AI Solutions

The Top 8 AIOps Solutions

Explore AI for IT operations (AIOps) platforms that ensure efficient and scalable AI workflows in production environments through features including data analysis, alert management, and automated remediation.

The Top 8 AIOps Solutions include:
  • 1. Aisera AIOps Platform
  • 2. BigPanda
  • 3. BMC AIOps
  • 4. FreshWorks FreshService
  • 5. IBM AIOps Solutions
  • 6. Infosys AI Operations
  • 7. ScienceLogic SL1
  • 8. ServiceNow Predictive AI Ops

AIOps solutions, (Artificial Intelligence for IT Operations), are tools that use machine learning and big data analytics to automate and optimize IT operations processes such as issue detection, event correlation, root cause analysis, and remediation. AIOps solutions extract and aggregate data from across the IT infrastructure and collate that data in a single, central big data platform. Once the data is collected, the AIOps solution applies machine learning algorithms—including predictive analytics and anomaly detection, to the data—enabling it to identify patterns, relationships, anomalies, and issues. When an issues is identified, the solution either initiates an automated corrective response, or sends targeted alerts to the appropriate IT personnel, minimizing troubleshooting time.

Using AIOps, IT and DevOps teams can improve system reliability and performance, reduce operational expenses, enhance productivity due to minimized system disruption, improve their mean time to respond (MTTR) to threats or issues in their environment (or, in the case or DevOps teams, their application), and improve employee satisfaction. That’s because AIOps solutions eliminate the need for IT staff to manually sift through countless system logs and error messages, allowing them to focus on strategic initiatives and innovation.

In this article, we’ll explore the top 10 AIOps solutions designed to help you streamline and optimize your IT operations. We’ll highlight the key use cases and features of each solution, including data analysis capabilities, automated remediation, alert management, integration with other management tools, and usability.

Aisera

Aisera’s AIOps Platform aims to improve how ITOps, CloudOps, DevOps, and NOC teams can detect and handle major incidents and performance issues. By utilizing domain-specific language models through features like AI Copilot and AiseraGPT for AIOps, Aisera correlates incidents from ticketing platforms to relevant data from monitoring tools. This process helps accurately pinpoint root causes, speeds up resolution times, and reduces downtime. Aisera provides proactive real-time alerts and notifications about infrastructure, applications, and microservices health status, communicated in a user-friendly natural language form.

The Aisera AIOps Platform offers AI-powered observability, designed to work across any vendor or domain to provide a comprehensive view of the entire technology stack. A key feature of this platform is automated root cause analysis, minimizing time spent on resolving major incidents by producing detailed cause-effect graphs and providing natural language explanations. Supplemented by supervised, unsupervised, and human-in-the-loop AI, the accuracy of predictions is continuously improved.

The AI Discovery feature provides alerts, logs, traces and metrics to track endpoints, apps, and infrastructure, ensuring no security compromise or blind spots. In addition, the dynamic CMDB and Probabilistic Service Maps feature uses data from incident requests, change requests, and alert data to provide a current and accurate image of service topology. Aisera also features AI workflows for remediation that automatically triage and fix significant incidents, suggesting the most effective course of action.

Aisera
BigPanda Logo

BigPanda is an AIOps solution focusing on delivering actionable alerts and preventing IT incidents. The core offering of BigPanda is a unified operational suite, with features including an Open Integration Hub, Alert Intelligence, Incident Intelligence, and Workflow Automation.

The Open Integration Hub combines monitoring, changes, topography, service maps, and trace information. It provides a central hub for managing the operational status of IT systems. Together with the Alert Intelligence feature, it consolidates event and alert data, reduces alert noise, identifies actionable alerts, and eliminates monitoring silos. The Incident Intelligence feature helps to pre-empt problems, triage using business context, investigate potential root causes, and reduce disruptive conference calls. The Workflow Automation feature automates known incident response steps, reduces escalations and minimizes interruptions, generates automatic ticketing through bi-directional ITSM sync, and alerts the correct response teams via automated chat and page notifications.

BigPanda’s solution also includes an Event Enrichment Engine and Generative AI. The Event Enrichment Engine harmonizes data from various sources into context-rich alerts ready for correlation. BigPanda’s Generative AI delivers instant insights, including real-time root cause analysis. The Generative AI is designed to save time on each incident, reducing incident escalations. BigPanda’s toolbox also includes Unified Analytics, which aggregates operational data to provide metrics of the highest relevance to your organization. These features aim to provide comprehensive understanding and control over IT networks, ensuring more efficient system performance and less downtime.

BigPanda Logo
BMC Logo

BMC offers a range of AIOps solutions designed to enhance visibility and generate proactive insights across various application infrastructures, including cloud, data center, and mainframe. Their solutions facilitate real-time activity monitoring and swift identification and response to issues, whilst enabling IT personnel to concentrate on high value projects.

BMC’s AIOps solutions use artificial intelligence and machine learning algorithsm to quickly identify operational issues. The platform consolidates enterprise data sources into a unified, actionable view. Specific products featuring these capabilities include BMC Helix Operations Management with AIOps, and BMC AMI Ops.

BMC’s tools also have built-in anomaly detection that automate responses based on metrics, helping to reduce manual incident management, improve mean time to resolution, and increase service availability. These features can be found in their BMC Helix Operations Management, BMC AMI Ops, and BMC Helix Continuous Optimization products.

Finally, BMC’s AIOps software suite provides advanced analysis of data across infrastructure and applications. This allows for faster root cause analysis, improved resource management, and efficient resource and container optimization. These features are available in their BMC Helix Continuous Optimization and TrueSight Capacity Optimization products.

BMC Logo
Freshworks Logo

FreshWorks’ FreshService helps teams to manage IT complexity by providing AI-powered solutions for data analysis and issue resolution. As its key feature, FreshService uses an enterprise-grade AI engine called ‘Freddy’ to perform Automated Grouping, a function that improves the incident context and reduces time taken to find and fix issues. This is achieved by studying and correlating alert patterns from various sources and then associating relevant alerts to open incidents, enriching their context and reducing duplication.

FreshService delivers powerful automation tools that eliminate the need for repetitive tasks and manual processes, thereby enhancing the efficiency of service functions. This is combined with a no-code customization platform, enabling streamlined integration of service management across departments, increased visibility, quicker issue resolution, and cost savings.

FreshService is quick to deploy deployment via its easy-to-use no-code platform. This is complemented with expert onboarding, migration services, and round-the-clock support, ensuring a smooth implementation and operation process for businesses. Through the deployment process, FreshService ensures that any new or incoming alerts are automatically added into the system, keeping incidents updated in real-time and ensuring businesses can benefit from protection from the get-go.

Freshworks Logo
IBM Logo

IBM offers an array of Artificial Intelligence for IT Operations (AIOps) solutions. With an emphasis on automation, these solutions assist in optimizing IT operations and enhancing DevOps processes. IBM’s AIOps portfolio includes IBM Instana Observability, a tool for real-time application and IT infrastructure analysis, and IBM Turbonomic for cost-effective cloud optimization. Also available is IBM AIOps Insights, a SaaS offering that provides central IT operations teams with holistic visibility and holistic incident triage for speedier response times and reduced costs.

IBM’s AIOps solutions offer multi-faceted capabilities such as FinOps operationalization for data-driven cloud-spending decisions, aiding in responsible computing practices to cut data centers’ energy consumption and carbon emissions, and improving continuous integration and continuous deployment (CI/CD) pipelines. They also help to assure application performance by balancing costs against continual performance and optimizing resource utilization to meet demand.

IBM provide AIOPs tools for strengthening system resilience, offering real-time root cause analysis to mitigate incidents effectively. Overall, IBM’s AIOps solutions assimilate IT operations across the entire toolchain, offering a singular, comprehensive view for improved collaboration and efficiency.

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Infosys

Infosys AI Operations is a comprehensive platform designed to boost the performance, reliability, and availability of your key business apps. Developed on Infosys’ Live Enterprise Application Management Platform, this solution merges predictive analytics with site reliability engineering techniques, whilst offering full stack observability.

Infosys AI Operations provides full-stack observability so teams can oversee the performance of applications and their associated IT stacks, down to the core network and infrastructure. This feature allows for the reduction of noise from multiple data sources such as alerts, logs, metrics, and traces. This enables teams to detect potential disruptions and anomalies, and in many cases auto-corrects performance or availability issues before the end-customer or business operation is affected, improving application resiliency. Infosys applies principles of site reliability engineering to sense various signals including infrastructure alerts, application components, and database server data. The Live Enterprise AIOps engine processes this data using correlations, anomaly detection, and prediction algorithms. The system then triggers automated actions powered by the platform’s BOT Factory, whether that be self-correction or automated notifications.

A range of additional features are incorporated into the platform, including code level metrics, user experience, and behavior telemetry. It also offers intelligence features such as anomaly detection, root cause analysis, and knowledge graph analytics, alongside self-healing automation facilities for problem prioritization, auto-remediation and real-time monitoring of business process KPIs. The Infosys AI Operations platform also includes a digital business control center offering real-time KPI visualization and full visibility of failure points.

Infosys
ScienceLogic

ScienceLogic SL1 is a technology management solution that provides comprehensive visibility into multi-cloud and distributed architectures. The platform enables the discovery of all enterprise components, accumulating and storing diverse data in an orderly and normalized manner.

SL1 creates a relationship map between infrastructure, applications, and business services, and then uses AI/ML to generate meaningful insights from this data that can help inform decisive actions. Taking an integrated and interconnected approach, it can utilize normalized data to drive intelligent automations within an organization’s IT environment.

SL1’s monitoring capabilities extend to a wide variety of both legacy and emerging technologies. These include public clouds, virtualization solutions, servers, storage, and more. The platform ingests multiple data points and houses them in a consistent operational data lake that grants end-to-end visibility to an organization’s IT estate. The real-time SL1 PowerFlow service augments data synchronization with IT ecosystem tools, elevating automated workflows across various systems.

ScienceLogic ensures a vigorous security posture for SL1, safeguarding client data through industry-standard security technologies and processes. The solution can be deployed in different environments, based on customer preference, including on-premises, customer-managed public clouds, or through a ScienceLogic-managed SaaS, making it suitable for a wide range of organizations looking to improve and streamline their IT operations.

ScienceLogic
ServiceNow Logo

ServiceNow Predictive AIOps is an artificial intelligence-powered solution designed to predict and pre-empt service issues, preventing negative impact on users and speeding up remediation process. The major advantage of this tool is its ability to turn an unmanageable number of events into prioritized, actionable alerts.

ServiceNow Predictive AIOps employs machine learning-driven techniques to analyze logs and metrics, which enables it to detect anomalies in application behavior that conventional monitoring methods might overlook. By utilizing machine learning and analytics, Predictive AIOps can proactively discover and resolve complicated, unforeseen service complications, specifically in evolving cloud and virtualized environments.

The solution consists of three key components: Log Analysis and Anomaly Detection, Metric Analytics, and Event Management. The Log Analysis and Anomaly Detection feature uses machine learning to determine standard operating patterns in logs, traces, and metrics, then spot disruptions to pre-emptively flag potential service issues. Metric Analytics uses machine learning to model normal metrics behavior, set adaptive thresholds, and detect anomalies. Event Management reduces the noise from event tags and metrics.

Predictive AIOps also facilitates automatic remediation of service issues by responding automatically to identified alerts. Users can utilize the solution’s Flow Designer and IntegrationHub to create remediation actions that can be triggered automatically or manually initiated. The tool also includes connectors to many log collection tools, which can be integrated with other event sources.

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The Top 8 AIOps Solutions