Best Log Analysis Software
Log analysis software helps enable the documentation of application log files for records and analytics. This type of software provides tools to increase the collection of logs as well as centralized databases for storing data. Furthermore, log analysis tools include analytics components such as prebuilt dashboards to identify the cause and impact of events, while also offering the ability to query the logs to discover actionable data. Monitoring features also form a large component of log analysis; these features, sometimes powered by machine learning, help detect, predict, and prevent future anomalies. Companies use this data to better understand performance failures, remediate them, and learn how to prevent them in the future, with a goal of improved application performance and reliability.
Some application performance monitoring (APM) software, container management software, and enterprise monitoring software offer log analytics features, but typically do not focus on log management specifically. Business users looking to analyze log data in real time can leverage stream analytics software and analyze data transferred among a whole range of internet of things (IoT) endpoints and devices, including smart cars, machinery, or home appliances.
To qualify for inclusion in the Log Analysis category, a product must:
Best Log Analysis Software At A Glance
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Dynatrace is advancing observability for today’s digital businesses, helping to transform the complexity of modern digital ecosystems into powerful business assets. By leveraging AI-powered insights,
- Software Engineer
- Senior Software Engineer
- Information Technology and Services
- Financial Services
- 69% Enterprise
- 23% Mid-Market
18,793 Twitter followers
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- User Satisfaction
- Seller Details
Coralogix is a modern, full-stack observability platform transforming how businesses process and understand their data. Our unique architecture powers in-stream analytics without reliance on indexing
- Software Engineer
- DevOps Engineer
- Computer Software
- Information Technology and Services
- 54% Mid-Market
- 32% Enterprise
4,066 Twitter followers
- Overview
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- User Satisfaction
- What G2 Users Think
- Seller Details
New Relic invented cloud APM for application engineers. Today it is a leader in observability and source of truth for all engineers to make decisions with data across their entire software stack and t
- Software Engineer
- Senior Software Engineer
- Information Technology and Services
- Computer Software
- 45% Mid-Market
- 30% Small-Business
- Reviewers appreciate the ability to monitor performance and reliability of all their various application with New Relic
- Reviewers mention the quantity and frequent addition of helpful features, but some noted that features feel incomplete or overwhelming
- Reviewers like the ability to easily customize alerts, and the automated alerts the tool provides
68,174 Twitter followers
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- User Satisfaction
- Seller Details
The Oracle Cloud Infrastructure Logging service is a highly scalable and fully managed single pane of glass for all the logs in your tenancy. Logging provides access to logs from Oracle Cloud Infrastr
- Information Technology and Services
- Computer Software
- 61% Enterprise
- 20% Mid-Market
823,886 Twitter followers
- Overview
- Pros and Cons
- User Satisfaction
- What G2 Users Think
- Seller Details
Datadog is the monitoring, security and analytics platform for developers, IT operations teams, security engineers and business users in the cloud age. The SaaS platform integrates and automates infra
- Software Engineer
- DevOps Engineer
- Information Technology and Services
- Computer Software
- 48% Mid-Market
- 32% Enterprise
- Reviewers like the way that Datadog provides a centralized view of their entire organizational infrastructure
- Reviewers often highlight the ability to view specific logs in realtime, and pinpoint issues that may be occurring
- Reviewers like the ability to ingest, monitor, and analyze many types of data in the platform
49,771 Twitter followers
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- User Satisfaction
- Seller Details
Find out what is happening in your business and take meaningful action quickly with Splunk Enterprise. Automate the collection, indexing and alerting of machine data that's critical to your operations
- Software Engineer
- Senior Software Engineer
- Information Technology and Services
- Computer Software
- 62% Enterprise
- 26% Mid-Market
732,001 Twitter followers
- Overview
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- User Satisfaction
- Seller Details
For applications running on Google Cloud Platform and Amazon Web Services.
- Information Technology and Services
- Computer Software
- 32% Mid-Market
- 28% Small-Business
32,691,321 Twitter followers
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- Seller Details
Sumo Logic, Inc. unifies and analyzes enterprise data, translating it into actionable insights through one AI-powered cloud-native log analytics platform. This single source of truth enables Dev, Sec
- Software Engineer
- Senior Software Engineer
- Information Technology and Services
- Computer Software
- 49% Mid-Market
- 40% Enterprise
6,590 Twitter followers
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- User Satisfaction
- Seller Details
Logz.io is an AI-powered observability platform designed to help teams solve critical log management, monitoring, and troubleshooting challenges. Built for modern environments, Logz.io unifies log man
- Software Engineer
- Software Developer
- Computer Software
- Information Technology and Services
- 53% Mid-Market
- 30% Small-Business
3,225 Twitter followers
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- User Satisfaction
- Seller Details
Better Stack lets you see inside any stack, debug any issue, and resolve any incident. Visualize your entire stack, aggregate all your logs into structured data, and query everything like a single dat
- CEO
- Software Engineer
- Computer Software
- Information Technology and Services
- 90% Small-Business
- 7% Mid-Market
8,677 Twitter followers
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- User Satisfaction
- Seller Details
ManageEngine Site24x7 offers unified cloud monitoring for DevOps and IT operations within small to large organizations. The solution monitors the experience of real users accessing websites and applic
- CEO
- IT Manager
- Information Technology and Services
- Computer Software
- 44% Small-Business
- 43% Mid-Market
7,686 Twitter followers
- Overview
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- User Satisfaction
- Seller Details
Solarwinds® Kiwi Syslog® Server is a syslog management tool for network and systems engineers. It receives syslog messages and SNMP traps from network devices (routers, switches, firewalls, etc.), and
- Information Technology and Services
- 53% Enterprise
- 47% Mid-Market
19,990 Twitter followers
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- User Satisfaction
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LogicMonitor® offers hybrid observability powered by AI. The company’s SaaS-based platform, LM Envision, enables observability across on-prem and multi-cloud environments. We provide IT and business t
- Infrastructure Manager
- Senior Systems Engineer
- Information Technology and Services
- Computer Software
- 52% Mid-Market
- 29% Enterprise
12,676 Twitter followers
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- User Satisfaction
- Seller Details
SignalFx is the only real-time cloud monitoring platform for infrastructure, microservices, and applications. The platform discovers and collects metrics across every component in your cloud environme
- Software Engineer
- Computer Software
- Information Technology and Services
- 35% Enterprise
- 33% Mid-Market
732,001 Twitter followers
- Overview
- Pros and Cons
- User Satisfaction
- Seller Details
ManageEngine Log360 is a unified solution that offers holistic organizational security by bringing together crucial security capabilities like UEBA, DLP, CASB to improve visibility into your organizat
- 46% Enterprise
- 38% Mid-Market
7,686 Twitter followers
Learn More About Log Analysis Software
What is Log Analysis Software?
Businesses rely on a vast array of tools, including applications, legacy systems, and mainframes. These tools produce log files (or logs) which are records of events that occur on a network, in an operating system, or within other software. These messages based on activity and data flow indicate how the resources within the network environment are performing or being used. Log analysis software helps to not only document and collect these logs, but also provides tools for analyzing them to better understand the cause and impact of events.
As IT infrastructure becomes more complex and distributed, it is becoming increasingly important to ensure that it is properly understood in all of its facets. Log analysis software provides the tools that businesses need to understand the infrastructure, whether it is an application, operating system, or device. Log analysis helps users understand patterns and trends in activity within the infrastructure.
Log analysis data may be used to troubleshoot performance issues with specific applications and identify potentially threatening anomalies. Regular log management, analysis, and archiving are also key tasks for demonstrating compliance with various security standards and regulations. Overall, users are enabled to make the most of the benefits of log data analysis by incorporating log analysis tools into their business practices.
What Types of Log Analysis Software Exist?
Log analysis software, with logs at its core, is able to handle different varieties of logs, allowing businesses to get a bird's eye view of their IT system and beyond. As such, it is helpful to understand the different types of logs which these tools analyze.
Event log analysis
Event logs record events taking place in the execution of a system to provide an audit trail that is used to understand the activity of the system and to diagnose problems. They are essential to understand the activities of complex systems, particularly in the case of applications with little user interaction, such as server applications.
Transaction log analysis
Most database systems maintain some kind of transaction log, which are not mainly intended as an audit trail for later analysis, and are not intended to be human readable. These logs record changes to the stored data to allow the database to recover from crashes or other data errors and maintain the stored data in a consistent state.
Message log analysis
Instant messaging programs, peer-to-peer file applications with chat functions, and multiplayer games commonly have the ability to automatically log or save textual communication, both public and private chat messages between users.
What are the Common Features of Log Analysis Software?
Log analysis tools are designed to streamline the process of collecting, archiving, and deriving actionable insights from data log files. They both centralize and standardize logs from across the network. The files come in different formats as many different elements of IT infrastructure generate event logs. Log viewer software streamlines the process by relegating all files to a shared format and terminology. This ensures cohesive and uniform analysis and archiving, and more accurate and comprehensive reports and statistics.
The following are some core features within log analysis software that can help users in monitoring, visualizing, and understanding their log data:
Monitoring: Monitoring is a large part of log analysis. These features help detect, predict, and prevent future anomalies. Companies use this data to better understand performance failures, remediate them, and learn how to prevent them in the future. In regards to how one can interact and engage with this data, log analysis software helps businesses query, filter, and analyze log data effectively and efficiently. For more advanced tools, users are enabled to search in a natural, intuitive manner or sift through many logs with a few clicks.
Visualization: Customizable dashboards help align teams by visualizing logs, metrics, and performance data for full-stack visibility and reliable delivery.
Alerting: Real-time analytics help users rapidly identify and resolve potential cyber attacks, detect and prevent breaches, and reduce compliance costs.
Data centralization: Log analytics tools integrate with applications and make it easy to aggregate data across the stack.
Other Features of Log Analysis Software: Automated Tagging Capabilities, Data Discovery Capabilities, Detect Anomalies Capabilities, Live Tail Capabilities, Track Trends Capabilities
What are the Benefits of Log Analysis Software?
Log analysis data may be used to troubleshoot performance issues with specific applications and identify potentially threatening anomalies. Regular log management, analysis, and archiving are also key tasks for demonstrating compliance with various security standards and regulations. Overall, users are enabled to make the most of the benefits of log data analysis by incorporating log analysis tools into their business practices.
Compliance: With log analysis tools, businesses continually track whether they are meeting benchmarks for regulations such as General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA).
Better security: Log analysis provides instant awareness of any security red flags. A log analyzer tool helps block and filter incoming network traffic, keep IT admins alerted about failed authentication attempts, and ensure firewall configurations are operating most effectively.
Smarter business operations: Departments such as finance and accounting, HR, and legal rely on IT resources to carry out their business-critical tasks and responsibilities. Hence, log analysis tools provide the functionality necessary to spot critical system errors or trends and address them quickly and efficiently.
Who Uses Log Analysis Software?
DevOps engineers: DevOps engineers can use log analysis tools to troubleshoot, helping them find system errors. This can help improve operational efficiency by reducing production downtime.
System administrators: System administrators can use these tools to gain visibility into the performance and health of applications and infrastructure. By reviewing event logs, for example, they can see an audit trail which helps them better understand system behavior and diagnose any potential issues.
Site reliability engineers: Site reliability engineers are bridging the gap between production and development teams, ensuring properly running sites that meet operational requirements. As such, they focus largely on application monitoring and must have a deep knowledge of the application's inner workings and underpinnings, such as code and configuration. Therefore, they can benefit from log analysis to help them create and maintain operational runbooks, monitor application performance, and more.
Web developers: Logging gives developers and other DevOps professionals a way to understand what went wrong and provides insight into how to fix it. They can use this software to parse server log files from web servers, which can provide information about things such as when, how, and by whom a web server is visited. Through reports, dashboards, and custom queries, they can get a better understanding of website performance and determine steps forward for monitoring their website.
What are the Alternatives to Log Analysis Software?
Alternatives to log analysis software can replace this type of software, either partially or completely:
Log monitoring software: Log monitoring software helps users looking for a basic tool to keep track of their logs, without the need for sophisticated analytics. This helps maintain IT infrastructure performance and pinpoints issues to prevent downtime and mitigate risks. These tools will often integrate with IT alerting software, log analysis software, and other IT issue resolution products to more aptly flesh out the IT infrastructure maintenance ecosystem.
Application performance monitoring (APM) software: APM tools allow users to monitor and track the performance of particular software or web applications to identify and solve any performance issues that may arise. These solutions provide performance metrics for applications, with specific insights into the statistics such as the number of transactions processed by the application or the response time to process such transactions.
Network monitoring software: Network monitoring software focuses more heavily on network traffic and health. APM software can reveal network-side issues with application performance, where network monitoring would take over to provide further details on any issues.
Analytics platforms: Analytics platforms might include integrations for log data, but are broader-focused tools that facilitate the five elements: data preparation, data modeling, data blending, data visualization, and insights delivery.
Security information and event management (SIEM) software: SIEM software includes log analysis and provides tools for taking actions based on log files. This software helps to centralize security operations into a single location, helping teams navigate historical logs, identify trends, and better fortify their networks.
Software Related to Log Analysis Software
Related solutions that can be used together with log analysis software include:
Data warehouse software: Most companies have a large number of disparate data sources, so to best integrate all their data, they implement a data warehouse. Data warehouses can house data from multiple databases and business applications, which allows business intelligence (BI) and analytics tools to pull all company data from a single repository. This organization is critical to the quality of the data that is ingested by analytics software.
Data preparation software: A key solution necessary for easy data analysis is a data preparation tool and other related data management tools. These solutions allow users to discover, combine, clean, and enrich data for simple analysis. Data preparation tools are often used by IT teams or data analysts tasked with using BI tools. Some BI platforms offer data preparation features, but businesses with a wide range of data sources often opt for a dedicated preparation tool.
Challenges with Log Analysis Software
Software solutions can come with their own set of challenges.
Data security: Companies must consider security options to ensure the correct users see the correct data. It must also have security options that allow administrators to assign verified users different levels of access to the platform.
Adoption: At the start, analytics tools may not seem valuable to all employees; end users might struggle to adopt the solutions. Therefore, it’s important for companies to have a plan to encourage and promote user adoption.
Time to market: As with any software implementation, it is important to think about how long it will take to implement. Users should also consider related software that a company might need, such as data integration software.
Which Companies Should Buy Log Analysis Software?
In the data-driven world, IT is no exception. While IT teams, including DevOps engineers and system administrators, are the most common users of log analysis software, self-service tools and dashboards allow for this data and analysis to be shared with the broader business. With almost all businesses having some sort of IT function, log analysis software can have a positive impact on businesses across all industries and company sizes. Here are a couple of examples:
Retail: If web purchases drive a majority of the business revenue, optimal website and web application performance is critical. Continual monitoring helps businesses to not only avoid overloads but also understand their standard traffic patterns. This is then utilized to predict the optimal allocation of resources for site growth.
Healthcare: Technological uptime and performance are imperative when the goal is improving the customer’s health. Log analysis solutions allow providers to monitor their IT in real time, which helps catch and prevent downtimes before they affect patients. Full topological and transactional visibility provided by log analysis software helps providers continue giving quality patient care despite technological hiccups.
How to Buy Log Analysis Software
Requirements Gathering (RFI/RFP) for Log Analysis Software
If a company is just starting out on their IT journey, g2.com can help in selecting the best software for the particular company and use case. Since the particular solution might vary based on company size and industry, G2 is a great place to sort and filter reviews based on these criteria, along with many more.
The variety, volume, and velocity of data are vast. Therefore, users should think about how the particular solution fits their particular needs, as well as their future needs as they accumulate more data. In this case, it is key for IT professionals to develop a broad IT strategy and ensure that they have the basics in place, such as IT alerting software, before they begin to look at the added benefit of log analysis.
To find the right solution, buyers should determine their pain points and write them down. Things to keep in mind and evaluate include: log data types, the types of visualizations which would be helpful, the forms and frequencies of alerts, etc. These should be used to help create a checklist of criteria. Additionally, the buyer must determine the number of employees who will need to use this software, as this drives the number of licenses they are likely to buy.
Taking a holistic overview of the business and identifying pain points can help the team springboard into creating a checklist of criteria. The checklist serves as a detailed guide that includes both necessary and nice-to-have features including budget, features, number of users, integrations, security requirements, cloud or on-premises solutions, and more.
Depending on the scope of the deployment, it might be helpful to produce a request for information (RFI), a one-page list with a few bullet points describing what is needed from log analysis software.
Compare Log Analysis Software Products
Create a long list
From meeting the business functionality needs to implementation, vendor evaluations are an essential part of the software buying process. For ease of comparison after all demos are complete, it helps to prepare a consistent list of questions regarding specific needs and concerns to ask each vendor.
Create a short list
From the long list of vendors, it is helpful to narrow down the list of vendors and come up with a shorter list of contenders, preferably no more than three to five. With this list in hand, businesses can produce a matrix to compare the features and pricing of the various solutions.
Conduct demos
To ensure the comparison is thoroughgoing, the user should demo each solution on the shortlist with the same use case and data sets. This will allow the business to evaluate like for like and see how each vendor stacks up against the competition.
Selection of Log Analysis Software
Choose a selection team
As log analysis software is all about the data, the user must make sure that the selection process is data driven as well. The selection team should compare notes and facts and figures which they noted during the process, such as time to insight, number of visualizations, and availability of advanced analytics capabilities.
Negotiation
Just because something is written on a company’s pricing page, does not mean it is not negotiable (although some companies will not budge). It is imperative to open up a conversation regarding pricing and licensing. For example, the vendor may be willing to give a discount for multi-year contracts or for recommending the product to others.
Final decision
After this stage, and before going all in, it is recommended to roll out a test run or pilot program to test adoption with a small sample size of users. If the tool is well used and well received, the buyer can be confident that the selection was correct. If not, it might be time to go back to the drawing board.
What Does Log Analysis Software Cost?
Businesses decide to deploy log analysis software with the goal of deriving some degree of a return on investment (ROI).
Return on Investment (ROI)
As businesses are looking to recoup their losses that they spent on the software, it is critical to understand the costs associated with it. This software is typically billed per user, which is sometimes tiered depending on the company size. More users will typically translate into more licenses, which means more money.
Users must consider how much is spent and compare that to what is gained, both in terms of efficiency as well as revenue. Therefore, businesses can compare processes between pre- and post-deployment of the software to better understand how processes have been improved and how much time has been saved. They can even produce a case study (either for internal or external purposes) to demonstrate the gains they have seen from their use of the log analysis tool.
Implementation of Log Analysis Software
How is Log Analysis Software Implemented?
Implementation differs drastically depending on the complexity and scale of the data. In organizations with vast amounts of data in disparate sources (e.g., applications, databases, etc.), it is often wise to utilize an external party, whether that be an implementation specialist from the vendor or a third-party consultancy. With vast experience, they can help businesses understand how to connect and consolidate their data sources and how to use the software efficiently and effectively.
Who is Responsible for Log Analysis Implementation?
It may require a lot of people, or many teams, to properly deploy an analytics platform. This is because data can cut across teams and functions. As a result, it is rare that one person or even one team has a full understanding of all of a company’s data assets. With a cross-functional team in place, a business can piece together their data and begin the journey of analytics, starting with proper data preparation and management.
Log Analysis Software Trends
Log analysis software is getting supercharged with the help of technology like machine learning. With this advanced version of the software, business professionals without a strong data background are able to use the tools, digging deep into the data to better understand the business.
Volume, velocity, and variety of data
Data is being produced at a rapid rate and the data types are not all of one flavor. Individual businesses produce a range of data types like sensor data from internet of things (IoT) devices, event logs, and clickstreams. As such, the tools needed to process and distribute this data need to be able to handle this load in a way that is scalable, cost efficient, and effective. Advances in artificial intelligence (AI) techniques, such as machine learning, are helping to make this more manageable.
Self service
As with other types of analytics tools, there is an increasing trend for software to be of a self-service nature. This means that non professionals should be able to use the tool easily with little to no IT support for setting it up. With drag-and-drop interfaces or highly customizable setups, average business users are being empowered by statistical analysis capabilities.
Augmented analytics
AI and machine learning are making inroads across most industries and business use cases with statistics being no exception. With machine learning powering statistical analysis, users are able to discover data, determine the best type of analysis to deploy for a particular data set or problem, and more.
