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For the term "management".

The Definition of Service

As I’ve blogged previously (The S in #SRE), I’m in the process of transitioning my team from database and system administration to a team focused on service reliability. As I’m continuing to evangelize DevOps and Service Reliability Engineering within my business unit, I’ve realized that I need to have a good strong definition of what exactly a service is. I figure if I’m going to work through this, might as well do it in my blog so I can find it later.

A Service:

Is an abstraction of value. Services are containers for delivering value to a customer, either internal or external.
Has a consistent definition. It’s comprised of people, products, and processes, and while the relationship between those elements can change, but the inputs and outputs of a service are relatively consistent.
Requires a backup strategy. Disaster Recovery Plans and Business Impact Analysis are foundational tools for the management of quality associated with a service. While a DRP may contain multiple recovery strategies, a Service should be able to be recovered entirely.
Should be continuously improvable. This means that a service is only fixed at a point-in-time; components should be versioned so that management processes (including recovery) are synchronized with the delivery of value at a given time.

More to come.

#DevOps – Lead by example, but set the right example.

Last weekend, I missed a data center migration.

It was a scheduling conflict; for Christmas last year, my wife had bought me tickets to High Water music festival (which was great, btw), and when they set the dates for the data center migration, I was worried. The tickets were expensive, and we had booked hotels, etc; I couldn’t change plans to work with the schedule, and there were too many teams involved in the migration for them to pick a different date. We’d done this migration once before (6 months ago), and I was confident in my team’s ability, but still… I was worried. You see, missing an after-hours deployment or a maintenance window of this size wasn’t usually considered to be an option before (by me). I’ve always been a firm believer in the management rule of: Don’t Ask Others to Do Something You Won’t Do.

So, every migration, every deployment, every maintenance window… I was there. Weekends, mornings, evenings… I was there. When our first major data center migration blew up a year ago, I was there for 26 hours. I THOUGHT I was sending the message that “I’m here for you… I’m leading the way… I’m being a team player.”

That’s not the message I was sending.

What happened while I was away is that others stepped up and filled the void left in my absence. They didn’t do things exactly like I would have done, and they had to take on some additional responsibilities during the migration, so their timing wasn’t as efficient as if I had been there. But the work got done, and we survived without me. I could have looked at that and said “aha; I’m not really necessary; there’s some waste savings there!”. Instead, I realized that what I thought was a four-person job was really a three person job, and that meant that the fourth person could do what was more important than work; life.

You see, the message that I was sending by being at every activity outside of work was that I Expect Y’All to Give Up Your Free Time for Your Job, Just Like I Do. I didn’t mean it that way, but my employees picked up on it. I was there; they were there. Every time. And that’s no way to work.

What I realized this weekend is that Leading By Example also means Resting By Example. If the job really is a three person job, then four people don’t need to show up to do it (or else work will expand to make it a four person job; a variant of Parkinson’s law). And while I should still be willing to do the job, I need to be willing to do it when it’s my turn. I’m now scheduling rotations (I’m in one of those rotations as an engineer), and letting my team understand that it’s not just OK to not be at every maintenance window activity; it’s expected. A job is what you do to pay the bills and enjoy life. If I believe that for myself, then I need to set that example for my team as well.

2018-04-26 by Stuart Ainsworth Blogging is FUN! DevOps SQLServerPedia Syndication 0

The S in #SRE

As I’ve blogged previously, my responsibilities at work have shifted to focus more on the application of Site Reliability Engineering principles to the delivery of our business services to our customers. Unofficially, we’re calling my team Service Reliability Engineering for a few reasons. I thought I’d take some time to explain what the differences are, and why I think the name matters. I realize I’m just one lonely guy in the wilderness, and I’m going up against Google, but I think one word in the title is wrong. Before I explain why, let me explain what I do like about the title.

Engineering defines consistency of methods.

I realize that engineering is an interesting terms these days, with lots of different definitions; you can even be sued if you call yourself an engineer inappropriately in the wrong jurisdiction. However, the term itself is widely used in technology careers to describe the systematic design and operation of complex systems. Most modern applications are actually comprised of several smaller applications, all in varying states of underlying complexity. Furthermore, the delivery of an application to an end user (particularly web applications) can span the entire spectrum from infrastructure to platform to software. Additionally, applications can vary in terms of scalability, configuration, and location. Engineering addresses complexity, not just complication through systematic processes; engineers experiment, learn, and integrate consistent practices into their daily processes.

Reliability refers to purpose.

When your job title identifies reliability as a name, it means that you have a specific goal in mind, and that goal is not limited to a technology. Reliability engineers work with networking equipment, operating systems, applications, middleware, and/or database systems. They may specialize in a area (e.g., database reliability engineering is now a thing), but a robust team is comprised of necessary skill sets required to meet service level objectives across the entire technology stack. Reliability as a goal must first be defined, and then measured, and SRE responsibilities are responsible for measuring and addressing reliability across the entire spectrum, from infrastructure to platform to software. However, reliability measurement must also account for not only technological issues, but also the processes and people responsible for developing and operating the system. There’s a reason that a just culture is an integral part of the SRE experience (and the DevOps movement at large); people are responsible for how well technology performs, both in terms of defining expectations and day-to-day delivery of service. It only makes sense to look beyond technology when examining reliability, and that leads to where I disagree with the standard SRE nomenclature.

“Site” implies a technical focus; “Service” implies a business function.

The word “Site” in the IT domain typically refers to either a physical location (data center site) or an application (web site); however, the heart of the definition is sociotechnical, not strictly technology. From an undated (seriously, Google?) interview with Ben Traynor, the founder of the SRE movement: “… we have a bunch of rules of engagement, and principles for how SRE teams interact with their environment — not only the production environment, but also the development teams, the testing teams, the users, and so on.” While the previous paragraph of that interview specifically focuses on the type of work that’s being done by Google’s SRE team, these rules of engagement show that SRE’s should be concerned with the entire value stream of service delivery including not only operations, but development, testing, and ultimately the end user experience. In, other words. SRE’s are concerned with the reliability of the whole service, not just the technical parts.

2017-12-01 by Stuart Ainsworth DevOps Professional Development SQLServerPedia Syndication 2

The DBA is dead; long live the DBA!

Been reading some interesting arguments over the future of DBA jobs lately, and as usual, I find a lot of truth somewhere in the middle. Let me try to sum up the positions of the three authors that impressed me the most:

Thomas LaRock – Why I’m Learning Data Science:

Tom kind of kicked off this discussion with his post; the three main takeaways I got from it are:

The traditional role of the DBA is being automated away, right in front of our keyboards.
As computers get better about self-tuning, it will be difficult to justify the expenditure of a dedicated database administrator
Computers are only good at providing answers; humans are good at asking questions.

Brent Ozar – Twitter Posts

Brent responded via twitter to “a couple of emails” stating that “the DBA career has a time bomb”. The three key points I got out of the thread are:

The tools are getting better, but the problems are getting harder.
SQL Server still ships with some legacy baggage that require hands-on experience to adjust; if computers were smart, why hasn’t that been fixed?
Even as the technology gets better, adoption is slow.

Grant Fritchey – There Is A Magic Button, A Rant

Grant took the humorous route, telling the tale of the “Run Really Fast” button that all database administrators know about once they achieve a certain level of competence.

Tools are getting better, but they can’t fix problems with design (both software and hardware).
Automation can reduce drudgery, but design is fundamental.
DBA’s are all secret alchemists.

Where I sit…

All three of these guys are smart folks that I respect a lot, and honestly, I see a lot of truth in what they’re all saying. The tools ARE getting better, and I do believe that automation is going to significantly change a lot of different jobs in IT, including database administrators. The role of a DBA is particularly susceptible to this because of the hybrid nature of the work. There’s elements of design (system and software), development, and operations associated with that role, and the stack is getting increasingly complicated. The Microsoft Data Platform now sits over relational and non-relation data, and encompasses analytics, visualization, reporting, integration services, high availability, disaster recovery, and much more. The stack is getting too complicated for the average DBA to be a master of all of it. However, it’s hard to deny the necessity of expertise, particularly with all of the technical debt associated with a product like SQL Server.

But what if we sliced the stack differently?

The cloud paradigm talks about breaking the computing stack up into various services, each acting as a black box to the level above it; Software as a Service is built on top of a Platform as a Service, which in turn is built on top of an Infrastructure as a Service. As enterprises begin to embrace the cloud, they will reorganize resources along these lines. Why? Because it lays the foundation for consolidating resources where it counts, and allows for future portability. In other words, companies can start at the bottom of the stack, and port their Platform and Software services over to cloud providers without significant alteration of those upper level. Likewise, as technology matures, migrating the Software layer to a new Platform provider will get easier over time (we’re not there yet, but it’s coming).

I would argue that the current role of database administration straddles the line between software and platform; traditional maintenance and server configuration task are part of the Platform layer, and database design are part of the Software layer. The term DBA will mean multiple things to multiple people, depending on where that role sits along this divide. In other words, a DBA that works at the Software layer will tend to focus on questions of database design, data software performance tuning, and architectural issues associated with the ever expanding set of options for databases beyond just the relational db. DBA’s at this layer need to become full-fledged member of the development team, which may eventually lead to a fuzzier distinction between application and database developers. DBA’s at this layer will need to be well-versed in the concepts of multiple data management technologies (and possibly other development technologies). Opportunities should abound here, but diversity should be valued over full-stack mastery of a single product.

DBA’s at the Platform level will change roles as well; they’ll no longer need to be steward of data, or responsible for tuning bad code. Their job will be to make the Platform support contracted levels of performance, and identify and correct resource utilization and configuration issues. Automation will have a huge impact here; Platform DBA’s will be responsible for supporting multiple instances of SQL Server, including support for high availability and disaster recovery. Scripting skills are highly desirable, as is mastery knowledge of specific products. I would expect job opportunities to slow in this area, but experts will still be needed in the future.

In short, I don’t think the role of a DBA is going away, but I do think that it’s going to split. That’s exciting, because it means that people have options. We still need experts, and there will still be opportunities for folks who love data to find meaningful work; their expertise will just become part of a different structure than we’re accustomed to now.

Now, where’d I put that Philosopher’s Stone?

2017-08-04 by Stuart Ainsworth DevOps Professional Development SQLServerPedia Syndication 3

#DevOpsDays & #SQLSaturdays

I’ve been meaning to write this post for a while, but life rolls on, as it always does. I had the privilege of attending DevOpsDays Atlanta back in April. This was my second DevOpDays event to attend (the first being Nashville), and overall, I’ve enjoyed the events. However, as a long-time organizer and speaker with the SQL Saturday events, it’s hard for me not to compare my experiences between the two conferences. They’re both community-run, low-cost, voluntary technical events; however, there were some things that I really like about the DevOpsDays format (and some things I wish were different).

Cost

The cost models of the two conferences are different; in short, SQLSaturday’s are free to the attendees (although a lunch fee is usually provided as an optional service), and DevOpsDays charges a small fee ($99-$150). Both rely on sponsors to pick up the tab for the bulk of the expenses (usually location fees). Speakers are volunteers, as well as event management staff. The benefit for the attendee is guaranteed swag (an event t-shirt is typical) and a great lunch (food was fantastic at DevOpsDaysAtlanta).

Charging a higher fee does a couple of things; it allows organizers to get a more accurate attendance estimate; if an attendee pays more to go to a conference, it’s more likely that they’ll show up. This has a trickle effect on luring sponsors; it’s easier to justify sponsoring an event if you know that you’re going to get a certain amount of foot traffic. A fee also guarantees amenities that are important to technical folk; good Wifi, and livestreams (although sessions weren’t recorded at the Atlanta DevOpsDays event). You can also direct some of those funds to getting a premier meeting space.

On the other hand, a free event with a nominal lunch has the potential of bringing in a much larger audience; DevOpsDays Atlanta was hosted in a 230-seat theatre, so attendance was probably around 250 (with standing room, vendors, and speakers). Last year’s Atlanta SQL Saturday had over 600 attendees, and this year’s event had slightly over 500 attendees. Attendance counts shouldn’t be considered a metric of superiority, but it does provide a different incentive for pursuing sponsors. As an attendee, I like the SQLSaturday model; as an organizer, I like the DevOpsDays model.

Parent Organization Involvement

DevOpsDays is a highly decentralized model (true to the agile underpinnings of the movement). The parent organization appears (from the outside) to be very hands off; local event organizers handle their own sponsorships, registration, and other details. This allows for a lot of fluidity when it comes to branding, networking, etc. For example, see the differences in advertising logos for the DevOpsDays organization, the Atlanta 2017 event, and the upcoming Nashville 2017 event:

DEVOPSDAYS (GENERIC)	ATLANTA 2017	NASHVILLE 2017

In contrast, PASS (the Professional Association for SQL Server) retains tight control over the marketing of SQLSaturday; registrations and event planning are handled by their internally-developed tools, and the branding has recently evolved to provide a more consistent association with the parent organization (although not without some concerns).

PASS LOGO	SQLSATURDAY LOGO

From an attendee perspective, branding probably doesn’t make much of a difference; however, the tools used for registration are highly visible. Both DevOpsDays events I attended used EventBrite, a well know tool for managing, well, events. SQLSaturday relies on a custom registration site that has improved over time, but still often leaves attendees confused (despite all the best guidance from organizers). Furthermore, if a SQLSaturday event has a precon, those events are usually managed by EventBrite, which leads to an additional disconnect between the precon event and the actual SQLSaturday. Despite my love for SQLSaturdays, I think the DevOpsDays approach to branding and tooling is better.

Educational Delivery Format

One area that SQLSaturday feels more comfortable to me is the format of the sessions. SQLSaturdays typically follow the traditional multi-track model in a single day (not counting pre-cons), where attendees can choose from multiple sessions at the same time; for example, SQLSaturday Atlanta 2017 had 10 concurrent tracks, each with sessions lasting about an hour. Note that this format is not required; smaller events may only have a single track, or have multiple tracks with longer sessions.

In contrast, the DevOpsDays standard of delivery is multiple days, with a single track in the morning of longer talks, followed by a single-track of short talks (“Ignites“), and then open-space sessions in the afternoon. For me, this is a mixed bag of effectiveness; bringing everyone in the conference together to hear the same discussion can (in theory) promote better cross-communication between the various stakeholders in the DevOps audience. For example, having managers and deployment specialists hear a programmer discussing pipelines may promote perspective-taking, one of the fundamentals of good communication. In reality, however, my experience has been that many presenters don’t do a great job of relating to all of the stakeholders in the audience, making it difficult to bridge that gap. Granted, I’ve only been to two events, but of the 16 main talks that I heard across the two events, about half of them seemed relevant to me. Ignites have some of the same limitations, but the time constraints mean that they hold attention spans for longer.

Most people either love or hate open spaces; letting the audience drive discussions is a great concept in theory; in reality, discussions are typically dominated by a few extroverts in the group, and most people merely observe. Although there are usually self-appointed moderators, the dynamic selection of topics just prior to the discussion makes it difficult to engage or guide. When they work, they work well; however, too often open spaces lend themselves to the seven-minute lull Ideally, I think the most effective method of delivery would be a blended approach; a couple of keynote sessions in the morning, followed by a few Ignite sessions. Do multiple tracks in the afternoon, including open-space discussion, both free-form and guided. However, this is mostly a matter of personal preference; I’d love to try it and see what people think of it.

Conclusion

I’m enjoying the transition of my career away from being a SQL Person to a DevOps person; both communities seem vibrant and engaged, and I plan on attending more DevOpsDays conferences in the future (and perhaps even help with planning one). Events like these offer a lot of opportunity to learn high-quality material in a low-cost setting, and I only expect them to get better (or I’ll get better) over time.

2017-07-27 by Stuart Ainsworth DevOps Professional Development SQLServerPedia Syndication 0

#FAIL

There’s been some great discussion in the #SQLFamily after Brent Ozar published a recent blog post: I Failed 13 College Courses. Lots of comments on Facebook about it, and other people soon came forward with their own brief tales of academic failure (and subsequent successes). I was particularly touched by Mike Walsh’s video (What Advice Should I Share on Career Day?), where he talked about dropping out of high school. Most of the conversations were about the struggles in academia, but there was real underlying thread: You can succeed and be happy after facing failure.

I’m friends with a lot of smart, successful people, and for those of us that are engaged in information industry, failing at an intellectual exercise (like college or high school) can be perceived as a mark of shame. I think what Brent, Mike, and others are showing is that recovering from failure is not only possible, but normal. We all fail at something, and that often puts on a new path to figuring out something else. Failure teaches us more than success.

My Story…

(Note: I just realized that my last blog post touched on this story briefly. Must be on my mind a lot lately.)

I didn’t fail in high school (WMHS, 1989).

I didn’t fail during my Bachelor’s degree (ULM, 1993 – B.A, RadioTVFilm Production).

I didn’t fail during my first Master’s degree (ULM, 1995 – M.A, Communication).

I didn’t fail on my coursework for my doctoral degree. (UGA, PhD coursework completed in 1999).

Nope. I waited until I was 28 years old (with a wife and two kids depending on me) to fail at my first academic exercise. I bombed my doctoral comprehensive exams not once, but twice over a 6 month period. In April of 2000, I was waiting outside my major advisor’s office to discuss my options for a third attempt. I waited for two hours, brooding over the shape of my life at the moment. She never came, so I walked out the door and didn’t go back (stopping at a bookstore on the way home to purchase two books on SQL). I didn’t hear from her until a few years ago when she friended me on Facebook, and we’ve never really discussed it. I’m happy, and she’s moved on to greater successes as well.

As an aside to this story, I had been working at the American Cancer Society while going to school; my official title on most publications was Research Assistant, but I was the shadow DBA for the Behavioral Research Center. I had been working with Microsoft Access to manage contact information for cancer registries as well as using SPSS with SQL to analyze data. I parlayed that interest in data management into a new job in August of 2000; I had decided that I wasn’t cut out for anything academic, and I wanted to move into IT full time.

I did go back in 2001 to finish a second Master’s degree in Education (UGA, 2002 – M.Ed. Instructional Technology). Yes, I have three college degrees, and none of them are in information Technology.

What I Learned…

Lots of lessons I picked up out of this.

First, I learned that the fear of failure often motivates me to pick the easier path. Looking back over my academic career, I’ve always been smart enough to know what my limitations are, and lazy enough to not challenge them. I got a degree in Radio Production, not just because I enjoyed the theatrical end musical elements but also because I knew I didn’t have to take harder courses (like Chemistry, Physics or Calculus; all of I which I had managed to avoid in High School). I used to think it was working smarter, not harder; in hindsight, I just didn’t want to fail.

Second, a fear of failure often blinds me from looking at the bigger picture. When I’m scared that something is going off the rails, my instinct is to drive forward at full speed and force it to succeed. Over time, I’ve learned to be sensitive to those warning signs, and try to put the brakes on and redirect. At several points in my graduate career, I knew that I was in the wrong field. But I had a job in academic research, and I had never failed before, so I was going to see this through and will it to be. That obviously didn’t work.

Third, fail early, because failing late in the game is expensive. I racked up over $120,000 in student loans in my doctoral program; if I had recognized early on that I wasn’t going to be happy, I could have avoided that. If I had challenged myself earlier with smaller risks, I might have predicted that academia wasn’t for me. Hindsight is amazingly clear; in the thick of it, however, I’ve learned that it’s best to take small risks when possible, and fail often. Failing at something gives you two choices: you challenge yourself to try something different and succeed in the future, or you curl up in a ball and “accept your limitations”. It’s easier to bounce back when the consequences of the failure are small.

Summary

I’m no guru; I’m just a guy trying to figure it all out just like you. I’ve gone on to have other epic failures, as well as some incredible successes. I will say that my own personal journey has resonated with my perspectives on software and service development recently. Below are some great reads about failure.

Successful Failure

Fail Fast and Fail Hard

Blameless post mortems – strategies for success

2017-06-08 by Stuart Ainsworth Professional Development SQLServerPedia Syndication 1

The Technical Manager

I used to present a session called Managing a Technical Team: Lessons Learned (Alexa: Remind me to update and submit this session again); the point of it was to reflect on some of the lessons I learned early in my career transitioning from a database developer into a management position. I was trying to give a view from the trenches, mostly to help other folks get a perspective on what it’s like to fumble through a career change. Management, like development, is a process of learning and continuous improvement; the difference is that other people have some expectation that you know what you’re doing (and often, you don’t). Inevitably, I’d get asked some version of this question:

“Can I still be technical and manage a team effectively?”

I used to have a quasi-canned answer, something along the lines of “at some point you must choose your path; management is about people, not technology”. I still kind of believe that, but recent experiences in my own career path have caused me to reconsider giving an answer. Instead, I’ve started asking the questions:

“Why does it matter? What’s your goal for your career? What do you think you should do?”

The truth is, I don’t know what’s best for you, but I trust that you do (that satisfies my libertarian soul). Everybody’s got different experiences, different beliefs, different goals, and different circumstances. When you bundle those things together, it makes for a very complex decision tree; even a simple question about how you want to conduct your day-to-day affairs becomes overwhelming for someone sitting on the outside to answer. That being said, I still want to help, so I thought that I would share some of my decision factors using the four buckets above.

Experiences

Here’s some of experiences that have gotten me to this point:

I don’t have a technology-related degree; I have a BA in RadioTVFilm Production, a MA in Communication, and a MEd in Instructional Technology. I got into database work when I flunked out of a PhD program in Health Communication (and salvaged some of those hours into the MEd). I had failed my comprehensive exams twice, and had a meeting set up with my advisor to discuss a third attempt. She never showed; I drove off campus that night, bought some books on SQL and relational design (having done stats work as a grad student), and started looking for a job.
In my first IT job, I worked for a good manager (a developer running a support organization). When he left, I worked for an awful manager (a project manager who had no clue about anything related to computers). I try to emulate the former and check my actions to make sure I’m not acting like the latter.
I’ve been with the same company for almost 15 years since then. Different roles, different responsibilities, different owners.

Beliefs

These are some of the core beliefs I have about management and technology; these will be tough to change.

Management is more about people than tools.
Management should be more strategic than tactical. While a team may be responsible for specific operations, the manager of that team should understand the unit’s role in the bigger picture.
Technology is used to solve business problems; a good manager will focus more on solving the problem than on the tools used at any point in time. SQL Server is the tool I’m accustomed to using, but the problems I’ve been focused on lately aren’t database problems (they’re IT infrastructure and networking issues).

Goals

Goals are tough for me, because I believe they should be a mixture of both long-term and immediate. As such, they change more often than you would think (at least for me).

I want to be forward-thinking; I want to keep being exposed to new tools and technologies.
I want to be compensated well, and I want to continue gaining new responsibilities.
I want to feel like I’m making a difference; I’m not interested in continually addressing the same problems over and over again. I want to make a change and move on.

Circumstances

Everybody’s got different external factors that influence their decisions; managers are no different. For me, the following things are true:

I’ve been a remote worker for the last 8 years; it would be tough for me to go back to having a daily commute.
I’m project focused, not time-focused. I like having flexibility to get things done without a set schedule.
I’m a dad, and time with my kids is critically important. That means that I’ve had to pass up on opportunities because I’d rather take time for them.

What does this all mean?

For me, it means that I don’t want to be a single-technology manager; I want to figure out how to make technology work for business, even if it’s a technology that I’m unfamiliar with. The logistics of scale means that I can’t be the single source of authority when it comes to implementing technical solutions. I scale out by relying on my team to be the experts, and I want to keep building teams that can handle lots of different problems.

More to come later.

2017-05-08 by Stuart Ainsworth Professional Development SQLServerPedia Syndication 0

#DevOps: Remote Workers and Minimizing Silos

Been a while since I’ve posted, so I thought I’d try to put down some thoughts on a lightweight topic. I’m a full-time remote worker; I have been for the last 10 years). My company has embraced remote workers, and provides lots of tools for people to contribute from all over the country (including the wilds of North Georgia); tools include instant messaging clients, VOIP, remote presentation software, etc. Document sharing and discussion is easy, but as you probably know, DevOps is as much about relationship building as it is about knowledge sharing. How do you minimize silos between teams when teams aren’t physically located near each other?

Here’s some different methods:

1. First, in-person communication provides the greatest avenue for relationship-building. Bringing a remote worker in from the field from time to time can greatly reduce isolation. If your chief developer is in Wisconsin, and your main sysops guy is in Georgia, flying both in periodically is probably the best way to create opportunities for conversation. Better yet, send them both to a conference somewhere in between.
If in-person conversation is the gold standard for discussion but isn’t an option for economic or practical reasons, seek methods to emulate that experience. Conference calls or web conferencing tools are common, but video conferencing adds an additional dimension to discussions. In general, the higher the bandwidth, the better because it forces “presence” in conversations.
Encourage remote employees to add depth to relationships by providing them with a virtual space to connect. Internal blogs (with personal pictures or activities), or slack channels for goofing off provide teams with meta information beyond their work ability. Knowing that another person loves Die Hard as much as you do gives you a common place to start building relationships.
Organize virtual non-work events, such as multi-player gaming marathons (Leeroy Jenkins would be proud; NSFW) or virtual parties.

The main point is that while face-to-face interaction is desirable, it isn’t necessary. Employees (and companies) can thrive if they actively seek methods of encouraging high-bandwidth interactions with depth. Distance increases difficulty, but it’s not insurmountable.

Feel free to drop a suggestion for enhancing remote communication and decreasing silos.

2017-03-13 by Stuart Ainsworth Blogging is FUN! Development DevOps SQLServerPedia Syndication 0

Geek Sync: #DevOps, the Cloud Paradigm, and the Microsoft Data Platform

I’m pleased to announce that I’ll be presenting a Geek Sync webinar (hosted by Idera) to talk about what I see as the evolution of the DBA in light of movements like DevOps and the Cloud Paradigm. Registration’s free, so please feel free to join on January 25, 2017 at 12:00 EST.

The Future of the DBA: DevOps, the Cloud Paradigm, and the Microsoft Data Platform

We’re on the cusp of exciting times for database development and administration; data storage is set to explode in volume over the next 5 years by as much as 500%. Companies are struggling to manage traditional relational databases and several forms of Big Data, including dark, binary, and streaming data. New theories of development, administration, and data management have matured, but what impact do they have on DBA’s? What are the concepts and skills needed for future career growth? In the (paraphrased) words of Dr. Seuss:

“Oh, the places you’ll go!
You have brains in your head
And SQL Skills to boot
You’ll soar to great heights
On the Data Platform, too”

Join IDERA and Stuart R. Ainsworth as we explore how DevOps and the Cloud Paradigm have developed to address modern software delivery challenges. We’ll also examine how the Microsoft Data Platform provides a framework for career enhancement for SQL Server professionals.

Stuart Ainsworth (MA, MEd) is an IT manager working in financial information security. Over the past 20 years, he’s worked as a research analyst, a report writer, a DBA, a programmer, and a public speaking professor. He’s a chapter leader for AtlantaMDF, the SQL Server user group in Atlanta, as well as a speaker at SQLSaturdays, PASS Summit, code camps, and user groups.

2017-01-10 by Stuart Ainsworth SQLServerPedia Syndication The Social Web 0

#DevOps – Starting the path

Last week, I had the pleasure of attending my first DevOps conference (DevOpsDays Nashville), and the first conference that had absolutely nothing to do with SQL Server since graduate school. The conference was great; I met some new folks, and had some great moments of insight early on. The DevOps community is a very welcoming community, but as a relatively new explorer, I quickly got lost. The sessions ranged from culture to technology, and somewhere in between; the speakers were very casual, and to be honest, a little unstructured. It was very different than my previous experiences at tech conferences, where even professional development talks were goal-focused.

One the last day of the event, during one of the keynotes, I encountered the following tweet:

I’d love to hear people’s experience on this “DevOps is Disintegrating… But Maybe That’s OK” by @jpaulreed https://t.co/uc9mBJ97g7

— Kaimar Karu (@kaimarkaru) November 11, 2016

Paul Reed’s piece is interesting, because it helped me begin to form a schema around all that is DevOps; he defines the following frameworks underneath the umbrella of DevOps:

Automation and Application Lifecycle Management – basically, the tools needed to insure micro-deployments and increased time-to-market. The focus here is on Continuous IntegrationDeploymentDelivery, and Configuration Management.

Cultural Issues – Reed breaks these out into a relatively fine grain in a manner that he didn’t do with technology, but he defines three subsections of culture: Organizational Culture, Workflow, and Diversity. Each of these areas has a slightly different area of focus, but they all deal with the “soft, fuzzy, human interactions that lie just beyond the technology.” Organizational Culture can refer to breaking down silos, restructuring, and/or management & leadership. Workflow refers to the application lifecycle methodology, such as the conjunction of Agile and Lean methods. Diversity is a focus on bringing different voices into technology, including feminist, LGBTQ, and minority perspectives.

The Indescribable – finally, Reed finishes with basically an “everything else” definition. Some organizations which have pioneered DevOps practices don’t really call them that; they’ve just organically grown their own processes to focus on efficiency, including minimizing silos and rapid delivery.

I have to admit, it helped me to reframe my perspective on various lectures using this structure; that may not be true to the spirit of DevOps itself (which de-emphasizes artificial constraints), but it’s given me some room for thought in terms of the areas I want to study and learn. The technology is interesting, but I don’t see myself working in those areas anytime soon; my real focus will be on organizational culture and workflow. As a manager, I want to increase my efficiency by building a team, and I think the path I’m on is to figure out how to push my team of system engineers and database administrators to prepare for continuous integration.