The document discusses Oracle's Automatic Workload Repository (AWR) and how it can be used to analyze database performance issues. It provides an overview of AWR basics and functionality, walks through analyzing an AWR report including a real-world case study of identifying a performance regression, and discusses AWR administration and diagnostics.
The document discusses memory usage in Linux systems. It begins by describing the boot process and how the kernel loads into memory. It then explains that Linux uses virtual memory, where each process has its own virtual address space. Physical memory is limited by factors like CPU architecture and motherboard configuration. When an executable runs, not all of its code is loaded; dynamic libraries it depends on are mapped into its address space as well, significantly increasing its memory usage compared to the executable size alone.
The document discusses SQL tuning methodology. The three pillars of SQL tuning are: 1) diagnostics collection to identify problematic SQL, 2) root cause analysis to determine why SQL is performing poorly, and 3) remediation steps to address issues. It covers tools for diagnostics collection like SQL trace, AWR, and explains execution plans and the cost-based optimizer. The document provides a methodology for SQL tuning including identifying SQL, collecting data, analyzing root causes, and testing and implementing solutions.
This document discusses Oracle wait events. It explains that wait events track where Oracle is spending its time, including different types of waits like CPU time, I/O events, enqueue events and latch events. It provides examples of specific wait events like db file sequential read, direct path write, log file sync and buffer busy waits. It also gives recommendations for interpreting wait event data and resolving high wait times through methods like tuning SQL, improving I/O speeds, and reducing contention.
This document discusses key performance indicators (KPIs) for monitoring the health and resource utilization of Exadata database machines using Oracle Enterprise Manager. It defines 10 metric extensions to monitor storage servers, including metrics for I/O operations per second, throughput, response time, load, and composite metrics to evaluate overall disk health. Instructions are provided on creating these metric extensions in Enterprise Manager using SQL queries and setting initial warning and critical thresholds. The document also covers Exadata and storage server architecture and explains how to monitor components holistically using these defined KPIs and Enterprise Manager services.
This document provides a system capacity plan for Company's new architecture. It determines the server, memory, and disk capacity requirements for the production, user learning, and testing environments to support the Oracle applications and business volumes over the next 3 years. Key results found sufficient initial capacity for cutover but identified future upgrades that may be needed. It also specifies desktop client machine requirements.
This document describes a visualization technique for SQL tuning called Visual SQL Tuning (VST). VST involves drawing the tables involved in a SQL query as nodes and the joins between the tables as connecting lines to show the relationships. It also identifies any filter conditions in the WHERE clause marked on the relevant tables. This visual representation of the tables, joins, and filters can help identify the optimal execution path for the SQL query.
The document provides information on useful Linux/UNIX command line tools for Oracle DBAs to monitor and troubleshoot the underlying operating system and Oracle database. It discusses tools such as sar, sadc, sadf, mpstat, vmstat, ipc, and others that provide statistics on CPU usage, memory usage, paging activity, process activity and interprocess communication resources. For each tool, it provides examples of commands and output to understand what statistics are reported. The document is a guide to key Linux/UNIX command line performance monitoring and diagnostic utilities for Oracle DBAs.
The document discusses Oracle's Automatic Workload Repository (AWR) and how it can be used to analyze database performance issues. It provides an overview of AWR basics and functionality, walks through analyzing an AWR report including a real-world case study of identifying a performance regression, and discusses AWR administration and diagnostics.
The document discusses memory usage in Linux systems. It begins by describing the boot process and how the kernel loads into memory. It then explains that Linux uses virtual memory, where each process has its own virtual address space. Physical memory is limited by factors like CPU architecture and motherboard configuration. When an executable runs, not all of its code is loaded; dynamic libraries it depends on are mapped into its address space as well, significantly increasing its memory usage compared to the executable size alone.
The document discusses SQL tuning methodology. The three pillars of SQL tuning are: 1) diagnostics collection to identify problematic SQL, 2) root cause analysis to determine why SQL is performing poorly, and 3) remediation steps to address issues. It covers tools for diagnostics collection like SQL trace, AWR, and explains execution plans and the cost-based optimizer. The document provides a methodology for SQL tuning including identifying SQL, collecting data, analyzing root causes, and testing and implementing solutions.
This document discusses Oracle wait events. It explains that wait events track where Oracle is spending its time, including different types of waits like CPU time, I/O events, enqueue events and latch events. It provides examples of specific wait events like db file sequential read, direct path write, log file sync and buffer busy waits. It also gives recommendations for interpreting wait event data and resolving high wait times through methods like tuning SQL, improving I/O speeds, and reducing contention.
This document discusses key performance indicators (KPIs) for monitoring the health and resource utilization of Exadata database machines using Oracle Enterprise Manager. It defines 10 metric extensions to monitor storage servers, including metrics for I/O operations per second, throughput, response time, load, and composite metrics to evaluate overall disk health. Instructions are provided on creating these metric extensions in Enterprise Manager using SQL queries and setting initial warning and critical thresholds. The document also covers Exadata and storage server architecture and explains how to monitor components holistically using these defined KPIs and Enterprise Manager services.
This document provides a system capacity plan for Company's new architecture. It determines the server, memory, and disk capacity requirements for the production, user learning, and testing environments to support the Oracle applications and business volumes over the next 3 years. Key results found sufficient initial capacity for cutover but identified future upgrades that may be needed. It also specifies desktop client machine requirements.
This document describes a visualization technique for SQL tuning called Visual SQL Tuning (VST). VST involves drawing the tables involved in a SQL query as nodes and the joins between the tables as connecting lines to show the relationships. It also identifies any filter conditions in the WHERE clause marked on the relevant tables. This visual representation of the tables, joins, and filters can help identify the optimal execution path for the SQL query.
The document provides information on useful Linux/UNIX command line tools for Oracle DBAs to monitor and troubleshoot the underlying operating system and Oracle database. It discusses tools such as sar, sadc, sadf, mpstat, vmstat, ipc, and others that provide statistics on CPU usage, memory usage, paging activity, process activity and interprocess communication resources. For each tool, it provides examples of commands and output to understand what statistics are reported. The document is a guide to key Linux/UNIX command line performance monitoring and diagnostic utilities for Oracle DBAs.
2024 State of Marketing Report – by HubspotMarius Sescu
https://www.hubspot.com/state-of-marketing
· Scaling relationships and proving ROI
· Social media is the place for search, sales, and service
· Authentic influencer partnerships fuel brand growth
· The strongest connections happen via call, click, chat, and camera.
· Time saved with AI leads to more creative work
· Seeking: A single source of truth
· TLDR; Get on social, try AI, and align your systems.
· More human marketing, powered by robots
ChatGPT is a revolutionary addition to the world since its introduction in 2022. A big shift in the sector of information gathering and processing happened because of this chatbot. What is the story of ChatGPT? How is the bot responding to prompts and generating contents? Swipe through these slides prepared by Expeed Software, a web development company regarding the development and technical intricacies of ChatGPT!
Product Design Trends in 2024 | Teenage EngineeringsPixeldarts
The realm of product design is a constantly changing environment where technology and style intersect. Every year introduces fresh challenges and exciting trends that mold the future of this captivating art form. In this piece, we delve into the significant trends set to influence the look and functionality of product design in the year 2024.
How Race, Age and Gender Shape Attitudes Towards Mental HealthThinkNow
Mental health has been in the news quite a bit lately. Dozens of U.S. states are currently suing Meta for contributing to the youth mental health crisis by inserting addictive features into their products, while the U.S. Surgeon General is touring the nation to bring awareness to the growing epidemic of loneliness and isolation. The country has endured periods of low national morale, such as in the 1970s when high inflation and the energy crisis worsened public sentiment following the Vietnam War. The current mood, however, feels different. Gallup recently reported that national mental health is at an all-time low, with few bright spots to lift spirits.
To better understand how Americans are feeling and their attitudes towards mental health in general, ThinkNow conducted a nationally representative quantitative survey of 1,500 respondents and found some interesting differences among ethnic, age and gender groups.
Technology
For example, 52% agree that technology and social media have a negative impact on mental health, but when broken out by race, 61% of Whites felt technology had a negative effect, and only 48% of Hispanics thought it did.
While technology has helped us keep in touch with friends and family in faraway places, it appears to have degraded our ability to connect in person. Staying connected online is a double-edged sword since the same news feed that brings us pictures of the grandkids and fluffy kittens also feeds us news about the wars in Israel and Ukraine, the dysfunction in Washington, the latest mass shooting and the climate crisis.
Hispanics may have a built-in defense against the isolation technology breeds, owing to their large, multigenerational households, strong social support systems, and tendency to use social media to stay connected with relatives abroad.
Age and Gender
When asked how individuals rate their mental health, men rate it higher than women by 11 percentage points, and Baby Boomers rank it highest at 83%, saying it’s good or excellent vs. 57% of Gen Z saying the same.
Gen Z spends the most amount of time on social media, so the notion that social media negatively affects mental health appears to be correlated. Unfortunately, Gen Z is also the generation that’s least comfortable discussing mental health concerns with healthcare professionals. Only 40% of them state they’re comfortable discussing their issues with a professional compared to 60% of Millennials and 65% of Boomers.
Race Affects Attitudes
As seen in previous research conducted by ThinkNow, Asian Americans lag other groups when it comes to awareness of mental health issues. Twenty-four percent of Asian Americans believe that having a mental health issue is a sign of weakness compared to the 16% average for all groups. Asians are also considerably less likely to be aware of mental health services in their communities (42% vs. 55%) and most likely to seek out information on social media (51% vs. 35%).
AI Trends in Creative Operations 2024 by Artwork Flow.pdfmarketingartwork
Creative operations teams expect increased AI use in 2024. Currently, over half of tasks are not AI-enabled, but this is expected to decrease in the coming year. ChatGPT is the most popular AI tool currently. Business leaders are more actively exploring AI benefits than individual contributors. Most respondents do not believe AI will impact workforce size in 2024. However, some inhibitions still exist around AI accuracy and lack of understanding. Creatives primarily want to use AI to save time on mundane tasks and boost productivity.
Organizational culture includes values, norms, systems, symbols, language, assumptions, beliefs, and habits that influence employee behaviors and how people interpret those behaviors. It is important because culture can help or hinder a company's success. Some key aspects of Netflix's culture that help it achieve results include hiring smartly so every position has stars, focusing on attitude over just aptitude, and having a strict policy against peacocks, whiners, and jerks.
PEPSICO Presentation to CAGNY Conference Feb 2024Neil Kimberley
PepsiCo provided a safe harbor statement noting that any forward-looking statements are based on currently available information and are subject to risks and uncertainties. It also provided information on non-GAAP measures and directing readers to its website for disclosure and reconciliation. The document then discussed PepsiCo's business overview, including that it is a global beverage and convenient food company with iconic brands, $91 billion in net revenue in 2023, and nearly $14 billion in core operating profit. It operates through a divisional structure with a focus on local consumers.
Content Methodology: A Best Practices Report (Webinar)contently
This document provides an overview of content methodology best practices. It defines content methodology as establishing objectives, KPIs, and a culture of continuous learning and iteration. An effective methodology focuses on connecting with audiences, creating optimal content, and optimizing processes. It also discusses why a methodology is needed due to the competitive landscape, proliferation of channels, and opportunities for improvement. Components of an effective methodology include defining objectives and KPIs, audience analysis, identifying opportunities, and evaluating resources. The document concludes with recommendations around creating a content plan, testing and optimizing content over 90 days.
How to Prepare For a Successful Job Search for 2024Albert Qian
The document provides guidance on preparing a job search for 2024. It discusses the state of the job market, focusing on growth in AI and healthcare but also continued layoffs. It recommends figuring out what you want to do by researching interests and skills, then conducting informational interviews. The job search should involve building a personal brand on LinkedIn, actively applying to jobs, tailoring resumes and interviews, maintaining job hunting as a habit, and continuing self-improvement. Once hired, the document advises setting new goals and keeping skills and networking active in case of future opportunities.
A report by thenetworkone and Kurio.
The contributing experts and agencies are (in an alphabetical order): Sylwia Rytel, Social Media Supervisor, 180heartbeats + JUNG v MATT (PL), Sharlene Jenner, Vice President - Director of Engagement Strategy, Abelson Taylor (USA), Alex Casanovas, Digital Director, Atrevia (ES), Dora Beilin, Senior Social Strategist, Barrett Hoffher (USA), Min Seo, Campaign Director, Brand New Agency (KR), Deshé M. Gully, Associate Strategist, Day One Agency (USA), Francesca Trevisan, Strategist, Different (IT), Trevor Crossman, CX and Digital Transformation Director; Olivia Hussey, Strategic Planner; Simi Srinarula, Social Media Manager, The Hallway (AUS), James Hebbert, Managing Director, Hylink (CN / UK), Mundy Álvarez, Planning Director; Pedro Rojas, Social Media Manager; Pancho González, CCO, Inbrax (CH), Oana Oprea, Head of Digital Planning, Jam Session Agency (RO), Amy Bottrill, Social Account Director, Launch (UK), Gaby Arriaga, Founder, Leonardo1452 (MX), Shantesh S Row, Creative Director, Liwa (UAE), Rajesh Mehta, Chief Strategy Officer; Dhruv Gaur, Digital Planning Lead; Leonie Mergulhao, Account Supervisor - Social Media & PR, Medulla (IN), Aurelija Plioplytė, Head of Digital & Social, Not Perfect (LI), Daiana Khaidargaliyeva, Account Manager, Osaka Labs (UK / USA), Stefanie Söhnchen, Vice President Digital, PIABO Communications (DE), Elisabeth Winiartati, Managing Consultant, Head of Global Integrated Communications; Lydia Aprina, Account Manager, Integrated Marketing and Communications; Nita Prabowo, Account Manager, Integrated Marketing and Communications; Okhi, Web Developer, PNTR Group (ID), Kei Obusan, Insights Director; Daffi Ranandi, Insights Manager, Radarr (SG), Gautam Reghunath, Co-founder & CEO, Talented (IN), Donagh Humphreys, Head of Social and Digital Innovation, THINKHOUSE (IRE), Sarah Yim, Strategy Director, Zulu Alpha Kilo (CA).
Trends In Paid Search: Navigating The Digital Landscape In 2024Search Engine Journal
The search marketing landscape is evolving rapidly with new technologies, and professionals, like you, rely on innovative paid search strategies to meet changing demands.
It’s important that you’re ready to implement new strategies in 2024.
Check this out and learn the top trends in paid search advertising that are expected to gain traction, so you can drive higher ROI more efficiently in 2024.
You’ll learn:
- The latest trends in AI and automation, and what this means for an evolving paid search ecosystem.
- New developments in privacy and data regulation.
- Emerging ad formats that are expected to make an impact next year.
Watch Sreekant Lanka from iQuanti and Irina Klein from OneMain Financial as they dive into the future of paid search and explore the trends, strategies, and technologies that will shape the search marketing landscape.
If you’re looking to assess your paid search strategy and design an industry-aligned plan for 2024, then this webinar is for you.
5 Public speaking tips from TED - Visualized summarySpeakerHub
From their humble beginnings in 1984, TED has grown into the world’s most powerful amplifier for speakers and thought-leaders to share their ideas. They have over 2,400 filmed talks (not including the 30,000+ TEDx videos) freely available online, and have hosted over 17,500 events around the world.
With over one billion views in a year, it’s no wonder that so many speakers are looking to TED for ideas on how to share their message more effectively.
The article “5 Public-Speaking Tips TED Gives Its Speakers”, by Carmine Gallo for Forbes, gives speakers five practical ways to connect with their audience, and effectively share their ideas on stage.
Whether you are gearing up to get on a TED stage yourself, or just want to master the skills that so many of their speakers possess, these tips and quotes from Chris Anderson, the TED Talks Curator, will encourage you to make the most impactful impression on your audience.
See the full article and more summaries like this on SpeakerHub here: https://speakerhub.com/blog/5-presentation-tips-ted-gives-its-speakers
See the original article on Forbes here:
http://www.forbes.com/forbes/welcome/?toURL=http://www.forbes.com/sites/carminegallo/2016/05/06/5-public-speaking-tips-ted-gives-its-speakers/&refURL=&referrer=#5c07a8221d9b
ChatGPT and the Future of Work - Clark Boyd Clark Boyd
Everyone is in agreement that ChatGPT (and other generative AI tools) will shape the future of work. Yet there is little consensus on exactly how, when, and to what extent this technology will change our world.
Businesses that extract maximum value from ChatGPT will use it as a collaborative tool for everything from brainstorming to technical maintenance.
For individuals, now is the time to pinpoint the skills the future professional will need to thrive in the AI age.
Check out this presentation to understand what ChatGPT is, how it will shape the future of work, and how you can prepare to take advantage.
The document provides career advice for getting into the tech field, including:
- Doing projects and internships in college to build a portfolio.
- Learning about different roles and technologies through industry research.
- Contributing to open source projects to build experience and network.
- Developing a personal brand through a website and social media presence.
- Networking through events, communities, and finding a mentor.
- Practicing interviews through mock interviews and whiteboarding coding questions.
Google's Just Not That Into You: Understanding Core Updates & Search IntentLily Ray
1. Core updates from Google periodically change how its algorithms assess and rank websites and pages. This can impact rankings through shifts in user intent, site quality issues being caught up to, world events influencing queries, and overhauls to search like the E-A-T framework.
2. There are many possible user intents beyond just transactional, navigational and informational. Identifying intent shifts is important during core updates. Sites may need to optimize for new intents through different content types and sections.
3. Responding effectively to core updates requires analyzing "before and after" data to understand changes, identifying new intents or page types, and ensuring content matches appropriate intents across video, images, knowledge graphs and more.
A brief introduction to DataScience with explaining of the concepts, algorithms, machine learning, supervised and unsupervised learning, clustering, statistics, data preprocessing, real-world applications etc.
It's part of a Data Science Corner Campaign where I will be discussing the fundamentals of DataScience, AIML, Statistics etc.
Time Management & Productivity - Best PracticesVit Horky
Here's my presentation on by proven best practices how to manage your work time effectively and how to improve your productivity. It includes practical tips and how to use tools such as Slack, Google Apps, Hubspot, Google Calendar, Gmail and others.
The six step guide to practical project managementMindGenius
The six step guide to practical project management
If you think managing projects is too difficult, think again.
We’ve stripped back project management processes to the
basics – to make it quicker and easier, without sacrificing
the vital ingredients for success.
“If you’re looking for some real-world guidance, then The Six Step Guide to Practical Project Management will help.”
Dr Andrew Makar, Tactical Project Management
2024 State of Marketing Report – by HubspotMarius Sescu
https://www.hubspot.com/state-of-marketing
· Scaling relationships and proving ROI
· Social media is the place for search, sales, and service
· Authentic influencer partnerships fuel brand growth
· The strongest connections happen via call, click, chat, and camera.
· Time saved with AI leads to more creative work
· Seeking: A single source of truth
· TLDR; Get on social, try AI, and align your systems.
· More human marketing, powered by robots
ChatGPT is a revolutionary addition to the world since its introduction in 2022. A big shift in the sector of information gathering and processing happened because of this chatbot. What is the story of ChatGPT? How is the bot responding to prompts and generating contents? Swipe through these slides prepared by Expeed Software, a web development company regarding the development and technical intricacies of ChatGPT!
Product Design Trends in 2024 | Teenage EngineeringsPixeldarts
The realm of product design is a constantly changing environment where technology and style intersect. Every year introduces fresh challenges and exciting trends that mold the future of this captivating art form. In this piece, we delve into the significant trends set to influence the look and functionality of product design in the year 2024.
How Race, Age and Gender Shape Attitudes Towards Mental HealthThinkNow
Mental health has been in the news quite a bit lately. Dozens of U.S. states are currently suing Meta for contributing to the youth mental health crisis by inserting addictive features into their products, while the U.S. Surgeon General is touring the nation to bring awareness to the growing epidemic of loneliness and isolation. The country has endured periods of low national morale, such as in the 1970s when high inflation and the energy crisis worsened public sentiment following the Vietnam War. The current mood, however, feels different. Gallup recently reported that national mental health is at an all-time low, with few bright spots to lift spirits.
To better understand how Americans are feeling and their attitudes towards mental health in general, ThinkNow conducted a nationally representative quantitative survey of 1,500 respondents and found some interesting differences among ethnic, age and gender groups.
Technology
For example, 52% agree that technology and social media have a negative impact on mental health, but when broken out by race, 61% of Whites felt technology had a negative effect, and only 48% of Hispanics thought it did.
While technology has helped us keep in touch with friends and family in faraway places, it appears to have degraded our ability to connect in person. Staying connected online is a double-edged sword since the same news feed that brings us pictures of the grandkids and fluffy kittens also feeds us news about the wars in Israel and Ukraine, the dysfunction in Washington, the latest mass shooting and the climate crisis.
Hispanics may have a built-in defense against the isolation technology breeds, owing to their large, multigenerational households, strong social support systems, and tendency to use social media to stay connected with relatives abroad.
Age and Gender
When asked how individuals rate their mental health, men rate it higher than women by 11 percentage points, and Baby Boomers rank it highest at 83%, saying it’s good or excellent vs. 57% of Gen Z saying the same.
Gen Z spends the most amount of time on social media, so the notion that social media negatively affects mental health appears to be correlated. Unfortunately, Gen Z is also the generation that’s least comfortable discussing mental health concerns with healthcare professionals. Only 40% of them state they’re comfortable discussing their issues with a professional compared to 60% of Millennials and 65% of Boomers.
Race Affects Attitudes
As seen in previous research conducted by ThinkNow, Asian Americans lag other groups when it comes to awareness of mental health issues. Twenty-four percent of Asian Americans believe that having a mental health issue is a sign of weakness compared to the 16% average for all groups. Asians are also considerably less likely to be aware of mental health services in their communities (42% vs. 55%) and most likely to seek out information on social media (51% vs. 35%).
AI Trends in Creative Operations 2024 by Artwork Flow.pdfmarketingartwork
Creative operations teams expect increased AI use in 2024. Currently, over half of tasks are not AI-enabled, but this is expected to decrease in the coming year. ChatGPT is the most popular AI tool currently. Business leaders are more actively exploring AI benefits than individual contributors. Most respondents do not believe AI will impact workforce size in 2024. However, some inhibitions still exist around AI accuracy and lack of understanding. Creatives primarily want to use AI to save time on mundane tasks and boost productivity.
Organizational culture includes values, norms, systems, symbols, language, assumptions, beliefs, and habits that influence employee behaviors and how people interpret those behaviors. It is important because culture can help or hinder a company's success. Some key aspects of Netflix's culture that help it achieve results include hiring smartly so every position has stars, focusing on attitude over just aptitude, and having a strict policy against peacocks, whiners, and jerks.
PEPSICO Presentation to CAGNY Conference Feb 2024Neil Kimberley
PepsiCo provided a safe harbor statement noting that any forward-looking statements are based on currently available information and are subject to risks and uncertainties. It also provided information on non-GAAP measures and directing readers to its website for disclosure and reconciliation. The document then discussed PepsiCo's business overview, including that it is a global beverage and convenient food company with iconic brands, $91 billion in net revenue in 2023, and nearly $14 billion in core operating profit. It operates through a divisional structure with a focus on local consumers.
Content Methodology: A Best Practices Report (Webinar)contently
This document provides an overview of content methodology best practices. It defines content methodology as establishing objectives, KPIs, and a culture of continuous learning and iteration. An effective methodology focuses on connecting with audiences, creating optimal content, and optimizing processes. It also discusses why a methodology is needed due to the competitive landscape, proliferation of channels, and opportunities for improvement. Components of an effective methodology include defining objectives and KPIs, audience analysis, identifying opportunities, and evaluating resources. The document concludes with recommendations around creating a content plan, testing and optimizing content over 90 days.
How to Prepare For a Successful Job Search for 2024Albert Qian
The document provides guidance on preparing a job search for 2024. It discusses the state of the job market, focusing on growth in AI and healthcare but also continued layoffs. It recommends figuring out what you want to do by researching interests and skills, then conducting informational interviews. The job search should involve building a personal brand on LinkedIn, actively applying to jobs, tailoring resumes and interviews, maintaining job hunting as a habit, and continuing self-improvement. Once hired, the document advises setting new goals and keeping skills and networking active in case of future opportunities.
A report by thenetworkone and Kurio.
The contributing experts and agencies are (in an alphabetical order): Sylwia Rytel, Social Media Supervisor, 180heartbeats + JUNG v MATT (PL), Sharlene Jenner, Vice President - Director of Engagement Strategy, Abelson Taylor (USA), Alex Casanovas, Digital Director, Atrevia (ES), Dora Beilin, Senior Social Strategist, Barrett Hoffher (USA), Min Seo, Campaign Director, Brand New Agency (KR), Deshé M. Gully, Associate Strategist, Day One Agency (USA), Francesca Trevisan, Strategist, Different (IT), Trevor Crossman, CX and Digital Transformation Director; Olivia Hussey, Strategic Planner; Simi Srinarula, Social Media Manager, The Hallway (AUS), James Hebbert, Managing Director, Hylink (CN / UK), Mundy Álvarez, Planning Director; Pedro Rojas, Social Media Manager; Pancho González, CCO, Inbrax (CH), Oana Oprea, Head of Digital Planning, Jam Session Agency (RO), Amy Bottrill, Social Account Director, Launch (UK), Gaby Arriaga, Founder, Leonardo1452 (MX), Shantesh S Row, Creative Director, Liwa (UAE), Rajesh Mehta, Chief Strategy Officer; Dhruv Gaur, Digital Planning Lead; Leonie Mergulhao, Account Supervisor - Social Media & PR, Medulla (IN), Aurelija Plioplytė, Head of Digital & Social, Not Perfect (LI), Daiana Khaidargaliyeva, Account Manager, Osaka Labs (UK / USA), Stefanie Söhnchen, Vice President Digital, PIABO Communications (DE), Elisabeth Winiartati, Managing Consultant, Head of Global Integrated Communications; Lydia Aprina, Account Manager, Integrated Marketing and Communications; Nita Prabowo, Account Manager, Integrated Marketing and Communications; Okhi, Web Developer, PNTR Group (ID), Kei Obusan, Insights Director; Daffi Ranandi, Insights Manager, Radarr (SG), Gautam Reghunath, Co-founder & CEO, Talented (IN), Donagh Humphreys, Head of Social and Digital Innovation, THINKHOUSE (IRE), Sarah Yim, Strategy Director, Zulu Alpha Kilo (CA).
Trends In Paid Search: Navigating The Digital Landscape In 2024Search Engine Journal
The search marketing landscape is evolving rapidly with new technologies, and professionals, like you, rely on innovative paid search strategies to meet changing demands.
It’s important that you’re ready to implement new strategies in 2024.
Check this out and learn the top trends in paid search advertising that are expected to gain traction, so you can drive higher ROI more efficiently in 2024.
You’ll learn:
- The latest trends in AI and automation, and what this means for an evolving paid search ecosystem.
- New developments in privacy and data regulation.
- Emerging ad formats that are expected to make an impact next year.
Watch Sreekant Lanka from iQuanti and Irina Klein from OneMain Financial as they dive into the future of paid search and explore the trends, strategies, and technologies that will shape the search marketing landscape.
If you’re looking to assess your paid search strategy and design an industry-aligned plan for 2024, then this webinar is for you.
5 Public speaking tips from TED - Visualized summarySpeakerHub
From their humble beginnings in 1984, TED has grown into the world’s most powerful amplifier for speakers and thought-leaders to share their ideas. They have over 2,400 filmed talks (not including the 30,000+ TEDx videos) freely available online, and have hosted over 17,500 events around the world.
With over one billion views in a year, it’s no wonder that so many speakers are looking to TED for ideas on how to share their message more effectively.
The article “5 Public-Speaking Tips TED Gives Its Speakers”, by Carmine Gallo for Forbes, gives speakers five practical ways to connect with their audience, and effectively share their ideas on stage.
Whether you are gearing up to get on a TED stage yourself, or just want to master the skills that so many of their speakers possess, these tips and quotes from Chris Anderson, the TED Talks Curator, will encourage you to make the most impactful impression on your audience.
See the full article and more summaries like this on SpeakerHub here: https://speakerhub.com/blog/5-presentation-tips-ted-gives-its-speakers
See the original article on Forbes here:
http://www.forbes.com/forbes/welcome/?toURL=http://www.forbes.com/sites/carminegallo/2016/05/06/5-public-speaking-tips-ted-gives-its-speakers/&refURL=&referrer=#5c07a8221d9b
ChatGPT and the Future of Work - Clark Boyd Clark Boyd
Everyone is in agreement that ChatGPT (and other generative AI tools) will shape the future of work. Yet there is little consensus on exactly how, when, and to what extent this technology will change our world.
Businesses that extract maximum value from ChatGPT will use it as a collaborative tool for everything from brainstorming to technical maintenance.
For individuals, now is the time to pinpoint the skills the future professional will need to thrive in the AI age.
Check out this presentation to understand what ChatGPT is, how it will shape the future of work, and how you can prepare to take advantage.
The document provides career advice for getting into the tech field, including:
- Doing projects and internships in college to build a portfolio.
- Learning about different roles and technologies through industry research.
- Contributing to open source projects to build experience and network.
- Developing a personal brand through a website and social media presence.
- Networking through events, communities, and finding a mentor.
- Practicing interviews through mock interviews and whiteboarding coding questions.
Google's Just Not That Into You: Understanding Core Updates & Search IntentLily Ray
1. Core updates from Google periodically change how its algorithms assess and rank websites and pages. This can impact rankings through shifts in user intent, site quality issues being caught up to, world events influencing queries, and overhauls to search like the E-A-T framework.
2. There are many possible user intents beyond just transactional, navigational and informational. Identifying intent shifts is important during core updates. Sites may need to optimize for new intents through different content types and sections.
3. Responding effectively to core updates requires analyzing "before and after" data to understand changes, identifying new intents or page types, and ensuring content matches appropriate intents across video, images, knowledge graphs and more.
A brief introduction to DataScience with explaining of the concepts, algorithms, machine learning, supervised and unsupervised learning, clustering, statistics, data preprocessing, real-world applications etc.
It's part of a Data Science Corner Campaign where I will be discussing the fundamentals of DataScience, AIML, Statistics etc.
Time Management & Productivity - Best PracticesVit Horky
Here's my presentation on by proven best practices how to manage your work time effectively and how to improve your productivity. It includes practical tips and how to use tools such as Slack, Google Apps, Hubspot, Google Calendar, Gmail and others.
The six step guide to practical project managementMindGenius
The six step guide to practical project management
If you think managing projects is too difficult, think again.
We’ve stripped back project management processes to the
basics – to make it quicker and easier, without sacrificing
the vital ingredients for success.
“If you’re looking for some real-world guidance, then The Six Step Guide to Practical Project Management will help.”
Dr Andrew Makar, Tactical Project Management
2. 2
Maaz Anjum
• Marietta, Georgia
• Solutions Architect
• EM12c
• Golden Gate
• Engineered Systems
• Member of IOUG, GOUG, RMOUG
RAC SIG, BIG DATA SIG
EM SIG
• Using Oracle products since 2001
Blog: maazanjum.com
Email: maaz.anjum@biascorp.com
Twitter: @maaz_anjum
About Me
3. 3
!
• Overview
• Background
• Capacity Planning
• Understanding EM Metrics
• Using EM Metrics
• Lessons
• Conclusion
Agenda
4. 4
What is EM12c?
!
Did you know it…
• Is Integrated with MOS
• Can be used for Database and Middleware Provisioning
• Can Monitor Engineered Systems
– Exadata, Exalogic, Big Data Appliance
• Can be used for Compliance tracking
• Has a Chargeback and Consolidation Planner feature
• Can Manage the Cloud!
• Is free to use!!
Overview
7. 7
!
• Overview
• Background
• Capacity Planning
• Engineered Systems
• Understanding EM Metrics
• Using EM Metrics
• Lessons
• Conclusion
Agenda
8. 8
The Question
• The Clients executive management team had a decision at hand of
whether to expand their Exadata footprint going into a key business
cycle.
!
• In order to support their procurement decision they tasked the database
management team with identify current capacity and resource utilization
within the Exadata environment.
!
• Being new to Exadata and a former mainframe shop, they looked to BIAS
to help create reports and metrics from which to base this and future
capacity planning decisions.
Background
9. 9
!
• Overview
• Background
• Capacity Planning
• Understanding EM Metrics
• Using EM Metrics
• Lessons
• Conclusion
Agenda
11. 11
Resource Utilization
• Is
there
monitoring
enabled
for
all
resources?
• Does
the
monitoring
tool
store
the
collected
data?
• Is
the
data
accessible?
• Can
reports
be
run
against
the
data?
12. 12
• With so many metrics to chose from which ones were relevant?
!
!
!
!
• Which target types?
!
!
!
• How should the data be represented?
Resource Utilization
• CPU Utilization
• Memory
• Storage
• IO
• Cluster
• Host
• Database
• BI Publisher is a free add-on to EM12c
• Reports leverage EM12c Repository
• Excel
• Good old excel!
13. 13
!
• Overview
• Background
• Capacity Planning
• Understanding EM Metrics
• Using EM Metrics
• Lessons
• Conclusion
Agenda
15. 15
Data in Enterprise Manager
!
• EM12c Collects Metrics on intervals defined
within a targets monitoring setup.
!
• Data is collected via the Management Agents
and stored in an Oracle Database Repository
!
• Collected Data can be access via the OMS
Console
!
• Metrics are collected as raw data points
!
• Aggregated over hourly, and daily
Understand the“metrics”
18. 18
• Default retention for Repository Metric Tables
– As per“12c Cloud Control Repository: How to Modify the Default
Retention and Purging Policies for Metric Data? (Doc ID 1405036.1)”
Understand the“metrics”
19. 19
Understand the“metrics”
ADF Business Components for Java
Agent
Application Deployment
Automatic Storage Management
Beacon
CSA Collector
Cluster
Cluster ASM
Cluster Database
Clustered Application Deployment
Database Instance
Database System
EM Servers System
EM Service
EMC CLARiiON System
Email Driver
Forms
Generic Service
Group
Host
Identity Management
Internet Directory
Listener
Metadata Repository
OC4J
OMS Console
OMS Platform
OMS and Repository
Oracle Access Management Cluster
Oracle Access Management Server
Oracle Application Server
Oracle Database Exadata Storage Server System
Oracle Database Machine
Oracle Engineered System Cisco Switch
Oracle Engineered System Healthchecks
Oracle Engineered System ILOM Server
Oracle Engineered System PDU
Oracle Exadata Storage Server
Oracle Exadata Storage Server Grid
Oracle Fusion Middleware Farm
Oracle HTTP Server
Oracle High Availability Service
Oracle Home
Oracle Infiniband Network
Oracle Infiniband Switch
Oracle Internet Directory
Oracle Management Service
Oracle Reports Server
Oracle SOA Infra Cluster
Oracle Service Bus
Oracle WebLogic Cluster
Oracle WebLogic Domain
Oracle WebLogic Server
SOA Composite
SOA Infrastructure
SOA Partition
Single Sign-On
Single Sign-On Server
User Messaging Service
Web Cache
• Data is collected per Target
Type
20. 20
Where are the“metrics”
• For“any”target, navigate to its home page
• Open the“Target Type”drop down
• Go to Monitoring
• Then“All Metrics”
24. 24
Where are the“metrics”
CPU Time (sec)
Oracle Database
Tablespaces
DB file sequential read (%)
Wait Time (sec)
Average Active Sessions
Full Index Scans (per second)
Open Cursors (per second)
Size
Free
Wait Bottlenecks
Throughput
25. 25
Where are the“metrics”
Exadata Metrics
• Aggregated Exadata CellDisk Metric
• Aggregated Exadata Capacity Metric
• Aggregated Exadata Diskgroup Capacity Metric
• Aggregated Exadata FlashDisk and HardDisk Metric
• Cell Generated Alert
• Exadata Cell Metric
• Exadata CellDisk Metric
• CellSrv Status Metric
• Exadata Capacity Metric
• Cell Configuration
• Cell Configuration Patches
• CELL CellDisk Configuration
• CELL Flash Cache Cell Disks Configuration
• CELL Flash Cache Configuration
• CELL Grid Disk Clients Configuration
• CELL Grid Disk Configuration
• IORM Category Plan
• CELL IORM Configuration
• Exadata Inter-database Plan
• CELL LUN Configuration
• CELL LUN Physical Disks Configuration
• Exadata Performance Metrics
• CELL Physical Disk Configuration
• CELL Physical Disk Luns Configuration
• Exadata Flash Cache Metric
• HCA Configuration
• HCA Port Connections and Configuration
• HCA Port Configuration Monitor
• HCA_PortConnConfigHelper
• HCA_PortConnections
• HCA Port Errors
• HCA Port State
• HCA Port State (For Alerts)
• Host Interconnect Statistics
• Exadata IORM Consumer Group Metric
• Exadata IORM DB Metric
• IORM Plan Status Metric
• Exadata CellDisk Load Imbalance
• Response
• Top CPU
26. 26
• Two ways to categorize
• By“System or Cluster”
!
!
!
!
!
!
!
• By“Line of Business”
Categorize the“metrics”
Host Host Host
Cluster
27. Categorize the“metrics”
Exadata A
Cluster B
Exadata C
Cluster D
Cluster Host
Server 1
Server 2
Server 3
Server 4
Server 1
Server 2
Server 3
Server 4
Server 1
Server 2
Server 3
Server 4
Server 1
Server 2
Server 3
Server 4
27
28. 28
Categorize the“metrics”
Finance
Marketing
Sales
Procurem
ent
Server 1
Server 2
Server 3
Server 4
EBS
Pre-Sales
Pro
SalesForce
ProcuPro
MarketMax
LOB Department Application Host Database Instance
DB A: Inst 1
DB A: Inst 2
DB B: Inst 1
DB B: Inst 2
DB C: Inst 1
DB D: Inst 1
Accounts
Payable
Account
Receivable
Sales
Procurem
ent
Marketing
29. 29
!
• Overview
• Background
• Capacity Planning
• Understanding EM Metrics
• Using EM Metrics
• Lessons
• Conclusion
Agenda
30. 30
• After lengthy discussions with The Client’s Architects, four metrics identified
in two categories
• Host
• CPU Utilization %
• Memory Utilization
• Storage Usage
!
• Database
• Database CPU Time
• To measure the CPU Utilization at a database level for each line of
business.
!
• This presentation will focus on CPU Utilization and Storage only.
The right“metrics”
31. 31
• We used gc$metric_values in the sysman schema
• Columns of interest
• Target Type
• Metric Group Label
• Metric Name
• Description
• Has to be enabled for
every target
• Requires Lifecycle
Management Pack access.
• It is used for Chargeback!
The right“metrics”
32. 32
• Great.
I
know
where
the
data
is,
but
what
does
it
look
like?
• Quite
raw!
col
entity_type
format
a15
heading
"Target
Type"
col
entity_name
format
a25
heading
"Target
Name"
col
metric_group_label
format
a7
heading
"Metric|Group|Label"
col
metric_column_name
format
a7
heading
"Metric|Column|Name"
col
value
format
99.99
heading
"Value"
!
select
a.entity_type
,a.entity_name
,a.metric_group_label
,a.metric_column_name
,a.collection_time
,a.value
from
sysman.gc$metric_values
a
where
entity_type
=
'host'
and
a.metric_column_name
=
'cpuUtil'
and
a.entity_name
like
'shade%'
order
by
collection_time;
!
Metric
Metric
Group
Column
Target
Type
Target
Name
Label
Name
COLLECTION_TIME
Value
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐
host
blue.color.com
Load
cpuUtil
10-‐FEB-‐14
12.00.08
AM
7.93
host
purple.color.com
Load
cpuUtil
10-‐FEB-‐14
12.02.26
AM
4.53
host
red.color.com
Load
cpuUtil
10-‐FEB-‐14
12.03.58
AM
4.72
host
green.color.com
Load
cpuUtil
10-‐FEB-‐14
12.04.08
AM
12.03
host
blue.color.com
Load
cpuUtil
10-‐FEB-‐14
12.05.08
AM
20.81
host
purple.color.com
Load
cpuUtil
10-‐FEB-‐14
12.07.26
AM
11.75
host
red.color.com
Load
cpuUtil
10-‐FEB-‐14
12.08.58
AM
10.65
host
green.color.com
Load
cpuUtil
10-‐FEB-‐14
12.09.08
AM
18.24
host
blue.color.com
Load
cpuUtil
10-‐FEB-‐14
12.10.08
AM
20.76
host
purple.color.com
Load
cpuUtil
10-‐FEB-‐14
12.12.26
AM
9.87
host
red.color.com
Load
cpuUtil
10-‐FEB-‐14
12.13.58
AM
7.77
host
green.color.com
Load
cpuUtil
10-‐FEB-‐14
12.14.08
AM
11.99
host
blue.color.com
Load
cpuUtil
10-‐FEB-‐14
12.15.08
AM
14.35
host
purple.color.com
Load
cpuUtil
10-‐FEB-‐14
12.17.26
AM
8.47
host
red.color.com
Load
cpuUtil
10-‐FEB-‐14
12.18.58
AM
19.19
host
green.color.com
Load
cpuUtil
10-‐FEB-‐14
12.19.08
AM
29.20
host
blue.color.com
Load
cpuUtil
10-‐FEB-‐14
12.20.08
AM
43.13
host
purple.color.com
Load
cpuUtil
10-‐FEB-‐14
12.22.26
AM
51.01
The right“metrics”
33. 33
• Molding the data
– Create a Base View from the metrics above mentioned
above
– Create Categorical views on top of the base view to
further refine the data
– Categorical Views leverage PIVOT and WITH clause
Time Slice
Per Target
Time Slice
Per
Business
Unit
Base View
per Metric
The right“metrics”
34. 34
• Base Views
• As mentioned in the table above, the metric_column_name value is the
key.
• Depending on the metric, simply change the value, and apply the
transformation
• Would contain data for a specific target type, for example host, database
instance etc
• Is a de-normalized data set
The right“metrics”
35. 35
The right“metrics”
col
entity_type
format
a4
heading
"Entity|Type"
col
host_name
format
a20
heading
"Host|Name"
col
database_machine
format
a4
heading
"DB|Machine"
col
metric_column_label
format
a19
heading
"Metric|Column|Label"
col
metric_column_name
format
a8
heading
"Metric|Column|Name"
col
metric_group_label
format
a6
heading
"Metric|Group|Label"
col
year_quarter
format
a8
heading
"Year|Quarter"
col
year_month
format
a8
heading
"Year|Month"
col
year_month_day
format
a22
heading
"Year|Month|Day"
col
avg_value
format
990.00
heading
"Per|Month|Max|CPU|Util%"
col
max_value
format
990.00
heading
"Per|Month|Avg|CPU|Util%"
!
-‐-‐create
or
replace
view
v_cpuutil_base
as
with
base
as
(
select
entity_type
,substr(entity_name,
1,
4)
as
database_machine
,entity_name
AS
host_name
,metric_column_label
,metric_column_name
,metric_group_label
,collection_time
,to_char(collection_time,'yyyy')
||
'-‐Q'
||
to_char(collection_time,'q')
as
year_quarter
,extract(year
from
collection_time)
||'-‐'
||
ltrim(to_char(extract(month
from
collection_time),'09'))
as
year_month
,collection_time
as
year_month_day
,round(avg_value,2)
as
avg_value
,max_value
from
sysman.gc$metric_values_hourly
where
entity_type
=
'host'
and
metric_column_name
=
'cpuUtil'
and
metric_group_label
=
‘Load')
select
*
from
base
where
database_machine
=
'shade';
entity_type
=
'host'
and
metric_column_name
in
('usedLogicalMemoryPct','logicMemfreePct')
and
metric_group_label
=
‘Load';
• Base Views
36. 36
Metric
Metric
Metric
Avg
Max
Enti
DB
Host
Column
Column
Group
Year
Year
Month
CPU
CPU
Type
Mach
Name
Label
Name
Label
COLLECTION_TIME
Quarter
Month
Day
Util%
Util%
-‐-‐-‐-‐
-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
12.00.00
AM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
12.00.00
AM
0.34
1.08
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
01.00.00
AM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
01.00.00
AM
0.26
0.27
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
02.00.00
AM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
02.00.00
AM
0.26
0.32
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
03.00.00
AM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
03.00.00
AM
0.26
0.30
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
04.00.00
AM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
04.00.00
AM
0.26
0.27
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
05.00.00
AM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
05.00.00
AM
0.32
0.60
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
06.00.00
AM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
06.00.00
AM
0.28
0.34
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
07.00.00
AM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
07.00.00
AM
0.27
0.34
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
08.00.00
AM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
08.00.00
AM
0.33
0.66
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
09.00.00
AM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
09.00.00
AM
0.37
0.65
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
10.00.00
AM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
10.00.00
AM
0.28
0.31
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
11.00.00
AM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
11.00.00
AM
0.29
0.36
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
12.00.00
PM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
12.00.00
PM
0.30
0.39
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
01.00.00
PM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
01.00.00
PM
0.30
0.65
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
02.00.00
PM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
02.00.00
PM
0.36
0.57
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
03.00.00
PM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
03.00.00
PM
0.37
0.56
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
04.00.00
PM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
04.00.00
PM
0.30
0.37
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
05.00.00
PM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
05.00.00
PM
0.39
1.56
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
06.00.00
PM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
06.00.00
PM
0.27
0.30
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
07.00.00
PM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
07.00.00
PM
0.27
0.29
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
08.00.00
PM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
08.00.00
PM
0.28
0.34
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
09.00.00
PM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
09.00.00
PM
0.28
0.31
host
shade
blue.color.com
CPU
Utilization
(%)
cpuUtil
Load
29-‐MAR-‐13
10.00.00
PM
2013-‐Q1
2013-‐03
29-‐MAR-‐13
10.00.00
PM
0.27
0.28
The right“metrics”
38. 38
The right“metrics”
• Cluster Views
• Built using the“base”view, for example v_cpuutil_base
• Use analytical functions for maximum, average, and 95th percentile
col
cluster_name
format
a4
heading
"DB|Machine"
col
metric_column_label
format
a24
heading
"Metric|Column|Label"
col
metric_column_name
format
a15
heading
"Metric|Column|Name"
col
metric_group_label
format
a6
heading
"Metric|Group|Label"
col
year_quarter
format
a8
heading
"Year|Quarter"
col
per_q_dbm_max_cpuutil_pct
format
990.00
heading
"Max
Per
Quarter|CPU|Util%"
col
per_q_dbm_avg_cpuutil_pct
format
990.00
heading
"Avg
Per
Quarter|CPU|Util%"
col
per_q_dbm_max_95th_pct
format
990.00
heading
"95th
Per
Quarter|CPU|Util%”
!
-‐-‐create
or
replace
view
v_cpuutil_cluster_per_quarter
select
distinct
cluster_name
,metric_column_label
,metric_group_label
,year_quarter
,round(max(max_value)
over
(partition
by
cluster_name,
year_quarter),
2)
as
per_q_dbm_max_cpuutil_pct
,round(percentile_cont(0.05)
within
group
(order
by
max_value
desc)
over
(partition
by
cluster_name,
year_quarter),
2)
as
per_q_dbm_max_95th_pct
,round(avg(avg_value)
over
(partition
by
cluster_name,
year_quarter),
2)
as
per_q_dbm_avg_cpuutil_pct
from
v_cpuutil_base
where
cluster_name
=
'shade'
order
by
year_quarter;
Change
these
selected
columns
for
quarter,
month,
day
etc
for
cluster
vs
hosts
views
39. 39
The right“metrics”
Metric
Metric
Max
Per
Quarter
95th
Per
Quarter
Avg
Per
Quarter
DB
Column
Group
Year
CPU
CPU
CPU
Mach
Label
Label
Quarter
Util%
Util%
Util%
-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
shade
CPU
Utilization
(%)
Load
2013-‐Q1
95.32
90.05
24.17
shade
CPU
Utilization
(%)
Load
2013-‐Q2
99.89
84.24
22.42
shade
CPU
Utilization
(%)
Load
2013-‐Q3
99.83
96.89
32.45
shade
CPU
Utilization
(%)
Load
2013-‐Q4
99.83
87.13
31.27
shade
CPU
Utilization
(%)
Load
2014-‐Q1
99.04
81.48
30.54
• Cluster/Database Machine CPU Utilization Per Quarter
• Cluster/Database Machine CPU Utilization Per Month
Metric
Metric
Max
Per
Quarter
95th
Per
Quarter
Avg
Per
Quarter
DB
Column
Group
Year
CPU
CPU
CPU
Mach
Label
Label
Month
Util%
Util%
Util%
-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
shade
CPU
Utilization
(%)
Load
2013-‐03
95.32
90.05
24.17
shade
CPU
Utilization
(%)
Load
2013-‐04
99.89
85.97
19.33
shade
CPU
Utilization
(%)
Load
2013-‐05
99.02
80.99
22.39
shade
CPU
Utilization
(%)
Load
2013-‐06
99.65
84.51
25.53
shade
CPU
Utilization
(%)
Load
2013-‐07
99.83
98.07
32.84
shade
CPU
Utilization
(%)
Load
2013-‐08
99.82
97.25
31.95
shade
CPU
Utilization
(%)
Load
2013-‐09
99.67
87.84
32.57
shade
CPU
Utilization
(%)
Load
2013-‐10
99.83
91.13
35.64
shade
CPU
Utilization
(%)
Load
2013-‐11
96.15
85.08
29.54
shade
CPU
Utilization
(%)
Load
2013-‐12
94.68
74.73
28.38
shade
CPU
Utilization
(%)
Load
2014-‐01
94.46
79.88
28.31
shade
CPU
Utilization
(%)
Load
2014-‐02
99.04
83.22
31.94
shade
CPU
Utilization
(%)
Load
2014-‐03
97.66
80.45
32.89
40. 40
• But what about the Portfolio/Line of Business Views
!
• Remember this from earlier?
!
!
• We created customized mapping between the Database/
Database Services and their portfolio structure.
• For example, Finance -> Accounts Payable -> AP_APP
(Host/Database) -> RAC_SVC_AP_APP (RAC Service).
• Why do I mention Database and Database Service
• Database; To map storage to an Application
• Database Service; To map db cpu time to an
Application. How does an application connect to the
database?
The right“metrics”
41. 41
• But what about the Portfolio/Line of Business
CREATE
TABLE
portfolio
{
line_of_business
NOT
NULL
VARCHAR2(4000)
,department
NOT
NULL
VARCHAR2(256)
,application
NOT
NULL
VARCHAR2(256)
,host_name
NOT
NULL
VARHCAR2(256)
,database_name
NOT
NULL
VARCHAR2(256)
,service_name
NOT
NULL
VARCHAR2(256)
};
SQL>
SELECT
*
FROM
portfolio;
line_of_business
department
application
host_name
database_name
service_name
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
Supply
Chain
Transformation
Pricing
blue.color.com
RACDB03
RACDB03_PRC_01
Supply
Chain
Transformation
Consolidation
blue.color.com
RACDB03
RACDB03_CSL_01
Supply
Chain
Transformation
Transformation
blue.color.com
RACDB03
RACDB03_TSF_01
Merchandising
Handling
Breakage
green.color.com
RACDB05
RACDB05_BKG_01
Merchandising
Handling
Returns
green.color.com
RACDB05
RACDB05_RTN_01
IT
Order
Management
Inventory
purple.color.com
RACDB07
RACDB07_INV_01
IT
Order
Management
Supply
purple.color.com
RACDB07
RACDB07_SUP_01
The right“metrics”
• Alternatively, leverage Groups in EM12c
42. 42
• But what about the Portfolio/Line of Business
with
base
as
(
select
a.entity_type
,b.line_of_business
,b.department
,b.application
,a.substr(entity_name,
1,
4)
as
database_machine
,a.entity_name
AS
host_name
,a.metric_column_label
,a.metric_column_name
,a.metric_group_label
,a.collection_time
,to_char(a.collection_time,'yyyy')
||
'-‐Q'
||
to_char(a.collection_time,'q')
as
year_quarter
,extract(year
from
a.collection_time)
||'-‐'
||
ltrim(to_char(extract(month
from
a.collection_time),'09'))
as
year_month
,a.collection_time
as
year_month_day
,round(a.avg_value,2)
as
avg_value
,a.max_value
from
sysman.gc$metric_values_hourly
a
,portfolio
b
where
a.host_name
=
b.host_name
and
a.entity_type
=
'host'
and
a.metric_column_name
=
'cpuUtil'
and
a.metric_group_label
=
‘Load')
select
*
from
base
where
line_of_business
=
'shade';
The right“metrics”
44. 44
CPU Utilization (%)
• The most profound and relative metric for a host is its CPU Utilization.
• According to Oracle Documentation
– “this metric represents the amount of CPU utilization as a percentage of
total CPU processing power available”
• Aggregation for hosts in a Cluster is easy to represent
• When CPU Utilization (%) data is aggregated over several months it can
appear skewed.
• Utilize 95th Percentile to show sustained peak values
Visualize the“metrics”
46. 46
Storage Utilization
• With storage, I’ve found that a common
question which always comes up is“How
much have I allocated vs actually used?”
• Whether the utilization in question is within
an ASM cluster or instance)
– Disk Group
– Database
– Tablespace
• EM12c captures two basic metrics
– Usable
– Total
• This data can be extended to various
groupings, by the mapping table mentioned
previously
Visualize the“metrics”
49. 49
What about BI Publisher?
Visualize the“metrics”
• A
free
add-‐on
to
Enterprise
Manager
12c.
• Under
restricted-‐user
license
agreement,
it
is
free
to
use
with
the
Enterprise
Manager
repository
only.
• Mini
OBIEE!
50. 50
What about BI Publisher?
Visualize the“metrics”
• Two
main
components
– Data
Model
– Report
53. 53
!
• Overview
• Background
• Capacity Planning
• Understanding EM Metrics
• Using EM Metrics
• Lessons
• Conclusion
Agenda
54. 54
• What did The Client Need VS What they asked for?
– Important to recognize realistic goals
– Set them for The Client!
– Be like water, use the path of least resistance!
!
• Whether or not additional hardware is required is always a good question
!
• Be patient, the“metrics”will reveal their secrets in due time!
Lessons
55. 55
!
• Overview
• Background
• Capacity Planning
• Understanding EM Metrics
• Using EM Metrics
• Lessons
• Conclusion
Agenda
56. 56
• When put in the right perspective, these reports will
• Highlight growth trends
• Technical as well as
• Business point of view
• Reports generate more questions than answers
• What caused the spike in CPU Utilization, or Memory?
• Were there more database on-boarded, or was there excessive load on the
existing ones?
• What could attribute to the spikes in Storage growth?
• The idea behind building these reports is simple
• Data (metrics) already available in EM12c
• Why not use them?
Conclusion