Enterprise IT professionals struggle to make their IT environments stable enough to meet business SLAs, and yet agile enough to support rapid business change. To succeed, they need to analyze the millions of logs that describe how applications, devices, clouds, networks, and containers all work together.

Log analytics drive the success of three inter-related disciplines: ITOps, the implementation, management, and monitoring of IT infrastructure; DevOps, the development, testing, release, monitoring, and management of applications; and CloudOps, which combines ITOps and DevOps for cloud environments.

With an effective log analytics product, ITOps, DevOps, and CloudOps engineers can help enterprises boost efficiency and gain competitive advantage.

This report recommends five criteria for ops engineers and their managers to evaluate log analytics products:

1. Ease of use: your log analytics product should make ops engineers’ jobs easier by reducing the time and effort required to make sense of logs.

2. Analytical flexibility: Your product should support search and query capabilities and granular sorting for both batch and streaming log data.

3. Performance and scalability: It should analyze high volumes of logs in a time frame that meets your latency and throughput SLAs while keeping compute costs within budget.

4. Support for an open architecture. It should integrate with a wide range of log sources, data stores, formats, APIs, drivers, visualization tools, and workflow tools with minimal effort.

5. Governance capabilities. It should minimize data copies to assist data quality, protect PII with features such as role-based access controls, and audit activities to assist compliance efforts.

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