Operations Insights' Exadata Warehouse for simplifying Exadata capacity planning and forecasting

September 28, 2022 | 5 minute read
Sriram Vrinda
Director of Product Management
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This blog introduces the new support for Exadata Warehouse in Oracle Cloud Infrastructure (OCI) Operations Insights for Oracle Engineered Systems like Exadata Database Machine and Zero Data Loss Recovery Appliance (ZDLRA) monitored via Oracle Enterprise Manager (EM). It provides a platform for long-term retention of fine-grained historical and forecast data for performance and capacity analysis and planning.

Exadata Warehouse features in OCI Operations Insights enable analysis for informed data-driven decisions

The OCI Operations Insights service enables business executives, database administrators, and DevOps personnel to make informed, data-driven decisions on compute resource and performance management related issues.

Capabilities of Operations Insights’ Exadata Warehouse:

  • Analyze resource usage for databases running on on-premises Exadata platforms across the enterprise 
  • Forecast future demand for resources based on historical trends

With the introduction of Exadata Warehouse, resource utilization of the Exadata systems can be analyzed to identify spare capacity for new workloads. This feature is available for Exadata systems that are managed by Oracle Enterprise Manager (EM) 13c Release 5 Update 7 (13.5.0.7) and above. The use of Exadata Warehouse features requires OCI Operations Insights service license subscription. 

Oracle EM allows Operations Insights' Exadata Warehouse to easily utilize target-level data managed by EM. EM enables the transfer of data from EM targets and Oracle Management Repository (OMR) to OCI Object Storage, where it is easily accessed by one or more cloud-native services such as Operations Insights and Logging Analytics.

Once OCI connectivity is set up, the target data is automatically uploaded at frequent intervals to Object Storage so that OCI cloud services are always working with the most recent target data.

Enterprise Manager diagram
Figure 1:  Oracle Enterprise Manager and Exadata Warehouse Integration Flow

Key functionality of fine-grained metric ingestion and forecasting

  • Ingest metrics to customer-owned Autonomous Databases in their tenancy
  • Machine learning seasonality models
  • Fine-grained metric data with per-minute granularity: Collects data by minutes granularity, covering 1,440 data point per metric/key
  • Backfill metric data to accommodate periods where monitoring of Exadata is interrupted 
  • Automated forecasts and roll-ups, updated periodically 
  • Generate quick forecasts with 30 days of historical data  
  • Forecast data for the next 3 months by analyzing 9 months of historical data for better accuracy

Data retention settings:

  • Fine-grained metric data - 13 months max
  • Hourly rollup metric data - 4 years max
  • Daily rollup metric data: 7 years max
  • Custom configuration

Key Exadata capacity planning questions that Exadata Warehouse can help answer

  • What is my current resource utilization?
  • What is my Compute Node CPU/Memory utilization?
  • Am I hitting the Hard/Flash Disk IO limit?
  • What about Cell Node CPU utilization?

Exadata Warehouse collects metrics from ASM Cluster, Exadata Storage Server and Exadata Compute Nodes and provides coverage for the areas below:

  • CPU/vCPU and Memory consumption
  • Storage Utilization
  • IO Capacity, utilization and performance 
  • Network performance 

Top metrics collected by Exadata warehouse:

ASM Cluster

Exadata Storage Server

Exadata Compute Nodes

   Disk Group 

  • Total Size
  • Usable Size 
  • Free Size
  • Used percentage

   Sparse Disk Group 

  • Free Size
  • Total Size
  • Large Read/Write Throughput
  • Small Read/Write Throughput
  • I/O Load
  • Average Large Read/Write Response Time
  • I/O Utilization
  • Flash Cache Size
  • Read Throughput Redirected to Disk for Scan
  • Read IOPS for Random I/O
  • CPU Utilization
  • Memory Utilization
  • Network Read Rate
  • Network Write Rate

Key Exadata Warehouse Capacity Planning and Forecasting Use Cases

Detect “noisy-neighbor” target problems scenario:

Typically, in a shared resource host environment, CPUs are over-allocated across databases. This assumes that not all DBs will fully utilize allocated resources at the same time. Noisy neighbor issue(s) occur when load increases and one neighbor hogs all the shared resources.

Goal:  Fleet view of hosts correlating performance and configuration data and highlight the problematic targets.

Exadata Warehouse can help with enterprise-wide analysis of resource utilization and capacity planning for Exadata:

  • Plotting trends and forecasts for Exadatas with Top CPU Utilization
  • Spotting Exadata systems with most under-utilized IOPS
  • Forecasting Exadata systems to reach storage limit
  • Forecasting resource utilization trends
  • Automatic prediction of near-term issues 

Trend and forecast IOPS utilization:

Track and trend the throughput usage and utilization percentage and plot the latency and Flash Input Output Resource Manager (IORM) waits to answer:

  • How much I/O is each database generating?
  • Are the I/Os from flash or disk?
  • How much did IORM throttle the I/Os?

The Exadata Warehouse data can be visualized to build reports in Oracle Analytics Cloud and interpret the workload distribution and basis which can be chosen to change an IORM strategy.

Conclusion

Operations Insights integrates with Oracle EM and simplifies onboarding for existing customers using automated collection of EM data and advanced analytics for EM targets. Exadata Warehouse for EM-managed systems aids in consolidation and troubleshooting.

Sign up for an Oracle Cloud Infrastructure trial account!

For more information about this feature and how to use it, see the documentation.

Sriram Vrinda

Director of Product Management

Sriram Vrinda is an experienced Product Manager with a demonstrated history of working in the information technology and services industry. Strong product management professional skilled in Oracle Database, Autonomous Databases, MySQL Databases, IT Service Management, Solution Architect, and Pre-sales. He has helped various customers with Oracle solutions specifically around performance, availability, and scalability aspects for about 20 years.