Log management: the key to reliable and secure applications

Companies have more data than ever before, and the amount of information they collect and store grows daily. Organizations increasingly rely on cloud solutions to power their business. Gartner estimates that by 2025, over half of IT spending in the application software, business process services, infrastructure software and system infrastructure markets will shift from traditional to public cloud solutions.

This change offers cloud-native SaaS organizations — and those undergoing digital transformation — an exciting opportunity to drive conversions and growth. Competition will be stiff, with the SaaS industry expected to grow at a compound annual growth rate (CAGR) of 11.7% between 2020 and 2026. For cloud-based SaaS organizations, these numbers present a few challenges:

• How do you ensure a highly reliable and secure digital experience for your customers?

• How do you reduce the effort to monitor, secure and optimize your applications in real time?

• How do you troubleshoot errors and reduce mean time to repair (MTTR) in order to maximize customer satisfaction and minimize potential churn?

• How do you leverage data to strengthen performance and improve your security posture?

Log management is a critical piece of the solution. But as companies increasingly rely on cloud applications, what is log management and why is it important? In this ultimate guide to log management, we explore:

• What is meant by terms like log management and centralized logging?

• How can log management improve observability and security?

• What is log analysis, and how can it superpower your operations?

• What are logging and monitoring best practices?

• What capabilities do the best log management tools and log analytics tools have?

Log management refers to a system or practice that allows organizations to process the massive amounts of computer-generated log events (or logs) created on a daily basis. These log files play a critical role in telling DevOps and security teams whether systems are performing as expected or were compromised and what might be causing the issues that occurred.

Especially for organizations that operate in a predominantly digital space, log management is an essential component of both observability and security — not to mention the ability to provide an outstanding digital customer experience for users. We’ll expand on these topics later, but first, let’s dive into more detail about logs, log management, log analytics and other key terms.

What are logs?

Logs are time-stamped digital records of actions and events that occur within a technology stack or IT infrastructure. They are generated from:

• Applications

• Application infrastructure

• Cloud infrastructure

• Containers

• Load balancers

• Message bus (Kafka)

• Networks

• Servers

Logs are essentially notes that developers leave for their future selves — similar to how you might leave a trail of breadcrumbs to mark where you’ve been. The data logs provide visibility into how an application is behaving at any given moment in time. They include data points like:

• Timestamp

• Host name

• Process type

• Log type

• Application

• Action

• TCP (Transmission Control Protocol) socket status

Why does this matter? Technical teams deal with a lot of surprises, from application slow downs to outages to security threats and so much more. Imagine receiving a security or outage alert without any additional context. Without logs, organizations don’t have the information they need to understand the chain of events that transpired, which could spell disaster.

With logs, organizations see data about infrastructure performance, availability, user access and behavior. The security alert mentioned above may be from a log showing a single user trying to log in from 50 different locations with several different IP addresses — a potential hack. Logs give DevOps and security teams the data they need to resolve the issue as efficiently as possible.

What is log management?

Log management addresses every aspect of log data. A log management system empowers businesses to centrally collect, parse, analyze, store and archive their log data.

Log management allows teams to monitor and improve system performance, quickly identify issues and bugs and bolster security across an enterprise’s entire system. Logs and log data are the foundation of effective troubleshooting for application and service reliability and security.

As digital companies generate more logs, a log management system quickly becomes mission-critical. Corporations are now dealing with petabytes of log files, not to mention all of their other data. Unsurprisingly, this data is only expected to grow; some estimates indicate that globally, data is expected to more than double between 2022 and 2026. A robust log management practice is the best way to store and analyze logs, ensuring optimal network and application observability and security.

What is centralized logging?

Centralized logging is a process that organizations use to collect and aggregate all of their logs from disparate systems and tools into a single location. Before the cloud, organizations typically stored and managed their data in data centers or on-premises servers. While these were workable solutions, they were limited in terms of capabilities like accessibility, scalability and convenience.

With centralized logging tools, organizations can improve operational efficiency by eliminating potential data silos and relying on cloud principles to offer increased scalability, accessibility and convenience. They can achieve a single source of truth for their logs while improving their ability to solve performance, availability and security issues.

What is a log management tool?

A log management tool is a software or platform that assists teams in doing some or all of their log management processes and procedures. Log management tools are increasingly important—especially for businesses building and/or running modern applications in the cloud — due to the huge increase in log data volume and the sheer number of applications and tools in an organization’s tech stack.

The best log management tools cover the entire log management process from start to finish, eliminating data silos and the need for duplicative IT tools. An end-to-end platform helps teams maintain information about their logs, data, system alerts, performance and more from a single pane of glass.

What’s more, with tools like Sumo Logic, which provides log management and analytics for reliability and security use cases, organizations can operate from a single source of truth on one platform. We’ll discuss our platform, which aims to make the world’s applications reliable and secure, later in this article. First, let’s dive into the log management process, why it matters and how log analytics can be a game changer for organizations.

When it comes to log management, every organization has its own specific policies and procedures based on its unique needs as well as any rules or regulations specific to its industry. Generally, there are five basic steps in the log management process.

1. Instrument and collect

As we’ve discussed, logs come from a number of different systems and applications, such as operating systems, software applications, cloud infrastructure, network devices and more. Before anything else in the log management process can be done, you must first collect your data from these disparate locations. A log collector allows you to ingest this data from any part of your tech stack. This process can be performed by a Syslog or applications writing the logs into the log management system via hypertext transfer protocol (HTTP).

Once the data is collected, it may require parsing. Log parsing means extracting templates and parameters to better interpret the logs. Not all log management tools support parsing of every type of log file, which may require you to develop your own custom parsers. Log management and analytics solutions like Sumo Logic allow you to extract fields from log messages, regardless of their format. Incorporating schema-on-read will expedite the process as you will not be required to pre-parse a log before it’s ingested into the log management system.

2. Centralize and index

In the second step, you will aggregate, normalize and index your logs into a single location to increase access and visibility across the entire application environment and IT infrastructure. Because organizations—especially those that operate in cloud environments—deploy a large number of applications and other infrastructure, having logs centralized in a single location is critical to security, operations and reliability.

By following centralized logging best practices like this, your DevOps and security teams will no longer have to jump between environments to group logs from different systems. Instead, they will be fully searchable in one place to improve the efficiency of developers and security analysts. At Sumo Logic, our cloud-native SaaS analytics platform offers top-tier log aggregation and log parsing capabilities, all with the ability to collect logs from almost any source to offer end-to-end log management and analytics functionality.

3. Search/query and analyze

Once aggregation is complete, DevOps teams, developers and security analysts can access, search and analyze the log data. This is where the magic happens. Traditionally, log search and analysis relied on running queries across silos of data. However, as log data scales, operating within silos is cumbersome at best. With cloud-native log management and analytics solutions like Sumo Logic, you can instead integrate with several environments using IIS web servers, NGINX and others to improve the log analysis process.

4. Monitor and alert

Along with analytics, monitoring is another vital component that benefits from a proper log management process. As we touched on previously, information from log files is used in a variety of ways. One such way is to monitor system performance for errors, anomalies or security breaches, which helps ensure greater reliability and security for your users.

Using the data collected and analyzed, IT teams can develop rules and alerts for various occurrences to notify the right people immediately if an issue arises, significantly increasing operational efficiency. You can even integrate with collaboration software like Jira, Slack and PagerDuty to alert users in the platforms they’re already using.

5. Report and dashboard

Finally, any organization knows that the ability to visualize and report data points and metrics for operational needs to business stakeholders and key decision-makers is critical. This information makes it quicker and easier to identify trends or anomalies in performance. Not only does this ensure that everyone — including individuals inside and outside the IT team — is on the same page regarding data and performance, it also empowers better business decisions at every stage.

At a high level, log analytics helps teams review, interpret and understand logs. Technical teams use log analytics to organize and extract various information from their centralized logs to improve business functions across the board. On a more granular level, log analytics is critical for monitoring, troubleshooting and investigating reliability and security issues. It gets down to the root cause of why that issue occurred. Log data is often the most detailed information available for a company’s systems. Using analysis to make sense of all that data is just plain smart.

What are the benefits of log management and log analytics?

Here are five critical benefits organizations can realize from leveraging log analysis.

• Log analytics leads to better root cause analysis, troubleshooting and reduced MTTR. Each of these minimizes downtime and performance issues, which is important for an excellent customer experience and reduced churn.

• Log analytics allows organizations to better monitor their cyber security posture and make their assets more secure. When it comes to log management and cyber security, logs act as a red flag when it comes to bad actors, providing information like IP addresses, HTTP status codes, client/server requests and more. This information enables teams to develop rules and thresholds to detect threats and potential security anomalies in real time.

• Log analytics help organizations maintain compliance with audits, security policies, or regulatory requirements. Organizations operating in certain industries may be required to comply with PCI, HIPAA, GDPR, FISMA, SOC, ISO, COBIT and others. Regular collection and analysis of log data provides organizations with information they need to comply with these bodies and assist with potential audit requirements.

• Log analytics drive product analytics and user analytics that feed business and adoption insights. Logs provide data about how customers use a product, what’s working and areas of a product that may have usability issues. Teams use this data to identify improvements for a better overall solution.

• Log analytics empower organizations to take a more proactive approach across the entire enterprise. Trend data can provide information about traffic loads or spikes to inform IT teams about how to improve website performance or even when to release a new version or update.

Whether you select a new log management system or revamp your current system, maintaining best practices helps ensure your organization reaps all the benefits you can. Use the following tips and best practices as you develop a log management procedure for your organization.

Develop a log management policy

Especially for companies working with a large, complex IT environments, implementing a log management policy helps ensure everyone follows set protocols. What information will your logs capture? How long should you store your logs? Are there regulatory or auditing requirements you must keep in mind? All of this should inform your policy. Data tiering, which we’ll discuss later in this section, can make it easier and more affordable to identify, sort and archive your log data into various categories.

Centralize your logs

Aggregating your logs is the best way to achieve an end-to-end experience where you can track all your log data in a single platform. This best practice eliminates data silos and reduces duplicative efforts.

Use structured logging

Traditional logging techniques relied on plain text files, which resulted in mass amounts of unstructured data. However, writing logs in formats like JSON or XML makes them easier to parse, query and analyze. This cuts down on time spent parsing and simplifies analysis.

Create meaningful log messages

Like most kinds of communication, the best log messages convey information clearly. Meaningful logs are descriptive and detailed. Include context — in addition to fields like timestamps, user request identifiers and unique identifiers. Context helps ensure teams have the information they need at their fingertips.

Avoid logging sensitive or proprietary data

While logging more information is almost always better, this isn’t necessarily the case with sensitive or proprietary data. Avoid logging application source codes, proprietary data, or any personally identifiable information (PII), unless it’s critical to diagnostics or root cause analysis. This helps ensure compliance with data privacy standards your company may be required to uphold.

Implement real-time monitoring

To ensure both reliability and an excellent user experience, monitor your logs in real time. This empowers IT teams to troubleshoot problems as they come up, leading to decreased downtimes and outages. It also catches potential security incidents as quickly as possible.

Use data tiers

For many companies, there is likely log data that you need to access frequently and log data that you don’t need to access as often. Data tiers sort your logging data into low-touch and high-touch logs. At Sumo Logic, our data tiering also helps you minimize costs, based on how often you plan to access the data you ingest.

Create analytics from logs

Log analytics are critical for troubleshooting and forensics investigations. Functions and methods, such as normalization, pattern recognition powered by machine learning, classification and tagging, correlation analysis and more, means you can manipulate log data to extract the performance, security and business information needed for IT teams and key stakeholders.

Use a cloud-native log management platform

Cloud-native log management companies understand the unique pain points and requirements that cloud-based SaaS companies face. As a cloud-native company ourselves, Sumo Logic understands how crucial reliability and security are—we require them both to maintain our own platform. We drink our own champagne, using our SaaS analytics solution to monitor, troubleshoot and diagnose issues. Partnering with a company that truly understands your perspective can take your log management to the next level.

We’ve discussed the process, the benefits and the best practices, but how do you find the best logging tool for your organization? As you begin your search for a log management and analytics solution, look for the following key features and functionalities.

• Integrated, full stack capabilities: While some very small companies may be able to use log management tools that are free, a paid solution often offers significantly more capabilities. The right log management solution will aggregate your data from cloud and on-premises infrastructure, eliminating silos to improve troubleshooting and security.

• Tool consolidation: Tech stacks have gotten massive, and the best solutions support tool consolidation. Sumo Logic, consolidates log data across both observability and security, providing you a single source of truth for all your data.

• Cloud-native architecture: The right solution will make it quick and easy to manage your log data, security and digital transformation. Cloud-native architecture provides the scale and elasticity you need to meet your business’ growing data needs.

• Machine learning analytics: The best log management tools empower teams to ingest and analyze any type of data, including structured, semi-structured and unstructured.

• Tiered analytics and credit licensing: The best log aggregation tools offer cost-effective data tiered pricing and credit licensing to help meet your budgetary requirements.

• Out-of-the-box auditing and compliance: Compliance and regulatory requirements are crucial components of the work you do every day. Look for a solution that offers cloud-native security and configuration analytics for rapid, continuous compliance for PCI, HIPAA, GDPR, FISMA, SOX, ISO, COBIT and others.

• Scale without compromising on reliability: The best log management tools offer you the flexibility to ingest data as it grows and scales without compromising on the performance.

In today’s increasingly digital world, customer satisfaction means providing a solution that’s reliable and secure. And that could be the difference between maintaining happy customers and losing too many customers thanks to unreliable software. With Sumo Logic’s log management and log analytics solution, you can do the following in a single, easy to use platform:

• Collect all your logs in one place

• Break down data silos

• Improve your application monitoring and troubleshooting

• Increase your security

• Gain key business insights across your entire organization

• Lower costs

Ready to learn more about how Sumo Logic superpowers log management and analytics? Explore our full log management and analytics solution or our case studies to find out how organizations just like yours are excelling with Sumo Logic. When you’re ready take the next step and start a free trial to discover the Sumo Logic difference.