Log Analytics

IT systems continually generate log files that contain timestamped events. Log analytics interrogates these files to visualize activity, discover anomalies, and analyze the root causes of issues.

Why it is Important

When IT systems fail, support staff investigate log files to see what anomaly caused the failure. Without analyzing these log files, the root cause analysis would be more challenging, historical trends would be harder to visualize, and transparency for audit purposes would be difficult.

Examples

Website Log Analytics

Website analytics allows businesses to analyze website visits, including the number of visitors, number of unique visitors, visit duration, number of page views, domains/countries of origin of visitors, most viewed, entry and exit pages, and more.

Network Log Analytics

Network analytics can show traffic volumes and sources of potential attacks, such as denial of service. Analytics can show where investment might be required for local mirror sites to improve the response time for distant customers and where large user populations are clustered.

Storage Log Analytics

Data storage on spinning disks and solid-state devices is subject to failure. Manufacturers build in some redundant capacity to handle corrupted storage blocks. Storage arrays and memory management systems create diagnostic logs for maintenance. Log analysis uncovers soft and hard failure rates so proactive maintenance can be scheduled, and the device can be gracefully retired without impacting users.

Security Log Analytics

Security analytics provides accurate, centralized reporting of application usage and growth over time. Failed login attempts help to identify potential security attacks and block malicious IP address ranges.

Application Log Analytics

Application log analytics is critical for maintaining the health of software applications. Applications logs contain information about errors, warnings, user interactions, performance, and other relevant information. Analyzing this data identifies issues such as performance bottlenecks, security threats, and application errors.

Internet of Things (Iot) Log Analytics

IoT log analytics provides insights from the vast amount of log data generated by IoT devices and systems. IoT devices often include sensors and components that continuously generate event logs. Analyzing this data helps to identify when a device is about to break down or degrade in performance so it can be repaired before the issue causes downtime.

Database Log Analytics

A transaction log records all database transactions and database modifications. Analyzing these logs provides valuable information about the database’s performance, security, and compliance. Database log analytics solutions typically provide alerts and reports when predefined conditions occur or when thresholds are met, enabling timely responses to critical issues.

Benefits

Below are some of the benefits:

• Log analysis can uncover changes to data that traditional monitoring tools can miss.
• It prevents system and application downtime by proactively monitoring for potential problems.
• IT administration costs are reduced as analytic systems can troubleshoot failures faster. This also improves Mean Time to Resolution (MTTR), an important SLA metric.
• Security is improved through improved monitoring of threat activity.
• Marketing benefits from real-time web activity knowledge so sales can act as prospects navigate the company website.

Actian

The Actian Data Platform provides a cloud-based analytics solution. The Actian platform includes a high-performance vector processing columnar database and a data integration service. Log data can be loaded into the Vector database or accessed in an external repository using SQL. Analytics can run on-premises and on cloud and hybrid cloud platforms, including AWS, Google Cloud and Microsoft Azure. Log files can be file-based and stream-based from sources, including JMS, Kafka, MSMQ, RabbitMQ, and WebSphere MQ.