Deck from a talk on cycle times and how to apply them for informed decision making (forecasting, team building, balance, process improvement) and evolution from traditional estimation approaches.
Kanban Metrics in practice for leading Continuous ImprovementMattia Battiston
Why should I bother collecting metrics? How can they help me? My CFD is pretty and colourful, but what is it actually trying to tell me?
CFD, control chart, lead time distribution, percentiles...Metrics can be daunting to start with but if you know how to interpret them they can drive continuous improvement and forecast the future and take your Kanban system to the next level! It’s much easier than you think, no need for complex maths or expensive software.
At Sky Network Services a few teams are using Kanban and metrics. In this talk I’ll share our experience: what metrics we use, how we use each one of them, what little data we collect to get a whole lot of value, what pitfalls we encountered.
Downloads
Powerpoint: https://goo.gl/4CkKJd
PDF: https://goo.gl/VDW93U
This is a concept I devised a couple of years ago, and it seems there is a new #NoEstimates audience that would like to know more about it.
A Slicing Heuristic is essentially:
An explicit policy that describes how to "slice" work Just-In-Time to help us create consistency, a shared language for work and better predictability.
The Slicing Heuristic seeks to replace deterministic estimation rituals by incorporating empirical measurement of actual cycle times for the various types of work in your software delivery lifecycle.
It is based on the hypothesis that empiricism leads to smaller cycle time duration and variation (which in business value terms means quicker time to market and better predictability) because it requires work to be sliced into clear, simple, unambiguous goals. Crucially, the heuristic also describes success criteria to ensure it is achieving the level of predictability we require.
Its application is most effective when used for all levels of work, but can certainly be used for individual work types. For example, a User Story heuristic can be an extremely effective way of creating smaller, simpler work increments, allowing teams to provide empirical forecasts without the need for estimating how long individual stories will take. However, if you are able to incorporate this concept from the portfolio level down, the idea is that you define each work type (e.g. Program, Project, Feature, User Story, etc.) along with a Slicing Heuristic, which forms part of that work type’s Definition of Ready.
Service Levels and Error Budgets - Paweł KucharskiPROIDEA
SREs work together with product managers, product developers in a spirit of peaceful coexistence and cooperation. This talk discusses the SRE approach to managing services in cooperation with partners and covers concepts of indicators, objectives, and agreements; error budgets in practice. It will try to answer questions from how to define the Service Level Indicators (SLI) and how to make them useful with monitoring and alerting to how to define how good a service should be.
What's Measured Improves: Metrics that matterRaj Indugula
“Every line is the perfect length if you don't measure it.”
- Marty Rubin
So your organization has embarked upon a transformation to be more nimble and responsive by employing the latest tools and thinking in the Agile and DevOps arena. In this transformational context, how do you know that your initiatives are effective? Empirical measurements should provide insights on business value flow and delivery efficiency, allowing teams and organizations to see how they are progressing toward achieving their goals, but all too often we find ourselves mired in measurement traps that don't quite provide the right guidance in steering our efforts.
Rooted in contemporary thinking and tested in practice, this talk explores the principles of good measurement, what to measure, what not to measure, and enumerates some key metrics to help guide and inform our Agile and DevOps efforts. If done right, metrics can present a true picture of performance, and any progression, digression of these metrics can drive learning and improvement.
“Every line is the perfect length if you don't measure it.” - Marty Rubin
So your organization has embarked upon a transformation to be more nimble and responsive by employing the latest tools and thinking in the Agile and DevOps arena. In this transformational context, how do you know that your initiatives are effective? Empirical measurements should provide insights on business value flow and delivery efficiency, allowing teams and organizations to see how they are progressing toward achieving their goals, but all too often we find ourselves mired in measurement traps that don't quite provide the right guidance in steering our efforts.
Rooted in contemporary thinking and tested in practice, this talk explores the principles of good measurement, what to measure, what not to measure, and enumerates some key metrics to help guide and inform our Agile and DevOps efforts. If done right, metrics can present a true picture of performance, and any progression, digression of these metrics can drive learning and improvement.
It is our hope that this session inspires organizations and teams to start or take a fresh look at implementing a valuable measurement program.
Kanban Metrics in practice for leading Continuous ImprovementMattia Battiston
Why should I bother collecting metrics? How can they help me? My CFD is pretty and colourful, but what is it actually trying to tell me?
CFD, control chart, lead time distribution, percentiles...Metrics can be daunting to start with but if you know how to interpret them they can drive continuous improvement and forecast the future and take your Kanban system to the next level! It’s much easier than you think, no need for complex maths or expensive software.
At Sky Network Services a few teams are using Kanban and metrics. In this talk I’ll share our experience: what metrics we use, how we use each one of them, what little data we collect to get a whole lot of value, what pitfalls we encountered.
Downloads
Powerpoint: https://goo.gl/4CkKJd
PDF: https://goo.gl/VDW93U
This is a concept I devised a couple of years ago, and it seems there is a new #NoEstimates audience that would like to know more about it.
A Slicing Heuristic is essentially:
An explicit policy that describes how to "slice" work Just-In-Time to help us create consistency, a shared language for work and better predictability.
The Slicing Heuristic seeks to replace deterministic estimation rituals by incorporating empirical measurement of actual cycle times for the various types of work in your software delivery lifecycle.
It is based on the hypothesis that empiricism leads to smaller cycle time duration and variation (which in business value terms means quicker time to market and better predictability) because it requires work to be sliced into clear, simple, unambiguous goals. Crucially, the heuristic also describes success criteria to ensure it is achieving the level of predictability we require.
Its application is most effective when used for all levels of work, but can certainly be used for individual work types. For example, a User Story heuristic can be an extremely effective way of creating smaller, simpler work increments, allowing teams to provide empirical forecasts without the need for estimating how long individual stories will take. However, if you are able to incorporate this concept from the portfolio level down, the idea is that you define each work type (e.g. Program, Project, Feature, User Story, etc.) along with a Slicing Heuristic, which forms part of that work type’s Definition of Ready.
Service Levels and Error Budgets - Paweł KucharskiPROIDEA
SREs work together with product managers, product developers in a spirit of peaceful coexistence and cooperation. This talk discusses the SRE approach to managing services in cooperation with partners and covers concepts of indicators, objectives, and agreements; error budgets in practice. It will try to answer questions from how to define the Service Level Indicators (SLI) and how to make them useful with monitoring and alerting to how to define how good a service should be.
What's Measured Improves: Metrics that matterRaj Indugula
“Every line is the perfect length if you don't measure it.”
- Marty Rubin
So your organization has embarked upon a transformation to be more nimble and responsive by employing the latest tools and thinking in the Agile and DevOps arena. In this transformational context, how do you know that your initiatives are effective? Empirical measurements should provide insights on business value flow and delivery efficiency, allowing teams and organizations to see how they are progressing toward achieving their goals, but all too often we find ourselves mired in measurement traps that don't quite provide the right guidance in steering our efforts.
Rooted in contemporary thinking and tested in practice, this talk explores the principles of good measurement, what to measure, what not to measure, and enumerates some key metrics to help guide and inform our Agile and DevOps efforts. If done right, metrics can present a true picture of performance, and any progression, digression of these metrics can drive learning and improvement.
“Every line is the perfect length if you don't measure it.” - Marty Rubin
So your organization has embarked upon a transformation to be more nimble and responsive by employing the latest tools and thinking in the Agile and DevOps arena. In this transformational context, how do you know that your initiatives are effective? Empirical measurements should provide insights on business value flow and delivery efficiency, allowing teams and organizations to see how they are progressing toward achieving their goals, but all too often we find ourselves mired in measurement traps that don't quite provide the right guidance in steering our efforts.
Rooted in contemporary thinking and tested in practice, this talk explores the principles of good measurement, what to measure, what not to measure, and enumerates some key metrics to help guide and inform our Agile and DevOps efforts. If done right, metrics can present a true picture of performance, and any progression, digression of these metrics can drive learning and improvement.
It is our hope that this session inspires organizations and teams to start or take a fresh look at implementing a valuable measurement program.
Following agile is hard but following distributed agile is harder. This workshop will help understand the challenges faced by distributed teams and how to fix them. Lets have some fun and see how an onshore offshore team works together to achieve a common goal.
Kanban Metrics in practice at Sky Network ServicesMattia Battiston
Why should I bother collecting metrics? How can they help me? My CFD is pretty and colourful, but what is it actually trying to tell me?
CFD, control chart, lead time distribution, percentiles...Metrics can be daunting to start with but if you know how to interpret them they can really take your Kanban system to the next level - drive continuous improvement and forecast the future! It’s much easier than you think, no need for complex maths or expensive software.
At Sky Network Services a few teams are using Kanban and metrics. In this talk I’ll share our experience: what metrics we use, how we use each one of them, what little data we collect to get a whole lot of value, what pitfalls we encountered.
Downloads
Powerpoint: https://goo.gl/19wOjU
PDF: https://goo.gl/AM69MF
DOES16 San Francisco - David Blank-Edelman - Lessons Learned from a Parallel ...Gene Kim
Lessons Learned from a Parallel Universe
David N. Blank-Edelman, Technical Evangelist, Apcera
Just within the last ten or so years, we have seen at least two separate communities evolve at the crossroads of development and operations. The first—DevOps—grew up very much in public, the second matured sequestered within the halls of “special” companies like Google and Facebook and is only now starting to gain visibility and traction in the wider world. The DevOps and Site Reliability Engineering (SRE) communities barely speak, yet both have common ancestors and much to offer each other. Let’s look at what they have in common, how they differ, and what are the key things we can learn from both.
DevOps Enterprise Summit San Francisco 2016
Scrum teams use burn down chart to represent/track the iteration progress, and the most common burn down chart is the time-based one. But when doing that our team got some problems, it's not accurate to use time-based burn down to represent the true velocity and the feature completion. We experienced the situation that the team-velocity was pretty good, which means team could "burn" enough hours, while we didn't DELIVER as many feature comparing with the burn down. This topic is a case study based on what we did trying to resolve our problems.
Most teams need to answer questions like “When will it be done? What can I get by date X?”. However, common estimation approaches often fail to give us the predictability we want, and tend to introduce bad behaviours like hard deadlines and hiding uncertainty.
In this session, I’ll show you how, step by step and with real life examples, my team uses their historical data and metrics to forecast the future and answer these questions with confidence.
Download slides at: http://bit.ly/2pD9rfQ
Book discount link: http://leanpub.com/metricsforbusinessdecisions/c/MATTIA20-BZXib2F
See how metrics can be used with your Kanban System for managing flow, your project and changes.
At least three practices of the Kanban Method imply the use of metrics. Metrics can be powerful tools. Sadly most kanban systems don’t make use of them and miss out on a big chance to make things easier. Metrics can help us with lots of different things we encounter in business like finishing projects on budget and on time, fighting for survival in the market, and continuous change to adapt in this complex world. Learn how metrics can help you and how to choose the right metric for your situation.
2017 Music City Agile Conference: NoEstimates WorkshopMatthew Philip
Slides from my workshop as facilitated at the 2017 Music City Agile Conference in Nashville, Tennessee. https://2017.musiccityagile.org/schedule/the-noestimates-game
It’s easy to fall into the trap of measuring everything, and achieving nothing. Or just measuring the wrong thing and getting stuck in a local optimum. We’ve seen how difficult this can be for a software development progress. Continuous Delivery, due to its more technical focus, can seem to be much easier to measure. But which measurements are important? What do they signal? How do we take action? And when should we perhaps do without?
In this talk I’ll discuss those subjects, and how the answers change along the way: from a small team to large scale; from beginning with agile to full continuous deployment; and from the team’s day-to-day decisions to the high-level management report.
Metrics and measurements are hard. For Continuous Delivery, due to its more technical focus, that can seem much easier. But which measurements are important? What do they signal? How do we take action? And when should we do without?
The answers change along the way: from small teams to large scale; from beginning with agile to full continuous deployment; and from teams’ day-to-day decisions to high-level management reports.
Agile Estimating & Planning by Amaad QureshiAmaad Qureshi
An introduction to Agile Estimating and how it can be used to measure the size and length of work.
Agile estimating & planning is a way of measuring the size and time it takes to complete a task. This technique is used by Agile teams in Enterprise and can be utilised in the same way by Start-ups not just for software but for all areas of the business. In this talk I will show you how estimating & planning works by:
- Writing effective user stories
- Writing tests to validate stories (acceptance criteria)
- Using story points to work out the size of a task
- Estimating using Planning Poker
- Using Story Points to calculate a team’s velocity (speed of work)
- Using a team’s velocity to calculate project length
Ever wonder why Agile teams swear by relative estimation? My teams improved sprint planning efforts by a factor or 3, once we started using relative estimation.
Without understanding Agile relative estimation, teams tend to fall back to using time-based methods. This often leads them to spend way too much time on obsolete estimates that will be made even more complex with all the unknowns and constant emergent requirements of an Agile world!
“It's better to be roughly right, than precisely wrong!”
~ John Maynard Keyenes
The Solution is simple: understand that relative estimation is only a rough order of magnitude estimate to quickly organize the product backlog. This empowers your product owners (PO) to quickly make value based trade-offs on backlog items and decide on what stories the team should work next. This gives the business the highest bang for their buck!
PROBLEMS WITH TIME-BASED ESTIMATES
-Teams spend too much time trying to get it right
-Lack of confidence/experience can lead to people being either optimistic or pessimistic
-Timeline you are estimating may be too far in the future
-Due to long timeline, there are too many risks, unknowns, changes or dependencies!
WHY USE RELATIVE ESTIMATION?
-Allows a quick comparison of stories in the backlog
-Allows you to select a predictable volume of work to do in a sprint
-Uses a simple arbitrary scale
-Allows PO to make trade-offs and take on the most valuable stories next
ESTIMATION TIPS
-Relative points or equivalent Tshirt sizes are used to estimate stories, leveraging the Fibonacci sequence modified for Agile.
-The team estimates the story, not management nor the customer.
-Story estimates account for three things: effort, complexity, and unknowns. Don’t short sell yourself by estimating effort alone, that’s where waterfall projects face issues.
-Remember to estimate all Stories, user stories or technical stories. Even estimate research or discovery spikes.
-Refine your backlog as a team on a continuous basis, to get your stories to meet the Definition of Ready.
-Only pull into your sprint, stories that are refined and estimated.
-Break down stories that are large, into smaller slivers of value to optimize your flow.
-Don’t sweat it if you get it wrong, teams often do early on but improve over time.
Following agile is hard but following distributed agile is harder. This workshop will help understand the challenges faced by distributed teams and how to fix them. Lets have some fun and see how an onshore offshore team works together to achieve a common goal.
Kanban Metrics in practice at Sky Network ServicesMattia Battiston
Why should I bother collecting metrics? How can they help me? My CFD is pretty and colourful, but what is it actually trying to tell me?
CFD, control chart, lead time distribution, percentiles...Metrics can be daunting to start with but if you know how to interpret them they can really take your Kanban system to the next level - drive continuous improvement and forecast the future! It’s much easier than you think, no need for complex maths or expensive software.
At Sky Network Services a few teams are using Kanban and metrics. In this talk I’ll share our experience: what metrics we use, how we use each one of them, what little data we collect to get a whole lot of value, what pitfalls we encountered.
Downloads
Powerpoint: https://goo.gl/19wOjU
PDF: https://goo.gl/AM69MF
DOES16 San Francisco - David Blank-Edelman - Lessons Learned from a Parallel ...Gene Kim
Lessons Learned from a Parallel Universe
David N. Blank-Edelman, Technical Evangelist, Apcera
Just within the last ten or so years, we have seen at least two separate communities evolve at the crossroads of development and operations. The first—DevOps—grew up very much in public, the second matured sequestered within the halls of “special” companies like Google and Facebook and is only now starting to gain visibility and traction in the wider world. The DevOps and Site Reliability Engineering (SRE) communities barely speak, yet both have common ancestors and much to offer each other. Let’s look at what they have in common, how they differ, and what are the key things we can learn from both.
DevOps Enterprise Summit San Francisco 2016
Scrum teams use burn down chart to represent/track the iteration progress, and the most common burn down chart is the time-based one. But when doing that our team got some problems, it's not accurate to use time-based burn down to represent the true velocity and the feature completion. We experienced the situation that the team-velocity was pretty good, which means team could "burn" enough hours, while we didn't DELIVER as many feature comparing with the burn down. This topic is a case study based on what we did trying to resolve our problems.
Most teams need to answer questions like “When will it be done? What can I get by date X?”. However, common estimation approaches often fail to give us the predictability we want, and tend to introduce bad behaviours like hard deadlines and hiding uncertainty.
In this session, I’ll show you how, step by step and with real life examples, my team uses their historical data and metrics to forecast the future and answer these questions with confidence.
Download slides at: http://bit.ly/2pD9rfQ
Book discount link: http://leanpub.com/metricsforbusinessdecisions/c/MATTIA20-BZXib2F
See how metrics can be used with your Kanban System for managing flow, your project and changes.
At least three practices of the Kanban Method imply the use of metrics. Metrics can be powerful tools. Sadly most kanban systems don’t make use of them and miss out on a big chance to make things easier. Metrics can help us with lots of different things we encounter in business like finishing projects on budget and on time, fighting for survival in the market, and continuous change to adapt in this complex world. Learn how metrics can help you and how to choose the right metric for your situation.
2017 Music City Agile Conference: NoEstimates WorkshopMatthew Philip
Slides from my workshop as facilitated at the 2017 Music City Agile Conference in Nashville, Tennessee. https://2017.musiccityagile.org/schedule/the-noestimates-game
It’s easy to fall into the trap of measuring everything, and achieving nothing. Or just measuring the wrong thing and getting stuck in a local optimum. We’ve seen how difficult this can be for a software development progress. Continuous Delivery, due to its more technical focus, can seem to be much easier to measure. But which measurements are important? What do they signal? How do we take action? And when should we perhaps do without?
In this talk I’ll discuss those subjects, and how the answers change along the way: from a small team to large scale; from beginning with agile to full continuous deployment; and from the team’s day-to-day decisions to the high-level management report.
Metrics and measurements are hard. For Continuous Delivery, due to its more technical focus, that can seem much easier. But which measurements are important? What do they signal? How do we take action? And when should we do without?
The answers change along the way: from small teams to large scale; from beginning with agile to full continuous deployment; and from teams’ day-to-day decisions to high-level management reports.
Agile Estimating & Planning by Amaad QureshiAmaad Qureshi
An introduction to Agile Estimating and how it can be used to measure the size and length of work.
Agile estimating & planning is a way of measuring the size and time it takes to complete a task. This technique is used by Agile teams in Enterprise and can be utilised in the same way by Start-ups not just for software but for all areas of the business. In this talk I will show you how estimating & planning works by:
- Writing effective user stories
- Writing tests to validate stories (acceptance criteria)
- Using story points to work out the size of a task
- Estimating using Planning Poker
- Using Story Points to calculate a team’s velocity (speed of work)
- Using a team’s velocity to calculate project length
Ever wonder why Agile teams swear by relative estimation? My teams improved sprint planning efforts by a factor or 3, once we started using relative estimation.
Without understanding Agile relative estimation, teams tend to fall back to using time-based methods. This often leads them to spend way too much time on obsolete estimates that will be made even more complex with all the unknowns and constant emergent requirements of an Agile world!
“It's better to be roughly right, than precisely wrong!”
~ John Maynard Keyenes
The Solution is simple: understand that relative estimation is only a rough order of magnitude estimate to quickly organize the product backlog. This empowers your product owners (PO) to quickly make value based trade-offs on backlog items and decide on what stories the team should work next. This gives the business the highest bang for their buck!
PROBLEMS WITH TIME-BASED ESTIMATES
-Teams spend too much time trying to get it right
-Lack of confidence/experience can lead to people being either optimistic or pessimistic
-Timeline you are estimating may be too far in the future
-Due to long timeline, there are too many risks, unknowns, changes or dependencies!
WHY USE RELATIVE ESTIMATION?
-Allows a quick comparison of stories in the backlog
-Allows you to select a predictable volume of work to do in a sprint
-Uses a simple arbitrary scale
-Allows PO to make trade-offs and take on the most valuable stories next
ESTIMATION TIPS
-Relative points or equivalent Tshirt sizes are used to estimate stories, leveraging the Fibonacci sequence modified for Agile.
-The team estimates the story, not management nor the customer.
-Story estimates account for three things: effort, complexity, and unknowns. Don’t short sell yourself by estimating effort alone, that’s where waterfall projects face issues.
-Remember to estimate all Stories, user stories or technical stories. Even estimate research or discovery spikes.
-Refine your backlog as a team on a continuous basis, to get your stories to meet the Definition of Ready.
-Only pull into your sprint, stories that are refined and estimated.
-Break down stories that are large, into smaller slivers of value to optimize your flow.
-Don’t sweat it if you get it wrong, teams often do early on but improve over time.
Presentation by Nico De Greef as delivered during the event "How successful teams are built on top
of Atlassian and Tempo" on the 29th of September, 2015
This August Scrum Breakfast, we have a new speaker - Mr. Pedro Gonzalez - Scrum Master at TINYpulse.
He will bring us an interesting topic about Agile estimation using story points, giving some tips on why relative estimations are far better than absolutes, why we shouldn't spend too long in details, and other issues he has experienced himself with his team.
Agile Patterns: Agile Estimation
We’re agile, so we don’t have to estimate and have no deadlines, right? Wrong! This session will consist of review of the problem with estimation in projects today and then an overview of the concept of agile estimation and the notion of re-estimation. We’ll learn about user stories, story points, team velocity, how to apply them all to estimation and iterative re-estimation. We will take a look at the cone of uncertainty and how to use it to your advantage. We’ll then take a look at the tools we will use for Agile Estimation, including planning poker, Visual Studio Team System, and much more. This is a very interactive session, so bring a lot of questions!
Estimating with MAGIC Approach – Measure, Analyze, Improve and Control without ‘Guess’ work
#) Measure & Analyze using ‘Story Point Matrix’ based on Functional & Technical Analysis
#)Improve & Control using Statistical Data Modeling based on Empirical Data extracted from agile project management tool
Speak To The Business! Agile Metrics That Inform Rather Confuse the Businesstroytuttle
Given to PMI KC Professional Development Days 2014 Conference.
In this session, we will investigate the challenges with the popular Agile planning and reporting concepts like story points, planning poker, and average velocity. We will explore some practical alternative planning and reporting practices that the business can understand. And we will look at metrics that are less of an abstraction from reality and more actionable by teams and management.
Have your Agile practices become stale or redundant? Does it feel like your team is just going through the motions? Have team members asked to discontinue “critical Agile practices” and ceremonies?
In Lean product development, the minimum viable product or MVP, is defined as the product with the highest return on investment versus risk. It’s a strategy to avoid building products that customers don’t need or want by maximizing our learning of what is valuable to the customer.
Agile is typically learned through exposure to a series of Agile practices, a recipe of sorts. But what if that recipe goes beyond minimal? Have we replaced heavy waterfall process with heavy Agile process?
This session will interrogate the thinking behind some of the Agile sacred cows like detailed sprint planning, detailed release planning, and even some popular estimation techniques. We will try to identify what is truly needed to be Agile, based on needs instead of prescribed recipes. What is minimally sufficient to start realizing the benefits of Agile?
What is your MVA? It might be different than you think!
I gave this presentation at Lean Kanban Asia-Pacific conference in Bangalore, India on December 11th, 2014 and at AgileDC on Washington, USA on October 21st, 2014.
I have several recent blog posts on this topic, This search link should get most of them: http://connected-knowledge.com/?s=lead+time. If you need one "best" post, here it is, Inside a Lead Time Distribution: http://connected-knowledge.com/2014/09/07/inside-lead-time-distribution/
Why should you multiply developer's estimation by 3?
What are the goals and crucial steps of estimation process?
And a little bit of theory.
See in this presentation.
You’re an expert developer, peacefully composing code into a profoundly elegant masterpiece, when suddenly your boss rushes in with the Next Big Idea that will Revolutionize The Way People Use The Internet. He’s on his way to pitch to a VC, and stops by to describe the Idea in excited terms. After a 30 second elevator pitch, he pops the question: “So, Peter, how long do you think it will take to build this thing-a-ma-bob?”
What do you say?
These eight Protips will cover your back, save your job, and keep your boss’s shirt.
Effective Quality Facilitation | Beyond NormalSPIN Chennai
The presentation gives a glance on the software quality analysts who has to take up the full responsibility to ensure compliance. It inspires the analysts with different methods and examples for a successful delivery.
Using MLOps to Bring ML to Production/The Promise of MLOpsWeaveworks
In this final Weave Online User Group of 2019, David Aronchick asks: have you ever struggled with having different environments to build, train and serve ML models, and how to orchestrate between them? While DevOps and GitOps have made huge traction in recent years, many customers struggle to apply these practices to ML workloads. This talk will focus on the ways MLOps has helped to effectively infuse AI into production-grade applications through establishing practices around model reproducibility, validation, versioning/tracking, and safe/compliant deployment. We will also talk about the direction for MLOps as an industry, and how we can use it to move faster, with more stability, than ever before.
The recording of this session is on our YouTube Channel here: https://youtu.be/twsxcwgB0ZQ
Speaker: David Aronchick, Head of Open Source ML Strategy, Microsoft
Bio: David leads Open Source Machine Learning Strategy at Azure. This means he spends most of his time helping humans to convince machines to be smarter. He is only moderately successful at this. Previously, David led product management for Kubernetes at Google, launched GKE, and co-founded the Kubeflow project. David has also worked at Microsoft, Amazon and Chef and co-founded three startups.
Sign up for a free Machine Learning Ops Workshop: http://bit.ly/MLOps_Workshop_List
Weaveworks will cover concepts such as GitOps (operations by pull request), Progressive Delivery (canary, A/B, blue-green), and how to apply those approaches to your machine learning operations to mitigate risk.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
12. Cycle Times
• Methodology Neutral Measurement
• Tool for understanding the big picture
and all of the little pictures within it
• Think Lean Manufacturing
15. Scenario Introduction
Backlog Ready… In… Ready… In… Ready for
Signoff
Done
- Req’ts
- To Do
- Ready for Dev
- Ready for UX
- Ready for
Design
- In Progress
- In Dev
- In UX
- In Design
- Ready for QA
- Ready for
Staging
- In QA
- Testing
- Build
- Ready for
Signoff
- Ready for PO
- Ready for
Build
- Ready for
Prod
- Ready for X
- Approved
17. Scenario In Progress
Backlog Ready for
Dev
In Dev Ready for
QA
In QA Ready for
Signoff
Approved
#10
Story Chore Bug
#12
#23
#14
#8
#3#9
#7
18. Scenario In Progress
Backlog Ready for
Dev
In Dev Ready for
QA
In QA Ready for
Signoff
Approved
#10
Story Chore Bug
#12
#23
#14
#8
#3#9#7
In Dev: 1.2 days
Ready for QA: .5
In QA: 1
Ready for
Signoff: 2 days
Total: 4.7 days
19. Cycle Time Definition
The time it takes for a unit to move
through a development process
• Unit is any piece of work: Story, Chore,
Defect/Bug, Technical Task, etc.
• Can be measured at the highest level
(start to finish) or incremental levels (as
small as you can)
• The value is based on what you put into it
20. How To:
Req. # Type Ready
Dev
In Dev Ready QA In QA Ready
Accept
Total
12 Story .4 .25 .5 1 2.4
9 Story .5 1 .5 .25 1.5 4.5
14 Chore 1.5 1.5
26 Story .5 1.5 1 .5 .25 3.75
33 Bug .75 .3 1.4 1.25 3.9
21. When To:
• As is the case with “How to” – it depends
on the tools you use
• Grab the data as frequently as you can,
always better to do it as soon as possible
• The rule is up to you
27. Scenario Flashback
Backlog Ready for
Dev
In Dev Ready for
QA
In QA Ready for
Signoff
Approved
#10
Story Chore Bug
#12
#23
#14
#8
#3#9
#7
28. How To Flashback:
Req. # Type Ready Dev In Dev Ready QA In QA Ready
Accept
Total # of Handoffs
12 Story .4 .25 .5 1 2.15 3
9 Story .5 1 .5 .25 1.5 3.75 5
14 Chore 1.5 1.5 0
26 Story .5 1.5 1 .5 .25 3.75 4
33 Bug .75 .3 1.4 1.25 3.9 3
29.
30.
31.
32. Endless Opportunities
• Individual Efficiency
• Pair Productivity
• Process changes (intro of new tools)
• Knowledge of handbacks
• Ability to plan when a person (or entire
skill set) will not be available and know
the impact based on data
• Planning, forecasting, estimating…
33. Overhead from Planning
• Time = Money
• Inaccurate Estimates
– Waterfall = 14% success
– Agile = 42% success
– PSP/TSP = 94% accurate (small sample & consider the
significant overhead)
“Humans aren't very good at estimating in general, regardless
of what measure is used.” – Joshua Kerievsky
Time is money & estimates are often inaccurate
36. How To Flashback #2:
Req. # Type Ready Dev In Dev Ready QA In QA Ready
Accept
Total # of
Handoffs
# of Story
Pts
12 Story .4 .25 .5 1 2.4 3 3
9 Story .5 1 .5 .25 1.5 4.5 5 5
14 Chore 1.5 1.5 0 1
26 Story .5 1.5 1 .5 .25 3.75 4 8
33 Bug .75 .3 1.4 1.25 3.9 3 5
38. #NoEstimates
• Pull the carpet out from story points and
use total # of units (stories + chores +
bugs, etc.)
• Balance slices or come to terms with
tradeoffs – Big tickets will balance out
with little ones
“Using story counting does not imply that all the stories are roughly the same
size (although some teams do work that way). Stories can still vary in size,
but over time the bigger and smaller stories will cancel each other out, hence
a simple count ends up the same.” – Martin Fowler
39. Benefits of Unit-based Planning
• Standardize expectations & remove opportunity
for inflation
• Save engineering time
• Use ongoing data to plan more accurately and
with less overhead