ELK Log Analysis vs. XpoLog Log Manager- Analyzer – Monitoring Tool
We performed a comparison between ELK log analysis tool and XpoLog log management tool.
Main points to notice when considering using ELK for your log analysis Vs. XpoLog:
1. XpoLog provides a unique auto mining technology which profiles systems and app log data.
XpoLog tool is able to build automatic IT intelligence which helps to understand the source of the problem and subsequently correlate and compute trends on those problems and then create the search analysis queries for the user. This allows application, systems and security groups to automate their log mining process and time to value on unknown data.
2. Our customers do not need to be superbly technically proficient in the area of searches.
XpoLog brings automation and AI technology to empower the admin – dozens of apps with ready to use reports and dashboards, auto-detection of problems, errors, exceptions, trends and more, predefined filters, monitors, automated log parsing. XpoLog allows simple use of the analytical console to: investigate, discover, and isolate their problems which affect their IT.
3. XpoLog is agentless – for *nix systems we utilize SSH and therefore is able to collect thousands of servers/apps logs without the need for agent installation. This feature is a major advantage for MSPs.
4. The price of our solution is considerably lower than the cost of an Open Source Logs management solution eventually and especially for an enterprise solution. This is a major advantage for customers who are initially put off by the high cost of Splunk or are looking to switch to a more advanced system with a better ROI/TCO.
Download XpoLog Free – Get Online Support Session to Improve Your Logs Monitoring System.
|Parameter||ELK Stack (Elastic-search, Logstash, Kibana)||XpoLog|
(Total Cost of Ownership)
|On premise||Yes (but with limited security features)||Yes|
|Cloud support||No|| Yes.|
Includes integration with all major cloud providers.
|Data Collection and Parsing|
|Out of the box applications|| No.|
Relies on a community to build it
Linux, Windows, IIS, Apache, Tomcat, NGINX, Log4net, Log4J, WebSphere, and more
Amazon AWS – S3, CloudFront, CloudTrail, Linux AMI, ELB, RDS,
|Health status||Requires an additional product license called like Marvel – that is relatively new||Built-in no additional costs|
|Full Text Search|| Built-in.|
In addition includes Analytical Search, analytical layers on top of the search.
Meaning that the search results are more relevant, include criticality scoring, etc.
|Visualization|| Based on Kibana.|
Visualization is time-based only (no visualization of criticality, etc.).
| Extremely rich visualization including analytical layers that show critical events throughout the timeline.|
Users can easily create dashboards and reports, including charts, geomaps, and more.
|Semantic analysis||No|| Yes.|
XpoLog uses analytics technologies like machine learning analysis, semantic profiling and anomaly detection on all the gathered logs to establish meaning and importance of the various log event messages.
That knowledge is then used to establish the criticality level of the events.
The critical analysis is used to pro-actively surface important events that require the user’s attention.
|Real-time data||Depends highly on implementation||Yes|
|Extraction of value from the data||Heavily dependent on the user’s experience, knowledge, and acquaintance with a monitored environment.|
In any case, the extraction of value takes time.
|Less dependent on the user’s experience and technical know-how.|
The system proactively surfaces important events that require the user ’s attention.
|Security||Coming soon|| Yes.|
Enterprise-grade security features.
|Summary|| Considering the cost of the paid components (e.g. Marvel and Shield) and the complexity in deployment and integration, the “open source” solution is definitely not free.|
By adding a little bit to the licensing cost, clients can get XpoLog, which is much more robust and includes important features that enable users to extract more value from the data quickly without relying on their expertise.
Your Guaranteed Added Value
- Accelerate Problem Resolution by 80%
- Discover 37% More Problems in your systems
- Accelerate Logs Troubleshooting by 90%
- Reduce 80% MTTR (Mean Time to Repair)
- Increase Your Company’s App Intelligence
Your Fast & Easy Universal ELK / Elastic search / Logstash / Kibana Logs Analysis & Manager – Full Auto-pilot Analytics – All Your Logs at All Sizes Across All Folders and Servers
XpoLog logs analysis and management for ELK / Elastic search / Logstash / Kibana visualizes your ELK Events hidden for your machine-generated data values as well as errors with a set of built-in dashboards and presents advanced log data analytics on physical & logical system entities from all log files across multiple clusters and run both on-premise and in the cloud. The ELK / Elastic search / Logstash / Kibana auto-pilot mode enables you to view dashboards in 2 clicks! XpoLog ELK / Elastic search / Logstash / Kibana logs analysis server is highly customizable and you can work your system in manual mode to fit your logs data analytics exact needs. With XpoLog ELK / Elastic search / Logstash / Kibana logs analyzer you get periodical alerts, reports, and notifications on all your important insights. XpoLog’s built-in servers’ logs analytic layers for ELK / Elastic search / Logstash / Kibana event logs scan your log files and application data and showcase a prioritize list of all insights and intelligence based on your users’ transactions. XpoLog ELK / Elastic search / Logstash / Kibana event logs analyzer has a patented algorithm that delivers a live Root Cause Analysis on all your servers logs across all folders. Analysis of logs pinpoints crucial problems and hidden values – XpoLog ELK / Elastic search / Logstash / Kibana Logs Manager analyzes all logs across multiple folders and devices and present critical IT, DevOps, Web Admins, Webmasters, and Business quality and availability insights with a deep root cause analysis.
XpoLog ELK / Elastic search / Logstash / Kibana Events Logs Analyzer helps you unlock and discover IT hidden errors, problems, and patterns in any log data at any size as well as Business values by making any ELK / Elastic search / Logstash / Kibana log data easily accessible for search and visualization in real time.
XpoLog Logs Analyzer & Manager for ELK / Elastic search / Logstash / Kibana – Analyze & Visualize Hidden Values & Errors
XpoLog logs analysis system works in real time on all ELK / Elastic search / Logstash / Kibana log events and messages combined with all other services, applications, and databases on all line of business products Specifically designed for IT Admins, Web Admins, DBAs, DevOps, Developers, and Apps managers.
Typical ELK / Elastic search / Logstash / Kibana deployments include tens and often hundreds of servers Apache, Windows and other applications, which may generate millions of events every day expanding the ELK / Elastic search / Logstash / Kibana logs content and overall storage exponentially. Both cloud and on-premise infrastructures make data centers even more highly dynamic and complex to analyze which in turn makes ELK machines generated data analysis and management process even more tricky.
XpoLog automatic Analytics on ELK / Elastic search / Logstash / Kibana events’ log files presents detailed logs queries data reports on physical & logical system entities from all log files and run both on-premises or in the cloud. On the Errors sides XpoLog automatically tracks invalid event messages and transactions, not found pages and security breaches and more to get a real-time view and analytics of all your servers issues. You get periodical alerts, reports, and notifications on all your important insights.
Your ELK / Elastic search / Logstash / Kibana infrastructure will not change – XpoLog agent-less logs analysis architecture uses common protocols such as SSH/UDP/TCP to listens and connect with all your servers and devices all over your network clusters so you can search log files and application data even faster than ever before, and gain visibility into unknown problems, errors and anomalies with live NOC dashboards on all multiple Apache Tomcat application tiers. You design your system so users have the best end-user experience – XpoLog logs analysis server is designed so You have the best experience in debugging your system’s servers and increase your users’ user experience and company’s reputation. With XpoLog logs analysis and reporting system for ELK / Elastic search / Logstash / Kibana, you see all application performance and quality problems issues in order to take immediate actions on.
XpoLog ELK Logs Analyzer – Performance – Stability – Integrity
XpoLog ELK / Elastic search / Logstash / Kibana Logs Analyzer features advanced analytics on web events, reports and Root Cause Analysis on all log types and sizes to discover hidden faults, improve your system’s uptime, reduce your IT problems thus increase your revenues. XpoLog ELK / Elastic search / Logstash / Kibana logs analysis integrates with all logs and automatically Scan – Parse – Aggregate – Read – Analyzes & Report your logs’ hidden values in real time and presents your ELK / Elastic search / Logstash / Kibana Server’s Heat Map AKA Problem Map Dashboard: events messages, events errors, events exceptions, server use cases, events transactions performance, logs’ usage, events queries, logs profiling, error codes, number of queries in logs and their performance, and ELK / Elastic search / Logstash / Kibana logs problem per server. XpoLog ELK logs analysis platform serves IT Admins, Sys Admins and Dev operations teams which need a fast identification of logs’ errors, queries statistics, problems trends, server overview of hidden values and anomalies. XpoLog ELK logs analysis provides full insights on all ELK / Elastic search / Logstash / Kibana machines generated data, applications data, software data and transaction logs with an advanced visualization tools and automatic analysis that correlates your unique identifiers across servers and time like servers’ exceptions, faults, problems, geographic data, referers, resources, requests, performance data, information on users and many more trends and statistics.