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Visualizing Your Log Data

Haim Koschitzky

How do we organize log data in a meaningful way that will not only make sense, but also be practical, usable, visible, and accessible quickly; in addition to being organized to support DevOps and APM insights?

Despite numerous log data analysis deployments, we still identify many challenges users face regarding IT log data visualization, analysis, and insights. How can we make sure anomaly detection is fast and easy so that log management does not become too time-consuming? Here are some guidelines for building meaningful operational views and dashboards for IT, leveraging log search, log analysis, machine learning, and advanced analytics.

First Ask Questions

Although stating the obvious, before investing expensive efforts and resources into analyzing data, it is crucial to define your expectations and requirements. While in the past, merely collecting all log data and making it available for search was good enough, this is no longer the case.

In order to ask the right questions, determine what the most important use cases your log data has shown you and what role you want your log data to play in your future ongoing work. To do this, you must monitor system availability, software quality, continuous deployment, application performance, and business insights, troubleshoot, analyze security incidents, compliance audit etc.

There are specific use cases for the application life cycle. Architect, developer, tester, DevOps, APM, operations, and production support all have specific uses cases and requirements. Giving the right answer to the right question makes a big impact and will drive smart actions.

Then Visualize

Once the requirements and expectations are well defined, it is crucial to be able to visualize your findings for further analysis; the more detailed, the better. We recommend creating an App that contains a collection of dashboards. If possible, create a dashboard per topic or use case, and provide each one with a meaningful name (“performance”, “errors”, “user audit”).

Now create search queries, or use out of the box gadgets for analytics, to find example Apps that you will be able to use as examples of best use cases for log analysis data visualization.

How to Visualize

Once you’ve created search queries to analyze data and generate proper result sets, you will need to select the visualization gadget that best reads these result sets and visualizes it in the most effective way.

Here is a result set that aggregated and computed the avg. memory consumption and total memory usage of two application servers. Take a look at the figure below. On gadget 1 you can see the totals over 24 hr aggregated memory consumption at 1 hr intervals. This gadget tells the story of both servers. Gadgets 2 and 3 represent the same data but for each of the individual servers. Once we split the data for each server we discover that each of the servers had a very different memory consumption pattern.

An hourly aggregation for memory is far from being accurate; memory changes at a much faster rate. On the upper row of gadgets we see the totals for both servers (gadget 4), and two additional gadgets, 5 and 6, representing each server in 1 min intervals.


We were looking to monitor our application server memory consumption to avoid spikes that might crash one of our clusters. Choosing the right visualization tools, and in this case, intervals, makes a big difference.

Optimize Insights

Optimize your dashboards and visualization gadgets by verifying that they deliver the insights you’re after in the right resolution. In the example above, analyzing memory for the entire cluster did not provide a clear status image of the memory consumption, but grouping by server and later reducing the time interval resolution to minutes gave a clear understanding of which cluster spiked.

Actions

Once your Apps and Dashboards provide clear views and visualization, it becomes much easier to identify problems, trends, and insights on your IT and applications. Now you can monitor or view the dashboards live. Leverage the visibility and you will be able to take actions that will make your applications more agile, secure, and optimized for the business.

Ask More Questions

Go back to the first step. This is an ongoing process. Data changes every day. The content of logs and other data types is being updated by IT, developers, and vendors continuously. In order to stay ahead, keep asking questions and never stop looking for the answers.

Haim Koschitzky is CEO of XpoLog Ltd.

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Visualizing Your Log Data

Haim Koschitzky

How do we organize log data in a meaningful way that will not only make sense, but also be practical, usable, visible, and accessible quickly; in addition to being organized to support DevOps and APM insights?

Despite numerous log data analysis deployments, we still identify many challenges users face regarding IT log data visualization, analysis, and insights. How can we make sure anomaly detection is fast and easy so that log management does not become too time-consuming? Here are some guidelines for building meaningful operational views and dashboards for IT, leveraging log search, log analysis, machine learning, and advanced analytics.

First Ask Questions

Although stating the obvious, before investing expensive efforts and resources into analyzing data, it is crucial to define your expectations and requirements. While in the past, merely collecting all log data and making it available for search was good enough, this is no longer the case.

In order to ask the right questions, determine what the most important use cases your log data has shown you and what role you want your log data to play in your future ongoing work. To do this, you must monitor system availability, software quality, continuous deployment, application performance, and business insights, troubleshoot, analyze security incidents, compliance audit etc.

There are specific use cases for the application life cycle. Architect, developer, tester, DevOps, APM, operations, and production support all have specific uses cases and requirements. Giving the right answer to the right question makes a big impact and will drive smart actions.

Then Visualize

Once the requirements and expectations are well defined, it is crucial to be able to visualize your findings for further analysis; the more detailed, the better. We recommend creating an App that contains a collection of dashboards. If possible, create a dashboard per topic or use case, and provide each one with a meaningful name (“performance”, “errors”, “user audit”).

Now create search queries, or use out of the box gadgets for analytics, to find example Apps that you will be able to use as examples of best use cases for log analysis data visualization.

How to Visualize

Once you’ve created search queries to analyze data and generate proper result sets, you will need to select the visualization gadget that best reads these result sets and visualizes it in the most effective way.

Here is a result set that aggregated and computed the avg. memory consumption and total memory usage of two application servers. Take a look at the figure below. On gadget 1 you can see the totals over 24 hr aggregated memory consumption at 1 hr intervals. This gadget tells the story of both servers. Gadgets 2 and 3 represent the same data but for each of the individual servers. Once we split the data for each server we discover that each of the servers had a very different memory consumption pattern.

An hourly aggregation for memory is far from being accurate; memory changes at a much faster rate. On the upper row of gadgets we see the totals for both servers (gadget 4), and two additional gadgets, 5 and 6, representing each server in 1 min intervals.


We were looking to monitor our application server memory consumption to avoid spikes that might crash one of our clusters. Choosing the right visualization tools, and in this case, intervals, makes a big difference.

Optimize Insights

Optimize your dashboards and visualization gadgets by verifying that they deliver the insights you’re after in the right resolution. In the example above, analyzing memory for the entire cluster did not provide a clear status image of the memory consumption, but grouping by server and later reducing the time interval resolution to minutes gave a clear understanding of which cluster spiked.

Actions

Once your Apps and Dashboards provide clear views and visualization, it becomes much easier to identify problems, trends, and insights on your IT and applications. Now you can monitor or view the dashboards live. Leverage the visibility and you will be able to take actions that will make your applications more agile, secure, and optimized for the business.

Ask More Questions

Go back to the first step. This is an ongoing process. Data changes every day. The content of logs and other data types is being updated by IT, developers, and vendors continuously. In order to stay ahead, keep asking questions and never stop looking for the answers.

Haim Koschitzky is CEO of XpoLog Ltd.

Hot Topics

The Latest

According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

Image
Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

Image
Broadcom

From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...