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The No-BS Guide to Logging - Part 2

A vendor-neutral checklist to help you get your log strategy straight
Sven Dummer


Start with The No-BS Guide to Logging - Part 1

Coming off of the last post outlining the necessity for log management, the process of choosing logging software can seem daunting. The following are major elements of a good log strategy and can also serve as checklist items when you shop for a log management solution:

Collect, Aggregate, Retain

It's crucial to think about your data retention needs and the costs associated with storing them. How long do you need to keep the logs? Do you need them just for troubleshooting, or also for business intelligence type of analysis? Are there regulatory or audit requirements that require you to keep the logs for a certain period of time?

Your daily log volume might already be large, but keep in mind that it doesn't take much to multiply the volume temporarily. For example, a component failure and the resulting log messages in a complex system could easily quadruple the amount of log messages. An external event could have the same effect: if you run an online store, Black Friday might balloon your sales as well as your log volumes. If your log aggregation doesn't scale, you could lose your main troubleshooting foundation when you need it most.

Handle Log Diversity

Log files come in a variety of formats, some following standards and conventions, others completely custom. Your log solution should be able to parse and present the data in a comprehensive form in near real-time, and it should allow to define custom parsing rules. A desirable feature is the ability to add metadata.

Reveal What Matters

Just having a search tool is not enough. To make sense of your log data and the correlation between different data points, you need real-time indexing and parsing, grouping, along with powerful analytics, customizable dashboards, and data visualization. Your log analytics solution should provide a treasure map to the contents of your logs, not just a metal detector that you must use to scan indiscriminately.

Detect Anomalies

Given the volume and complexity of log data, you can't rely on searching for problems. Things you never anticipated happening are typically the type of problems that hurt the most. A good log analytics solution should be able to learn what is “normal” in your log data, and automatically identify and highlight any deviations from norms.

Make Your Own Apps Log

If you write your own code, your log management solution must be able to parse and analyze it. Consider using a well-established data format like JSON (our recommendation) or XML. Whatever you choose, make sure it's plain text format (not binary), that it is human-readable, and easy to parse. Your log solution should be able to easily receive the logs from your application and allow you to set up custom parsing rules if needed.

Be Alert(ed)

Just like every good monitoring application, every good log management solution should allow to send you and your teams alerts based on defined events, like error messages. It should be possible to send these alerts through common third party collaboration tools.

Don't Break the Bank

Cloud technologies made running distributed systems and elastic compute farms affordable for SMBs. The bill for the troubleshooting tools should be affordable, too. There are fully cloud-based SaaS solutions out there, as well as on-premise products and hybrids, which typically come at higher costs (including those for hardware and datacenter footprint).

Key criteria to decide if SaaS or on-premise solutions are right for you are the sensitivity and volume of your data. Security or privacy concerns or regulatory requirements may keep you from transferring data across public networks. Similarly, the sheer data volume could make this impossible or too expensive.

Sven Dummer is Senior Director of Product Marketing at Loggly.

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The No-BS Guide to Logging - Part 2

A vendor-neutral checklist to help you get your log strategy straight
Sven Dummer


Start with The No-BS Guide to Logging - Part 1

Coming off of the last post outlining the necessity for log management, the process of choosing logging software can seem daunting. The following are major elements of a good log strategy and can also serve as checklist items when you shop for a log management solution:

Collect, Aggregate, Retain

It's crucial to think about your data retention needs and the costs associated with storing them. How long do you need to keep the logs? Do you need them just for troubleshooting, or also for business intelligence type of analysis? Are there regulatory or audit requirements that require you to keep the logs for a certain period of time?

Your daily log volume might already be large, but keep in mind that it doesn't take much to multiply the volume temporarily. For example, a component failure and the resulting log messages in a complex system could easily quadruple the amount of log messages. An external event could have the same effect: if you run an online store, Black Friday might balloon your sales as well as your log volumes. If your log aggregation doesn't scale, you could lose your main troubleshooting foundation when you need it most.

Handle Log Diversity

Log files come in a variety of formats, some following standards and conventions, others completely custom. Your log solution should be able to parse and present the data in a comprehensive form in near real-time, and it should allow to define custom parsing rules. A desirable feature is the ability to add metadata.

Reveal What Matters

Just having a search tool is not enough. To make sense of your log data and the correlation between different data points, you need real-time indexing and parsing, grouping, along with powerful analytics, customizable dashboards, and data visualization. Your log analytics solution should provide a treasure map to the contents of your logs, not just a metal detector that you must use to scan indiscriminately.

Detect Anomalies

Given the volume and complexity of log data, you can't rely on searching for problems. Things you never anticipated happening are typically the type of problems that hurt the most. A good log analytics solution should be able to learn what is “normal” in your log data, and automatically identify and highlight any deviations from norms.

Make Your Own Apps Log

If you write your own code, your log management solution must be able to parse and analyze it. Consider using a well-established data format like JSON (our recommendation) or XML. Whatever you choose, make sure it's plain text format (not binary), that it is human-readable, and easy to parse. Your log solution should be able to easily receive the logs from your application and allow you to set up custom parsing rules if needed.

Be Alert(ed)

Just like every good monitoring application, every good log management solution should allow to send you and your teams alerts based on defined events, like error messages. It should be possible to send these alerts through common third party collaboration tools.

Don't Break the Bank

Cloud technologies made running distributed systems and elastic compute farms affordable for SMBs. The bill for the troubleshooting tools should be affordable, too. There are fully cloud-based SaaS solutions out there, as well as on-premise products and hybrids, which typically come at higher costs (including those for hardware and datacenter footprint).

Key criteria to decide if SaaS or on-premise solutions are right for you are the sensitivity and volume of your data. Security or privacy concerns or regulatory requirements may keep you from transferring data across public networks. Similarly, the sheer data volume could make this impossible or too expensive.

Sven Dummer is Senior Director of Product Marketing at Loggly.

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 ...

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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 ...

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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 ...