As the complexity of application and cloud environments increases exponentially, ITOps and DevOps teams are increasingly turning to AI to automatically monitor, analyze, and report on the data that is collected. And with the rise of AIOps across organizations, we’re pleased to say that G2 has recently updated their ranking for the top AIOps Vendors, and Dynatrace ranks #1.
With 935 reviews at the time of publishing, and a score of 4.5 out of 5, Dynatrace easily accounts for Splunk (266) and 4.2 out of 5 and Cisco AppDynamics (204) and 4.2 out of 5.
There are many great quotes to choose from but this one summarizes the next section of the blog so well – “It’s APM but it’s so much more, including ‘revolutionize the performance monitoring and AIOps space.”
AIOps definition and classification
Dynatrace for a long time wasn’t even considered in the AIOps category. How could this be? When you review what the criteria are for AIOps vendors it covers precisely what the Dynatrace Software Intelligence Platform can do. Importantly – not including all that it can do, which I’ll come back to.
The basic premise of AIOps is:
- Automatically monitor and analyze large sets of data across applications, logs, hosts, services, networks, meta, and processes through to end-users and outcomes.
- Create a topology of how everything is interconnected.
- Automatically baseline performance and present findings on what can be improved.
- Provide root cause and assist in mean time to repair (MTTR).
- Minimize alert noise from disparate systems.
- Integrate into ITSM platforms for enriched ticket details, CMDB updates, and ticket routing.
Given the list above, you’d argue Dynatrace is purpose-built as the ultimate AIOps platform. So why are we sometimes omitted?
Because we do much more than just AIOps. Dynatrace is a full-stack, all-in-one platform strategy vs a niche tool in a single category. It’s actually a lot harder to market that you are a leader in this, and that, and this, and that, than if you focus on one category.
Dynatrace customers speak to the value of Davis and AIOps
Whilst we are sharing the value of AIOps, it’s worth including a reference to our customers, who have enjoyed using our AI engine Davis for years. Before the AIOps category even emerged.
Dynatrace ranks #1 in multiple categories on G2 Crowd
As a true all-in-one platform we are pleased to be a leader in every one of the below categories;
- AIOps Platforms Software
- Application Performance Monitoring (APM) Software
- Container Monitoring Software
- Session Replay Software
- Cloud Infrastructure Monitoring Software
- Digital Experience Monitoring (DEM) Software
For more on our scoring and reviews, check out the press release here.
Niche machine learning like Moogsoft vs purpose-built full-stack Dynatrace
There are different approaches to AIOps. I’m not going to spend an entire blog dissecting the ins and outs but instead will summarize for you.
Some vendors, who were early market movers, like Moogsoft, gather data and then run algorithms and machine learning on top of the data to provide insights. It’s a good solution to minimize alert noise, but it’s difficult to ascertain adequate actionable insights given the disparate data it’s analyzing. It’s also not as simple to get started, as you need to configure all data sources and consume people hours to configure, test, and measure.
If you do have legacy monitoring tools, and can’t modernize, or are stuck without Dynatrace, it’s better than most. Obviously, if you could collect the data and analyze it in the one platform, it’s by far more beneficial in terms of the ability of the AI to provide more actionable and precise answers.
Biased? Of course, which leads me to the Dynatrace solution.
Dynatrace primarily collects its own data using it’s a single agent-based deployment, as well as integrating and enriching data collection through the ecosystem. The depth and breadth of the data collected, as well as the power and domain-specific intelligence from the AI-engine Davis, means the answers provided are precise, actionable, and always in context.
For a detailed analysis of how our approach to AIOps, you can download our AIOps Done Right eBook.
Correlation vs Causation – Sounds techie but it’s important
If you are in need of answers, and the answers impact the performance of your digital systems and ultimately brand, revenue, and potentially your job, it’s best not to guess. Trusting the data you present is more important today than ever before.
Joseph Hoffman did a blog a few years back that explains why Causation approaches are critical.
Personally, I still think the below example is the best representation of why correlation can at times provide comical insights:
Shout out to Hamilton Chang for this insightful correlation.
Try Dynatrace today
Okay. If you made it this far, you should probably give Dynatrace a go. Alternatively, you can check out the following resources if you need further convincing: