Why Your Company Should Be Using Log Management Software

In today‘s complex and rapidly-changing IT environments, every system, application, and device generates a constant stream of log data. This machine-generated data contains a wealth of valuable information that can help organizations optimize performance, enhance security, ensure compliance, and deliver better software faster. However, attempting to collect, process, and analyze the massive volume, variety, and velocity of log data being generated across the enterprise is a monumental challenge.

That‘s where log management software comes into play. A log management solution automates and centralizes the process of aggregating, parsing, storing, and analyzing log data at scale. By providing a unified platform to ingest, search, visualize, and alert on logs from across the IT environment, log management tools enable organizations to extract actionable insights and value from their machine data more efficiently.

In this deep dive, we‘ll explore what log management software is, how it works, and why it‘s becoming an essential tool for modern IT operations. We‘ll examine common use cases and key capabilities to look for, as well as real-world examples of the benefits and ROI of log management. By the end, you‘ll have a clear understanding of why your company should be using log management software and how to get started.

What is Log Management Software?

At its core, log management software is a tool to help collect, process, and analyze the data generated by systems, applications, and devices in the form of log files or machine data. Every activity or event occurring in an IT environment – an application error, a configuration change, a user login, a network connection – generates a log entry recording what happened.

Log files are essential for understanding the behavior and health of systems and troubleshooting issues when they arise. Logs can also provide valuable data for security investigations, auditing user activity, and tracking KPIs and metrics.

However, the volume of log data generated in most organizations is staggering. Some key statistics highlighting the scale of log management challenge include:

• Companies manage an average of 6 TB of log data per month (Source)
• A single enterprise server generates over 1 GB of log data per day (Source)
• The average organization sees over 10,000 security events per second (Source)

Trying to manage this volume of log data manually is simply not feasible. Teams waste hours or days trying to track down the log entries they need to investigate an issue. Critical events get lost in the noise of routine log messages. Logs in different formats and locations make it difficult to see the full picture.

Log management software solves these challenges by automating the repetitive aspects of log management and providing a centralized system to handle log data at scale. A typical log management solution will perform the following key functions:

1. Collection: Gather log data from all the various sources across the environment – servers, containers, applications, databases, network devices, security tools, cloud platforms, etc. This is done through a combination of agent-based and agentless methods.

2. Processing: Parse the raw log data to extract key fields, normalize different formats, and enrich logs with additional context (e.g. GeoIP info, user details). Logs are typically compressed and encrypted at this stage as well.

3. Storage: Securely store the processed log data in a centralized, indexed repository. This is often a purpose-built NoSQL database or distributed storage system optimized for storing and searching large volumes of semi-structured log data.

4. Analysis: Provide tools to search, filter, visualize, and analyze the aggregated log data. This includes dashboards, reports, alerts, and ad-hoc querying capabilities to help users discover trends, patterns, anomalies, and insights.

5. Retention: Automatically manage the retention and archival of log data to meet compliance, security, and operational requirements. Logs can be tiered to different storage layers or deleted after a specified period.

By handling these core log management functions, log management software enables organizations to spend less time wrestling with log data and more time extracting value from it. Instead of logs being an administrative headache, they become a strategic asset that drives faster problem-solving, better decision making, and continuous improvement.

How Does Log Management Software Work?

To dive a little deeper into the inner workings of log management software, let‘s walk through how a typical log message flows through the system.

1. Log Generation: An event occurs – say a user authenticates to a web application. This activity is recorded as a log entry containing key metadata (timestamp, severity, etc.) along with a message describing what occurred. The application writes this log locally to a file on disk.

2. Log Collection: A logging agent running on the application server detects the new log entry and forwards it to the log management system. The agent handles buffering data to account for network latency and potential outages in the log management stack. Most log shippers support multiple protocols (e.g. syslog, HTTP/S) and can tail log files, listen on ports, or make API calls to pull in log data.

3. Log Ingestion: The log management system receives the raw log data from the agent. An ingestion pipeline validates the data, applies any specified parsing rules or transformations, and writes the normalized log data to a central repository. Parsing and schema enforcement is key to enable effective querying and analysis later.

4. Log Indexing: To make log data searchable in real-time, the log management system indexes the relevant fields extracted during ingestion. Indexes are typically optimized for full text search and filtering on structured fields. Logs can be enriched with additional metadata to provide valuable context.

5. Log Storage: Indexed log data is written to a distributed storage system designed for fast, scalable log management. Many solutions leverage a NoSQL database like Elasticsearch or Cassandra that can scale horizontally while providing powerful search and aggregation capabilities. Data is automatically sharded and replicated across a cluster of nodes for high availability and fast query performance.

6. Log Analysis: Users interact with the log data through a web interface that provides a variety of real-time dashboards, reports, search tools, and visualization options. Alerts can be configured to automatically notify teams when specific conditions are detected in the log stream (e.g error rates exceed a threshold). Many log management solutions also provide a CLI and REST API for programmatic interaction and integration with other tools.

7. Log Retention: As log data ages, the system automatically manages retention and archiving based on predefined policies. Older data may be moved to cheaper storage tiers or deleted entirely after a certain period. Retention policies help manage costs while ensuring data is preserved as needed for compliance, security, or analytical purposes.

Throughout this process, the log management system handles the heavy lifting of log data – collection, parsing, indexing, storage, and retrieval – in a secure, resilient, and scalable way. The end result is a centralized log repository and analytics engine that teams can leverage to extract valuable insights from their machine data more efficiently.

Why Use Log Management Software? Key Benefits and Use Cases

With an understanding of what log management software is and how it works, let‘s explore some of the key benefits and common use cases.

Improving IT Operations and Performance

One of the primary use cases for log management is enhancing IT operations. Centralized logging gives you a single pane of glass to monitor the health and performance of your entire environment – from the underlying infrastructure to individual applications and services. With real-time visibility into system behavior and centralized access to diagnostic data, IT teams can:

• Accelerate troubleshooting and root cause analysis
• Proactively identify and resolve issues before they impact users
• Optimize resource utilization and capacity planning
• Perform post-incident reviews and establish KPIs/SLAs
• Reduce MTTR (Mean Time to Resolution) and minimize downtime

For example, Sumo Logic (a cloud-based log management solution) reports that their customers see a 67% reduction in downtime on average. By leveraging machine learning to identify anomalies across system and application logs in real-time, IT teams can detect and resolve issues much faster. Log insights also help teams make data-driven decisions to optimize performance and user experience.

Enhancing Security and Compliance

Log data is also critical for security and compliance purposes. As the volume and sophistication of cyber threats continues to grow, organizations need an effective way to detect, investigate, and respond to potential security incidents. Log management software provides the foundation for security monitoring and threat hunting by:

• Enabling real-time alerting on suspicious activity
• Providing a forensic audit trail for incident investigations
• Facilitating reporting and evidence gathering for compliance audits
• Supporting threat detection and investigation through centralized searching and correlation

According to the 2019 SANS SOC Survey, organizations using a centralized logging system identified 66% more threats than those without one. By collecting and analyzing logs from across the enterprise, security teams can identify potential indicators of compromise, investigate incidents more efficiently, and respond faster to contain threats and limit damage.

Centralized logging is also essential for meeting a variety of regulatory compliance requirements – from PCI DSS and HIPAA to SOX, GDPR, and more. Many regulations explicitly require log collection and retention as an audit trail. With a log management system, you can ensure comprehensive visibility, streamline compliance workflows, and demonstrate due diligence to auditors and stakeholders.

Accelerating Software Development and Troubleshooting

Log management is equally valuable for application development and support teams. Developers rely on application logs to understand how code is executing in production, troubleshoot bugs, and analyze performance issues. Log management software empowers DevOps teams to:

• Centralize application logs across distributed environments
• Trace transactions and identify bottlenecks
• Troubleshoot errors and exceptions at scale
• Analyze user behavior and application usage patterns
• Measure release quality and track KPIs

For example, CCP Games (maker of popular MMO Eve Online) uses Logentries to monitor over 100 different services and 4,500 game server instances. By centralizing 50 GB of log data per day, their DevOps team can quickly identify issues impacting game performance and resolve them before they affect players. Consolidated logs also help them analyze game data to inform new features and optimization.

Evaluating Log Management Solutions

As the importance of log management has grown, so has the market for log management software. From open source tools to enterprise-grade cloud services, there are a variety of solutions available to fit different needs and budgets. When evaluating log management platforms, here are some key capabilities and considerations to keep in mind:

• Comprehensive log collection from all relevant sources
• Scalable ingestion pipeline to handle high-volume, high-velocity log data
• Powerful, flexible search and alerting capabilities
• User-friendly analysis tools and visualizations
• Integration with key security and observability tools
• Automated and customizable parsing to extract value from logs
• Secure multi-tenant architecture and granular access controls
• Retention and archiving features to meet compliance needs
• Extensibility and ability to support custom use cases

The build vs. buy decision is also an important factor. Open source tools like the ELK stack (Elasticsearch, Logstash, Kibana) are popular choices for those with the technical resources to deploy and manage them. Commercial solutions provide an out-of-the-box experience with additional features, scalability, and support. Ultimately, the right choice depends on your specific requirements, in-house expertise, and budget.

Real-World ROI and Case Studies

To further illustrate the value of log management software for organizations of all types and sizes, here are a few real-world examples and case studies:

• Salesforce processes over 2.3 billion log events per day across its SaaS applications. They built a custom streaming log management system called LogStream that enables them to ingest, analyze, and act on this data in real-time. With LogStream, Salesforce has reduced MTTR by 80%, sped up debugging by 92%, and scaled to support over 150,000 users. (Source)

• GE Digital ingests over 1 TB of log data per day from their Industrial IoT platform. They use Sumo Logic‘s cloud-based log management solution to centralize and analyze this data for improved operations and security. With Sumo Logic, GE Digital has reduced issue resolution time by 50%, increased operational efficiency by 33%, and improved application quality. (Source)

• Aspen Skiing Company relies on log management to monitor and troubleshoot their business-critical resort and lodging systems. They use Splunk to ingest and analyze logs from a wide range of sources – applications, servers, network gear, ski lifts, snow making equipment, etc. Centralized logging has helped Aspen reduce unplanned outages by 92%, speed up troubleshooting by 60-80%, and improve end user experience for over 1.4 million guests annually. (Source)

These are just a few examples among thousands that demonstrate the tangible benefits and ROI of log management software. From improving system reliability and security to enhancing customer experience and decision making, log management provides the foundation for data-driven IT operations.

Conclusion

As the IT landscape continues to grow more complex and dynamic, effective log management is no longer just a nice-to-have – it‘s a necessity. Log data contains a wealth of valuable insights that can help your organization optimize performance, strengthen security, ensure compliance, and deliver better services. But to capture this value, you need a scalable, secure, and efficient way to collect, process, and analyze log data across the enterprise.

That‘s where log management software comes in. By providing a unified platform for aggregating, storing, and analyzing log data at scale, log management tools enable you to solve a wide range of IT challenges – from troubleshooting and root cause analysis to threat detection, compliance reporting, and application monitoring.

If your organization isn‘t leveraging a log management solution today, you‘re likely spending too much time and effort wrestling with log data and not enough extracting value and insights from it. As the volume, variety, and velocity of machine data continues to grow, investing in log management software is becoming a key IT imperative.

Of course, log management software is not a silver bullet. To be successful, you need to choose the right solution for your needs, implement it effectively, and build the right processes and skillsets to leverage it on a daily basis. But the effort is well worth it. By harnessing the power of your log data, you can improve service levels, reduce operational costs, and make faster, better decisions.

So if you haven‘t already, it‘s time to take the next step in your data-driven journey by adopting log management software. Your systems – and your customers – will thank you.