Top 3 BigPanda Competitors and Alternatives for AIOps (+ Our Recommendation for SMBs)
BigPanda, recognized as the best cloud automation solution, is an incident intelligence and automation platform created to assist IT operations teams in managing the complexities of modern production environments.
By eliminating the silos that typically isolate tools and processes, BigPanda reduces ticket volume by 60% and cuts MTTR (Mean Time to Resolution) by 40%.
However, if you’re looking for an alternative to BigPanda for your business needs or the following reasons, you have reached the right place.
- Slow response times from BigPanda’s support, typically spanning 3 to 5 days
- Its inability to show the alert count in specific incidents
- Its Activity Tab lacks the ability to filter between comments, incident sharing, and status changes
- Its machine-learning capabilities are lacking, as it only offers a basic table for alert correlations
In this post, we’ll present a comprehensive review of three AIOps tools: appNeura, Moogsoft and ScienceLogic SL1.
Bigpanda Alternatives: Top 3 Competitors to Check Out in 2023
In the three alternatives we are covering today, appNeura Sniper stands out due to its proficient team, potent recommendation engine, and use of unsupervised learning. Moogsoft is known for its robust incident management system and advanced AI capabilities. Users appreciate the comprehensive infrastructure monitoring and automated discovery features of ScienceLogic SL1.
Presented below is an in-depth review of each of these tools.
Bigpanda Alternatives #1 :appNeura Sniper
appNeura Sniper is an AIOps Incident Management Platform that leverages big data and AI/ML technologies to enhance IT systems’ availability and performance monitoring.
It utilizes sophisticated algorithms to automate the analysis, deduplication, blacklisting, and correlation of events and alerts.
What would take humans hours to accomplish can be done in mere minutes with Sniper.
The platform can automatically reduce hundreds of thousands of alerts and events to hundreds of alerts and tens of incidents, thereby streamlining and optimizing IT operations management.
Key Features of Sniper
Sniper comes with an array of robust features designed to optimize your ITOps processes:
- Unsupervised PRCA Engine
- Alert Noise Reduction and Correlation
- Metric Causal and Correlation analysis
- NLP-Based Recommendations for Resolving Issues
- Observability
- Domain Expertise
Unsupervised PRCA Engine
One of Sniper’s standout features is its unsupervised Probable Root Cause Analysis (PRCA) engine, which leads to the following benefits:
- Improved Efficiency: The PRCA engine can sift through massive amounts of data and identify underlying patterns much faster than a human can, leading to quicker identification and resolution of problems.
- Reduced Error: The automated nature of the unsupervised PRCA engine minimizes the chance of human error that can occur during manual root cause analysis.
- Proactive Problem-Solving: The engine can detect anomalies and deviations from the norm, enabling the ITOps team to proactively identify potential issues and intervene before they escalate into more significant problems.
- Mitigated Future Risks: By identifying the root causes of past incidents, the PRCA engine can help prevent similar issues in the future, thereby increasing system reliability and uptime.
- Lower Operational Costs: By automating root cause analysis, the PRCA engine reduces the need for manual intervention, saving time and reducing operational costs.
Alert Noise Reduction and Correlation
Sniper is a game changer with its advanced alert noise reduction and correlation features.
By employing machine learning, Sniper efficiently manages alert storms from various APM tools during cascading incidents. It detects and eliminates duplicate alerts to reduce noise and mitigate alert fatigue.
This function can reduce alerts by up to 90%, enabling your IT team to focus on critical incidents, thus improving your IT operations. Moreover, Sniper’s robust system has been tested to handle up to 5 million incidents per minute.
Metric Causal and Correlation Analysis
Managing data and metrics in today’s IT environment has become complex due to the sheer volume and diversity of information produced by various systems and applications.
In this context, Sniper’s automated metric correlation feature is critical for efficient incident management. It proactively correlates incidents across multiple data sources, identifying relationships and dependencies.
This capability allows IT teams to quickly identify incident root causes, thereby reducing mean time to detect (MTTD) and repair (MTTR) and employing machine learning and pattern recognition to reveal intricate metric relationships.
By unveiling these hidden insights, Sniper enables IT teams to address issues and ensure peak system performance promptly.
NLP-Based Recommendations for Resolving Issues
Sniper provides a proactive solution for incident resolution with its NLP-based Recommendation Engine, designed to address incidents before they affect end users.
Leveraging supervised learning, Sniper’s engine utilizes insights from over 5000 resolved technical issues to suggest performance issue solutions.
Its expansive knowledge base integrates information from various resources, including technical documents, online articles, and user feedback.
Furthermore, Sniper’s capacity for automated incident resolution, based on its past problem-solving experiences, enhances IT team productivity and efficiency.
Observability
Sniper facilitates observability by analyzing data from metrics and logs, allowing for swift issue detection and performance optimization.
It enables distributed tracing to understand request flow across multiple systems and uses AI and machine learning for anomaly detection.
Offering real-time monitoring, it allows IT teams to address issues proactively.
Supported Integrations
- APM: Dynatrace, Appdynamics, Zabbix, Datadog, Newrelic
- Cloud: AWS
- Open Source: FileBeat, MetricBeat
- Ticketing Tools: JIRA, Freshdesk and Lighthouse
Advantages of Using Sniper
- Ease of Use with Unified Dashboard – Users can access all the necessary monitoring information in one dashboard with a unified view of the monitored systems.
- Exceptional Domain Expertise – The team behind Sniper offers unparalleled domain expertise. With a decade of proven performance engineering experience, it excels at solving complex performance issues within enterprise IT.
- Patented Technology – The company behind Sniper holds a patent for batch monitoring of performance data – US Patent No 10025659 – used to compute the context of the system alerts.
Bigpanda Alternatives #2: Moogsoft
Moogsoft is an AIOps and observability platform that offers a range of features that help IT teams reduce noise, detect incidents early, identify root causes, and automate incident management workflows.
Moogsoft lets businesses visualize patterns based on text, time, and topology across systems to identify changes and incidents affecting the service.
Key Features of Moogsoft
- Noise Reduction
Moogsoft applies statistical calculations and noise reduction algorithms to remove noise and distractions.
- Enrichment
Moogsoft’s Enrichment feature automatically adds context to troubleshooting by referencing external data sources, which helps to deliver better correlation and reduce noise.
- Anomaly Detection
By leveraging machine learning and advanced correlation techniques, Moogsoft guarantees uninterrupted operations. Its cutting-edge capabilities enable proactive incident detection and prevent potential issues.
- Correlation
Moogsoft’s advanced correlation automatically detects anomalies and connects the issue between all alerts, enabling IT teams to identify root causes faster.
- Custom Integration
Moogsoft’s custom integration feature allows users to connect all their disparate observability and monitoring tools easily.
- Collaboration
Moogsoft’s collaboration feature provides multiple channels and tools for cross-functional collaboration, enabling teams to work collectively.
- Self Service
Moogsoft’s self-servicing feature offers observability on demand with an intuitive interface, instant answers to questions, and easy integrations.
Limitations of Moogsoft
Moogsoft is an industry-leading AIOps and observability platform. However, there are some limitations to using Moogsoft that customers have mentioned.
Some of the major limitations are:
While evaluating user reviews on various forums, some customers complained about Moogsoft’s automation process. They said it creates too many tickets for the same issue causing inconvenience. Here’s one such review.
Some customers have also complained that Moogsoft does not properly connect to their ticketing system, correlate events, remove worked alerts, and allow comments.
Bigpanda Alternatives #3: ScienceLogic SL1
ScienceLogic SL1 is an AIOps platform connecting your estate to automate multi-directional data flows and workflows. The platform breaks down data silos by merging data from any technology, vendor, and location into a real-time, operational data lake of events.
Source – ScienceLogic
Key Features of ScienceLogic SL1
- Hybrid Cloud Monitoring
Hybrid cloud monitoring enables organizations to monitor and optimize the performance of diverse resources across on-premises and multi-cloud environments, bridging visibility gaps, correlating impact, reducing event noise, and enhancing service performance and reliability.
- Business Service Visibility
Business service visibility enables organizations to model multi-tier services, integrate app relationships, dynamically detect topology changes, assess service impact, and expedite incident resolution by leveraging anomaly detection, correlation and recommended actions to speed up incident resolution.
- ITSM Workflow Automation
ITSM workflow automation keeps CMDB up to date, unifies monitoring, syncs with ITSM tools (e.g. ServiceNow, Cherwell, BMC Remedy), automates ticketing, eliminates manual workflows, reduces risk and costs, and tracks CI changes for ITOps & DevOps alignment.
- IT Workflow Automation
IT workflow automation automates troubleshooting, enriches tickets with real-time data, accelerates incident resolution, reduces MTTR, enables low-code workflows, and expedites automation roll-out, reducing manual work and accelerating technology onboarding.
Limitations of ScienceLogic SL1
ScienceLogic remains a popular choice for IT infrastructure monitoring and management, providing organizations with various features to gain better visibility into their IT environment, automate workflows, and improve security and compliance.
However, based on the reviews on popular forums like G2, Gartner Peer Insights and TrustRadius, ScienceLogic has some limitations. Let’s look into some of them.
According to a review on TrustRadius, users have to switch between different monitoring tools or platforms. Not providing a unified view of the monitored systems creates confusion and is time-consuming.
A few customers also complained about delays between when an issue occurs and when the platform alerts about it. Such delays can be problematic, leading to more extended downtimes.
Unleash the Next Generation AIOps With Sniper
Sniper by appNeura is ideal for small businesses and startups seeking AIOps to monitor and enhance their IT operations.
What sets Sniper apart from competitors is its proficient team, who has a strong background in performance engineering.
By using unsupervised PRCA, a recommendation engine, and a vast knowledge base of 5000 complex cases, Sniper’s proactive resolution helps you prevent similar issues and automate incident resolution.
Sign up for a free trial of our intuitive solution that combines the power of big data and AI/ML functionality to enhance your IT systems’ availability and performance monitoring significantly.