Presented at INSYNC 21

Session ID: 100490

Over the years, we have been following certain Oracle Database best practices which helped us to utilize database resources efficiently and run things smoothly minimizing unexpected downtimes. It is also important to use correct tools and techniques to quickly analyze and address any performance problems in the database. In this session, I'll talk about different database performance best practices we follow for SaaS application databases as far as development and DBA teams are concerned. Along with that, would like to share Oracle Database tuning tools and techniques we found most effective to resolve database performance problems as situation demands.

Presented at INSYNC 21

Session ID: 101400

This session focuses on how Oracle is applying Machine Learning technologies in Oracle to prevent performance issues and maintain availability. Autonomous Health architectures and algorithms are covered for both Autonomous Database and on-premise deployments. Deep dive use cases detail their use to proactively detect performance degradation through the phases of detection, root-cause analysis and targeted corrective actions. Actual use cases protecting session, database instances, nodes and storage are presented. Next, diagnostic use cases for rapid recovery monitoring configurations, log and trace files where analysis is based upon anomalous events and record signatures. The final section will cover integration into DevOps processes.

Presented at INSYNC 21

Session ID: 100980

The Latest Persistent Memory such as Intel Optane Persistent Memory (PMEM) combines near-DRAM performance with the data persistence of storage. It can be configured in memory mode or application direct mode.  When the memory mode is used, PMEMs can be considered as volatile and can be used as main memory and DRAM is treated as a write-back cache. PMEMs can also be configured in application direct mode to store database files and redo logs. This presentation will discuss the use cases of PMEM:1)  In memory mode use PMEMs for Oracle In Memory store ;2) in Application direct  mode to store the database files, namely persistent Memory Database in  Oracle 21c. We will discuss the significant performance benefits that can be achieved from either of these two modes. We will discuss the Persistent Memory Database feature that includes directly mapped buffer cache and Persistent Memory Filestore (PMEM Filestore) in Oracle 21c. We will also discuss how PMEMs are used in Oracle Exadata X8M.

Presented at Quest Experience Week (QXW) – Database & Technology Day

Imagine managing your Oracle environment with a unified database operating model while delivering simplicity, performance, availability, and security across private and public clouds. Gone are the late-night outage fire drills and the long hours troubleshooting strange performance issues. Nutanix eliminates database management complexity by up to 90% so that organizations can accelerate time to market by as much as 8X.

Learn how to keep your business running with near-zero downtime and still reduce DBA off-hour workload by as much as 50%. Regardless of where your database resides, find out how Nutanix can save you time and transform you into a business driver.

Presented at Quest Experience Week (QXW) – Database & Technology Day

You think you have seen it all… and then you see something new. I have studied literally hundreds of AWR reports and thought through thousands of performance scenarios. While I know how to use an AWR or Statspack report to analyze Oracle performance, I have also learned how to totally mess-up the analysis. There are some obvious ways to totally invalidate your analysis. But there are also some subtle mess-ups that fool you into thinking your time-based analysis is rock solid…yet it’s worthless and probably misleading. Join me for a light-hearted session as we explore what NOT to do.

Presented at Quest Experience Week (QXW) – Database & Technology Day

One of the most critical aspects of building effective systems is the successful management of unstructured/semi-structured information. The database is no longer only a place to store dollars and cents for the purposes of accounting. Efficient manipulation of JSON has become one of the most critical elements of contemporary database infrastructure. Even though you can store JSON documents in VARCHAR2 columns, in reality, you will quickly outgrow VARCHAR2 size limitations and will have to switch to LOBs for storage. However, few people in the development community really understand the underlying mechanics of Oracle LOB datatypes and consider it yet another DBA issue. This presentation attempts to fill that knowledge gap.

Presented at Quest Experience Week (QXW) - Database & Technology Day

Tired of continuously adjusting your performance monitoring and alerting rules? How about using machine learning to create the rules instead! Sure, we can train a supervised ML model to recognize patterns of poor performance. But what if your IT department is not ready to embrace it?

A novel solution is to train a supervised machine learning model to recognize patterns of poor performance, but then extract the rules in plain English and then manually enter them into your existing monitoring and alerting platform. Is this possible? Yes, it is! And, I will demonstrate how you can do this.

To ensure you can easily do everything I do, I will use industry-standard Python ML libraries, the industry-standard Jupyter notebook, AWR, and support ticket data. You can experiment with the demonstration materials “as is” and then use them to push your ML and rule creation knowledge deeper.

Quest Forum Digital Event 2020

This presentation will provide insight into How a DBA can help Tune the PeopleSoft (PSoft) Applications of PeopleTools, HCM & CRM.  There are rather unique opportunities how PSoft works, and how the Oracle RDBMS may impact performance. The DBA team leveraged their expertise in SQl*Plus, Sql*Developer, OEM & Diagnostic Performance Tuning to provide tuning assistance to the PSoft Application Team, and their long-running processes (SQL).