Across the technology and IT infrastructure domain, log files are recognized as often time-stamped files that can virtually record all critical information about events occurring within the purview of your IT network, OS, or other software applications. Some log files are humanly interpretable, while others are largely meant for machines to consume. With the wide spectrum of use-cases, log files are often categorized into audit logs, transaction logs, customers, logs, message logs, logs for errors or events, and so on.
Log files can shrink the lead time taken to garner insights about an event and make the RCA process more efficient. While the value of log files is irrefutable, extracting that value becomes challenging as the costs scale. Networks and platforms that process a high degree of log files can skew a significant proportion of your overall budget and create a variance in these costs as the log file throughputs are not consistent. Even after incurring the costs, you may end up with log files that carry idiosyncratic value in very specific use-cases.
A Rule-Based Approach to Log Management
Formulating and implementing log management policies can optimize resource allocation across the IT network. Beyond that, there are well-defined dimensions on which the idea of log management rests. One dimension focuses on the exploratory nature where vulnerabilities between connected devices, cloud platforms, and distributed systems can be filtered and flagged in time.
The other dimension focuses on sharpening the network’s performance by ensuring consistent uptime. To achieve these security and system reliability goals, IT network management professionals need thoughtful log management policies in place. The critical questions that can help in creating substantially effective log management policies revolve around:
- What is the storage alternative that provides optimal resource consumption against its value proposition?
- What should be the ideal tenure of a log file existing within varied storage channels governed by different authorization, security, and accessibility rules?
- Is there a categorical form of the log required only in very specific situations and otherwise unnecessary?
- Which are the categories of log files that are largely homogenous, and hence a sample can serve the same value as the entire set of files?
Log Management Policies for Network Efficiency
1. Log File Forwarders to Centralized Log Management
A log forwarder should become the central unit of your log management system. This will give your team greater control, easier accessibility, and the perspective to optimize log files as per the allocated budget by handling throughput.
Under this system of operating, enterprise applications will produce log files in the local systems, and the forwarder will extend the log files to conduct analytics. All the compression takes place at the forwarder level with its ability to resend the files. This frees up space for your core application to operate in an undisturbed and yet managed environment.
The same log file forwarder can act as your go-to backup solution in case of systemic failure. If the system breaks down, as soon as it restarts, the forwarder can send the files. This reduces your dependencies on the system’s uptime for sending critical log files.
2. Creating Guidelines for Access and Notifications
Most log files come under two categories of logging processes – the one responsible for sending the entries and the other one responsible for pulling the entries out. When log entries are being sent, there should be established guidance on the level of loggings available and what level is appropriate for which use-case.
Sending out large amounts of information can result in noisy data and sub-optimal resource consumption. So, on the receiving-end of the logging data, system security and IT operations take the preferred position. Authorization of sensitive data in the log files can be misused for posing threats to the entire system. Hence, the log policies on notification should focus entirely on one question – who is notified about what, when, and how?
3. Compliance Ensured for Log Data Collection
The log data should collect information in a manner that satisfies the guidelines established under PCI DSS, FISMA, SOX, HIPAA, and other policies relevant to the business requirements specified. Reports that entail the information showcasing compliance must be easily created.
4. Go for Virtually Limitless Log Data Storage
Sometimes, during ingestion, it can become inefficient from a cost and process perspective to filter log data at an early stage since there are no substantial indicators showing which log file will be usable for the given IT challenges. The platform should be engineered to solve this issue by allowing you to store terabytes of log data daily. Once you have the data in one place, you can create indexing rules to prioritize your use-cases’ log files.
5. Create Adaptive Indexing Policies
If your system is dynamic and can have varied exposure to potential risks, your log files should not be indexed statically. This means that when your system shows an error or you have a critical challenge at hand, you should not be going through burdensome server-side filtering policies. The platform allows you to override indexing policies easily, which can save a lot of time in the instance of a just-discovered urgency.
6. A Log Management Platform Calibrated for Optimal Performance
Motadata’s Log Management Solution has the ability to collect, aggregate, and intelligently index all the log data irrespective of its format. This way, you are storing data interpretable to humans as well as the one generated by machines, in a structured or unstructured format. With the rich Data Analytics capabilities on the same platform, you can perform correlation analysis studies to efficiently gather reports on operational and security risks.
Alongside this, the Network Flow Analytics module helps in monitoring all the traffic between connected devices in the network that supports NetFlow V5 & V9, sFlow, IPFIX, and other layouts. You can leverage this flow data to garner insights on bottlenecks in the IT network based on trends in traffic and critical interactions between users or applications. You can easily adhere to high compliance standards like PCI DSS, FISMA, and HIPAA.
Leveraging its comprehensive data collection & aggregation capabilities, alongside intelligent indexing and a fluid search interface, your IT teams can use the Motadata Log Management to systematically optimize log file practices in your firm while adhering to the highest standards of compliance and operational efficiency.