Applications that are changing rapidly due to agile development and DevOps, and that are running on dynamic and distributed infrastructures such as virtualized data centers, software-defined data centers, and private, hybrid, and public clouds, present new challenges in managing application performance. It is imperative to measure application performance with modern application performance management (APM) or application-aware infrastructure performance management tools.
Articles Tagged with Application Performance Management
For years, Gartner has insisted that if an APM tool does not cover each of its “Five Dimensions of APM,” one of which is deep code analysis, then it is not an APM tool. Gartner has therefore defined APM to be relevant only to custom-developed applications. Well, it has finally woken up and realized that 70% of the applications that enterprises run are in fact purchased and that maybe the performance of these applications might be important as well. So, Gartner has created a new category, application-aware infrastructure performance management.
In “Agile Without Ops Is Not Really Agile,” Mike Kavis points out that the Agile Development process and the DevOps support process must culminate with a situation where operations has the tools and uses the processes required for operations itself to be agile. Therefore, Agile Operations should be the natural consequence of agility in development and support, but often this is not the case. This post is about how the right monitoring tools can be used to help operations become agile.
Hundreds of companies and products monitor and manage various elements of your data center and your clouds. But most of these products rely on commonly available management data that is accessed via either industry-standard APIs or management APIs provided by various vendors. A few products do the extra work to collect unique data, and these products will be the focus of this article.
Splunk, the provider of the leading software platform for real-time operational intelligence, today announced it has acquired Cloudmeter, Inc., a provider of network data capture technologies. The addition of Cloudmeter will enhance the ability of Splunk customers to analyze machine data directly from their networks and correlate it with other machine-generated data to gain insights across Splunk’s core use cases in application and infrastructure management, IT operations, security, and business analytics.
The software-defined data center (SDDC) requires a new breed of security tools that not only handle the velocity of data being generated within a secure hybrid cloud but also handle the volume and variety of data. In fact, this new breed of security tools uses big data backends to manage the data being received, though it asks different questions of the data than normal for the products: security questions. The new breed of security tools either started as some form of performance management tool or employs performance management techniques to provide the data to to be queried.