Moogsoft vs Splunk: Evaluating AIOps Solutions for IT Operations Efficiency
Artificial Intelligence for IT Operations, or AIOps has taken the world by storm. A term coined by Gartner, AIOps brings together the capabilities of big data and machine learning to transform the alerts avalanche to a few addressable critical alerts as well as automate remediations for common anomalies.
From event correlation to root cause identification, companies across the world are increasing their use of AIOps platforms and maturing their use cases across DevOps and site reliability engineering (SRE) practices besides ITOps.
In this blog, we are going to compare two popular AIOps platforms, Moogsoft and Splunk, and evaluate their various capabilities. We will also introduce you to a compelling alternative, the appNeura Sniper.
Moogsoft AIOps
Moogsoft AIOps paves the way for the continuous availability of IT operations. The platform offers automated noise reduction, correlation, and collaboration across the incident workflow, allowing teams to detect issues early and respond faster.
Source – Moogsoft
Splunk AIOps
Splunk AIOps empowers teams to modernize IT by leveraging a host of predictive management, event correlation, and automated incident response capabilities. The platform allows teams to drill down to the code level to conduct efficient root cause analysis in one place. Using service-level dashboards, teams can better understand their underlying infrastructure and track interactions across every system in the service stack.
Source – Splunk
Moogsoft vs. Splunk At a Glance
Although both Moogsoft and Splunk are popular platforms used for AIOps, they share some similarities and have certain differences. Let’s compare the two:
Overview | Moogsoft, with its domain-agnostic capabilities, handles diverse datasets, making it an effective tool for reducing alert fatigue. It applies advanced algorithms to correlate data into actionable incidents, providing root cause determination across various monitoring tools and data sources. | Splunk Enterprise is a leading domain-centric AIOps solution known primarily for its robust log management capabilities. It also offers a Machine Learning toolkit, enhancing its ability to process and analyze log data. |
Benefits | Use metrics and events to identify true anomalies early in the lifecycle and prevent issues from impacting user experience. Initiate automated workflows to appropriately route, remediate, and auto-close incidents. Find correlations and unearth patterns in events, preventing issues from happening again. | Use predictive performance analytics and reporting to prevent issues from impacting user experience. Use predictive analytics to prevent issues before they occur and improve efficiency with automated incident response. Leverage event correlation capabilities to prioritize and group alerts and quickly carry out root cause analysis. |
Free Trial | Yes | No |
Usability | Easy to set up, use, and administer | Easy to setup but usability is poor; users need training |
Incident Management | Specializes in incident management, correlating events, providing context, and reducing alert fatigue. | Requires additional configurations and integrations to handle incident workflows efficiently. |
Data Analytics | Relies on data from various monitoring and event sources to perform analytics. | Collects data from a variety of sources and excels at analyzing and visualizing data. |
Training options | In-person, live online, webinars, documentation, and videos | Videos, live online, and in-person |
Pros | Intelligent event correlationComprehensive machine learning capabilities Large range of event management toolsEasy to implement and useAdvanced observability | Extensive range of featuresAdd-on supportLive and custom dashboards KPI monitoringHighly configurable |
Cons | Limited support for unique data types Restrictive automation Limited integration options | Expensive for large data volumesDifficult to implement Steep learning curveLimited support for events |
Customer ratings | Source – Gartner | Source – Gartner |
Decoding Sniper – appNeura’s Innovative AIOps Incident Management Platform
appNeura Sniper uses the power of big data analytics and AI/ML technologies to transform alerts avalanche into a few addressable critical alerts across IT stacks and heterogeneous IT environments. Powered by patents from USPTO, this intuitive solution enables teams to meet necessary performance and availability SLAs for business applications.
Sniper offers a comprehensive view of IT infrastructure, enabling organizations to effectively manage and control complex systems. The platform’s real-time monitoring and alerting system quickly helps in root cause identification and alerts IT teams, allowing for quick resolution.
Sniper is packed with an exhaustive range of capabilities to monitor and streamline processes, technologies, and databases. The platform offers proactive, personalized, and dynamic insight into IT Service levels, allowing you to take steps to enable performance benchmarking and improve availability – and thus user experience.
The domain-agnostic tool fetches data from various Application Performance Monitoring tools and tests various parameters against predefined values. These parameters are presented via a unified dashboard – regardless of what the metrics or which APM tool the data is coming from. When an outlier is detected, an alert or event is generated for quick action to be taken.
Spiner fetches data from various APM tools including, AppDynamics, Dalado, Dynatrace, etc. It supports various ticketing tools, including Jira, Freshdesk, and Lighthouse. It offers various metric sets, including:
- CPU (idle, irq, user, system, etc.)
- Filesystem (total, available, type, free, used, etc.)
- Load (1 min, 5 min, 15 min, etc.)
- Memory (swap, total, used, free, actual, etc.)
- Network (in, out, errors, bytes, etc.)
- Process (state, memory, cpu, etc.)
- Service (memory, tasks, states, etc.)
- Uptime (of host operating systems such as Linux, Mac, Windows, etc.)
- Users (number of logged in users, associated sessions, etc.)
Source – appNeura
Combining big data and AI/ML functionality, Sniper AIOps platform leverages deep understanding and experience in performance engineering through a verified and proven knowledge base of over 5,000+ real-life complex IT operations and performance issues.
Using Sniper, teams can:
- Manage complex IT systems leveraging a centralized incident management dashboard.
- Ensure high levels of uptime and performance by identifying and resolving issues and bottlenecks proactively.
- Overcome tedious manual tasks via seamless and intelligent automation and focus on strategic initiatives and value-added activities.
- Enhance incident response times and minimize downtime via cross-team collaboration features.
- Uncover valuable insights and patterns across business applications and make accurate predictions to optimize IT operations.
- Gain comprehensive IT environment visibility to address potential issues before they impact operations.
Top Features
Sniper offers a range of state-of-the-art AIOPs features such as:
- Alert noise reduction and correlation
- Metric causal and correlation analysis
- NLP-based recommendations
- Probable root cause analysis
- Hybrid/cloud environment support
- Observability
Top Benefits
Sniper delivers several key business benefits including:
- 70-90% reduction in alerts, allowing teams to look at and solve meaningful alerts only.
- Reduced people dependency leading to a 30-50% improvement in ITOps team optimization.
- Multiple application performance monitoring dashboards consolidated in one, resulting in a 40% reduction in resolution time.
- Improved user experience monitoring leading to higher conversion rates across multiple user journeys via real-time AI-assisted business insights.
Top Use Cases
Increasing reliance on technology demands high technology QoS (Quality of Service). However, it is increasingly becoming difficult for IT teams to deliver on performance and availability SLAs of business applications due to:
- The presence of heterogeneous systems, agile processes, and multi-clouds
- Alert fatigue caused by the avalanche in data volumes, variety, and velocity. 70-90% of alerts are false negatives/positives.
- Dependence on manual root cause analysis that is not only time-consuming but also extremely error-prone.
- Lack of alert consolidation because of using multiple application performance monitoring tools for the same application/IT stack.
- Siloed approaches due to poor collaboration across Ops and Dev teams.
appNeura Sniper unleashes next-gen AIOps enabling organizations to monitor and enhance IT operations. By enabling automation across IT stacks & heterogeneous IT environments, it helps teams deliver on performance and availability SLAs. By reducing the alert storm by 70-90%, it allows businesses to enable necessary performance benchmarking and meet required availability SLAs.
Transform Your Approach to AIOps with Sniper
As organizations look to streamline ITOps, the heavy reliance on manual processes causes several issues along the way. To achieve compelling benefits, one needs to embrace a unified solution that enhances IT systems availability and performance monitoring.
Embrace Sniper today to automate the process of analyzing, de-duplicating, blacklisting, and correlating events and alerts. Automatically bring down the number of alerts and incidents and expedite root cause identification.
NLP-based resolution recommendations are the cherry on the cake, as these resolutions can be used, rated, and edited by engineers.
Get a free Sniper demo today!