Talk about the soft side of scalability, covering team management, process implementation and some solid technology-related principles. Based on 10 years of experience building scalable teams and scalable data platforms
What you till learn:
GOALS - What is the bar for data science teams
PITFALLS - What are common data science struggles
DIAGNOSES - Why so many of our efforts fail to deliver value
RECOMMENDATIONS - How to address these struggles with best practices
Presented by Mac Steele
Director of Product at Domino Data Lab
How to apply machine learning into your CI/CD pipelineAlon Weiss
A quick introduction to AIOps, the business reasons why the CI/CD pipeline needs to constantly improve, and how this can be accomplished with data that's already available with existing Machine Learning and other algorithms.
Bitkom Cray presentation - on HPC affecting big data analytics in FSPhilip Filleul
High value analytics in FS are being enabled by Graph, machine learning and Spark technologies. To make these real at production scale HPC technologies are more appropriate than commodity clusters.
LUISS - Deep Learning and data analyses - 09/01/19Alberto Paro
My participation to the course "Data Analysis, Mobility, Proximity and App-based Marketing".
A new perspective on how data support companies on strategic decisions.
What to Expect When You're Expecting (to Own Production)Michael Diamant
The intended presentation audience is developers unfamiliar with owning a production environment. I aim to share lessons I’ve learned while supporting production environments and to paint a path for how ownership can be built.
By no means is this intended to be a comprehensive guide to production ownership. Instead, it should be treated as an introduction or one of the first few steps into the topic.
This presentation was motivated by a former colleague seeking to help frame his team's mindset toward production ownership. He joined a team that was not accustomed to production deploys, on-call, etc and thought it would be valuable to share insight from our experience together in an environment where developers co-owned production.
The development of a product from the point of view of a technician, starting from the concept, passing to the minimum viable till a management of a fully operational and deployed app.
What you till learn:
GOALS - What is the bar for data science teams
PITFALLS - What are common data science struggles
DIAGNOSES - Why so many of our efforts fail to deliver value
RECOMMENDATIONS - How to address these struggles with best practices
Presented by Mac Steele
Director of Product at Domino Data Lab
How to apply machine learning into your CI/CD pipelineAlon Weiss
A quick introduction to AIOps, the business reasons why the CI/CD pipeline needs to constantly improve, and how this can be accomplished with data that's already available with existing Machine Learning and other algorithms.
Bitkom Cray presentation - on HPC affecting big data analytics in FSPhilip Filleul
High value analytics in FS are being enabled by Graph, machine learning and Spark technologies. To make these real at production scale HPC technologies are more appropriate than commodity clusters.
LUISS - Deep Learning and data analyses - 09/01/19Alberto Paro
My participation to the course "Data Analysis, Mobility, Proximity and App-based Marketing".
A new perspective on how data support companies on strategic decisions.
What to Expect When You're Expecting (to Own Production)Michael Diamant
The intended presentation audience is developers unfamiliar with owning a production environment. I aim to share lessons I’ve learned while supporting production environments and to paint a path for how ownership can be built.
By no means is this intended to be a comprehensive guide to production ownership. Instead, it should be treated as an introduction or one of the first few steps into the topic.
This presentation was motivated by a former colleague seeking to help frame his team's mindset toward production ownership. He joined a team that was not accustomed to production deploys, on-call, etc and thought it would be valuable to share insight from our experience together in an environment where developers co-owned production.
The development of a product from the point of view of a technician, starting from the concept, passing to the minimum viable till a management of a fully operational and deployed app.
Machine Data Is EVERYWHERE: Use It for TestingTechWell
As more applications are hosted on servers, they produce immense quantities of logging data. Quality engineers should verify that apps are producing log data that is existent, correct, consumable, and complete. Otherwise, apps in production are not easily monitored, have issues that are difficult to detect, and cannot be corrected quickly. Tom Chavez presents the four steps that quality engineers should include in every test plan for apps that produce log output or other machine data. First, test that the data is being created. Second, ensure that the entries are correctly formatted and complete. Third, make sure the data can be consumed by your company’s log analysis tools. And fourth, verify that the app will create all possible log entries from the test data that is supplied. Join Tom as he presents demos including free tools. Learn the steps you need to include in your test plans so your team’s apps not only function but also can be monitored and understood from their machine data when running in production.
Which design techniques do I have at my disposal & how do I know when to apply them? PART 1 of 2
There are a great number of design methods & it is important to choose those that are best suited to your particular circumstances & objectives.
In this class we look at some of those methods & talk about the criteria to take into account for their use.
Александр Махомет "Beyond the code или как мониторить ваш PHP сайт"Fwdays
Стабильный и быстрый сайт => довольные пользователи => успешный бизнес.
Хороший сайт это живой организм, он растет и меняется, и как всем живим организмам за ним требуется наблюдение.
Я расскажу об инструментах и методиках, помогающих поддерживать ваш сайт в тонусе на примере PHP сайта.
Важность DevOps культуры
Доступные инструменты для логирования, мониторинга и алертинга
Какие метрики собирать, как их анализировать
Особенности распределенной, микросервисной архитектуры
Опыт upwork.com в этой области
Рассмотрим следующие инструменты:
- Custom solutions
- Google Analytics
- New Relic
- ELK stack (Elasticsearch / Logstash / Kibana)
- Graphite / StatsD / Grafana
- PagerDuty / PostMortems
- Zipkin
- ...
Доклад во многом применим не только к РHP продуктам.
Managing an Experimentation Platform by LinkedIn Product LeaderProduct School
Main Takeaways:
-Establishing a culture of experimentation at scale
-Developing the product vision and strategy
-Backlog prioritization based on Impact Score formula
Learning Objective: Increase professional effectiveness, data management, and analytical skills
With evolving technology, many people are overloaded and overwhelmed with information and data. Businesses now have access to large amounts of feedback from internal and external sources. How do we make sense of the all of the information? Is the data reliable? How can we manage and utilize the data in order to impact business goals, visions, mission? This seminar with help you turn your information overload into powerful and reliable data that you can use to meet organizational goals.
At the end of this seminar, participants will be able to:
a. Assess and categorize data and information.
b. Identify tools and techniques to organize and interpret data.
c. Explore productivity tools and techniques.
d. Examine common data management challenges and solutions.
MineExcellence solutions help in designing, optimizing and analyzing how blasts are performing in an integrated manner. We also have a very innovative mobile app - Smart Blasting app available in Android and iPhone. We have products for some other areas in mining such as Drilling, MineSafety App and Operational Analytics.
1. Blast Designer
2. Blast Data Collection and Management (BIMS)
3. Mobile app for Blasting (Smart Blasting)
4. Blasting Predictors – Air and Ground Vibration, Fragmentation and Fly-rock. Pattern Simulation /Analysis
5. Blast Designer and BIMSu for underground blasting
6. Drilling Platform(Drill Log, Plod Reports and Daily activity)
7. Mine Safety APP
8. Operational Analytics : (Combines drilling, blasting, loading, hauling etc)
9. Web and Mobile Custom Forms for all aspects of mining Lifecycle
10. Drone Platform for Mining Operations
Test Design for Fully Automated Build ArchitectureTechWell
Imagine this … As soon as any developed functionality is submitted into the code repository, it is automatically subjected to the appropriate battery of tests and then released straight into production. Setting up the pipeline capable of doing just that is becoming more and more common and something you need to know about. But most organizations hit the same stumbling block—just what IS the appropriate battery of tests? Automated build architectures don't always lend themselves well to the traditional stages of testing. In this hands-on tutorial, Melissa Benua introduces you to key test design principles—applicable to organizations both large and small—that allow you to take full advantage of the pipeline's capabilities without introducing unnecessary bottlenecks. Learn how to make highly reliable tests that run fast and preserve just enough information to let testers and developers determine exactly what went wrong and how to reproduce the error locally. Explore ways to reduce overlap while still maintaining adequate test coverage. Take back ideas about which test areas could benefit from being combined into a single suite and which areas could benefit most from being broken out altogether.
How to Manage the Risk of your Polyglot EnvironmentsDevOps.com
In this webinar, we’ll explore how to navigate the tension between speed and security when it comes to open source languages.
Enterprises are challenged by conflicting interests:
Engineering teams want more time to focus on code quality, but product managers want to ship faster.
Developers want the best tool for the job, but companies resist adding more technology stacks to their growing tech debt.
Retrofitting for security and vulnerabilities after the fact becomes a big blocker for Development and Engineering teams. Enterprises are challenged with resolving new threats and vulnerabilities at the pace at which they crop up. And yet, speed wins over security because faster time-to-market takes a greater priority over fixing vulnerabilities.
Our expert panel will cover how to resolve the tension between speed and security by practices which:
Minimize DevOps overhead from retrofitting programming languages with new versions, dependencies, security patches, etc.
Enable Continuous Builds to keep up with your continuous deployments
Use Build Validation to vet your continuous builds against smoke tests
Not long ago the question was whether your organization had big data. Did you have the volume, the velocity, the technology. Now those basics are largely given for most of the people attending this event. The path to success is still fuzzy, however, with so many technologies to choose from – and so many ways to use them.
This presentation triangulates in a holistic manner on the modern business dilemma: how can we leverage technology to improve revenue, profit, market share, and numerous other success criteria. That said, this is not about the analytics or KPIs -- although it is about measurable improvement. It’s about lining up the right technologies and using them in effective, proven ways to maximize Return on Investment (ROI). Since the slant here is holistic, we’ll show how to blend infrastructure, tools, methods, and talent to avoid and constantly trim technical debt… and to produce success stories that are consistently repeatable, not a byproduct of individual heroics.
DevOpsRoadTrip San Francisco Final Speaking Deck VictorOps
Join well known industry thought leaders and experts from local San Francisco companies for a 1/2 day event focused on the latest and greatest in DevOps practices.
https://victorops.com/devops-roadtrip-sf/
Presentation given at the OpenStack summit in Paris (Kilo) on Tue Nov 4th.
Last summit I had the pleasure to present a talk which encountered some success "Are enterprise ready for the OpenStack transformation?" (also published on SlideShare) . This talk is a follow up on what are the best practices that are successful in operating the transformation. We will first focus on identifying the right use cases for a generic enterprise, then define a roadmap with an organisational and a technical track, to finish with the definition what would be our success criterias for our group. This will happen as a workshop summary based on the multiple engagements eNovance has been delivering over the past 2 years.
This presentation overviews some of the core use cases and business requirements that drive standard ETL processes. The presentation then addresses common failure cases and provides high level development and architectural guidance.
Monitoring at scale - Intuitive dashboard designLorenzo Alberton
At a certain scale, millions of events happen every second, and all of them are important to evaluate the health of the system. If not handled correctly, such a volume of information can overwhelm both the infrastructure that needs to support them, and people who have to make a sense out of thousands of signals and make decisions upon them, fast. By understanding how our rational mind works, how people process information, we can present data so it's more evident and intuitive. This talk will explain how to collect useful metrics, and to create the perfect monitoring dashboard to organise and display them, letting our intuition operate automatically and quickly, and saving attention and mental effort to activities that demand it.
Machine Data Is EVERYWHERE: Use It for TestingTechWell
As more applications are hosted on servers, they produce immense quantities of logging data. Quality engineers should verify that apps are producing log data that is existent, correct, consumable, and complete. Otherwise, apps in production are not easily monitored, have issues that are difficult to detect, and cannot be corrected quickly. Tom Chavez presents the four steps that quality engineers should include in every test plan for apps that produce log output or other machine data. First, test that the data is being created. Second, ensure that the entries are correctly formatted and complete. Third, make sure the data can be consumed by your company’s log analysis tools. And fourth, verify that the app will create all possible log entries from the test data that is supplied. Join Tom as he presents demos including free tools. Learn the steps you need to include in your test plans so your team’s apps not only function but also can be monitored and understood from their machine data when running in production.
Which design techniques do I have at my disposal & how do I know when to apply them? PART 1 of 2
There are a great number of design methods & it is important to choose those that are best suited to your particular circumstances & objectives.
In this class we look at some of those methods & talk about the criteria to take into account for their use.
Александр Махомет "Beyond the code или как мониторить ваш PHP сайт"Fwdays
Стабильный и быстрый сайт => довольные пользователи => успешный бизнес.
Хороший сайт это живой организм, он растет и меняется, и как всем живим организмам за ним требуется наблюдение.
Я расскажу об инструментах и методиках, помогающих поддерживать ваш сайт в тонусе на примере PHP сайта.
Важность DevOps культуры
Доступные инструменты для логирования, мониторинга и алертинга
Какие метрики собирать, как их анализировать
Особенности распределенной, микросервисной архитектуры
Опыт upwork.com в этой области
Рассмотрим следующие инструменты:
- Custom solutions
- Google Analytics
- New Relic
- ELK stack (Elasticsearch / Logstash / Kibana)
- Graphite / StatsD / Grafana
- PagerDuty / PostMortems
- Zipkin
- ...
Доклад во многом применим не только к РHP продуктам.
Managing an Experimentation Platform by LinkedIn Product LeaderProduct School
Main Takeaways:
-Establishing a culture of experimentation at scale
-Developing the product vision and strategy
-Backlog prioritization based on Impact Score formula
Learning Objective: Increase professional effectiveness, data management, and analytical skills
With evolving technology, many people are overloaded and overwhelmed with information and data. Businesses now have access to large amounts of feedback from internal and external sources. How do we make sense of the all of the information? Is the data reliable? How can we manage and utilize the data in order to impact business goals, visions, mission? This seminar with help you turn your information overload into powerful and reliable data that you can use to meet organizational goals.
At the end of this seminar, participants will be able to:
a. Assess and categorize data and information.
b. Identify tools and techniques to organize and interpret data.
c. Explore productivity tools and techniques.
d. Examine common data management challenges and solutions.
MineExcellence solutions help in designing, optimizing and analyzing how blasts are performing in an integrated manner. We also have a very innovative mobile app - Smart Blasting app available in Android and iPhone. We have products for some other areas in mining such as Drilling, MineSafety App and Operational Analytics.
1. Blast Designer
2. Blast Data Collection and Management (BIMS)
3. Mobile app for Blasting (Smart Blasting)
4. Blasting Predictors – Air and Ground Vibration, Fragmentation and Fly-rock. Pattern Simulation /Analysis
5. Blast Designer and BIMSu for underground blasting
6. Drilling Platform(Drill Log, Plod Reports and Daily activity)
7. Mine Safety APP
8. Operational Analytics : (Combines drilling, blasting, loading, hauling etc)
9. Web and Mobile Custom Forms for all aspects of mining Lifecycle
10. Drone Platform for Mining Operations
Test Design for Fully Automated Build ArchitectureTechWell
Imagine this … As soon as any developed functionality is submitted into the code repository, it is automatically subjected to the appropriate battery of tests and then released straight into production. Setting up the pipeline capable of doing just that is becoming more and more common and something you need to know about. But most organizations hit the same stumbling block—just what IS the appropriate battery of tests? Automated build architectures don't always lend themselves well to the traditional stages of testing. In this hands-on tutorial, Melissa Benua introduces you to key test design principles—applicable to organizations both large and small—that allow you to take full advantage of the pipeline's capabilities without introducing unnecessary bottlenecks. Learn how to make highly reliable tests that run fast and preserve just enough information to let testers and developers determine exactly what went wrong and how to reproduce the error locally. Explore ways to reduce overlap while still maintaining adequate test coverage. Take back ideas about which test areas could benefit from being combined into a single suite and which areas could benefit most from being broken out altogether.
How to Manage the Risk of your Polyglot EnvironmentsDevOps.com
In this webinar, we’ll explore how to navigate the tension between speed and security when it comes to open source languages.
Enterprises are challenged by conflicting interests:
Engineering teams want more time to focus on code quality, but product managers want to ship faster.
Developers want the best tool for the job, but companies resist adding more technology stacks to their growing tech debt.
Retrofitting for security and vulnerabilities after the fact becomes a big blocker for Development and Engineering teams. Enterprises are challenged with resolving new threats and vulnerabilities at the pace at which they crop up. And yet, speed wins over security because faster time-to-market takes a greater priority over fixing vulnerabilities.
Our expert panel will cover how to resolve the tension between speed and security by practices which:
Minimize DevOps overhead from retrofitting programming languages with new versions, dependencies, security patches, etc.
Enable Continuous Builds to keep up with your continuous deployments
Use Build Validation to vet your continuous builds against smoke tests
Not long ago the question was whether your organization had big data. Did you have the volume, the velocity, the technology. Now those basics are largely given for most of the people attending this event. The path to success is still fuzzy, however, with so many technologies to choose from – and so many ways to use them.
This presentation triangulates in a holistic manner on the modern business dilemma: how can we leverage technology to improve revenue, profit, market share, and numerous other success criteria. That said, this is not about the analytics or KPIs -- although it is about measurable improvement. It’s about lining up the right technologies and using them in effective, proven ways to maximize Return on Investment (ROI). Since the slant here is holistic, we’ll show how to blend infrastructure, tools, methods, and talent to avoid and constantly trim technical debt… and to produce success stories that are consistently repeatable, not a byproduct of individual heroics.
DevOpsRoadTrip San Francisco Final Speaking Deck VictorOps
Join well known industry thought leaders and experts from local San Francisco companies for a 1/2 day event focused on the latest and greatest in DevOps practices.
https://victorops.com/devops-roadtrip-sf/
Presentation given at the OpenStack summit in Paris (Kilo) on Tue Nov 4th.
Last summit I had the pleasure to present a talk which encountered some success "Are enterprise ready for the OpenStack transformation?" (also published on SlideShare) . This talk is a follow up on what are the best practices that are successful in operating the transformation. We will first focus on identifying the right use cases for a generic enterprise, then define a roadmap with an organisational and a technical track, to finish with the definition what would be our success criterias for our group. This will happen as a workshop summary based on the multiple engagements eNovance has been delivering over the past 2 years.
This presentation overviews some of the core use cases and business requirements that drive standard ETL processes. The presentation then addresses common failure cases and provides high level development and architectural guidance.
Similar to Scaling teams, processes and architectures (20)
Monitoring at scale - Intuitive dashboard designLorenzo Alberton
At a certain scale, millions of events happen every second, and all of them are important to evaluate the health of the system. If not handled correctly, such a volume of information can overwhelm both the infrastructure that needs to support them, and people who have to make a sense out of thousands of signals and make decisions upon them, fast. By understanding how our rational mind works, how people process information, we can present data so it's more evident and intuitive. This talk will explain how to collect useful metrics, and to create the perfect monitoring dashboard to organise and display them, letting our intuition operate automatically and quickly, and saving attention and mental effort to activities that demand it.
Modern Algorithms and Data Structures - 1. Bloom Filters, Merkle TreesLorenzo Alberton
The first part of a series of talks about modern algorithms and data structures, used by nosql databases like HBase and Cassandra. An explanation of Bloom Filters and several derivates, and Merkle Trees.
NoSQL databases get a lot of press coverage, but there seems to be a lot of confusion surrounding them, as in which situations they work better than a Relational Database, and how to choose one over another. This talk will give an overview of the NoSQL landscape and a classification for the different architectural categories, clarifying the base concepts and the terminology, and will provide a comparison of the features, the strengths and the drawbacks of the most popular projects (CouchDB, MongoDB, Riak, Redis, Membase, Neo4j, Cassandra, HBase, Hypertable).
The ability to grow (and shrink) according to the needs and the available resources is an essential part of designing applications. In this talk we'll cover the fundamental elements of scalability, including aspects involving people, processes and technology. With sound and proven principles and some advice on how to shape your organisation, set the right processes and design your application, this session is a must-see for developers and technical leads alike.
Graphs in the Database: Rdbms In The Social Networks AgeLorenzo Alberton
Despite the NoSQL movement trying to flag traditional databases as a dying breed, the RDBMS keeps evolving and adding new powerful weapons to its arsenal. In this talk we'll explore Common Table Expressions (SQL-99) and how SQL handles recursion, breaking the bi-dimensional barriers and paving the way to more complex data structures like trees and graphs, and how we can replicate features from social networks and recommendation systems. We'll also have a look at window functions (SQL:2003) and the advanced reporting features they make finally possible.
Trees In The Database - Advanced data structuresLorenzo Alberton
Storing tree structures in a bi-dimensional table has always been problematic. The simplest tree models are usually quite inefficient, while more complex ones aren't necessarily better. In this talk I briefly go through the most used models (adjacency list, materialized path, nested sets) and introduce some more advanced ones belonging to the nested intervals family (Farey algorithm, Continued Fractions, and other encodings). I describe the advantages and pitfalls of each model, some proprietary solutions (e.g. Oracle's CONNECT BY) and one of the SQL Standard's upcoming features, Common Table Expressions.
Enriching engagement with ethical review processesstrikingabalance
New ethics review processes at the University of Bath. Presented at the 8th World Conference on Research Integrity by Filipa Vance, Head of Research Governance and Compliance at the University of Bath. June 2024, Athens
The case study discusses the potential of drone delivery and the challenges that need to be addressed before it becomes widespread.
Key takeaways:
Drone delivery is in its early stages: Amazon's trial in the UK demonstrates the potential for faster deliveries, but it's still limited by regulations and technology.
Regulations are a major hurdle: Safety concerns around drone collisions with airplanes and people have led to restrictions on flight height and location.
Other challenges exist: Who will use drone delivery the most? Is it cost-effective compared to traditional delivery trucks?
Discussion questions:
Managerial challenges: Integrating drones requires planning for new infrastructure, training staff, and navigating regulations. There are also marketing and recruitment considerations specific to this technology.
External forces vary by country: Regulations, consumer acceptance, and infrastructure all differ between countries.
Demographics matter: Younger generations might be more receptive to drone delivery, while older populations might have concerns.
Stakeholders for Amazon: Customers, regulators, aviation authorities, and competitors are all stakeholders. Regulators likely hold the greatest influence as they determine the feasibility of drone delivery.
Specific ServPoints should be tailored for restaurants in all food service segments. Your ServPoints should be the centerpiece of brand delivery training (guest service) and align with your brand position and marketing initiatives, especially in high-labor-cost conditions.
408-784-7371
Foodservice Consulting + Design
Comparing Stability and Sustainability in Agile SystemsRob Healy
Copy of the presentation given at XP2024 based on a research paper.
In this paper we explain wat overwork is and the physical and mental health risks associated with it.
We then explore how overwork relates to system stability and inventory.
Finally there is a call to action for Team Leads / Scrum Masters / Managers to measure and monitor excess work for individual teams.
Org Design is a core skill to be mastered by management for any successful org change.
Org Topologies™ in its essence is a two-dimensional space with 16 distinctive boxes - atomic organizational archetypes. That space helps you to plot your current operating model by positioning individuals, departments, and teams on the map. This will give a profound understanding of the performance of your value-creating organizational ecosystem.
Senior Project and Engineering Leader Jim Smith.pdfJim Smith
I am a Project and Engineering Leader with extensive experience as a Business Operations Leader, Technical Project Manager, Engineering Manager and Operations Experience for Domestic and International companies such as Electrolux, Carrier, and Deutz. I have developed new products using Stage Gate development/MS Project/JIRA, for the pro-duction of Medical Equipment, Large Commercial Refrigeration Systems, Appliances, HVAC, and Diesel engines.
My experience includes:
Managed customized engineered refrigeration system projects with high voltage power panels from quote to ship, coordinating actions between electrical engineering, mechanical design and application engineering, purchasing, production, test, quality assurance and field installation. Managed projects $25k to $1M per project; 4-8 per month. (Hussmann refrigeration)
Successfully developed the $15-20M yearly corporate capital strategy for manufacturing, with the Executive Team and key stakeholders. Created project scope and specifications, business case, ROI, managed project plans with key personnel for nine consumer product manufacturing and distribution sites; to support the company’s strategic sales plan.
Over 15 years of experience managing and developing cost improvement projects with key Stakeholders, site Manufacturing Engineers, Mechanical Engineers, Maintenance, and facility support personnel to optimize pro-duction operations, safety, EHS, and new product development. (BioLab, Deutz, Caire)
Experience working as a Technical Manager developing new products with chemical engineers and packaging engineers to enhance and reduce the cost of retail products. I have led the activities of multiple engineering groups with diverse backgrounds.
Great experience managing the product development of products which utilize complex electrical controls, high voltage power panels, product testing, and commissioning.
Created project scope, business case, ROI for multiple capital projects to support electrotechnical assembly and CPG goods. Identified project cost, risk, success criteria, and performed equipment qualifications. (Carrier, Electrolux, Biolab, Price, Hussmann)
Created detailed projects plans using MS Project, Gant charts in excel, and updated new product development in Jira for stakeholders and project team members including critical path.
Great knowledge of ISO9001, NFPA, OSHA regulations.
User level knowledge of MRP/SAP, MS Project, Powerpoint, Visio, Mastercontrol, JIRA, Power BI and Tableau.
I appreciate your consideration, and look forward to discussing this role with you, and how I can lead your company’s growth and profitability. I can be contacted via LinkedIn via phone or E Mail.
Jim Smith
678-993-7195
jimsmith30024@gmail.com
Public Speaking Tips to Help You Be A Strong Leader.pdfPinta Partners
In the realm of effective leadership, a multitude of skills come into play, but one stands out as both crucial and challenging: public speaking.
Public speaking transcends mere eloquence; it serves as the medium through which leaders articulate their vision, inspire action, and foster engagement. For leaders, refining public speaking skills is essential, elevating their ability to influence, persuade, and lead with resolute conviction. Here are some key tips to consider: https://joellandau.com/the-public-speaking-tips-to-help-you-be-a-stronger-leader/
Integrity in leadership builds trust by ensuring consistency between words an...Ram V Chary
Integrity in leadership builds trust by ensuring consistency between words and actions, making leaders reliable and credible. It also ensures ethical decision-making, which fosters a positive organizational culture and promotes long-term success. #RamVChary
The Team Member and Guest Experience - Lead and Take Care of your restaurant team. They are the people closest to and delivering Hospitality to your paying Guests!
Make the call, and we can assist you.
408-784-7371
Foodservice Consulting + Design
Employment PracticesRegulation and Multinational CorporationsRoopaTemkar
Employment PracticesRegulation and Multinational Corporations
Strategic decision making within MNCs constrained or determined by the implementation of laws and codes of practice and by pressure from political actors. Managers in MNCs have to make choices that are shaped by gvmt. intervention and the local economy.
6. CULTURE
➤ Treat people as volunteers (*)
➤ Lead by living the values you
promote
➤ Respect, collaboration
➤ Promote fun in the workplace
➤ Culture of safety at work (**)
(*) Peter Drucker
(**) Google, Project Aristotle
7. EFFECTIVE TEAMS
PROJECTARISTOTLE(2012)
Psychological safety: team climate
characterised by interpersonal trust
and mutual respect in which people
are comfortable being themselves.
Feeling free to share the things that
scare us without fear of
recriminations.
Behaviours: conversational turn-
taking and empathy.
https://www.nytimes.com/2016/02/28/magazine/what-google-learned-from-its-quest-to-build-the-perfect-team.html
8. TEAMS VS. INDIVIDUAL CONTRIBUTORS
➤ Beware of toxic people
➤ Value communication and
team work over super-heroes
(*) Sunday afternoon test
10. TEAM SIZE
➤ Never underestimate the
power of a small team
➤ Small teams force alignment
and focus
➤ Bigger teams need an insane
amount of overhead
➤ Parkinson's Law: “Work
expands to fill the time available
for its completion”
work that keeps a person busy
but has little value in itself
11. TEAM STRUCTURE
No artificial boundaries around languages or skills
Try cross-functional teams
(less friction, better end to end collaboration, project ownership)
12. MIDDLE-MANAGEMENT CURSE
Mistakes:
➤ Prematurely re-organise for scale
(deep hierarchy, over-
specialisation)
➤ Process managers (factory
mentality) vs Problem solvers
➤ Micromanagement
➤ Non-engineering culture
➤ 1-on-1s as calendar-filler
➤ Not being “on the ground”
➤ Over-confidence in tooling
➤ OTOH, coordination can be hard
14. WHY ARE PROCESSES CRITICAL?
Ease management
of teams/projects
Standardise actions
in repetitive tasks
Reduce mundane
decisions to focus
on grander ideas
Allow the team to
react quickly to crisis
➤ A process shouldn’t exist for the sake of it
➤ Introduce processes gradually, only keep what works
➤ Don’t put too much confidence in tools alone to fix issues
16. PROMOTING SYSTEMS TO PROD
➤ Code reviews
➤ Dev, Test, Stage and Live
environments
➤ Manual and automated QA
processes
➤ Performance and stress testing
➤ Release check lists (runbook)
➤ Instrumentation checks
➤ Testing roll-back capability
Protection from significant failures
BARRIER CONDITIONS
17. DESIGN AND CODE REVIEWS
➤ Promote collaboration
➤ Validate ideas, assess risk, detect
flaws, simplify the solution
➤ Reason about behaviour before
coding
DAILY STAND-UPS
➤ Important for knowledge
sharing, collaboration,
alignment
18. CONTROLLING CHANGE: RISK ESTIMATION
http://dilbert.com/strips/comic/2008-05-08/
➤ Limit / log the impact of changes
➤ Assess risk methodologies:
• Gut feeling / finger in the air
• Semaphore method
• Failure Mode and Effect Analysis
19. RISK MANAGEMENT
➤ Risk is cumulative
➤ Determine limits and
tolerance
➤ Stress, long hours, peer
pressure can multiply risk
20. WHEN/WHAT TO SCALE: DETERMINING HEADROOM
Capacity
Current Load
Why?
Budget plan
Prioritisation
Hiring plan
Determine starting point, remaining capacity, expected demand
21. LOAD TESTING
➤ Identify, document and
eliminate bottlenecks through
a strict controlled process of
measurement and analysis
➤ Measure system’s response
and stability
➤ Verify the app can meet the
desired performance
objectives (SLA)
➤ Establish success criteria, test
environment, tests, what
needs to be monitored, what
data needs to be collected
22. STRESS TESTING
➤ Determine the app’s stability
when subjected to above-
normal loads
➤ Verify the app’s behaviour
when close to the breaking
point
➤ Positive testing: progressively
increase load to overwhelm
the system’s resources
➤ Negative testing: take away
resources (memory, threads,
connections) to test the
application recoverability
24. DO NOT SCALE UNTIL YOU CAN’T AVOID IT ANYMORE
➤ “Go meet your people. Do things that don’t scale.” (Paul
Graham to AirBNB’s founders)
➤ Solve for specific problems
➤ Don’t generalise until you rebuilt something for the 3rd time
➤ Don’t over-engineer the solution
➤ Automate repetitive and error-prone tasks
➤ Avoid complicating things
✴ Phone system
25. MVP APPROACH
➤ Test ideas before spending a
year building something you
haven’t proven in the market
first
➤ Fake it till you make it
➤ Example: Zappos
26. ARCHITECTURAL / DESIGN PRINCIPLES
N + 1 nodes for rollback to be disabled
(feature flags)
to be monitored
for multiple live
systems/sites
use mature
technology
asynchronous
communications
stateless
systems
+1
buy when
non core
27. FAULT-TOLERANT STRUCTURES
➤ Swim lanes: isolate and limit the
impacts of failure within the
system by segmenting pipelines
➤ Barrier and Guide (shard)
➤ Increase availability
➤ Make incidents easier to detect,
identify and resolve
➤ Favour the transactions making
the company money first
➤ Isolate functions causing repetitive
problems (or busy tenants)
➤ Consider the natural layout or
topology of the site
28. SCALING IN DIFFERENT DIRECTIONS
x
y z
AKF Scaling Cube, “The Art of Scalability”, M.L.Abbott, M.T.Fisher
cloning of services and data
without any bias
(e.g. more serving nodes in a worker
pool where any node can do the work)
separation of work
responsibility by type of data
or type of work
(different specialised worker
pools)
separation of work by
customer or requestor
(dedicated highly specialised
worker pools)
29. SCALING IN DIFFERENT DIRECTIONS - 1. SCALING WORK / APPS
x
cloning of entities
or data - unbiased
distribution of work
y
separation of work
by activity or data
z
separation of work
by person for whom
the work is done
web site
(mirror 1)
web site
(mirror 2)
search
server
shopping
cart server
premium site
standard site
LB
30. SCALING IN DIFFERENT DIRECTIONS - 1. SCALING WORK / APPS
x mirroring
+ scale transactions
- scale data
y split by service
+ scale isolation
+ scale function data
- scale customer data
z
split by need /
location / value
+ scale isolation
+ scale customer data
- scale function data
31. SCALING IN DIFFERENT DIRECTIONS - 2. SCALING DATA
x
data cloning
(replication /
clustering) + load
balancer
y
split different things
by service / resource /
data affinity
z
split similar things
by modulus / hash-
based lookups
copy 1 copy 2 copy 3
ABC DEF GHI
32. SCALING IN DIFFERENT DIRECTIONS - 2. SCALING DATA
x
data cloning
(replication /
clustering) + load
balancer
+ easy to implement
+ scale transaction volume
+ useful in case of high read to write ratio
- scale data size and growth
y
split different things
by service / resource /
data affinity
+ fault isolation
+ reduce query time
- more difficult
- data migration
z
split similar things
by modulus / hash-
based lookups
+ uniformly balanced demand
+ fault isolation
+ scale data and transactions
- more costly
39. MONITORING
➤ Measure all the things!
➤ Think about what metrics to
track when you design your
app: system/app/user level
➤ Engage with Ops / QA early
on in the design phase
➤ Invest in a good monitoring
solution
➤ Data integrity checks (bucket
analysis, statistical analysis)
➤ Alerting and monitoring
dashboards should be intuitive
39
43. OTHER SCALING TIPS
➤ Use caching aggressively (CDNs,
app & object caches)
➤ Design to scale out horizontally
➤ Simplify scope, design,
implementation: lean == fast
➤ Know latencies
➤ Relax temporal constraints
➤ Discuss and Learn from mistakes
➤ Design for fault tolerance,
graceful failure, and resilience
➤ Avoid SPOFs
➤ Avoid or distribute state
➤ Be competent