Sunday, March 28, 2021

Three Types of Technology Leaders

Technology leaders have many different focus areas and motivations. On today’s show, we’ll discuss three common types of leaders - Visionaries, Maintainers and Resume-Builders.

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THREE TYPES OF TECHNOLOGY LEADERS

VISIONARIES | TRANSFORMERS

  • Speak in stories, painting big pictures.
  • Truly understand the overall business, the broader markets, and the potentially changing landscapes ahead over both the near-term and long-term
  • Understand the timing of the markets and when change is needed vs. nice-to-have
  • Understand the breadth of competitive threats to the business
  • Understand both opportunities and opportunity costs 

MAINTAINERS | PROTECTORS 

  • Would like to be a visionary, but always default back to focusing on re-optimizing legacy investments
  • Tend to believe that all decisions are build vs. buy. Aren’t focused on creating longer-term partnerships
  • Run long RFI processes vs. creating a mindset of incremental experimental scenarios.
  • Have a protectionist mindset (“avoid vendor lock-in”) with new opportunities, but don’t release that with sunk costs. 

RESUME BUILDERS

  • Recognize that the world is moving fast (lots of new technologies, business models), but aren’t in an optimal starting position.
  • Establish a big, audacious goal that portrays a visionary mindset. 
  • Establish an “everything” or “all-inclusive” policy, even when it doesn’t make economic sense. 
  • The old 5yrs of building an ERP system is now the 2yrs of transforming to the cloud. Springboard to build the resume without finishing the project. 


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Wednesday, March 24, 2021

From Engineer to Technology Leadership

Nick Weaver (@lynxbat, VP Architecture, Innovation, Data/Analytics at @Dicks) talks about the journey from engineer to technology leader within large corporations, the challenges of leading teams during COVID, and the realities of digital transformation.  

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Topic 1 - Welcome back to the show. It’s been almost two years. What are you up to these days?

Topic 2 - The last 5-6 years, you’ve really embraced moving from being a hard-core, hands-on engineer to being a leader of very large technology teams, projects and initiatives. Walk us through some of the new muscles developed, some of the unexpected, and some of the stuff you still need to figure out.

Topic 3 - When you were at Nike, you lived through a legitimate “digital transformation”, both in how the company engaged with the market, but also how you dealt with suppliers/vendors. Help us understand some of the dynamics in going through those changes.

Topic 4 - We all know lots of people on the vendor side of things, and how those dynamics work as people compete, collaborate or change companies. How does that work amongst “customers”, either in the same industry or cross-industry?

Topic 5 - You’re still a technologist at heart. What technologies are interesting to you these days? 

Topic 6 - From where you are today, how would you mentor a young Nick Weaver that just did a 5 minute demo during an EMCworld keynote in 2008-2009? 


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Sunday, March 21, 2021

Did COVID transform Tech?

The COVID-19 pandemic will last ~18 months, but how long will the impact to the technology industry last? 

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HOW WILL COVID CHANGE THE TECH INDUSTRY?

REMOTE WORK and COLLABORATION

  • The foundational tools are in place (GitHub, Zoom, Slack, Jira, Public Cloud) but are they really designed for large # of remote workers collaborating? 
  • Event sign-ups were up 5-10x, but have people actually been consuming the content? 
  • Will companies continue to encourage and support remote workers, or do we see a boomerang in late 2021 and 2022? 

MORE RAPID ADOPTION OF THE PUBLIC CLOUD

  • Less people in the office, so more adoption of public clouds?
  • Public clouds grew, but not at faster rates than before - 2021/2022 might be better indicators, as 2020 had “budget concerns” for many companies (uncertainty)
  • More adoption of SaaS-like offerings (be near the clouds, align buying models, more flexible)
  • Acceleration of more agile approaches, as the world becomes more polarized - hence stability may be shorter intervals? 

WHY DIDN’T THE CLOUD PROVIDERS DO MORE?

  • Cloud providers have massive cash reserves (Microsoft, $137B, Google $112B, Amazon $50B), but no major acquisitions.
  • Nobody has initiate price-wars, but we are seeing more long-range ELAs announced

WHERE IS THE “NEXT BIG THING”?

  • 2006/2007 - iPhone, AWS launch ; 2008 Financial Crash
  • 2020 - ???


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Wednesday, March 17, 2021

Understanding SaaS Financial Models

Ben Murray (@br_murray, Founder of SaaS CFO and SaaS Academy) talks about how to understand the financial models behind successful SaaS companies, the tradeoffs on profit vs. growth, and how to spot the health of SaaS businesses.

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Topic 1 - Welcome to the show. We don’t usually get CFOs on the show. Tell us a little bit about your background and what brought you into the SaaS world. 

Topic 2 - The more we study SaaS companies, the more it seems like everyone needs to understand the financial model and associated metrics (executives, product managers, marketing, customer service, etc.). How do you go about teaching best practices to SaaS companies?

Topic 3 - Let’s talk about the core financial concepts that SaaS companies need to think about (CAC, MRR, ACV, LCV, Churn, Gross Margin, etc.)

Topic 4 - Are there some common financial patterns (metrics, ratios, etc,) to tell how a SaaS company is doing (good or bad)? If so, are there established best-practices to get them out of bad situations?  

Topic 5 - Can you help us better understand why some people get excited when a SaaS company has revenue growth and loses money, and others freak out? Help us understand that in growth stages vs. stable stages. (SaaS Rule of 40?)

Topic 6 - Have you found that SaaS businesses are unique in their financial modeling, or can some of these best practices be applied to non-SaaS software businesses?

Topic 7 - You just started SaaS CFO and SaaS Academy. Give us an overview of what people will learn. 

 

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Sunday, March 14, 2021

The Complexities of Edge Computing

It’s smaller computers, doing limited tasks. So why is Edge Computing so complicated, and why are there so many definitions?

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THE COMPLEXITIES OF EDGE COMPUTING

No single definition of edge, because of so many use-cases

  • Branch office
  • Near-Edge 
  • Far-Edge
  • Disconnected

Hardware can dictate quite a bit about edge characteristics

  • Custom-OS or COTS OS
  • General purpose HW or Specialized HW (GPU, NVMe, DPUs)
  • #of computing devices; volume of local storage

Networking can dictate quite a bit about edge characteristics

  • Are the devices always connected to the Internet?
  • How are disconnected environments handled?
  • How much bandwidth is available? Is it symmetric or asymmetric? 
  • What are the traffic patterns of the applications? Local vs. Backhaul. 

Security can dictate quite a bit about edge characteristics

  • How does Security happen on Day 0?
  • What are the security vs. usability tradeoffs? (direct user interaction) 
  • How is security maintained? (CVE, Local Security services, etc.)

Maintenance can dictate quite a bit about edge characteristics

  • How much does it cost to deploy new edges?
  • How often are the edges expected to be upgraded? 
  • How will maintenance happen? (Local tech, remote download, etc.)
  • How sophisticated is the Day 2 Ops? (Telemetry, Environmentals, Benchmarks, etc.) 

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Wednesday, March 10, 2021

The Value of Value-Steam Mapping

Steve Pereira (@SteveElsewhere, Value-Stream Whisperer @ Visible) talks about measuring, understanding business and technology process through Value-Stream Mapping.

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Topic 1 - Welcome to the show. Tell us a little bit about your background and how you eventually became focused on helping companies improve their Value-Streams.

Topic 2 - Let’s start by talking about Value-Streams and Mapping. What are they, why do we need them, what do they provide? 

Topic 3 - Walk us through a Value-Stream-Mapping exercise with a company. What is their pre-homework? What questions do you ask? How do you keep it focused on their language? 

Topic 4 - Do you need to fix everything at once, or can it be done in phases? How much of the improvement has to do with the application, and how much is adjusting existing processes?  

Topic 5 - Lots of people like to compare this to Lean Manufacturing (Toyota Production System, Six Sigma, etc.). Optimize the system, design for efficient flows, empower the workers to make changes and give feedback, etc. But does this break with software, where there isn’t really an end to a production line? 

Topic 6 - Once people understand it, what tends to work well and what tends to lead to on-going failures? 

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Sunday, March 7, 2021

Lessons Learned from Cloud Foundry

Cloud Foundry was going to create an open source alternative to Heroku, as well as replace how Enterprise companies built software. But change is never easy. Looking back, what can we learn from the lessons of Cloud Foundry?

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HOW DID CLOUD FOUNDRY EVOLVE?

An open source, programmable cloud application platform (PaaS). Heroku (2007), Google AppEngine (2008) existed before Cloud Foundry (April 2011). OpenShift launched in May 2011. Apcera was launched in 2012 by Derek Collison 

  • Open Source, Multi-cloud
  • Multiple languages, frameworks
  • Automation for the infrastructure (BOSH)
  • Integrated Logging, Tracing, Routing, GUI
  • Data Services live off the platform, via Service Broker
  • Very heavy platform footprint (up to 50 VMs)
  • Diego container scheduler 
  • Warden container runtime 

Many large vendors got involved once it became a foundation. 

  • IBM, SAP, Intel, Cisco, EMC/VMware
  • Many end-user customers joined (great for recruiting)
  • None of the Cloud providers, other than an infrastructure stem-cell

By 2016-17, most large Cloud Foundry vendors were shifting their focus to Kubernetes

LESSONS LEARNED FOR THE FUTURE

  • Single-vendor led communities are difficult, especially if a foundation is created.
  • Technology transitions are hard, oftentimes impossible. Cloud Foundry chose to downplay Docker and Kubernetes as “just for infrastructure”, even within their own community. 
  • Make it simple to get environments/clusters (Managed Kubernetes services, Cluster API, laptop-level environments (minikube). Needs to be a managed cloud service on good clouds. 
  • Platform-aware, Infrastructure automation is important (e.g. like BOSH, except that it works)
  • Industry is mixed on if stateful / data services should run on-platform or off-platform. Having to also manage the off-platform is difficult. 

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