Break New Ground

DevOps Meets Monitoring and Analytics

Much has been said about the role new technologies play in supporting DevOps, like automation and machine learning. My colleague Padmini Murthy wrote “DevOps Meets Next Gen Technologies”. In that post, Padmini does a great job discussing the DevOps ecosystem, partly based on a recent DevOps.com survey.

New technologies are rapidly shaping the way companies address Security and Application Performance Monitoring as well.

The same survey found 57% of companies have already adopted, and another 36% are planning to adopt modern monitoring in the next 12 months. Major reasons are: enhanced security, increased IT efficiency, and faster troubleshooting as shown in the chart below.  

Figure 1: “DevOps Meets Next Gen Technologies” by Devops.com; benefits and adoption profile for security, performance, and analytics monitoring.

Traditional IT practices would suggest application and security monitorings are oil and water, they don’t mix. Those responsible for applications and those responsible for IT security think and work dramatically different.  Here also, the landscape is changing rapidly.  The rapid proliferation of mobile and web applications built on modular microservices architectures or the like means monitoring needs to be agile and automatic.  At the same time, security strategies need to go beyond a good firewall, intrusion detection, and identity management.

What have emerged are commonalities between security and performance monitoring.  Both are using real-time monitoring of transactions through the entire stack.  Both are using machine learning to translate massive amounts of data into IT and security insights in real time.  Both are correlating data across an entire transaction in real time to quickly find performance or security issues.  Both are summarizing normal and abnormal behavior automatically to identify what’s important to view and what’s normal behavior.

This is what’s behind the design for Oracle Management Cloud.  It unifies all the metadata and log files in the cloud.  It normalizes the information on a big data analytics platform and applies machine learning algorithms to deliver IT Ops and Security dashboards pre-built specifically for security and performance teams with insights in real time, and automatically.

Figure 2: Oracle Management Cloud provides an integrated platform for security and performance monitoring.

Here are some lessons we’ve learned working with customers on DevOps efforts:

  1. Stop denying there is a problem. Ops teams are constantly bombarded by “false Signal” alerts.  They want better intelligence sooner about performance and security anomalies and threats. Read this Profit Magazine article to learn more about what Oracle is doing to help customers defend against ever-changing security and performance threats.
  2. Eliminate operational information silos so you eliminate finger pointing. Put your operational data (security, performance, configuration, etc.) in one place, and let today’s machine-learning-powered tools do the heavy lifting for you. You will reduce finger pointing, troubleshoot faster, and you may be able to eliminate the “war room” entirely. Watch this video to hear what one Oracle customer says about the power of machine learning.

Figure 3: Why Machine Learning is a key enabler for cloud-based monitoring.

  1. Monitor what (really) matters – your actual end-users. Over 70% of IT issues are end-user complaints. This can hinder the Ops team’s ability to respond to important issues. Look at this infographic highlighting the value of application and end-user monitoring. Figure 4 pinpoints why traditional monitoring tools miss the mark when it comes to delivering value.

Figure 4: End-user and application performance monitoring are key to a successful monitoring strategy.

  1. It’s in the logs! Logs are everywhere, but most organizations don’t use them because they are overwhelmed with the amount of data involved. Next-generation management clouds that are designed to ingest big data at enterprise-scale can cope with today’s log data volume and velocity. Check out this infographic for more details on Oracle Management Cloud’s Log Analytics service.

Figure 5: Key challenges with using logs to troubleshoot issues.

  1. Planning is an everyday activity. Leverage analytical capabilities against your unified store of operational information to answer a variety of forward-looking questions to improve security posture, application performance and resource utilization. If you’ve followed my advice in steps 1 through 4 above, you have all the data you need already available. Now it’s time to use it.

Further resources on Oracle Management Cloud:

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Comments ( 1 )
  • Julian Fortes Tuesday, February 5, 2019
    Interesting post! Thank you for sharing. My team would learn a lot just by reading this. If you're looking for a DevOps system solution, you should try this.
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