COVID-19 has impacted the lives of almost everyone on the planet. Health and safety are obviously the top concerns. But as everyone knows, it has also severely disrupted businesses worldwide and has, specifically, created chaos for CIOs as they struggle to ensure operational continuity even as things change in an unprecedented fashion overnight.

It’s common for modern businesses to rely on 2,000+ custom-developed applications and it requires substantial cost, time and effort to ensure 24/7 optimal performance of those applications. IT Ops teams depend on advanced application performance monitoring (APM) to scale up key business capabilities and boost innovation. But the APM tools that provide the deepest insights for critical applications are extremely expensive and are cumbersome to deploy.

Gartner’s latest Market Guide for IT Infrastructure Monitoring Tools has just been released, and we are once again proud to be included as a Representative Vendor. Unsurprisingly, Gartner has found that customer trends toward the adoption of multicloud technologies continue to progress, which can have big implications on the monitoring platforms deployed to keep pace.

In our previous blog post, we discussed how investments in AIOps platforms have been justified on the basis of their ability to decrease mean time to problem resolution and the resultant cost reduction. But one of the challenges most IT Ops teams face is in the approach of deploying AIOps solutions for business-critical use cases: Where do we start? Some use AIOps to analyze unstructured data in order to identify higher-level correlations that traditional IT monitoring tools wouldn’t be capable of.

In our previous blog post, we discussed how we are approaching an important inflection point in the cloud migration timeline. Certain legacy applications will remain on owned infrastructure for the foreseeable future, but the scale and agility offered by cloud platforms offers competitive and operational advantages that most organizations cannot ignore. As cloud adoption became mainstream, many enterprises saw fewer objections to migrating their infrastructure to cloud.

IT monitoring solutions haven’t kept pace with the rapid evolution of modern IT infrastructures. Many organizations still rely on disparate and siloed monitoring tools built on legacy framework that present a fragmented view of IT operations.

In our previous blog post, we discussed how AIOps functionality has been used primarily in support of IT Ops processes that enable monitoring or observation of IT infrastructure, application behavior or digital experience.

In our previous blog post, we discussed the three core capabilities that constituted AIOps solutions: data ingestion and handling, machine learning analytics, and remediation. With an exponential increase in the amount of data generated by all these devices and siloed tool sets, the job of IT Ops can only get more challenging.

It is increasingly clear that tools developed to keep a single system or a small cluster running are no longer sufficient in today’s highly distributed, complex environment. The tools that offer service assurance must be able to move their way through complex application systems and prevent slowdowns or application failures. These complex systems now include physical systems, virtual systems and even systems found in a cloud service provider’s data center.

There is a lot of activity in the AIOps vendor market today. With that activity can come a lot of noise and many varying approaches and points of view, and quite a few thought leaders have offered their thoughts on the potential value of AIOps solutions. (Here’s a great take from our own CTO: The Truth About AIOps.) But most IT practitioners starting projects today want to know how they can use AIOps to make their teams more productive in the near term.