The document discusses IO resource management (IORM) on Oracle Exadata. IORM governs and prioritizes IO requests to Exadata storage servers when databases are consolidated on Exadata. It describes the IORM architecture which uses categories, inter-database plans, and intra-database plans to allocate IO resources across consumer groups and databases. The document also provides details on monitoring IORM metrics using tools like CellCLI and analyzing cellsrv dump files.
The Top 5 Reasons to Deploy Your Applications on Oracle RACMarkus Michalewicz
A presentation for developers, DBAs, and managers. This presentation was first presented in course of the AIOUG Maximum Availability Architecture (MAA)-focus month August 2021. The first reason might surprise you!
AskTom: How to Make and Test Your Application "Oracle RAC Ready"?Markus Michalewicz
Oracle Real Application Clusters (Oracle RAC) is the preferred availability and scalability solution for Oracle Databases, as most applications can benefit from its capabilities without making any changes. This mini session explains the secrets behind Oracle RAC’s horizontal scaling algorithm, Cache Fusion, and how you can test and ensure that your application is “Oracle RAC ready.”
This deck was first presented in OOW19 as an AskTom theater / mini session and will be presented as a full version in other conferences going forward at which time I will provide an updated version of the deck.
This PPT is all about Fast Start Failover DataGuard and it will also helps you to easily understand basics of Fast Start Failover DataGuard in Oracle 12c.
in this PPT I have covered topics as below :
1.FSFO(Fast_Start Failover)
2.Dataguard
3.Types of Dataguard
4.Protection Modes
5.FSFO with physical Standby
6.Dataguard Broker
7.Observer Process.
The Top 5 Reasons to Deploy Your Applications on Oracle RACMarkus Michalewicz
A presentation for developers, DBAs, and managers. This presentation was first presented in course of the AIOUG Maximum Availability Architecture (MAA)-focus month August 2021. The first reason might surprise you!
AskTom: How to Make and Test Your Application "Oracle RAC Ready"?Markus Michalewicz
Oracle Real Application Clusters (Oracle RAC) is the preferred availability and scalability solution for Oracle Databases, as most applications can benefit from its capabilities without making any changes. This mini session explains the secrets behind Oracle RAC’s horizontal scaling algorithm, Cache Fusion, and how you can test and ensure that your application is “Oracle RAC ready.”
This deck was first presented in OOW19 as an AskTom theater / mini session and will be presented as a full version in other conferences going forward at which time I will provide an updated version of the deck.
This PPT is all about Fast Start Failover DataGuard and it will also helps you to easily understand basics of Fast Start Failover DataGuard in Oracle 12c.
in this PPT I have covered topics as below :
1.FSFO(Fast_Start Failover)
2.Dataguard
3.Types of Dataguard
4.Protection Modes
5.FSFO with physical Standby
6.Dataguard Broker
7.Observer Process.
This is a recording of my Advanced Oracle Troubleshooting seminar preparation session - where I showed how I set up my command line environment and some of the main performance scripts I use!
With the Oracle Multitenant option of Oracle Database 12c, the services of individual pluggable databases (PDBs) can be opened selectively on specified nodes of an Oracle Real Application Clusters (Oracle RAC) cluster. A true symbiotic relationship: the Oracle Multitenant option makes Oracle RAC better, and Oracle RAC makes the Oracle Multitenant option better! UPDATE for IOUG 2014.
Make Your Application “Oracle RAC Ready” & Test For ItMarkus Michalewicz
This presentation talks about the secrets behind Oracle RAC’s horizontal scaling algorithm, Cache Fusion, and how you can ensure that your application is “Oracle RAC ready.”. It discusses do's and don'ts and how to test your application for "Oracle RAC readiness". This version was first presented in Sangam19.
ORACLE 12C DATA GUARD: FAR SYNC, REAL-TIME CASCADE STANDBY AND OTHER GOODIESLudovico Caldara
The new release of Oracle Database has come with many new exciting enhancements for the High Availability.
This whitepaper introduces some new Data Guard features. Among various enhancements, special attention will be given to
the new Far Sync Instance and the Real-Time Cascade Standby.
"Extended" or "Stretched" Oracle RAC has been available as a concept for a while. Oracle RAC 12c Release 2 introduces an Oracle Extended Cluster configuration, in which the cluster understands the concept of sites and extended setups. This knowledge is used to more efficiently manage "Extended Oracle RAC", whether the nodes are 0.1 mile or 10 miles apart.
The presentation was last updated on August 7th 2017 to add a reference to the new MAA White Paper: "Installing Oracle Extended Clusters on Exadata Database Machine" - http://www.oracle.com/technetwork/database/availability/maa-extclusters-installguide-3748227.pdf and to correct some minor details.
This presentation provides a clear overview of how Oracle Database In-Memory optimizes both analytics and mixed workloads, delivering outstanding performance while supporting real-time analytics, business intelligence, and reporting. It provides details on what you can expect from Database In-Memory in both Oracle Database 12.1.0.2 and 12.2.
Tanel Poder Oracle Scripts and Tools (2010)Tanel Poder
Tanel Poder's Oracle Performance and Troubleshooting Scripts & Tools presentation initially presented at Hotsos Symposium Training Day back in year 2010
Oracle Active Data Guard: Best Practices and New Features Deep Dive Glen Hawkins
Oracle Data Guard and Oracle Active Data Guard have long been the answer for the real-time protection, availability, and usability of Oracle data. This presentation provides an in-depth look at several key new features that will make your life easier and protect your data in new and more flexible ways. Learn how Oracle Active Data Guard 19c has been integrated with Oracle Database In-Memory and offers a faster application response after a role transition. See how DML can now be redirected from an Oracle Active Data Guard standby to its primary for more flexible data protection in today’s data centers or your data clouds. This technical deep dive on Active Data Guard is designed to give you a glimpse into upcoming new features brought to you by Oracle Development.
12c Multi-Tenancy and Exadata IORM: An Ideal Cloud Based Resource ManagementFahd Mirza Chughtai
Cloud database enables administrators to scale up and down the resource usage according to the business requirements. Oracle 12c renders multi-tenancy to manage multiple pluggable databases within a multitenant container database. In an Exadata, at the compute nodes, the resource manager controls the resources among pluggable databases, and all this resource management is trickled down to the storage servers, where IORM controls the resources. This presentation lucidly explains as how a business can leverage the benefits of 12C multi-tenancy, DBRM, and IORM in an Exadata realm to have an ideal cloud based resource management.
This is a recording of my Advanced Oracle Troubleshooting seminar preparation session - where I showed how I set up my command line environment and some of the main performance scripts I use!
With the Oracle Multitenant option of Oracle Database 12c, the services of individual pluggable databases (PDBs) can be opened selectively on specified nodes of an Oracle Real Application Clusters (Oracle RAC) cluster. A true symbiotic relationship: the Oracle Multitenant option makes Oracle RAC better, and Oracle RAC makes the Oracle Multitenant option better! UPDATE for IOUG 2014.
Make Your Application “Oracle RAC Ready” & Test For ItMarkus Michalewicz
This presentation talks about the secrets behind Oracle RAC’s horizontal scaling algorithm, Cache Fusion, and how you can ensure that your application is “Oracle RAC ready.”. It discusses do's and don'ts and how to test your application for "Oracle RAC readiness". This version was first presented in Sangam19.
ORACLE 12C DATA GUARD: FAR SYNC, REAL-TIME CASCADE STANDBY AND OTHER GOODIESLudovico Caldara
The new release of Oracle Database has come with many new exciting enhancements for the High Availability.
This whitepaper introduces some new Data Guard features. Among various enhancements, special attention will be given to
the new Far Sync Instance and the Real-Time Cascade Standby.
"Extended" or "Stretched" Oracle RAC has been available as a concept for a while. Oracle RAC 12c Release 2 introduces an Oracle Extended Cluster configuration, in which the cluster understands the concept of sites and extended setups. This knowledge is used to more efficiently manage "Extended Oracle RAC", whether the nodes are 0.1 mile or 10 miles apart.
The presentation was last updated on August 7th 2017 to add a reference to the new MAA White Paper: "Installing Oracle Extended Clusters on Exadata Database Machine" - http://www.oracle.com/technetwork/database/availability/maa-extclusters-installguide-3748227.pdf and to correct some minor details.
This presentation provides a clear overview of how Oracle Database In-Memory optimizes both analytics and mixed workloads, delivering outstanding performance while supporting real-time analytics, business intelligence, and reporting. It provides details on what you can expect from Database In-Memory in both Oracle Database 12.1.0.2 and 12.2.
Tanel Poder Oracle Scripts and Tools (2010)Tanel Poder
Tanel Poder's Oracle Performance and Troubleshooting Scripts & Tools presentation initially presented at Hotsos Symposium Training Day back in year 2010
Oracle Active Data Guard: Best Practices and New Features Deep Dive Glen Hawkins
Oracle Data Guard and Oracle Active Data Guard have long been the answer for the real-time protection, availability, and usability of Oracle data. This presentation provides an in-depth look at several key new features that will make your life easier and protect your data in new and more flexible ways. Learn how Oracle Active Data Guard 19c has been integrated with Oracle Database In-Memory and offers a faster application response after a role transition. See how DML can now be redirected from an Oracle Active Data Guard standby to its primary for more flexible data protection in today’s data centers or your data clouds. This technical deep dive on Active Data Guard is designed to give you a glimpse into upcoming new features brought to you by Oracle Development.
12c Multi-Tenancy and Exadata IORM: An Ideal Cloud Based Resource ManagementFahd Mirza Chughtai
Cloud database enables administrators to scale up and down the resource usage according to the business requirements. Oracle 12c renders multi-tenancy to manage multiple pluggable databases within a multitenant container database. In an Exadata, at the compute nodes, the resource manager controls the resources among pluggable databases, and all this resource management is trickled down to the storage servers, where IORM controls the resources. This presentation lucidly explains as how a business can leverage the benefits of 12C multi-tenancy, DBRM, and IORM in an Exadata realm to have an ideal cloud based resource management.
Presentation by John Peterson at RMH Field Care Audit on 1/18/12. videos are posted on youtube.com/4docmontey
http://youtu.be/ahCxJ5vEcF0
http://youtu.be/Av0IJ-THnIE
Forefront 2010 Unified Access Gateway with SharePoint 2010 takes considerable planning and considerations depending on your topology. Here are a few things to note about it, and at least one way to do it.
Your company requires more than an alternate site contract with redundant equipment. When analyzing your current recovery solution, you may find your organization has no documented DR plan or process, no recovery facility, equipment constraints, or human resource limitations. A managed disaster recovery service provides your organization a backup and recovery assessment, a full recovery as part of the assessment, documentation for your businesses recovery plan, and equipment for future recovery needs, plus a recovery test each year and staff to perform the full recovery in the event of a disaster. Your disaster recovery solution will reduce risk and exposure, meet your corporate disaster recovery objectives, provide recovery time and recovery point assurance, and demonstrate a successful, documented test in a geographic diverse recovery center.
Monitoring VMware vFabric with Hyperic and Spring InsightC2B2 Consulting
Webinar presented by Steve Millidge, C2B2 Director, on the 19th of November 2012.
This webinar demonstrates how you can significantly improve your support of production tcServer environments using Hyperic and Spring Insight. In the webinar C2B2's experienced support engineer will show you how to gather extensive internal metrics from your production tcServer instances, how to configure alerts to warn you of potential problems in your production tcServer cluster and how to diagnose and triage poorly performing transactions with Spring Insight.
To watch high quality version of this webinar please visit https://www4.gotomeeting.com/register/941934207
View this presentation to gain insight into optimizing Postgres and savings for your data management. Visit EntepriseDB's > Resources > Webcasts to view the presentation by Jay Barrows, VP of Field Operations.
During this 45 -minute presentation, Jay Barrows, VP of Field Operations, will provide a business review of how, where and why businesses are leveraging PostgreSQL. In addition, he will go over the primary pains and business drivers shaping the data management landscape such as significant cost pressures combined with recent improvements to open source database options. Oracle migration is often considered the most powerful cost reduction opportunity if you understand the migration risks, and have a clear migration game plan.
Jay will discuss several use cases selected that highlight how enterprise customers are leveraging their findings from the adoption of other OSS products, to helping to bring Postgres to the extremely expensive and mission critical part of their IT stack - the DB. By doing so they are driving TCO down in very meaningful ways, sacrificing nothing in terms of performance, scalability, security or reliability. Many businesses are already leveraging OSS in much lower cost parts of IT stack (OS, middleware).
This presentation will be beneficial to decision-makers interested in enhancing their data management with PostgreSQL. I
Infor is committed to bringing you IBM's Power® Systems platform as the best possible support for our existing and new business applications that are Power- enabled and cloud-ready.
Infor System i Business Cloud, our cloud computing platform is robust enough to ensure that those applications will keep running efficiently and effectively, enabling you to maintain 'business as usual' for both users and customers.
In this presentation, we explore the options that enterprises have for deploying and managing cloud databases, including:
Data and application migration strategies.
New private, public, and hybrid cloud deployment models.
Enterprise tools for data management and resiliency.
Database workflow automation with virtual machines and containers.
About the presenter:
Jamie Watt is EDB's Vice President of Global Support Services and is in charge of leading technical support, customer care, remoteDBA services, and EDB's online community platform of PostgresRocks.com.
This presentation provides a brief overview eFolder BDR. eFolder BDR is a wholesale, backup and disaster recovery solution designed for MSPs, solution providers, and VARs.
You will learn how to create file archives, upload them to Amazon S3, and manage permissions and lifetimes, giving you the ability to back up any amount of data and to retain it for as long as you'd like. A number of open source and commercial backup and archiving tools will be demonstrated, as time permits.
You will also learn how to use built-in AWS facilities to quickly and easily create and restore snapshots of entire disk volumes.
eFolder Webinar, Seven Great Reasons to Upgrade Legacy BDRs NowDropbox
eFolder partner Erik Thorsell explores the reasons to aggressively upgrade your BDR installed base. Erik shares essential learnings from his 18 month refresh of his entire client base.
By leveraging services in the cloud, businesses can host new applications and services in a cost effective manner. Existing systems can also leverage the cloud in its entirety or for specific aspects of the system to reduce infrastructure management costs and to support potential scale-out requirements as usage increases. Windows Azure offers many services from application hosting, storage, content delivery, messaging, caching and security. Pricing each of these services to estimate your costs requires some thoughtfulness around how you will use each service within your architecture, and some predictions about the number of users, payload traffic and number of transactions. How then can you estimate your costs, or price your own offering to customers when there are so many variables? Pricing is not a perfect science and each business will have its own level of tolerance for cost absorption vs. costs to be deferred to customers. In this session we will break down the pricing model of the cloud, look at ways to quantify your service using various architectural examples, and look at ways you can track usage, validate costs and ultimately collect your costs across the core Windows Azure features to gain perspective on what you need to charge your customers for those services, along with some ideas on how to project revenue.
Any DBA from beginner to advanced level, who wants to fill in some gaps in his/her knowledge about Performance Tuning on an Oracle Database, will benefit from this workshop.
Using SQL Plan Management (SPM) to Balance Plan Flexibility and Plan StabilityEnkitec
This presentation is about understanding all 3 components of SPM and how we can use this technology to efficiently migrate "good" Execution Plans from one Release to another, or from one System to another.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
IO Resource Management on Exadata
1. IO Resource Management
CONFIDENTIAL |1
2012 Centroid Systems, Inc. All rights reserved. Reproduction of this document or any portion thereof without prior written consent is prohibited.
2. Contents
§ What is IO Resource Management?
§ IO Resource Management and DBRM
§ IORM Architecture
§ IORM Monitoring
§ IORM in Action
§ Business Justification for IORM
CONFIDENTIAL |2
2012 Centroid Systems, Inc. All rights reserved. Reproduction of this document or any portion thereof without prior written consent is prohibited.
3. About Me
§ John Clarke, Centroid
§ Specialized in
§ Oracle Exadata
§ Performance Tuning and RAC
§ Data Warehousing, 11g, Linux
§ Oracle Apps DBA
§ john.clarke@centroid.com, www.centroid.com
§ www.centroid.com
§ Blogs at www.centroid.com/knowledgebase
§ Sporadically dumps random thoughts at @jccclarke
CONFIDENTIAL |3
2012 Centroid Systems, Inc. All rights reserved. Reproduction of this document or any portion thereof without prior written consent is prohibited.
4. What is IORM?
§ IORM = IO Resource Management
§ IORM is a means to govern and prioritize IO requests to Exadata
storage servers
§ Often used in conjunction with DBRM
§ If consolidating databases on Exadata, use IORM
§ If you’re not consolidating, still often makes sense!
CONFIDENTIAL |4
2012 Centroid Systems, Inc. All rights reserved. Reproduction of this document or any portion thereof without prior written consent is prohibited.
5. What is IORM?
Some basics …
§ Exadata “IORM Plan” = Inter-Database plan + Category plan
§ A category plan specifies resource allocations per category of resource
consumer groups
– Categories are assigned to DBRM resource consumer groups
– Categories (can) span databases
– Consumer groups are within a database
§ A Inter-Database plan specifies IO resource allocations per database
§ An Intra-Database plan = a DBRM Plan
CONFIDENTIAL |5
2012 Centroid Systems, Inc. All rights reserved. Reproduction of this document or any portion thereof without prior written consent is prohibited.
6. What is IORM? (continued)
There are 3 IORM methods
§ Category IORM
– (implies categories assigned to resource consumer groups)
§ Inter-Database IORM
– (i.e., IO resource allocation between databases)
§ Intra-Database IORM
– (i.e., allocations within a database)
You can use combinations of the above …
CONFIDENTIAL |6
2012 Centroid Systems, Inc. All rights reserved. Reproduction of this document or any portion thereof without prior written consent is prohibited.
7. What is IORM? – In Pictures
PROD consumer
groups
CG: FIN_OLTP CAT: NORMAL_PRIORITY
DB% for PROD PROD CG: FIN_REPORTS CAT: LOW_PRIORITY
CG: SHIPPING_OLTP CAT: HIGH_PRIORITY
CG: DW_CRITICAL CAT: HIGH_PRIORITY
DB% for DWPRD DWPRD CG: DW_NORMAL CAT: NORMAL_PRIORITY
DWPRD consumer
groups
DEV consumer
group
DB% for DEV DEV CG: DEV_ALL CAT: LOW_PRIORITY
CONFIDENTIAL |7
2012 Centroid Systems, Inc. All rights reserved. Reproduction of this document or any portion thereof without prior written consent is prohibited.
8. Database Resource Management (DBRM)
§ Database Resource Management (DBRM) – see
http://docs.oracle.com/cd/E14072_01/server.112/e10595/dbrm.htm
§ Used within a single database when you’ve got workloads with different
performance requirements
§ Resource consumer groups allow you to group sessions by workload
§ Administrator specifies resource allocations per consumer group
§ Administrator maps sessions to consumer groups
§ The combination of consumer groups and session mappings = a
resource plan
§ A DBRM plan is also called an Intra-Database resource plan
CONFIDENTIAL |8
2012 Centroid Systems, Inc. All rights reserved. Reproduction of this document or any portion thereof without prior written consent is prohibited.
9. IORM and DBRM
Intra-Database IORM
§ If you have multiple workloads within a database, you need an Intra-Database
resource plan
§ If you only have only one database on your Exadata, the Intra-Database plan is
all you need for IORM
§ Exadata automatically prioritizes IO requests based on this Intra-Database plan
CONFIDENTIAL |9
2012 Centroid Systems, Inc. All rights reserved. Reproduction of this document or any portion thereof without prior written consent is prohibited.
10. IORM and DBRM
Inter-Database IORM
§ If you have multiple databases on an Exadata that you wish to control IO
allocations amongst, you need an Inter-Database plan
§ Rules for an Inter-Database plan specify IO allotments per database, not
resource consumer groups
CONFIDENTIAL | 10
2012 Centroid Systems, Inc. All rights reserved. Reproduction of this document or any portion thereof without prior written consent is prohibited.
11. IORM and DBRM
Category IORM
§ A category plan is used to control IO resource utilization by classification of
work being done – i.e., by categories of consumer groups
§ Category plans assume Intra-Database plans are in effect
CONFIDENTIAL | 11
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12. IORM Architecture
DBRM runs in the database
IORM part of CELLSRV
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13. IORM Architecture – Rules of Engagement
§ IORM only kicks in to prioritize IO when needed
§ “When needed” = when IO is saturated to cell disks
§ Any disk allocation not fully utilized is made available to other
workloads
§ Background IO is scheduled based on priority relative to user IO
§ Redo and control file writes always have higher priority
§ DBWR writes scheduled at same priority as user IO
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14. IORM Architecture – IO Queues
§ For each cell disk, each database accessing cell has one
IO queue per consumer group and three background
queues
§ Background IO queues are mapped to high, medium, and
low priority requests with different IO types mapped to each
queue
§ If no Intra-Database plans are set, all non-background IO
requests are grouped into a single queue called
OTHER_GROUPS
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15. IORM Architecture – IO Queues
No consumer groups
No consumer groups
All user IO goes to
Other Groups
queue
OTHER_GROUPS OTHER_GROUPS
High BG High BG
Medium BG Medium BG
Low BG Low BG
PROD Queues DEV Queues
Cell Disk CD_00_cm01cel01
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16. IORM Architecture – IO Queues
DBRM consumer groups
CG: OLTP
PROD configured
CG: REPT with three resource
consumer groups
CG: FINANCE
OTHER_GROUPS OTHER_GROUPS
High BG High BG
Medium BG Medium BG
Low BG Low BG
PROD Queues DEV Queues
Cell Disk CD_00_cm01cel01
CONFIDENTIAL | 16
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17. IORM Architecture
iDB message contains database
name, consumer group + category,
IO type, extents to get, etc.
PROD DWPRD DEV
PROD Cell disk 1 DWPRD Cell Disk 7 DEV Cell Disk 11
FIN_OLTP DW_CRITICAL DEV_ALL
FIN_REPORTS DW_NORMAL OTHER_GROUPS
SHIPPING_OLTP OTHER_GROUPS HIGH
OTHER_GROUPS HIGH MEDIUM
HIGH MEDIUM LOW
MEDIUM LOW
LOW
PROD Cell disk 2 DWPRD Cell Disk 2 DEV Cell Disk 2
PROD Cell disk 3 DWPRD Cell Disk 3 DEV Cell Disk 3
PROD Cell disk N DWPRD Cell Disk N DEV Cell Disk N
IO queues and cell services
Disk 1 Disk 3 Disk 5 Disk 7 Disk 9 Disk 11 Exadata Cell Disks
Disk 2 Disk 4 Disk 6 Disk 8 Disk 10 Disk 12
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18. IORM Architecture
PROD DWPRD DEV
PROD Cell disk 1 DWPRD Cell Disk 7 DEV Cell Disk 11
FIN_OLTP DW_CRITICAL DEV_ALL
FIN_REPORTS DW_NORMAL OTHER_GROUPS
SHIPPING_OLTP OTHER_GROUPS HIGH
OTHER_GROUPS HIGH MEDIUM
HIGH MEDIUM LOW
MEDIUM LOW
LOW
PROD Cell disk N DWPRD Cell Disk N DEV Cell Disk N
IORM
IO queues and cell services
Disk IO queues
ordered after IORM
does its logic
Disk 1 Disk 3 Disk 5 Disk 7 Disk 9 Disk 11 Exadata Cell Disks
Disk 2 Disk 4 Disk 6 Disk 8 Disk 10 Disk 12
CONFIDENTIAL | 18
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19. IORM Architecture – The Math
Methods are evaluated based on a fixed order:
§ Category IORM is evaluated first
Intra CG% / sum (x) =
§ Inter-Database IORM next “Consumer group
weight” (my words …)
§ Intra-Database IORM next
“cat%” = percentage of
CG% = (Intra CG% / Σ(x)) * db% * cat% resource allocation for
the category in which
the consumer group
belongs
“CG%” = IORM “Intra CG%” =
determined resource
resource allocation for
allocation for consumer group “x” = sum of Intra- db% = percentage of
consumer group within an Intra- Database consumer database allocation in
sessions Database plan group allocations for all the Inter-Database plan
consumer groups in the
same category
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20. IORM Architecture – The Math
All User IO
No IORM
100%
9.87% = Cat% * DB% * CG weight
Cat% = 65%
Category IORM
Cat1: 65% Cat2: 25% Cat3: 10%= 40%
DB%
CG Weight = 60% / (sum over Cat1)
= 60% / (80% + 8% + 60% + 10%)
= 37.7%
9.87% = 65% * 40% * 37.7%
Inter-Database IORM
DB1: 60% DB2: 40% DB1: 60% DB2: 40% DB1: 60% DB2: 40%
39% 26% 15% 10% 6% 4%
CG1: 80% L1, Category=Cat1 19.97% CG1: 60% L1, Category=Cat1 9.87%
CG2: 40% L2, Category=Cat1 1.97% CG2: 10% L1, Category=Cat1 1.65%
Intra-Database IORM
CG3: 40% L2, Category=Cat3 0.38% CG3: 40% L2, Category=Cat2 5.45%
DB1 DB2
CG4: 50% L3, Category=Cat2 6.82% CG4: 40% L2, Category=Cat3 3.75%
CONFIDENTIAL | 20
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21. Or if you like Excel …
Enter values in the blue
IORM resource calculation
https://dl.dropbox.com/u/92079964/IORM%20Planning%20Calculator.xlsx
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22. Monitoring IORM
Here’s what I’m going to talk about in the next few slides …
§ IORM metrics
§ Using CellCLI to monitor IORM
§ metric_iorm.pl (MOS note 1337265.1)
§ cellsrv_statedump
§ What I like to do with the data
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23. Monitoring IORM: IORM Metrics
§ Exadata tracks IORM metrics in the storage cell. Metrics include:
– Counter and wait metrics
– Utilization and throughput metrics
§ Exadata metrics can be queried from CellCLI as of:
– Now, using LIST METRICCURRENT
– Historically, using LIST METRICHISTORY
§ Exadata groups IORM metrics by:
– Category IORM method
§ objectType=‘IORM_CATEGORY’
§ name like ‘CT_.*’
– Inter-Database IORM method
§ objectType=‘IORM_DATABASE’
§ name like ‘DB_.*’
– Consumer group IORM method
§ objectType = ‘IORM_CONSUMER_GROUP’
§ name like ‘CG_.*’
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24. Monitoring IORM: Category IORM Metrics
[root@cm01cel01 ~]# cellcli -e list metricdefinition where objectType='IORM_CATEGORY'!
Name Description Type Unit
CT_FC_IO_BY_SEC Number of megabytes of I/O per second for this category to flash cache Instantaneous MB/sec
CT_FC_IO_RQ Number of IO requests issued by an IORM category to flash cache Cumulative IO requests
CT_FC_IO_RQ_SEC Number of IO requests issued by an IORM category to flash cache per second Rate IO/sec
CT_FD_IO_BY_SEC Number of megabytes of I/O per second for this category to flash disks Instantaneous MB/sec
CT_FD_IO_LOAD Average I/O load from this category for flash disks Instantaneous Number
CT_FD_IO_RQ_LG Number of large IO requests issued by an IORM category to flash disks Cumulative IO requests
CT_FD_IO_RQ_LG_SEC Number of large IO requests issued by an IORM category to flash disks per second Rate IO/sec
CT_FD_IO_RQ_SM Number of small IO requests issued by an IORM category to flash disks Cumulative IO requests
CT_FD_IO_RQ_SM_SEC Number of small IO requests issued by an IORM category to flash disks per second Rate IO/sec
Throughput, MB/sec
CT_IO_BY_SEC Number of megabytes of I/O per second for this category to hard disks Instantaneous MB/sec
by category
CT_IO_LOAD Average I/O load from this category for hard disks Instantaneous Number
CT_IO_RQ_LG Number of large IO requests issued by an IORM category to hard disks Cumulative IO requests
CT_IO_RQ_LG_SEC Number of large IO requests issued by an IORM category to hard disks per second Rate IO/sec
CT_IO_RQ_SM Number of small IO requests issued by an IORM category to hard disks Cumulative IO requests/sec
IO requests
CT_IO_RQ_SM_SEC Number of small IO requests issued by an IORM category to hard disks per second Rate IO/sec
CT_IO_UTIL_LG Percentage of disk resources utilized by large requests from this category Instantaneous %
Disk utilization by
CT_IO_UTIL_SM Percentage of disk resources utilized by small requests from this category Instantaneous category
%
CT_IO_WT_LG IORM wait time for large IO requests issued by an IORM category Cumulative ms
CT_IO_WT_LG_RQ Average IORM wait time per request for large IO requests issued by an IORM category Rate ms/request
CT_IO_WT_SM IORM wait time for small IO requests issued by an IORM category Cumulative IO wait ms
time/sec
CT_IO_WT_SM_RQ Average IORM wait time per request for small IO requests issued by an IORM category Rate ms/request
CONFIDENTIAL | 24
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25. Monitoring IORM: Inter-Database IORM Metrics
[root@cm01cel01 ~]# cellcli -e list metricdefinition where objectType='IORM_DATABASE'!
Name Description Type Unit
DB_FC_IO_BY_SEC Number of megabytes of I/O per second for this database to flash cache Instantaneous MB/sec
DB_FC_IO_RQ Number of IO requests issued by a database to flash cache Cumulative IO requests
DB_FC_IO_RQ_SEC Number of IO requests issued by a database to flash cache per second Rate IO/sec
DB_FD_IO_BY_SEC Number of megabytes of I/O per second for this database to flash disks Instantaneous MB/sec
DB_FD_IO_LOAD Average I/O load from this database for flash disks Instantaneous Number
DB_FD_IO_RQ_LG Number of large IO requests issued by a database to flash disks Cumulative IO requests
DB_FD_IO_RQ_LG_SEC Number of large IO requests issued by a database to flash disks per second Rate IO/sec
DB_FD_IO_RQ_SM Number of small IO requests issued by a database to flash disks Cumulative IO requests
DB_FD_IO_RQ_SM_SEC Number of small IO requests issued by a database to flash disks per second Rate IO/sec
Throughput, MB/sec
DB_IO_BY_SEC Number of megabytes of I/O per second for this database to hard disks Instantaneous MB/sec
by DB
DB_IO_LOAD Average I/O load from this database for hard disks Instantaneous Number
DB_IO_RQ_LG Number of large IO requests issued by a database to hard disks Cumulative IO requests
DB_IO_RQ_LG_SEC Number of large IO requests issued by a database to hard disks per second Rate IO/sec
DB_IO_RQ_SM Number of small IO requests issued by a database to hard disks Cumulative IO requests/sec
IO requests
DB_IO_RQ_SM_SEC Number of small IO requests issued by a database to hard disks per second Rate IO/sec
DB_IO_UTIL_LG Percentage of disk resources utilized by large requests from this database Instantaneous %
Disk utilization by
DB_IO_UTIL_SM Percentage of disk resources utilized by small requests from this database Instantaneous DB
%
DB_IO_WT_LG IORM wait time for large IO requests issued by a database Cumulative ms
DB_IO_WT_LG_RQ Average IORM wait time per request for large IO requests issued by a database Rate ms/request
DB_IO_WT_SM IORM wait time for small IO requests issued by a database Cumulative IO wait ms
time/sec
DB_IO_WT_SM_RQ Average IORM wait time per request for small IO requests issued by a database Rate ms/request
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26. Monitoring IORM: Inter-Database IORM Metrics (cont)
[root@cm01cel01 ~]# cellcli -e list metricdefinition where objectType='IORM_DATABASE'!
Name Description Type Unit
DB_FL_IO_BY The number of MB written to the Flash Log Cumulative MB
DB_FL_IO_BY_SEC The number of MB written per second to the Flash Log Instantaneous MB/sec
DB_FL_IO_RQ The number of I/O requests issued to the Flash Log Cumulative IO Requests
DB_FL_IO_RQ_SEC The number of I/O requests per second issued to the Flash Log Instantaneous IO/sec
CONFIDENTIAL | 26
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27. Monitoring IORM: Consumer Group IORM Metrics
[root@cm01cel01 ~]# cellcli -e list metricdefinition where objectType='IORM_CONSUMER_GROUP'!
Name Description Type Unit
CG_FC_IO_BY_SEC Number of megabytes of I/O per second for this consumer group to flash cache Instantaneous MB/sec
CG_FC_IO_RQ Number of IO requests issued by a consumer group to flash cache Cumulative IO requests
CG_FC_IO_RQ_SEC Number of IO requests issued by a consumer group to flash cache per second Rate IO/sec
CG_FD_IO_BY_SEC Number of megabytes of I/O per second for this consumer group to flash disks Instantaneous MB/sec
CG_FD_IO_LOAD Average I/O load from this consumer group for flash disks Instantaneous Number
CG_FD_IO_RQ_LG Number of large IO requests issued by a consumer group to flash disks Cumulative IO requests
CG_FD_IO_RQ_LG_SEC Number of large IO requests issued by a consumer group to flash disks per second Rate IO/sec
CG_FD_IO_RQ_SM Number of small IO requests issued by a consumer group to flash disks Cumulative IO requests
CG_FD_IO_RQ_SM_SEC Number of small IO requests issued by a consumer group to flash disks per second Rate IO/sec
Throughput, MB/sec
CG_IO_BY_SEC Number of megabytes of I/O per second for this consumer group to hard disks Instantaneous MB/sec
by CG
CG_IO_LOAD Average I/O load from this consumer group for hard disks Instantaneous Number
CG_IO_RQ_LG Number of large IO requests issued by a consumer group category to hard disks Cumulative IO requests
CG_IO_RQ_LG_SEC Number of large IO requests issued by a consumer group to hard disks per second Rate IO/sec
CG_IO_RQ_SM Number of small IO requests issued by a consumer group to hard disks Cumulative IO requests/sec
IO requests
CG_IO_RQ_SM_SEC Number of small IO requests issued by a consumer group to hard disks per second Rate IO/sec
CG_IO_UTIL_LG Percentage of disk resources utilized by large requests from this consumer group Instantaneous %
Disk utilization by
CG_IO_UTIL_SM Percentage of disk resources utilized by small requests from this consumer group Instantaneous CG
%
CG_IO_WT_LG IORM wait time for large IO requests issued by a consumer group Cumulative ms
CG_IO_WT_LG_RQ Average IORM wait time per request for large IO requests issued by a consumer group Rate ms/request
CG_IO_WT_SM IORM wait time for small IO requests issued by a consumer group Cumulative IO wait ms
time/sec
CG_IO_WT_SM_RQ Average IORM wait time per request for small IO requests issued by a consumer group Rate ms/request
CONFIDENTIAL | 27
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28. Monitoring IORM
§ Even if you don’t implement IORM plans, database IO is tagged and
some database metrics are populated
§ These ‘DB_.*’ metrics can be valuable No IORM plan active
Did some large IO
on DWPRD, metrics
displayed
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29. Monitoring IORM: Using CellCLI
§ Use cellcli “list” to display IORM metrics
§ “list metriccurrent” displays current metrics and “list metrichistory”
displays historical metrics
§ Query with dcli to show metrics on all the nodes
§ Examples:
Display historical metrics for
Show historical metrics
all cells using dcli
based on date range
Display current metrics for
MB/sec per database
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30. Monitoring IORM: Common challenges with CellCLI
1. Difficult to remember metric names
2. Difficult to remember/type cellcli query syntax, especially with
metrichistory and dates
3. Lack of ability to monitor metrics over time interval, real-time (like
“sar –u <interval> <iterations>”
4. Difficult to assemble output and make it usable
Here’s how I address it:
§ celldig.sh => Addresses #1 & #2 above
§ cellstats.sh => Addresses #3 above
§ celliormbundle.sh => Addresses #4 above
§ celliormbundle2.sh => Uses ageInMinutes criteria (got lazy)
https://dl.dropbox.com/u/92079964/cellscr.zip
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31. Monitoring IORM: celldig.sh
Download and try it out …
CONFIDENTIAL | 31
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32. Monitoring IORM: celldig.sh
Start from now – 1 day
and display 20 min of data
Here’s the cellcli command
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33. Monitoring IORM: cellstats.sh
Query all cells, 2 second
intervals, 5 iterations
Query single cell, 2 second
intervals, 5 iterations
CONFIDENTIAL | 33
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34. Monitoring IORM: celliormbundle.sh
What it does:
1. Collects cell server metrics for IORM-related objects
2. Accepts a “from” and “to” date range
3. Output directed to temp files and loaded from external tables
Prep work: Run celliormbundle_setup.sh
celliormbundle.sh and celliormbundle2.sh will be used to gather
performance metrics for IORM test scenarios later …
CONFIDENTIAL | 34
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35. Monitoring IORM: celliormbundle.sh
Usage
Execution
Loading IORM_METRICS
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36. Monitoring IORM: celliormbundle2.sh
Usage
Execution
Load IORM_METRICS
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37. Monitoring IORM: metric_iorm.pl
§ metric_iorm.pl nicely summarizes IORM metrics and can be
downloaded from MOS note 1337265.1
§ Without any input parameters, displays current metrics
§ With collectionTime-scoped input parameters, displays historical
metrics summarized by minute
§ Good way to understand what resources are consuming the most IO,
whether disk latencies are reasonable, flash cache hit metrics per
database, and overall IORM plan impact on performance
§ Works regardless of whether IORM plan is active
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38. Monitoring IORM: metric_iorm.pl
Example: Show current metrics for a cell:
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39. Monitoring IORM: metric_iorm.pl
Example: Display metrics between 9:00am and 9:30am on 7/12/2012
Summarizes cell
stats as well
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40. Monitoring IORM: metric_iorm.pl
Example: Display metrics from ½ hour ago for a duration of 10 minutes
Use “ageInMinutes” syntax
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41. Monitoring IORM: metric_iorm.pl
Example: Collect across all cells using dcli
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42. Monitoring IORM: Inside a CELLSRV statedump
§ Event cellsrv.cellsrv_statedump dumps current state of cell to trace file
§ Contains some good IORM information
§ Invoke like this:
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43. Monitoring IORM: Inside a CELLSRV statedump
Under the “IORM State Dump” section, trace file organized like:
§ IORM Enabled heading
– Current IORM Plans
§ Category Plan details
– Map of database and consumer groups to categories
§ Inter-Database Plan details
§ Intra-Database Plan details
§ Complete Mappings
– Queued IO Requests for cellDisk /dev/sdX (repeated for each cell disk)
§ Category Plan
– Inter-Database Plan
» Intra-Database Plan
» IO queuing details per consumer group, database, category, and cell
disk
– Queued IO Requests for cellDisk /dev/sdY (repeat previous section)
CONFIDENTIAL | 43
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44. Monitoring IORM: Inside a CELLSRV statedump
Search for this section in trace file
Currently, no IORM plan is enabled
CONFIDENTIAL | 44
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45. Monitoring IORM: Inside a CELLSRV statedump
Sections arranged by disk device
IORM boost = ratio of IOs skipped
to IOs scheduled
= relative measure of how active
IO scheduling is happening
Broken down by Category first
… then database
… then intra db consumer group
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46. Monitoring IORM: Inside a CELLSRV statedump
Here’s one with IORM enabled
Dumps Category plan first
… then DB + CG to Category mapping
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47. Monitoring IORM: Inside a CELLSRV statedump
Next is displays Inter-Database plan
Intra-Database plans for each database
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48. Monitoring IORM: Inside a CELLSRV statedump
For each devices, shows queued IO
requests – we have none here
Detail section similar to before
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49. Monitoring IORM: What to do with the data
I like to do this:
§ When analyzing a specific time period:
– Run celliormbundle.sh or celliormbundle2.sh
– Query the data in CELLIORM.IORM_METRICS via SQL
– Dump output to Excel and graph
– Capture test timings
§ When analyzing performance for “right now”:
– Run metric_iorm.pl with no arguments and examine output
– Run cellstats.sh and iterate over a period of time for a specific metric for a metric or 2
CONFIDENTIAL | 49
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50. IORM in Action
§ Test #1: Inter-Database IORM plan with 4 databases
§ Test #2: Inter-Database IORM plan with 4 databases + DB limits
§ Test #3: Category IORM plan
§ Test #4: Inter-Database IORM + Category IORM
§ Test #5: Inter-Database IORM + Category IORM, give DWPRD all the
resources it needs
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51. IORM in Action
For each test, we’ll:
§ Plan
§ Show expected resource allocations
§ Implement
§ Validate
§ Conduct a load test
§ Analyze
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52. IORM in Action: Baseline Test
First I’ll run a baseline without IORM plans active and analyze data …
§ I’ll use a modified version of Karl Arao’s IOsaturationtoolkit-v2 (
http://karlarao.wordpress.com/2012/05/14/iosaturationtoolkit-v2-with-
iorm-and-awesome-text-graph/) to generate load
§ In this, I’ll run 4 concurrent full-scans against a large table with 3
separate schemas (ORACLE,ORACLE2, and ORACLE3) across 4
databases (DWPRD, DWPROD, VISX, and VISY)
§ I’ll analyze the following:
– Output from IOsaturationtoolkit-v2 log files
– Data in IORM_METRICS from celliormbundle.sh
– Data from output of metric_iorm.pl
Test started at 2012-07-17T17:22:43 and ended at 2012-07-17T17:28:45
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53. IORM in Action: Baseline Test
IOsaturationtoolkit-v2 Results
Statistics
relatively random
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54. IORM in Action: Test 1 Planning
Inter-Database IORM with 4 databases
Inter-Database IO allocation:
§ VISX: 55%
§ DWPRD: 25%
§ DWPROD: 15%
§ VISY: 5%
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55. IORM in Action: Test 1 Resource Allocations
Inter-Database IORM with 4 databases
Empty the Category cells
Enter IORM % per DB
per plan
Select DB, enter arbitrary
consumer groups, select OTHER/ALL
Category
Inter-Database IO allocations calculated
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56. IORM in Action: Test 1 Implement
Inter-Database IORM with 4 databases
I like to do this first …
Set VISX to 55%, level 1
Set DWPRD to 25%, level 1
Set DWPROD to 15%, level 1
Set VISY to 5%, level 1
Set OTHER to 100%, level 2
Activate plan
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57. IORM in Action: Test 1 Validate
Inter-Database plan using 4 databases
“list iormplan detail”
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58. IORM in Action: Test 1 Validate (continued)
Inter-Database plan using 4 databases
Issue cell server statedump
IORM plan active
Just 2 categories …
OTHER = all DBs for now .
OTHER_GROUPS since
no Intra-Database plans
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59. IORM in Action: Test 1 Load Test
Inter-Database IORM with 4 databases
We’ll conduct the same load test we did in our Test 0 baseline test
Sampled DB_IO_WT_LG_RQ
(avg. IO wait time / request / large)
Notice wait times per DB
align with inter-database plan
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60. IORM in Action: Test 1 Analyze
Inter-Database IORM with 4 databases
IOsaturationtoolkit-v2 Results:
Test duration times matched expectations IO throughput matched expectations
visx < dwprd < dwprod < visy visx > dwprd > dwprod > visy
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61. IORM in Action: Test 1 Analyze
Inter-Database IORM with 4 databases
CELLORM.IORM_METRIC data
Query or MBPS, IOPS,
Utilization, and Waits
CONFIDENTIAL | 61
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62. IORM in Action: Test 1 Analyze
Inter-Database IORM with 4 databases
CELLORM.IORM_METRIC data
As expected, VISX
had best throughput
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2012 Centroid Systems, Inc. All rights reserved. Reproduction of this document or any portion thereof without prior written consent is prohibited.
63. IORM in Action: Test 1 Analyze
Inter-Database IORM with 4 databases
CELLORM.IORM_METRIC data
VISX had highest
IOPs and VISY the lowest
CONFIDENTIAL | 63
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64. IORM in Action: Test 1 Analyze
Inter-Database IORM with 4 databases
CELLORM.IORM_METRIC data
Utilization numbers match
expectations
CONFIDENTIAL | 64
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65. IORM in Action: Test 1 Analyze
Inter-Database IORM with 4 databases
CELLORM.IORM_METRIC data
VISY waited the most,
on average, per request
CONFIDENTIAL | 65
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66. IORM in Action: Test 1 Analyze
Inter-Database IORM with 4 databases
metric_iorm.pl output
Seeing non-zero queue
times
CONFIDENTIAL | 66
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67. IORM in Action: Test 2 Planning
Inter-Database IORM plan with 4 databases and IORM database limits
§ Inter-Database plan requirements same as Test 1
– VISX: 55%
– DWPRD: 25%
– DWPROD: 15%
– VISXY: 5%
§ IORM database IO limits also imposed on each database:
– VISX: 80%
– DWPRD: 10%
– DWPROD: 5%
– VISXY: 5%
CONFIDENTIAL | 67
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68. IORM in Action: Test 2 Resource Allocations
Inter-Database IORM plan with 4 databases and IORM database limits
IO limits per database
Adjusted resource limits
CONFIDENTIAL | 68
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69. IORM in Action: Test 2 Implement
Inter-Database IORM plan with 4 databases and IORM database limits
Note limit clauses
CONFIDENTIAL | 69
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70. IORM in Action: Test 2 Validate
Inter-Database IORM plan with 4 databases and IORM database limits
CONFIDENTIAL | 70
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71. IORM in Action: Test 2 Validate
Inter-Database IORM plan with 4 databases and IORM database limits
DB limit
CONFIDENTIAL | 71
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72. IORM in Action: Test 2 Load Test
Inter-Database IORM plan with 4 databases and IORM database limits
We’ll conduct the same load test we did previously
Note wait distribution
CONFIDENTIAL | 72
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73. IORM in Action: Test 2 Analyze
Inter-Database IORM plan with 4 databases and IORM database limits
IOsaturationtoolkit-v2 Results:
VISX and DWPRD took the least amount of time IO throughput numbers significantly lower than Test 1
but limits caused overall IO time to be less than in Test 1 Relative MB/s/database as expected
CONFIDENTIAL | 73
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74. IORM in Action: Test 2 Analyze
Inter-Database IORM plan with 4 databases and IORM database limits
CELLIORM.IORM_METRICS data:
Throughput less than Test 1, as
expected
CONFIDENTIAL | 74
2012 Centroid Systems, Inc. All rights reserved. Reproduction of this document or any portion thereof without prior written consent is prohibited.
75. IORM in Action: Test 2 Analyze
Inter-Database IORM plan with 4 databases and IORM database limits
CELLIORM.IORM_METRICS data:
IOPs less than Test 1, as
expected
CONFIDENTIAL | 75
2012 Centroid Systems, Inc. All rights reserved. Reproduction of this document or any portion thereof without prior written consent is prohibited.
76. IORM in Action: Test 2 Analyze
Inter-Database IORM plan with 4 databases and IORM database limits
CELLIORM.IORM_METRICS data:
Utilization less – imposing
limits yields IO capacity
CONFIDENTIAL | 76
2012 Centroid Systems, Inc. All rights reserved. Reproduction of this document or any portion thereof without prior written consent is prohibited.
77. IORM in Action: Test 2 Analyze
Inter-Database IORM plan with 4 databases and IORM database limits
CELLIORM.IORM_METRICS data:
Significantly more queue time,
a reflection of limits
CONFIDENTIAL | 77
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78. IORM in Action: Test 3 Planning
Category IORM Plan
§ No Inter-Database Plan
§ Category Plan
– CAT_HIGH = 70%, Level 1
– CAT_MEDIUM = 20%, Level 1
– CAT_LOW = 80%, Level 2
§ Consumer Group Mappings
– DWPRD:
§ CG_CRITICAL (80% L1 intra) assigned CAT_HIGH category, mapped to user “ORACLE”
§ CG_NORMAL (20% L1 intra) assigned CAT_MEDIUM category, mapped to user “ORACLE2”
§ CG_OTHER (100% L2 intra) assigned CAT_LOW, mapped to user “ORACLE3”
– DWPROD:
§ CG_CRITICAL (70% L1 intra) assigned CAT_HIGH category, mapped to user “ORACLE”
§ CG_NORMAL (30% L1 intra) assigned CAT_MEDIUM category, mapped to user “ORACLE2”
§ CG_OTHER (100% L2 intra) assigned CAT_LOW , mapped to user “ORACLE3”
– VISX:
§ CG_SHIP_OLTP (50% L1 intra) assigned CAT_HIGH category, mapped to user “ORACLE”
§ CG_FIN_OLTP (40% L1 intra) assigned CAT_HIGH category, mapped to user “ORACLE2”
§ CG_FIN_REPT (10% L1 intra) assigned CAT_MEDIUM , mapped to user “ORACLE3”
– VISY:
§ CG_OLTP(100% L1 intra) assigned CAT_LOW category, mapped to user “ORACLE”
§ CG_REPT (100% L2 intra) assigned CAT_LOW category, mapped to user “ORACLE2”
§ CG_OTHER (100% L3 intra) assigned CAT_LOW category, mapped to user “ORACLE3”
CONFIDENTIAL | 78
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79. IORM in Action: Test 3 Planning
Category IORM Plan
VISX DWPRD DWPROD VISY
CG_SHIP_OLTP: 50% L1 CG_CRITICAL: 80% L1 CG_CRITICAL: 70% L1 CG_OLTP: 100% L1
CG_FIN_OLTP: 40% L1 CG_NORMAL: 20% L1 CG_NORMAL: 30% L1 CG_REPT: 100% L2
CG_FIN_REPT: 10% L1 CG_OTHER: 100% L2 CG_OTHER: 100% L2 CG_OTHER: 100% L3
CG_OTHER: 100% L2
CATEGORY: HIGH_PRIORITY (70% L1)
CATEGORY: MEDIUM_PRIORITY (20% L1)
CATEGORY: LOW_PRIORITY (80% L2)
CONFIDENTIAL | 79
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80. IORM in Action: Test 3 Resource Allocations
Category IORM Plan
Adjusted allocation percentages
CONFIDENTIAL | 80
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81. IORM in Action: Test 3 Implement
Category IORM Plan
Implementation steps:
§ Creating consumer groups in each database to match scenario and
assign consumer groups to categories
§ Map sessions to consumer groups and activate plan
§ Enable IORM Category plan
CONFIDENTIAL | 81
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82. IORM in Action: Test 3 Implement
Category IORM Plan (DWPROD Intra-Database plan)
Create categories
Create CG and
assign to category
Map users
Specify CG
allocations
Activate plan
CONFIDENTIAL | 82
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83. IORM in Action: Test 3 Implement
Category IORM Plan (DWPRD Intra-Database plan)
CONFIDENTIAL | 83
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84. IORM in Action: Test 3 Implement
Category IORM Plan (VISX Intra-Database plan)
CONFIDENTIAL | 84
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85. IORM in Action: Test 3 Implement
Category IORM Plan (VISY Intra-Database plan)
CONFIDENTIAL | 85
2012 Centroid Systems, Inc. All rights reserved. Reproduction of this document or any portion thereof without prior written consent is prohibited.
86. IORM in Action: Test 3 Implement
Category IORM Plan
Null out previous DB plan
Category IORM
CONFIDENTIAL | 86
2012 Centroid Systems, Inc. All rights reserved. Reproduction of this document or any portion thereof without prior written consent is prohibited.
87. IORM in Action: Test 3 Validate
Category IORM Plan
CONFIDENTIAL | 87
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88. IORM in Action: Test 3 Validate
Category IORM Plan
Shows my categories
Consumer group mapping per DB
per Category
cellsrv.statedump summarizes
this well
CONFIDENTIAL | 88
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89. IORM in Action: Test 3 Load Test
Category IORM Plan
IO wait pattern:
CAT_HIGH < CAT_MEDIUM < CAT_LOW
Consumer group wait data similar during run
CONFIDENTIAL | 89
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90. IORM in Action: Test 3 Analyze
Category IORM Plan
IOsaturationtoolkit-v2 Results
VISX had 2 peak MB/sec throughput due to two
Relatively smooth distribution because we had a
CAT_HIGH mappings
mix of category mappings between databases
(and corresponding “elapsed” time valleys)
CONFIDENTIAL | 90
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91. IORM in Action: Test 3 Analyze
Category IORM Plan
CELLIORM.IORM_METRICS data
Let’s look at category
metrics first
CONFIDENTIAL | 91
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92. IORM in Action: Test 3 Analyze
Category IORM Plan
CELLIORM.IORM_METRICS data
CONFIDENTIAL | 92
2012 Centroid Systems, Inc. All rights reserved. Reproduction of this document or any portion thereof without prior written consent is prohibited.
93. IORM in Action: Test 3 Analyze
Category IORM Plan
CELLIORM.IORM_METRICS data
CONFIDENTIAL | 93
2012 Centroid Systems, Inc. All rights reserved. Reproduction of this document or any portion thereof without prior written consent is prohibited.
94. IORM in Action: Test 3 Analyze
Category IORM Plan
CELLIORM.IORM_METRICS data
CONFIDENTIAL | 94
2012 Centroid Systems, Inc. All rights reserved. Reproduction of this document or any portion thereof without prior written consent is prohibited.