parallel open source project. This is where developers with real problems meet informed, trusted peers with real solutions. And there are two ways to get there — either by delighting or disappointing existing users!

Ensuring you are there for the right reasons is about early-stage product marketing — accurately identifying your target market. Any product vision that you share with users, can and should still be bold and creative (in its best sense). However, to avoid disaster, it needs to be firmly based on a real-world technical understanding of where, how and for which groups your product currently delivers its most tangible benefits. 

Traditional marcoms cannot materially improve a product or service, it cannot make it more delightful. However, a technically literate team with strong market knowledge can identify where your current capabilities have the greatest impact. Put simply, they can identify the groups where your offering delights new users the most, producing vital advocates and online champions. Furthermore, a skilled marcoms team should then analyse these success stories to help define, fulfill and refine your stated vision. This, in turn, creates a reinforcing, virtuous cycle: more targeted positioning attracts more of the right prospects and creates more delighted product champions. 

The New Place for Being Creative 

In areas where engineers and developers have become key decision influencers, technical papers and documentation, guides and tutorials are becoming powerful marketing collateral. 

A large part of successfully attracting and drawing-in prospects with this more technical marketing still lies in the market knowledge discussed above: research, targeting, retargeting, staying on top of shifting technology trends – tuning-in to those discussions happening down at the “crossroads”. 

Technical audiences want answers to the questions they actually have in front of them: the technical challenges they face, and the business challenges they are being asked to address – if your product/project is included in a practical guide for building the PoC that everyone is being asked for, it will do its own PR and social media marketing. 

But creativity still has an exciting role to play here. In many cases technical papers, guides and documentation are now where new users are guided into their first encounters with your product. This experience is not just an intro, it is an essential part of your product. 

You could draw the parallel here to what Apple pioneered with packaging in the 00’s: moving us on from cheap plastic and tear-open cardboard, towards beautiful, considered and tactile packaging materials that make unboxing a central part of the product experience. However, the Apple parallel (yes it is clichéd, sorry) doesn’t really go far enough, and only captures part of the picture. To be accurate, we would need to live in a world where bad packaging decisions would result in people discarding their MacBook Pro before they had finished opening it up. 

This should be a terrifying thought for many companies and projects out there because, as a whole, enterprise tech documentation is pretty terrible. Where documentation is even complete, it is typically a rushed afterthought from developers who were already focused on the far more interesting task of building the next feature.  

But what this really is, is a massive opportunity. Technical marketing is now the place to focus creativity and increasingly limited budgets, where it will make a real difference to your product and to adoption.

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Research from EDUCAUSE shows that 13% of colleges and universities are engaging in digital transformation today, 32% are developing a Digital Transformation strategy, and another 38% of higher education institutions are exploring Dx. With only 17% of institutions investing no time in Dx.

We have all heard (ad nauseam) that ‘data is the new oil’. But, much like oil, without the correct long-term storage and preservation, data leaks away into the ground or pollutants leech in through the cracks and render it worthless. 

For a long time, digital data in academia has fallen through the cracks: it sat somewhere between the remits of the librarian and the IT services department, and usually funded by neither. Costs for data storage and archival have typically been forced into short-term project budgets. Institutions across the globe face the same challenges around the long-term preservation of academic data. 

Storing research data correctly is an essential for repeatability and the review of academic results and conclusions. And in this sense, it can form a vital part of long term academic rigour and society’s accepted truth. Does a contentious academic paper still stand up, if its underlying data is lost to some obsolete, undocumented and inaccessible data format?

The openness with which we store data also has significant implications for academic collaboration, sharing, and accessibility – specifically the ability of researchers in developing nations to engage in high-cost fields of study.

Within the field of humanities (our focus for Phaidracon2021), digital data is often a valuable public good whose value stretches far beyond an individual research project. Digitized and stored correctly, research artefacts take on a new telepresence life for researchers, museums, enthusiasts, and members of the public around the globe.

And yet, we are still seeing digital data treated as a second class citizen in much of academia: a short-term cost burden, rather than a valuable asset. 

At this year’s Vienna Sessions we will exploring key questions and some possible solutions: 

• Is open source software the panacea it was once thought to be?
• Should we, and can we, separate data from the risks of software obsolescence?
• Do better standards and Application Programme Interfaces (APIs) have more to offer?
• Are there ways to make data a financial asset rather than a burden?

The open source Phaidra Project has one simple focus: The effective long term preservation of academic data.

This simple mission touches on topics at the core of modern academia and broader society: from accessibility, collaboration, and open science; through academic rigour accountability and repeatability; to more pragmatic subjects such as budget restraints, reuse, and even revenue generation.

Building on last year’s lively ‘Vienna Sessions’ (see the links above), Phaidracon 2021 starts with two more exciting roundtables. We invite anyone with an interest in digitization, ḧumanities, data preservation, data management, open access, scientific publications and digital library to tune in and join us in the interactive online debate.

Featured photo by Dan-Cristian Pădureț on Unsplash

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Make Community an Essential Part of Your Effort

Building a community is essential for the success of any software project. Introducing collaboration to the workflow of a company will probably revolve more around code than on culture at first. While coding is at the core, the culture change to collaboration and community building is something that needs to grow on an organization and needs to be nurtured without having a specific focus on software development.

Think about specifically assigning a community manager keeping the big picture on the social collaboration aspects of your endeavour. A central person that motivates people and communicates about progress is a big plus in any collaborative effort.

Treating Adversity as an Opportunity

Down the line things will go haywire. This is a universal truth, but also an illusion. All things trend toward disorder, but adversity is a learning experience and an opportunity in disguise.

When things go wrong in your project your expertise, your personal integrity might be on the line. Actually it is not so much the humans we need to be tough on. It is the task that needs our undivided attention. We set out with goals we truly believe in. Now it is time to take a step back and analyse what caused the negative experience. Think about the factors that brought you to this situation. What could you control, what couldn’t you control. Be careful not to over-analyse every small thing. Keep the big picture in mind.

As a next step trust in the fact that you learned something that energizes you and encourages you to get the project back on track. You have learned something that made you more resilient enabling you to lead the project in a more energized way.

Stay Positive: Learn From Your Mistakes

There is nothing worse than going through a difficult time in your life or in your project. You can start to feel burnt up, useless and nothing seems to amount to much. But you also want to make sense of what went wrong and us that for the positive, making sure the suffering was not in vain.

I used to try and avoid adversity as much as possible. The thing is: Adversity is around the corner and will show its face. Many years of working in a toxic environment left me broken and defeated. I was often in survival mode.

Having gone through that journey I learned that all change comes from within. Instead of seeing it as a rough tough time I learned to see it as a period where I have learned to become the real me.

Design for Success

A successful implementation does not so much depend on what needs to be achieved, but equally on who is involved in the project. Focusing on the material aspects only is designing for failure. Take the human aspect into the equation.

The challenge in designing for success lies in bringing users and technology together in a human-centric way. The tendency is to jump right into solution thinking overlooking who members of the team are and what problem we are actually trying to solve.

Take small steps

With the end goal in mind we are inclined to accelerate rather than carefully look at our current achievements. It is this acceleration that leads to failure. Remember collaboration and open source is a journey!

Focus on what you can work with. Success comes from taking small steps, smart steps. In the spirit of agile methodologies take the first step as quickly as possible. Look at what you have at hand and work with that. Also look at what that step might cost you if things might not work out. This allows you to gain traction and get others back on track.

Listen to yourself and inspect and adapt with every step. Now we have freed ourselves from traditional cascading project methodologies there are countless opportunities to learn at every step of the way.

Be accountable

All too often we find ourselves over enthusiastic and promising things we cannot deliver. We excuse ourselves being busy if we excuse ourselves at all. From my experience in managing projects and communities I found people even being insulted when reminding them of a promise.

Looking at what we previously talked about it is easier to show a small step than it is to take a jump. Maybe it is not even the individual promise you missed, but being in the mindset of not caring it is the cumulative impact that will not let you get back on track.

• No time for an hour-long meeting? Do a 10-minute stand up.
• No time to write a blogpost? Write a paragraph.
• No time to take the afternoon off? Take half an hour and go outside, leaving your mobile at your desk.
• Stick to your schedule, even in small ways.

Say no

Collaboration can be demanding. We are in it for the community and as the hierarchy fades away there are more individuals and teams that are on the same level playing field. Your expertise and skills are in high demand and everyone wants a piece of you. You want to say yes, but to remain in control and deliver quality it might be time to say NO.

If you get another request just step back, take a breath and think about how this fits in your workload. What are the benefits? Now you do not have to be blunt with a straight out NO, but you can also think about offering an alternative or schedule the request for a later date. If you say no say it in person (or through any other visual communication). Saying no in an email can be experienced as rather rude.

Care

Where things can go really wrong is when people find themselves in a position where they do not care any more. This will quickly destroy your project.

Getting into a project in a genuine manner is vital. We are not dealing with a management method, any more, where we put financial returns to the forefront, even though they are of course an essential part of why a company is in the game. Collaboration, people and communication in the limelight.

Connect to people in your team or project and communicate mindfully. Engage with awareness and really listen to what your team members have to say. You will see them light up. Bring out the best of yourself to bring out the best of someone else.

Moving Forward

We discussed a number of methods that can help you get your project back on track. While each and every method covers a specific topic, all have a few things in common that I would like to relate to as your true inner collaboration. Be mindful of what goes on around you in the project.

Take a pause, a step back before you are forced to. Be genuine and authentic in the way you act. This will keep your project moving forward.

Featured photo by Dominik Martin on Unsplash

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The term ‘MetOps’ is used to describe the bringing together of people, processes and tools within a modern business environment. The aim is to deliver the same benefits to monitoring, as DevOps has to operations and development. MetOps is not only intended to encompass technical elements such as servers and services, but also business data such as sales and finance.

In an ideal world, poor quality code releases which damage the customer experience should be easy to correlate with a drop in sales… Each of these things is an event or a metric. In a MetOps focused organisation these become valuable indicators, allowing developers and business people to alert and predict on issues before they become catastrophic.

In part one of this series, we laid out the foundations of the MetOps approach and examined the many benefits it can bring to an organisation. It covered the basic philosophy and some of the approaches to implementing MetOps in an existing business.

In part two we looked at how we could integrate MetOps into existing teams and leverage the business and technical skills that are already present. MetOps is a unifying approach that should have participation across a wide spectrum of departments and skill sets.

Those articles lead us to nicely to part three, the tools you can use to implement the MetOps maturity model. The MetOps maturity model is a loose set of stages that you can use to both gauge your current monitoring capabilities whilst planning for future tooling and processes.

The MetOps Stages

The four stages of MetOps are designed to guide an organisation through implementing a holistic monitoring regime, from simple first steps of state monitoring through to predictive alerting and forecasting at the top end. You can see the four stages in below figure.

1. Ad Hoc

Ad Hoc monitoring is where many teams find themselves, with alarms and alerts triggered when pre-set thresholds are reached. Monitoring is sparse, and only covers the essential systemic items such as CPU, RAM and disk space.

2. Past

This level refers to alerting on issues that have already occurred, and entails having both threshold alarms and log analysis. At this level of maturity it allows for more in-depth analysis of alerts created by stage one tools, as well as giving insight into the underlying platform activity.

3. Present

At this stage of the maturity stack, you have threshold, log and metric analysis. Metric gathering encompasses not only systemic items, but also business events such as API/Page requests per second, orders taken and other metrics that are key indicators of business health.

4. Future

At stage four you are taking the product of the first three stages and using techniques such as Machine Learning (ML) to process the outputs of your monitoring. Machine learning allows the creation of predictive alarms that track trends and patterns instead of requiring the setting of hard limits and thresholds.

The MetOps maturity model allows us to set our ambitions and to state our current position. We can also combine it with the four pillars of monitoring,  allowing us to focus on which stage of the maturity model a particular set of tooling fits.

The Four Pillars of Monitoring

As you can see, this maps nicely to the MetOps maturity model.  So now we are up to speed with the MetOps maturity model, what tools can we use to implement it?

Robust and Powerful State Alerting

Stage one is probably the most crowded market for both commercial and Open Source tools. State monitoring is the most basic form of monitoring and has been around since the dawn of computing. Most DevOps engineers will be familiar with tools such as Zabbix and Icinga, both of which are forks from the venerable Nagios project. However, modern alternatives are starting to arrive which scale better and offer more in-depth integration into a modern software stack. Two excellent tools at this level are Sensu or Elastic Metric Beats.

Sensu is a commercial Open Source project. Its key selling point is ease of installation and scalability.  Based on a message queue, Sensu allows clients to subscribe to checks rather then each host having to be assigned them individually. Once the checks have been executed on the host, the results are placed back on the queue for consumption by a master. By using a message queue architecture Sensu allows for massive scale without needing massive infrastructure.

Elastic offers similar functionality by using a combination of Metric, File and Command beats. Combining these three beats modules delivers a rich set of data that can be queried and alerted on. Through a combination of clustering and using indexing nodes, Elastic is also relatively straightforward to manage at scale. Although it lacks the elegance of the message queue oriented architecture, Elastic makes up in part by being exceptionally easy to deploy and scale. Elastic has built-in clustering, meaning that adding additional master nodes is extremely simple.

Using either of these tools will allow you to build a robust and powerful state alerting system which warns you when services or resources pass a pre-set threshold. Although not the most sophisticated approach, it is the basis for reliable monitoring that generates for an alert if there is a service outage.

Analyzing logs and event streams

Now that you have state monitoring, you can turn your attention to log and event stream monitoring. At present most organisations turn to either Elastic or Splunk for this functionality. Elastic is not the only Open Source option, there are excellent alternatives such as Graylog. However, they lack the rich feature set that both Splunk or Elastic offer. If you have already used Elastic to fulfil the first stage of the MetOps maturity model then you can leverage the investment in time and effort to reuse the existing alarms and dashboards. It also allows re-use of the existing infrastructure and skills from implementing it for state monitoring.

For some organisations offerings such as DataDog can be compelling, but these rely on the ability from a corporate governance perspective to ship potentially sensitive data off-site. With the advent of the General Data Protection Regulation (GDPR) this may mean that they are unsuitable, or may require additional expense to ensure that data is held in GDPR compliant regions.

Once in place, a log monitoring tool allows for robust monitoring and alerting, especially if you invest development time to ensure that log file hygiene is of a high standard (Only logging essential elements in a common layout,  preferably into a structured format such as JSON).

The Power of Time Series data

Stage three is where we fully utilise the power of metrics. The market for time series databases is fast growing, and entrants such as Influx and Prometheus have released compelling and powerful solutions. Not wanting to be left behind, Elastic too have joined the fray with the release of Metric Beats. Each of these tools has some exciting features, and importantly, are easy to integrate with. A metrics system is of little use if no one can bring themselves to actually populate it.  Each of these solutions ship with many tools that allow easy importing of data, be it system stats or custom metrics. Each has a reasonably intuitive GUI allowing the exploration and charting of the data, allowing semi-technical users the ability to create custom dashboards and alerts.

The primary competitors to these solutions are cloud offerings such as AWS Cloud Watch. However, Cloud Watch is reliant on shipping data outside of the corporate environs. Although AWS is ISO 27001 and GDPR compliant (Depending on region), recent scares such as Spectre and Meltdown have called into question the security of public clouds for the more security-focused entities.

Anomaly Detection

At stage four of the MetOps maturity model, you should have a complete picture of your infrastructure and receive timely alerts when anything goes wrong. The next step is to start predicting issues before they occur. To achieve this, you need some form of anomaly detection. Anomaly detection is the ability to take existing data and mine it for patterns and trends. Once established anything that falls outside of these patterns can be judged to be anomalous and therefore something to make visible and alert on.

Anomaly detection is in its infancy. Some promising Open Source projects are starting to surface such as Twitter’s AnomalyDetection project, but as yet none have gained significant traction. Elastic has taken the lead in this space with its Machine Learning component. Built into the Elastic X-pack, it is an ever-present monitor that tracks available metrics and intelligently builds up patterns. Once it understands these patterns, it surfaces them as actionable alerts.

. . .

Hopefully, this has given you a taster of the tools that are available to allow you to start implementing a MetOps practice within your organisation. Using any of these tools or their alternatives you can build a comprehensive monitoring platform that can collect, display, learn and alert on your essential business data. By bringing monitoring back into the technical teams, you both massively improve the quality of your monitoring and your ability to act on them.

And if nothing else, you can put up a huge TV in the office and admire the kaleidoscope of colourful graphs.

Featured Photo by Adam Sherez on Unsplash

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Challenge your thinking and create a new mindset

An open and playful mind is a sound basis for innovation. Opening up the mind towards creativity is a challenge as we tend to remain in trains of thought, our comfort zone. How do we define the open mind and how to reach such a state connecting our work and play together for living better and creating a better, vibrant, world while doing that?

Play To Innovate is not about colourful bubble clay, Nerf Guns, cardboards, pens, strings and so on…. Play To Innovate shows a playful understanding of life where innovation starts within and takes you to a level where innovation feels like the air we breathe.

Play To Innovate takes a step into the direction of change carried by mindfulness. As a take-away you will see some of the things you learned earlier in your childhood re-confirmed.

In small steps, baby steps, you start the Play To Innovate game. Play To Innovate is about gaining clarity through sharing experiences of life, dreams, goals, thoughts, feelings, perceptions, attitudes, and actions. It is about traveling on THE ROAD you really want to travel making your life and the life of the ones around you better

Explore these 5 steps to bring you closer to new habits and a new mindset.

1. Work without play can get boring. Play herein refers to playfulness for creativity, innovation, and be open-minded for solutions that may not emerge from work alone. (Einstein : doing the same thing over and over again…..expecting different results…)
2. Open Source and Open Mind as a connection. Even though we work in Open Source that is not a guarantee for an Open Mind. Innovation CAN lead to failure and seeing failure as a basis to inspect and adapt and go to the next step is not always easy as failure is almost regarded as a criminal offence especially in Europe.
3. Make Creative Thinking a Game. With some examples of simple games and exercises the apparent absurdity of problems can be solved by unconventional analysis not usually taken in classical problem-solving. This small step recognizes non-conformist thinking.
4. See and Feel. You were invited to play the game, but do you experience what you “see, feel and think”? Are your mind, body, eyes, ears supporting you? How does it feel to you and to your collaborators.
5. Ask a child for advice. For many people if you say the word, ‘storytelling’, they presume it is for children. ‘storytelling’ offers to soothe yourself in the mindset of a child and permitting yourself to ask the questions that come along with the creative power of ‘storytelling’.

 

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This year there will be a full day conference (CHAOSSCON + GRIMOIRECON) on February 2 prior to FOSDEM. The day features CHAOSS and GrimoireLab updates, use cases and practical workshops for developers, community managers, project managers, etc. It is a great opportunity for community managers, software development managers, developers and generally anyone involved in Open Source and Inner Source software development to meet up and exchange ideas and to discuss current trends in open source.

In September at the Open Source Summit Los Angeles, the Linux Foundation announced the Community Health Analytics Open Source Software project (CHAOSS). Initial interest and the impressive list of founder members ¹ illustrates a growing recognition that while open source is, strictly speaking, about a license; open source success is entirely dependent on a healthy community.

CHAOSS is a long-overdue initiative that is the result of years of enthusiasm, dedication and discussion around community and metrics. I distinctly remember the late night talks about community metrics at the Birds Of A Feather sessions at OSCON Portland around 2013. And, I remember being really intrigued by one of the few community metrics projects around at that time doing sentiment analysis.

This was very basic analysis, based on tallying the number of positive and negative words from mailing lists. At that time we only had nascent ideas of  the metrics which could be analysed around a community. But several Community Leadership Summits saw the range of topics grow around the metrics subject.

The Community Leadership Summit was one of the spots where discussion around community metrics found fertile soil. You could really feel community metrics becoming a trend. Being a community manager for the TYPO3 project back then I struggled with reporting back to my community on how effective community management was.

AoP partners Bitergia were a huge influence in starting this initiative. I can’t  remember meeting the guys and NOT speaking about community metrics.

One great example of how community metrics can be used, is shown in an Intel-commissioned report on gender diversity in the OpenStack community. While the technology industry has been a major source of innovation and economic growth, in the intro of the report, Nithya Ruff highlights the industry’s lagging ability to encourage diversity among its ranks. The report, shows in detail how women make up a maximum 20% of the community: be it in governance/leadership or technical contributions.

While the technology industry has been a major source of innovation and economic growth, Nithya Ruff mentions in the intro of the report, its ability to encourage diversity among its ranks lags. The report, that can be downloaded straight from the OpenStack website, shows in detail how women make up around (max) 20% of the community be it in governance/leadership or technical contributions. , tsides the telling outcome of the report The report hopefully promotes more dialogue and actions around diversity.

Footnote: Initial members contributing to the project include Bitergia, Eclipse Foundation, Jono Bacon Consulting, Laval University (Canada), Linaro, Mozilla, OpenStack, Polytechnique Montreal (Canada) Red Hat, Sauce Labs, Software Sustainability Institute, Symphony Software Foundation, University of Missouri, University of Mons (Belgium), University of Nebraska at Omaha, and University of Victoria.

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Patching is something organisations claim they do diligently, but rarely do completely. Tools such as Puppet, Ansible and Chef have ensured that patching operating systems and devices is both automated and easily audited. And the tendency is to leave things there. After all, if the network equipment, servers and desktops are patched things are OK

This is a mistake. These days the OS runs a slender attack surface and is not generally facing the wider internet. The biggest assault on OS’s comes from inside the network. Despite many warnings and the occasional bludgeoning, users still insist on opening Email attachments sent from people they’ve never heard of. In this case, OS patching is vitally important, as noted belatedly by the NHS in the aftermath of the wannacry outbreak.

However, for organisations that make a living by producing web facing apps, the largest attack surface is still the applications themselves. So it’s curious that development teams are still not taking patching seriously.

There are numerous reasons how this came to be. First of all, from a developer perspective updating dependent libraries can be painful. Even outside of major releases, some library updates have a nasty habit of breaking existing code. If it is a major release, then all bets are off, you’re almost certainly going to be re-writing the code that used this library. Developers are forced to wade through and rewrite existing code that is probably perfectly adequate for the task.

If it’s a pervasive library such as a date library then you could be in for a major piece of work as you visit each and every element that deals with dates and correct it for the new version of the library.

From a business owner’s point of view, application patching is costly and generally offers nothing visible to the end user. In complex applications, it can take up considerable time, time that isn’t being spent creating features for customers. This is a hard sell. Budget is finite and competition is fierce, and for some companies razor thin margins dictate that the Tech Debt credit card takes a battering, with patching being another line item on the ever growing list of tech niggles.

This is also a mistake. As many organisations will tell you, putting security on the back burner is a fundamental and potentially business ending mistake. However, it’s certain that every single CEO in the those organisations believed that systems were adequately patched. This may even extend to the CTO and project owners. Why is it then that there is such a disconnect? Partly, it comes down to outdated expectations and performance indicators.

Operations departments have always had patching at the core. Feature releases for operations departments are generally expressed in terms of rolling out new applications or operating systems, which are in themselves patches. A good operations department patches early, patches fast and patches completely.  Conversely, developers are judged on visible and revenue generating features and are seen as being ‘fussy’ or ‘perfectionists’ when they suggest cleaning up old code. By allowing one group to proactively pay down tech debt and punish the other, the message is sent that dependency patching is to be avoided.

“By allowing one group to proactively pay down tech debt and punish the other, the message is sent that dependency patching is to be avoided.”

Modern development practices also play their part. These days, development generally takes a Lego style approach, with the bulk of the application made up of a slew of third party libraries. Everything from dealing with dates through to low level elements such as multi threading are dealt with in an imported library. This makes sense, and is generally a good approach; business features pay the bills, so why re-invent the wheel on the dull stuff?

The problem then comes from managing and patching these libraries. Some languages revel in this approach, with Node in particular not blinking at having scores of dependent libraries for even the smallest app.

We should also examine the role that outsourcing plays. Many software companies outsource some, if not most, of their development to third parties. These third parties will generally deliver exactly what you asked for, and tend not to look into the wider needs of the product; that’s what the business analysts are for. Patching of libraries is rarely proactively offered by the outsourced developers and, without a strong technical lead on the product side, it is not asked for.

So how can we extend the patching culture to all corners of an organisation?

Managing dependent libraries has historically been painful, requiring developers to list, research and act on potentially hundreds of dependencies manually. This is no longer the case. Tools such as Black Duck or Nexus Lifecycle will tie into most continuous integration  systems and allow automated checking of dependencies.

With the advent of containers it is now possible to create a complete bill of materials that make up a deployment: from the operating system user space, right through to app libraries. Tools such as Anchore and Docker’s own security scan will then give a complete picture of which potential vulnerabilities exist within that deployment. Using this data, all levels of the organisation have an instant view of the current risk exposure within the application stack. This in turn can feed into corporate policy, setting out how much risk is allowable before deploying to the internet at large. This gives the development teams the much needed remit to improve, patch and secure code.

There is no excuse for not patching your applications. If you are a CEO/CTO then you need to be aware of the effort and impact of library patching and plan accordingly. If you are a product owner or scrum master, then you need to be pushing your team to patch early and patch often, and to be aware of the impact it’s going to have on productivity. And if you are a developer or DevOps engineer, it’s down to you to push from below, ensuring those above are aware of the risks.

After all, no one wants to be the next Equifax anymore.

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And it’s time for it to die.

Before you reach for the pitch fork, or worse, the comment button, hear me out. DevOps as the methodology is crucial to modern technology delivery. We should not return to the walled gardens of yesteryear: where siloed technology departments peered at each other through a haze of distrust and mutual suspicion of their respective skills, and occasionally lobbed releases at each other. The methodology of DevOps is excellent and is, indeed, now ripe for additional methodologies such as MetOps to join it. However, the use of DevOps, either as a job title, or adjunct to a job title, needs to end.

Aside from the ridiculous idea of naming a job title after a methodology (You do not for instance hire an ‘agile’) it also runs against the original ethos of the DevOps movement: that is to say, bringing the operations and developers together. By making someone ‘a DevOps’ or ‘DevOps Engineer’ you are still making them ‘the other’; albeit an other that is currently squatting in the same bullpen as the developers.

For a great many enterprise developers, nothing has changed. They still have a gatekeeper, it’s just a gatekeeper that happens to be sitting closer. In many enterprise settings, DevOps engineers have drifted into the niche of being mini operations departments. We’re still lobbing around releases, it’s just the distance you have to throw them is greatly reduced.

This can and will create friction within a team, with the traditional ‘Developers vs Operations’ happening as an internal team skirmish rather than writ large. This also has the unpleasant side effect of convincing CTO’s that they no longer need an operations department. Surely, with a profusion of people with the word ‘Ops’ in their job title we don’t need this extra ops departments?

The problem is DevOps engineers are generalists. By getting rid of Operational departments you lose deep and focused infrastructural skills, as well as fragmenting functions that should be centralised across many disparate departments. Every team I’ve worked with that has gone down this route, has ended up with massive issues due to having generalists working in a specialised area.

So given the fanfare around DevOps and automation, how have we arrived at this situation? Generally it’s due to corporate culture and inertia. At some point developers have been branded as too unsafe to be allowed unfettered access to infrastructure without supervision. This is much the same argument that no one should be allowed access to create application code and release it without supervision, and is a development issue that has long been solved with modern SDLC (Software Development Life Cycle). Didn’t Automation promise to eliminate this problem and usher in an era of developer freedom? Wasn’t that the whole point of the DevOps methodology?

Done correctly, automated infrastructure and software releases can be treated the same as any other code base. Infrastructure code is specced by a Business Analyst, audited by an architect, developed by a developer with unit tests and monitoring, checked by the QC, and finally, when it’s been through various test environments, released. When a new feature needs to be added to the infrastructure, the code should be branched, the feature developed, and a pull request issued, reviewed and accepted. There is no reason that an App Developer should not be able to branch the infrastructure code, add an improvement and issue a pull request. That pull request can then be reviewed by the infrastructure developers. If it’s a good change, it’s accepted and deployed. If it needs work then the infrastructure developers can add some feedback, and the original developer can then amend it and resubmit it. And if it’s rejected, the infrastructure developers have to publicly state why.  

So if that’s now possible then why do many developers still feel that they are waiting on something to be delivered from the ‘DevOps team’? Generally speaking I think it comes down to two things.

First and foremost, many projects that claim they follow the DevOps Methodology and have embraced automation simply haven’t. Quite often they’ve adopted a DevOps Engineer into the team (Or far worse, created a ‘DevOps team’) as a fig leaf to show that they are hip, cool and down with the Silicon Valley crowd. Dig below the surface though, and you still see the same old processes. The result is that instead of an Operations department you have a multitude of mini ops running around, gatekeeping elements and being given exclusive access to infrastructure to manually create elements. I’m yet to work in a business where they can truthfully claim that they have fully automated everything. At some point, be that DNS entries, network management or something else, it’s not automated, and you have to work through layers of bureaucracy to amend some part of the infrastructure. Despite this not being the fault of the ‘local’ DevOps engineer, it is still perceived as operational blocking.

Secondly, you have impatient developers. All good developers want to deliver code that is functional, secure, and above all else, cool and fun. It can be amazingly frustrating, when they are blocked from doing so, because of an ‘unnecessary’ wait for new compute, storage, networking etc.

However, the DevOps engineers are often shielding these developers from a lot of the corporate nonsense. The devs don’t realise that, the inherent complexities of enterprise accounting, security process or just plain politics, often make it painful just getting to the point where you can ‘spin-up a few boxes’ on the AWS console.

Another issue is where application developers can be left waiting for the infrastructure developers to finish building new features that are needed to progress. On occasion, this can be more complex than implementing a new application feature. It may involve challenging and simplifying an existing business process before being able to automate it. The actual code is normally relatively trivial, challenging decades of fixed wisdom of how host creation is budgeted, or DNS entries for the company allocated and managed less so.

The answer to this is to involve the application developers. If an app developer is blocked awaiting a new infrastructure feature which is in turn blocked by process, then bring the app developer along to the meetings where the process is discussed. That way they have an appreciation for the non-technical blockers that might need to be dealt with, and an understanding of the process as well.

Photo (with bad tv filter) by Eric Ward on Unsplash

So how do we collaborate more effectively? I’d suggest a good start is the top down adoption of the following rules:

1. There are only developers. There are no ‘DevOps’, ‘QC’s’ or other non developers. There are ‘Infrastructure Developers’, ‘Application Developers’,  ‘Test Developers’ and so on.
2. The only way *anything* happens to infrastructure is via released code, and all infrastructure code is available for development.

This eliminates the us vs them syndrome. There is no separate role, just developers with different specialisation. They are managed the same, follow the same processes as other developers and are, in every way, just a member of the dev team. If a developer is blocked by the lack of an infrastructure feature then this is simply a case of bad sprint management; the feature should have been identified, scoped and delivered before it become a blocker, the same as any dependent application feature. This process change should be relatively straight forward.

The second change is more far reaching. When we say the only way anything happens to infrastructure is via released code, that applies across the enterprise. Want a new top level DNS entry? It’s an amendment to the code. Want a new storage device allocated? Code. Want a new user? Code. And so on and so forth.

There is no reason why, if these elements are automated, that you can’t allow any developer in the company to make the code change and issue a pull request. Why not let projects add a new user? Since it’s coming in via a PR you have built in auditing and the ability to amend or reject it. Why not allow top level resources to be added via code? There are no insurmountable or good reasons why not. If nothing else, suggesting this approach will immediately flush out the lack of automation within the company, as well as driving collaboration with the operational teams that look after the infrastructure. By using Code as the lingua franca of change everyone has visibility on what’s happening and why.

So embrace DevOps the methodology and kill DevOps the job title. We’re all developers now, we just differ on our specialisations. We all want the same thing, to be able to concentrate on writing cool software that does amazing things.

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A powerful but often overlooked factor for selecting software is the politics of change

Ultimately there is no silver bullet, as with any decisions we can never be 100% sure of the outcome. All we can do is to ensure the decisions we make are informed to the best of our ability. In my book “NoDev NoOps NoIT” one the assertions made by the NoDev principle aims to raise awareness of the high level factors that IT decision makers must take into consideration when selecting new software technology. Specifically the assertion states:

It is not a matter of “Build vs Buy,” it’s political, technical and economical

The technical and economic factors are relatively easy to understand, and it is no coincidence that these factors are the ones that technology teams and their consultants focus on when evaluating different software solutions. For small organisations focusing on these two factors is often enough, not because they ignore the politics of the decision, but rather the political factor is more naturally expressed during the course of the decision making, be it implicitly.

In larger enterprises the politics are ignored at the peril of the decision makers. Anyone who has worked in IT for more than a few years will be able to recount stories of failed software selection with millions being wasted and good people leaving the organisation. We must ask ourselves what are the political considerations that we must be aware of when selecting and introducing new software?

Who stands to lose?

Even if you believe everyone will benefit from the introduction of new technology the chances are that there will be groups of individuals that will perceive the change as a threat and will organise to oppose the decision. From my experience the most common sources of descent comes from Enterprise IT and IT teams representing different business units or departments. These groups have very different perceptions of the threat, but the source of the anxiety almost always stems from lack of engagement in the decision making process.

For Enterprise IT, technology that increases productivity for business units and which reduces costs for the enterprise spells a whole lot of work, reskilling, hiring and job losses. Such impositions will not be opposed openly; instead a series of lengthy delays accompanied by a background chorus of general negativity will endeavour to kill the project through attrition. For IT teams supporting business units the opposition is generally vocal and aggressive. They will rightly demand to know why they were not properly consulted and their requirements included in the evaluation and selection process. These demands will force senior management to restart the process from scratch with the added bonus of hostile business units “contributing” to the process. From my own experience such projects result in those responsible for the new technology leaving the organisation.

How to make sure everybody wins?

Obviously including these stakeholders in the decision making process is of critical importance but this is not simply a matter of sending out a bunch of invitations to 10 weeks of meetings in order to review software products. On a very serious note the fastest way to alienate your stakeholders is to throw around your corporate hierarchy rank in this fashion. There is plenty of literature available on how best to draw stakeholders into the decision making process, however a simple and effective approach I have utilised in the past is to identify a small representative team of likeminded individuals and start the selection process with them.

Where does Community Software come into this?

Let’s assume that we have the necessary buy-in for the introduction of new software on technical and economic grounds, and that we have managed to shortlist two vendors. At this stage our focus should be on gaining adoption for the software once we have introduced it and this is where Community Software has an overwhelming advantage over other software.

We define Community Software as:

General Availability, Free and Open Source Software (FOSS) which is actively maintained by one or more commercial or non-profit entities that also offer professional services that appertain to the software.

All Community Software is FOSS but not all FOSS is Community Software. Our definition has been chosen to help us decide between different types of FOSS when making an IT decision for the business.

When evaluating software for use in the enterprise, one of the key criteria is to ensure that we can sustainably support software liabilities in the most cost effective manner for the business. Remember, if you are not in the business of IT, every line of code, whether you wrote it yourself or not, is a liability. Thus having a vibrant and active community to support the software is of vital importance.

By support I don’t simply mean help desk or professional services to resolve technical problems. I use the term support in a far broader sense for example; I would expect the software vendor to assist with the adoption of the software internally within the enterprise. Such assistance can take many forms including:

• Organising or participating in workshops and Hackathons.
• Actively advocating our programmes strategic objectives to everyone they engage with in our enterprise.
• Working onsite with our teams to help them migrate and on-board to the new software.
• Collaborate with our thought leaders to produce content (blogs, article, whitepapers, videos and webinars) to raises awareness of the technology, the benefits it affords and the use cases we have identified that are pertinent to our organisation and strategic objectives.

If one accepts the Free Software Foundation’s claim that they are the representatives of the ethical software development, and the Open Source Initiative’s emphasis on creating technically superior software then Community Software represents the buy-side, business interests of the software market.

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Winning image by Japheth Mast on Unsplash

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