With IT operations becoming even more agile and business demands growing at a blinding pace, IT organizations will need to adapt even more to support and manage fast changing business requirements. A solution is automation, and IT Operations Analytics (ITOA) becoming an integral part of IT automation.
However, today’s ITOA tools still focus on silo subsets of data, requiring extensive manual effort to correlate data coming from diverse sources. So to eliminate blind spots, IT Operations will need analytics tools that provide end-to-end visibility into the entire scope of operational data, intelligently correlating data produced by multiple systems across IT silos and generating accurate insights pointing to events and activities that can potentially lead to issues.
I expect to see a new generation of IT operations analytics tools, based on blended analytics that can more proactively detect anomalies, predict outages, provide deep diagnostics and resolve issues within a real-time business context. By correlating various silo-sourced data (log, performance, configurations, security etc.), the next generation of IT Operations Analytics tools will be better positioned to sift through terabytes of operations data in real time, spotting and presenting issues to users in a more understandable context.
Furthermore, with change being one of the primary sources of operational issues, blending multiple sources of data with a top-down analysis focused on change will be much more effective, offering quick access to actual and potential root causes, raising the level of automation necessary for managing complex and dynamic environments.
Sasha Gilenson is the Founder and CEO of Evolven Software.
The Latest
According to a study by Forrester Research, an enhanced UX design can increase the conversion rate by 400%. If UX has become the ultimate arbiter in determining the success or failure of a product or service, let us first understand what UX is all about ...
The requirements of an APM tool are now much more complex than they've ever been. Not only do they need to trace a user transaction across numerous microservices on the same system, but they also need to happen pretty fast ...
Performance monitoring is an old problem. As technology has advanced, we've had to evolve how we monitor applications. Initially, performance monitoring largely involved sending ICMP messages to start troubleshooting a down or slow application. Applications have gotten much more complex, so this is no longer enough. Now we need to know not just whether an application is broken, but why it broke. So APM has had to evolve over the years for us to get there. But how did this evolution take place, and what happens next? Let's find out ...
There are some IT organizations that are using DevOps methodology but are wary of getting bogged down in ITSM procedures. But without at least some ITSM controls in place, organizations lose their focus on systematic customer engagement, making it harder for them to scale ...
If you have deployed a Java application in production, you've probably encountered a situation where the application suddenly starts to take up a large amount of CPU. When this happens, application response becomes sluggish and users begin to complain about slow response. Often the solution to this problem is to restart the application and, lo and behold, the problem goes away — only to reappear a few days later. A key question then is: how to troubleshoot high CPU usage of a Java application? ...
Operations are no longer tethered tightly to a main office, as the headquarters-centric model has been retired in favor of a more decentralized enterprise structure. Rather than focus the business around a single location, enterprises are now comprised of a web of remote offices and individuals, where network connectivity has broken down the geographic barriers that in the past limited the availability of talent and resources. Key to the success of the decentralized enterprise model is a new generation of collaboration and communication tools ...
To better understand the AI maturity of businesses, Dotscience conducted a survey of 500 industry professionals. Research findings indicate that although enterprises are dedicating significant time and resources towards their AI deployments, many data science and ML teams don't have the adequate tools needed to properly collaborate on, build and deploy AI models efficiently ...
Digital transformation, migration to the enterprise cloud and increasing customer demands are creating a surge in IT complexity and the associated costs of managing it. Technical leaders around the world are concerned about the effect this has on IT performance and ultimately, their business according to a new report from Dynatrace, based on an independent global survey of 800 CIOs, Top Challenges for CIOs in a Software-Driven, Hybrid, Multi-Cloud World ...
APM tools are your window into your application's performance — its capacity and levels of service. However, traditional APM tools are now struggling due to the mismatch between their specifications and expectations. Modern application architectures are multi-faceted; they contain hybrid components across a variety of on-premise and cloud applications. Modern enterprises often generate data in silos with each outflow having its own data structure. This data comes from several tools over different periods of time. Such diversity in sources, structure, and formats present unique challenges for traditional enterprise tools ...
