An overabundance of siloed small-ITOA (IT Operations Analytics) tools is obscuring the big picture, holding companies back from understanding the real value of analytics and monitoring
I was reading an interesting article about whether log file analytics is better than agent-based Application Performance Management (APM).
The discussion on the thread was interesting because it soon became clear that clients have a bewildering choice of monitoring tools and, increasingly, a confusing choice of analytic tools.
The main outcome from the discussion is that there are three types of monitoring (data collection and rules-based alerting) tools out there. These are:
· Log file based tools. These include a range of open source-based products like Logstash, Elastic Search & Kibana (ELK), Solr, and Splunk
· Agent-based tools like Nagios & BMC Patrol. Some companies go further with an agent which is configured to monitor specific software, like ITRS’ Geneos which monitors the leading capital market solutions. These are sometimes called ‘outside the app’ tools since they read data from the database, log-files, messages queues and so on and therefore put no additional load on the software they are monitoring
· Integrated application monitoring tools, like NewRelic & AppDynamics. These tools are often integrated with the code of the application they are monitoring and therefore can read what is happening inside the software. These are called ‘inside the app’ monitoring tools
Which tool you use depends on what you are trying to monitor and alert on, and whether you develop your own applications or buy commercial software from vendors. Most companies will use more than one tool, often separating infrastructure monitoring and support from application/business support.
The problem that this is causing, is that as each monitoring solution adds analytic capabilities, something Gartner calls ‘small ITOA’, the data that they focus on is the data that they are already collecting for alerting purposes. So, Splunk users can do analysis on the log file data, and AppDynamic users can analyse the data they are collecting. However few are able to bring that data together to give a holistic view of what the IT estate is doing. How is the server or infrastructure performance affecting the application’s behaviour?
What is needed are analytic tools which are designed to be open and accept data from a wide variety of sources. Gartner call these ‘big ITOA’ tools. Vendors need to understand that this is important in preventing customers ending up with more and more analytic silos that fail to give the necessary insight into their production systems.
It’s heartening to see companies embrace and invest in ITOA. However, unless they focus on the big picture, they risk having in-depth analytics on every tree with no insights on the forest.
Are you a mobile apps guru? Take our quiz to find out!
Welcome to Silicon UK: AI for Your Business Podcast. Today, we explore how AI can…
Japanese tech investment firm SoftBank promises to invest $100bn during Trump's second term to create…
Synopsys to work with start-up SiMa.ai on joint offering to help accelerate development of AI…
Start-up Basis raises $34m in Series A funding round for AI-powered accountancy agent to make…
Data analytics and AI start-up Databricks completes huge $10bn round from major venture capitalists as…
Congo files legal complaints against Apple in France, Belgium alleging company 'complicit' in laundering conflict…