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Using APM for Security

There are quite a few architectures running around for Cloud and virtual environments, but except for a few, they seem to all be missing the ability to gain access to Application Performance Management (APM) data as a means to provide an early warning system for security issues.

Most security reference architectures rely on the old methods to get warnings about security issues such as use of a SIEM and a log analysis tool to interpret what is in the SIEM. However, there is a richer set of more immediate data that can help us with the problem of security notifications: APM Data.

APM Data provides a rich and different approach to security early warnings but the interpretation of the APM Data implies knowledge of the application that security professionals may not have. Yes, this is not a requirement as the security team and the applications team will be solving problems together that come up when there is an anomaly within any APM Data. The application team wants to know why there is an anomaly, perhaps a code path was taken unexpectedly, while the security team wants to insure that code path was not a hack attempt.

There are several ways to do this:

- Application and security professionals working together to determine if the APM Data shows a security issues or a code issue

- APM tools with built in mechanisms that could be used for security, such as a list of websites from which data comes into the system and to which data flows out of the system.

- APM tools that self learn the code path, so that when a new code path is used both security and application teams are notified

- APM tools that show both teams data about the code path when anomalies occur. Perhaps going so far as to highlight what was different

- APM Tools that show the exact process of events such as a database query to be investigated. Perhaps there was a SQL Injection within the query

APM tools have a rich set of data that could be used by security professionals. These tools know more about what is happening within an application than almost anyone else and could be helpful as a part of defense-in-depth. The smarter the APM tool, the more useful it becomes for security purposes.

Minimally, APM tools must contain the following abilities to be useful by security professionals:

- A way to see when external to the application resources were accessed, such as an external website.

- A way to see all database queries (even obfuscated if the APM solution is in the Cloud).

- A way to know when an anomaly has occurred, perhaps a different database query was made (possible SQL injection) or some normally unused code path was taken.

- A way to know when performance changes, perhaps activity is happening too fast (which could imply a DoS attack) or too slow (misconfigured or malware present).

In the end, however, it is all about determining when something anomalous has happened and a means of providing that data to the security team as well as the application team so that both work the problem side by side.

ABOUT Edward L. Halekty

Edward L. Halekty is Virtualization and Cloud Analyst, The Virtualization Practice LLC.

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Using APM for Security

There are quite a few architectures running around for Cloud and virtual environments, but except for a few, they seem to all be missing the ability to gain access to Application Performance Management (APM) data as a means to provide an early warning system for security issues.

Most security reference architectures rely on the old methods to get warnings about security issues such as use of a SIEM and a log analysis tool to interpret what is in the SIEM. However, there is a richer set of more immediate data that can help us with the problem of security notifications: APM Data.

APM Data provides a rich and different approach to security early warnings but the interpretation of the APM Data implies knowledge of the application that security professionals may not have. Yes, this is not a requirement as the security team and the applications team will be solving problems together that come up when there is an anomaly within any APM Data. The application team wants to know why there is an anomaly, perhaps a code path was taken unexpectedly, while the security team wants to insure that code path was not a hack attempt.

There are several ways to do this:

- Application and security professionals working together to determine if the APM Data shows a security issues or a code issue

- APM tools with built in mechanisms that could be used for security, such as a list of websites from which data comes into the system and to which data flows out of the system.

- APM tools that self learn the code path, so that when a new code path is used both security and application teams are notified

- APM tools that show both teams data about the code path when anomalies occur. Perhaps going so far as to highlight what was different

- APM Tools that show the exact process of events such as a database query to be investigated. Perhaps there was a SQL Injection within the query

APM tools have a rich set of data that could be used by security professionals. These tools know more about what is happening within an application than almost anyone else and could be helpful as a part of defense-in-depth. The smarter the APM tool, the more useful it becomes for security purposes.

Minimally, APM tools must contain the following abilities to be useful by security professionals:

- A way to see when external to the application resources were accessed, such as an external website.

- A way to see all database queries (even obfuscated if the APM solution is in the Cloud).

- A way to know when an anomaly has occurred, perhaps a different database query was made (possible SQL injection) or some normally unused code path was taken.

- A way to know when performance changes, perhaps activity is happening too fast (which could imply a DoS attack) or too slow (misconfigured or malware present).

In the end, however, it is all about determining when something anomalous has happened and a means of providing that data to the security team as well as the application team so that both work the problem side by side.

ABOUT Edward L. Halekty

Edward L. Halekty is Virtualization and Cloud Analyst, The Virtualization Practice LLC.

Hot Topics

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...