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Oracle Autonomous Database is a family of self-driving, self-securing, and self-repairing cloud services. Autonomous Database supports a complex mix of high-performance transactions, including reporting, batch, Internet of Things (IoT), and machine learning in a single database. Although this simplifies application development, a dedicated, robust monitoring tool is necessary for the upkeep of the Autonomous Database, and to ensure optimal performance of its dependent applications. With Applications Manager's Oracle Cloud monitoring, you can:
Metrics related to Oracle database, cloud and cloud storage instances are crucial parameters that need to be scrutinized regularly. Tracking these metrics can help you understand how this database works and also diagnose any issues. Mission-critical transactional databases must not only be always available, they must also deliver excellent transaction throughput. Databases that support enterprise data warehouses can become massive in size, with very complex queries that are expected to be resolved quickly.
Applications Manager enables you to visualize key parameters like throughput, transactions, session details, and statement details which are presented in the dashboard. With this information, you can identify critical queries that increase latency and optimize the database intervals.
Easily understand errors related to database connections with details like failed logons per minute and failed connections per minute.
Monitoring tablespaces enable you to effectively track how the data grows in the Oracle database and ensure proper provisioning at the right time. With Applications Manager's Oracle Autonomous Database monitor, get extensive tablespace details like allocated blocks and bytes stats, table read and write stats, and information about the performance of datafiles.
Applications Manager's Oracle Autonomous Database monitoring software provides essential details about Oracle sessions like session Elapsed Time, CPU Time Used, Memory Sorts, Table Scans, Physical Reads, Logical Reads, Commits, Cursor, Buffer Cache Hit Ratio and many more. You can also track Oracle processes that are using PGA and the top 10 processes that consume maximum PGA. By tracking the Oracle sessions and processes, you will get an insight on how loaded an Oracle Database is.
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Monitor the performance and status of Oracle jobs which are scheduled by the Oracle Scheduler. Information about the status of jobs, last run status, last run duration, run count, and failure count are available at your disposal. This data can reveal a lot about your Oracle database's efficiency which is a key component in the Autonomous Database system.
Diagnose and debug errors faster. Easily pinpoint the source of the errors with root cause analyzer. In addition to this, you can also set up thresholds and anomaly profiles to recognize performance degradation. You can establish the baseline values as a percentage of a fixed baseline value, or opt for "Dynamic Baselining" where the data will be compared with the previous week. You can associate alerts and automated actions such as SMS/email alerts, and webhook actions to the thresholds to be sent and performed when the values deviate from ideal behavior.
With the trend analysis reports offered by Applications Manager, you can analyze the historical data of various metrics over a period of time. You can also make informed decisions regarding your resources with the help of forecast reports. These reports employ machine learning techniques to predict growth and utilization trends for up to three years in the future.
It allows us to track crucial metrics such as response times, resource utilization, error rates, and transaction performance. The real-time monitoring alerts promptly notify us of any issues or anomalies, enabling us to take immediate action.
Reviewer Role: Research and Development