10 Best Practices for Log Management and Analytics

10-best-practices-for-log-management-and-analytics

Introduction

Today’s Log Management and Analytics Challenges

Within the last decade, the advancement of distributed systems has introduced new complexities in managing log data. Today’s systems can include thousands of server instances or micro- service containers, each generating its own log data. With the rapid emergence and dominance of cloud-based systems, we have witnessed explosive growth in machine-generated log data. As a result, log management has become a staple in modern IT operations, supporting a number of use cases including debugging, production monitoring, performance monitoring, support and troubleshooting.

While distributed systems offer efficiency in terms of scalability, teams referring to log data can find themselves unsure of where to start or what level of effort would be required to even locate the needed log files. IT Administrators, devOps professionals and those closest to the systems producing logs are faced with the challenge of managing decentralized log files while adhering to security and compliance protocols. Developers and engineers who need to debug application-level issues can find themselves limited by their access to production-level log files. Operation, Devs, Data Scientists and Support teams who need insight into user-behavior for trend analysis and troubleshooting often lack the technical expertise sometimes required to leverage log data. Given these challenges, it’s crucial to consider best practices when implementing a logging solution for your organization.

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Posted in DevOps, Log Analysis, Log Management

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