7 Features to Look for in AIOps Tools
As enterprise networks evolve, the transformation to digital business applications brings a cascade of ongoing challenges to maintaining service uptime.
- More often than not, services coexist with legacy systems, increasing the complexity to manage them
- Over time, the diversity of the components and services that comprise the infrastructure typically results in the deployment of multiple management tools
- This tool proliferation makes it even tougher to maintain a coherent view of the overall picture, and the resulting information silos make for the inefficient use of available data
- Compounding the problem, the increased number of events, logs, and information generated by these components threaten to overload IT operations teams
As a result of these challenges, it is becoming increasingly difficult to figure out the cause of issues in the infrastructure or to do so in a proactive manner. This results in longer Mean Time to Resolve (MTTR), which leads to degraded service delivery, negative customer experience and unsatisfactory outcomes in general.
The Advent of AIOps Tools
Fortunately, as the challenges evolve, so do the approaches to mitigate them. The advent of artificial intelligence for IT operations tools and platforms (or AIOps tools and platforms, for short) has revolutionized the service assurance landscape. AIOps platforms provide the capabilities that are best suited to manage the complexity and scale of the digital transformation of modern business service delivery.
According to Gartner, “AIOps platforms combine big data and machine learning functionality to support primary IT operations functions through the scalable ingestion and analysis of the ever-increasing volume, variety, and velocity of data generated by IT. The platform enables the concurrent use of multiple data sources, data collection methods, and analytical and presentation technologies.”1
The best AIOps tools primarily provide value by aggregating data, then extracting insights, and, finally, by acting upon this intelligence. So what features should you look for in your AIOps tools comparison?
1. Data Collection
Look for systems that play well with others. Essentially, your AIOps solution needs to be able to gather information from a diverse set of sources. These can include both physical infrastructure components and virtual entities such as services and applications. As they are deployed, they must be able to work with existing monitoring tools as well as new technologies.
2. Data Aggregation
Looks for capabilities that facilitate collaboration across domains. For starters, your AIOps solution needs to be able to aggregate data from IT infrastructure monitoring (ITIM), network performance monitoring and diagnostics (NPMD), digital experience monitoring (DEM) and application performance monitoring (APM).
3. Data Enrichment
Aggregation is a useful first step, but to realize true value, look for AIOps tools that enrich the data that is collected. Historical data, such as logs and events, offer a retroactive view and can be enriched by applying metadata and tags to provide context for search in indexing.
Real-time data such as performance and telemetry information can be enriched to generate useful time-series information by overlaying data points with time stamps. When this information is used later, adding suitable labels to provide key-value pairs brings further value.
4. Analytical Insights
Insights are the core of the value that AIOps tools provide. Look for capabilities that go beyond basic correlation and statistical analysis to determine root cause. Pattern discovery and anomaly detection are key features of a good AIOps system. They provide the basis for prescriptive insights that facilitate proactivity.
Beyond insights into the operation of the infrastructure, look for AIOps systems that provide the business impact of issues in the infrastructure. This enables service-level agreement (SLA) management and delivers immense value when dealing with non-technical stakeholders.
Automations bring about efficiency and effectiveness to IT operations management. Look for AIOps tools that provide the ability to rapidly generate and deploy workflows and automation. Look for capabilities that include the ability to maintain automation libraries while providing rapid sharing of workflows across operational streams. Superior automation capabilities lead to increased agility and a reduction in inadvertent process errors and also foster a higher level of service availability.
6. Ease of Use
AIOps platforms that provide a cloud-based management layer can provide immense efficiency by allowing IT teams to address problems across multiple sites and multiple customers in a secure and distributed fashion. AIOps platform that provide a monitored data pipeline make it easier for other tools to access collected information and to facilitate collaboration across teams.
7. Flexible Deployment of AIOps Products
When it comes to your service assurance needs, no two situations are alike. Looks for AIOps products that provide options when it comes to deployment. It is essential that the deployment model match the unique needs of your business and operational needs, whether that means utilizing a self-managed, remotely administered, or a platform-as-a-service approach.
AIOps Is Here to Stay
According to Gartner, 30% of large enterprises will be using AIOps platforms by 2023.2 AIOps use cases demonstrate the ability to bring about truly proactive IT operational management capabilities. They provide a superior approach to managing the complexity of your ever-evolving infrastructure.
Selecting one of the top AIOps tools to manage your business is key to the strategic outcomes of your business. Make sure your IT operations service provider takes the features covered above into consideration.