Top 8 AIOps
DatadogDynatraceDevoLogicMonitorBMC TrueSight Operations ManagementScienceLogicNew RelicOpsRamp
Datadog provides tracing and logging, whereas Dynatrace focuses on tracing, and Splunk is more of a logging tool. Datadog's advantage is that we don't need two tools.
Dynatrace has multiple features that I need, but I love that you can analyze traffic, including any bottlenecks. I also find the tool user-friendly and has an easy-to-navigate interface.
The alerting is much better than I anticipated. We don't get as many alerts as I thought we would, but that nobody's fault, it's just the way it is.
The most useful feature for us, because of some of the issues we had previously, was the simplicity of log integrations. It's much easier with this platform to integrate log sources that might not have standard logging and things like that.
The initial setup is very simple.
It is easy to set up and monitor an entire facility. This is crucial because we have around 80 facilities that require monitoring. LifePoint is a hub-and-spoke environment, so it is essential to understand all of the WAN interfaces.
What I like best about BMC TrueSight Operations Management is that it allows you to do granular monitoring and improves VM load.
The most valuable features of BMC TrueSight Operations Management are the blackouts and event management.
The most valuable features of ScienceLogic are AI and machine learning.
It has good monitoring capabilities across cloud environments, data centers, and hybrid environments.
New features are added often.
The pricing is pretty good.
Predictive analysis is a valued feature.
The feature we found most valuable in OpsRamp is alert generation because whenever there is any kind of spike on any virtual machine, the solution generates alerts based on the thresholds we implemented. We have integrated our ideas and tools with OpsRamp, so alerts are generated, then we notify the customers. That's the main feature we like about OpsRamp because we don't have to monitor each resource. Instead, OpsRamp does the monitoring for us, and it generates the alerts based on the thresholds.
Advice From The CommunityRead answers to top AIOps questions. 672,785 professionals have gotten help from our community of experts.
What are the four key stages of AIOps preparation?What are the four key stages of AIOps?What are the key benefits of AIOps?How can the benefits accrued through the use of AIOps be maximized?What is the difference between AIOps and DevOps?What are AIOps solutions?Benefits of AIOps PlatformsFeatures of AIOps Platforms
What are the four key stages of AIOps preparation?
When an organization wants to implement an AIOps solution, there are four key steps that are essential to their success. These four stages of the AIOps process are:
- Identification of problems. Before an organization aims to deploy an AIOps solution, they should first gauge what kinds of issues the IT team is confronted with and, by extension, what AIOps capabilities the organization needs.
- Understand the virtual environment. After an organization that is considering using an AIOps strategy figures out what its needs are, it should take stock of its IT resources. During this stage, the organization takes inventory of what it has available, not only in terms of digital tools, but also the teams that it can deploy. This inventory makes it possible for a business to plan for the kind of AIOps solution that they want to deploy.
- Define the criteria of success. The third step that an organization should take when they are considering deploying an AIOps solution is to decide what would constitute a successful deployment. The business will want to figure out what metrics they want to measure. This enables them to create a vision that they will be able to refer back to throughout the solution’s deployment. That baseline also makes it possible for them to set achievable concrete goals for themselves.
- Determine where to start. This final stage forces an organization to choose how they are going to begin deploying their AIOps strategy. It asks them to choose the goal that they want to tackle first. The simplest way to think about it is that this stage is where the organization creates the initial plan of attack for their AIOps deployment.
What are the four key stages of AIOps?
AIOps data collection consists of four key steps. The four steps are:
- Data collection. The very first stage of any activity performed by AIOps solutions is to collect data from an organization’s IT architecture. This initial stage provides the AIOps platform with the information it needs to effectively run operations.
- Data aggregation. In the second stage of the AIOps process, the solutions take the data that they collected and begin to sort the various pieces. This results in their being transformed into manageable packets consisting of similar data.
- Data analysis. Once the data has been compiled, it is then analyzed by the software. It picks through the data and uses it to make the system aware of everything relevant to its successful operation. At this stage, the system also makes decisions as to how it is going to interact with the organization’s IT architecture.
- Execution of the operation. During this final stage, the AIOps platform takes what it has gleaned from the data and uses it to take concrete action. The decision that the platform arrived at in the previous stage is initiated at this point.
What are the key benefits of AIOps?
Organizations that choose to employ AIOps software can benefit in many ways. These benefits can include:
- Event triaging. AIOps solutions enable users to triage events that take place in the organization’s network. The AI capabilities can grade the events so that users can devote their time and resources to those events that most demand them.
- Reduction of IT operational costs. Organizations that deploy AIOps software can cut the amount of money that they have to spend to run IT operations. They are able to proactively address issues and remedy them before they can develop into costly problems.
- Improved collaboration. AIOps takes an organization’s IT data and makes it actionable. Teams working on a project have access to enriched data that makes it easier for every member to be on the same page. Disparate departments are able to work together and access shared files with ease.
How can the benefits accrued through the use of AIOps be maximized?
In order for AIOps to be most effective, it should not exist in a vacuum. This process should be employed separately, but at the same time in conjunction with an organization’s already existing architecture. The AIOps solutions should be set up so that they can process all of the business’s IT data without being just another cog in the IT infrastructure. They should be an independent platform that is integrated with the existing system. This enables organizations to leverage all of their artificial intelligence capabilities to the fullest.
An organization looking to maximize the benefits that they gain through the implementation of an AIOps solution will want to diversify the needs that it serves. Instead of focusing on one or two highly specific areas of need, users will want to target many different functions. When organizations do this, they are able to address many more of the potential issues that can confront modern IT departments than if they were to limit the scope of their AIOps reach.
What is the difference between AIOps and DevOps?
DevOps are the set of practices that integrate software development and IT practice teams and tools. AIOps are tools that might be utilized by organizations that deploy DevOps practices.
What are AIOps solutions?
AIOps solutions are solutions that combine various types of AI technologies to enhance and improve the way that organizations run their IT operations.
Benefits of AIOps Platforms
AIOps platforms offer users various benefits. These benefits include:
Streamline IT operations. Users gain the ability to streamline the way that organizations go about performing their IT operations. AI technologies make it so that every aspect of IT operations are smoothly automated. This simplifies the process of conducting operations.
Remove uncertainty. AI technologies enable users to locate issues and potential issues so that they can be addressed. Users can conduct operations and remedy issues with solutions that their AI systems feed them based on all of the available data. Administrators don’t need to spend significant time trying to find an answer to an IT issue.
- Continuously monitor your digital environment. AI technologies enable users to keep up with growing digital environments. Users never need to worry about lapses in security. Their AIOps solution will make it possible for organizations to keep track of their growing IT architecture in ways that systems that rely on manual methods cannot.
Features of AIOps Platforms
Successful AIOps platforms offer users access to a wide array of features. These features include:
- Data collection. This feature enables an AIOps platform to integrate with databases and collect relevant bits of data from them.
- Data enrichment. Platforms that have this feature can take collected data and make them more meaningful than they would be as bits of raw data. It allows users to add contextual information that could help future analysis.
- Analytical insight. This enables the solution to dig into the data that it collects and mine it for valuable insights. Trends and other valuable pieces of information can enable users to be proactive instead of reactive.