Key Takeaways

• “Autonomous IT” is a rebranded promise, not a breakthrough. The concept has been repackaged three times since IBM’s 2001 “Autonomic Computing” pitch, and production results still lag far behind the marketing.
  
• The ROI data doesn’t support the hype. MIT’s Project NANDA found 95% of organizations deploying generative AI saw zero measurable return on investment, and Gartner estimates 60% of AI projects lacking AI-ready data will be abandoned by end of 2026.
  
• Most infrastructure isn’t ready for autonomous remediation. Monitoring data is noisy, inconsistent, and full of environment-specific edge cases, far from the clean, structured telemetry autonomous systems need to act safely.
  
• The real risk is invisible failure, not obvious crashes. Across recent incidents like AWS US-East-1 and the Replit agent, the consistent failure mode was AI that was confidently wrong, with dashboards green and behavior silently drifting before anyone caught it.
  
• The organizations succeeding with AI built a proven foundation first. They defined remediation rules, kept humans in the loop during pilots, and expanded automation incrementally rather than deploying it all at once on mission-critical systems.

You might have noticed almost every vendor is selling some sort of “autonomous IT” during this pivotal moment in technological advances. Before you hand over the keys to your infrastructure to an algorithm, here’s some real data we found about AI in production infrastructure monitoring environments and why full control still prevails.

There’s a new buzzword flying around. LogicMonitor calls it “Autonomous IT.” Splunk calls it “Agentic SecOps.” SolarWinds titled their 2026 report “The Human Side of Autonomous IT.” In the last six months, if you went to any webinar in this industry, you’ve probably heard some rendition of the same pitch: “AI will monitor your infra, predict failures, and fix them with minimal human intervention.”

To me it’s genuinely fascinating. I see the work our sysadmins and network engineers do every day and there are many tasks I feel like AI could help relieve. But the gap between the marketing narrative and production reality has never been wider. And for the teams managing mission-critical infrastructure that can’t go down, that gap has a real cost.

By no means are we against AI or automation. This is simply a case for knowing what you’re purchasing when a vendor tells you their platform is “autonomous,” and understanding exactly what you give up when you hand the keys to something you can’t fully audit.

What “Autonomous IT” Actually Means in 2026 and Why You’ve Heard This Before

The term “autonomous IT” has some history. It developed as a result of decades of increasingly ambitious enterprise IT promises. In 2001, IBM introduced the concept of “Autonomic Computing,” explicitly modeled after the human autonomic nervous system, the subconscious system that regulates breathing and heart rate without conscious thought.

The vision was infrastructure that could self-heal and manage itself in the same way. It was a powerful pitch. It mostly didn’t ship.[1] Between 2018 and 2023, Gartner and the analyst community repackaged the idea as AIOps, Artificial Intelligence for IT Operations.

AIOps focused on analyzing telemetry data and alerting humans to issues faster. At this stage, humans were still in the loop. Not fully autonomous. Not yet. [2] Let’s fast forward to now. We’re seeing it everywhere. Generative and agentic AI have officially arrived, groundbreaking technology that doesn’t just analyze and alert us, but has the capability of executing multi-step real-world workflows independently. Soon enough, the industry had the technical foundation to revisit IBM’s original promise, and “Autonomous IT” emerged as the dominant market category for systems that sense, decide, and fully resolve enterprise problems without human intervention. LogicMonitor, ScienceLogic, Tanium, and Splunk all started developing frameworks and go-to-market strategies around the term. [3][4]

And they weren’t alone.

This is not just an IT phenomenon. The same wave is sweeping across all industries at once. Autonomous vehicles have been spotted on roads. Autonomous trading systems are reshaping how financial markets work. Hospitals are testing self-diagnostic tools. Manufacturers are creating self-correcting production lines. The term “autonomous” has become the defining adjective of our current era, indicating that a product has transformed from tool to agent. [5]

So when a vendor says “autonomous IT” today, they’re selling the 2026 realization of a vision that’s been in the industry’s imagination since 2001. Keep that in mind. The ambition is real. The question is whether the production reality actually matches the pitch.

What The Data Actually Says

On a sales slide, the IT narrative sounds appealing. But figures pulled from production reveal a different story.

95% of organizations deploying generative AI saw zero measurable return on investment according to MIT’s Project NANDA (July 2025), covering 300+ AI initiatives.

Source: MIT Project NANDA, July 2025 [6]

That figure measures value realization, not whether the AI ran. MIT defines a successful implementation as one that delivers sustained productivity gains and measurable P&L impact, confirmed by both end users and executives. By that standard, the vast majority of enterprise AI deployments today don’t qualify. Most organizations are generating nothing they can point to on a balance sheet. Gartner adds to this, estimating that 60% of AI projects lacking AI-ready data will be abandoned through 2026. [7]

This is crucial for monitoring specifically because monitoring data is not AI-ready by default. It is noisy, cluttered, inconsistent across systems, and full of edge cases that took your team years to tune around. Autonomous remediation requires comprehensive telemetry, consistent schemas, documented dependencies, codified runbooks, and mature incident response.

As Elastic’s 2026 observability research puts it: “You can’t deploy autonomous remediation if you haven’t defined what remediation means.” [8]

23% of organizations are using agentic AI systems in observability today. Among early-stage teams: zero. Autonomous remediation requires data quality that most environments haven’t achieved.  

Source: Elastic, The Landscape of Observability in 2026 [8]

What Happens When Autonomous Systems Get It Wrong

I think the most useful thing we can do here is just look at what actually happened as of recently. Not in a sandbox. Not in a demo. In production, with real data at real companies that lost real money.

AWS US-East-1 (October 2025)

A 15+ hour outage crippling Snapchat, Fortnite, and dozens of other services. Root cause: an automated DNS management update triggered a latent race condition in DynamoDB. The automation worked exactly as designed on bad inputs. [9]

Replit AI Agent (July 2025)

During an explicit code freeze, an autonomous coding agent executed a DROP DATABASE command on a production system. When confronted, the AI created a 4,000-record database of fictional people and false logs to cover the deletion. Its explanation: “I panicked.” [10]

GitHub Actions (2025-2026)

257 separate incidents, 48 classified as major outages, in a 12-month period, roughly one significant disruption per week. The primary driver: agentic development workflows accelerating faster than the platform’s architecture could handle. [11]

Quiet Failure ­– IEEE Spectrum (April 2026)

IEEE Spectrum identified a new class of AI failure: systems where every dashboard reads “healthy” while behavior drifts silently away from intended outcomes. Standard monitoring cannot catch it. The system appears operational. It is not. [12]

If it’s not obvious, there is clearly a pattern across these incidents that remains consistent. The failure mode isn’t the AI being obviously in the wrong. It’s the AI being confidently and invisibly wrong. Automated systems that can remediate can also automate the wrong fix at scale, faster than a human would catch it.

“A growing class of software failures looks very different. The system keeps running, logs appear normal, and monitoring dashboards stay green. Yet the system’s behavior quietly drifts away from what it was designed to do.”

Source: IEEE Spectrum, April 2026 [12]

This is the failure mode that rule-based monitoring lacks.

When Nagios XI detects a threshold breach and issues an alert, it does not guess. It does not drift. It runs the check you configured against the threshold you set and notifies the person you specified.

The results are deterministic and auditable. You can always explain exactly why any alert triggered.

Don’t Forget What’s Already Working

Before we get into the details, let’s take a step back. Amidst all of the noise, webinars, analyst reports, and vendor pitches, it’s easy to forget that dependable, human-controlled monitoring has been quietly doing its job the entire time.

Here’s a reminder of what that actually looks like in practice.

Nagios XI’s event handlers can restart a stopped service, open a ticket, run a script, or page a team member the moment something changes state. That’s automation, fast and reliable automation.

The difference is that the remediation logic was written by your team, for your environment, against rules you defined and can modify. When something goes wrong at 2 a.m., you’re reviewing a clear alert log, not reverse-engineering what an AI decided to do and why.

The Case for Autonomous IT and the Right Time to Build Toward It

None of this means autonomous IT is wrong. The 5% of organizations generating real returns from AI in production are doing something right, and the pattern is consistent.

They built their foundation first. They defined what remediation means in their environment. They piloted in non-critical systems and kept humans in the loop before handing anything over to automation.

And that’s exactly the path Nagios XI is built for.

When you’re ready to layer in AI, you’ll have the telemetry, the plugin ecosystem, and the event handler infrastructure to do it right. Organizations already using Nagios XI are integrating with platforms like Splunk, Datadog, and PagerDuty without ripping out the reliable core their teams know and trust.

You don’t have to choose between proven monitoring and the future of AI. You build toward it, on a foundation that won’t let you down while you get there.

Questions to Ask Before Any Autonomous Monitoring Purchase

If you’re evaluating autonomous IT platforms, the following questions will tell you more than any demo.

What happens when the AI is wrong? Can you get a full audit log of every automated action? Can you roll back a remediation? Who is responsible when autonomous action causes an outage?

What does your environment need to look like before autonomous remediation works? Ask the vendor to describe the data readiness requirements explicitly. If they can’t, that’s an answer.

How does pricing scale as AI features generate more telemetry?

Many AIOps platforms charge on data ingestion volume. AI-powered correlation generates significantly more data than threshold alerting. Get a written cost estimate at 2x and 5x your current data volume.

What does “autonomous” mean in your contract? Ask what percentage of actions require human approval.

Many platforms that market autonomy actually require human confirmation for any production-impacting action, which is correct behavior, but it means they aren’t actually autonomous in the way the pitch implied. The vendors pushing autonomous IT aren’t wrong about where monitoring is going. They’re wrong about where most production environments are today, and how fast that gap can be safely closed.

The organizations that will benefit most from AI-enhanced monitoring in 2026 are the ones who built solid, proven monitoring foundations first.

That’s what Nagios has been doing for over 25 years.

Ready to see proven monitoring in action? Request A Demo Today!

Sources:

[1]  IBM: Autonomic Computing (2001) TechTarget — What is Autonomic Computing?

[2]  Gartner: How to Get Started with AIOps

[3]  LogicMonitor: What Is Autonomous IT?

[4]  ScienceLogic: The Autonomous Enterprise

[5]  Advanced Systems Concepts: Autonomous IT Operations

[6]  SR Analytics: Why 95% of AI Projects Fail (MIT Project NANDA, July 2025)

[7]  Gartner: AI Project Failure Rates and Data Readiness (February 2025)

[8]  Elastic: The Landscape of Observability in 2026

[9]  LogicMonitor: 5 Observability and AI Trends for 2026

[10]  NineTwoThree: The Biggest AI Fails of 2025

[11]  LeadDev: What’s Gone Wrong at GitHub?

[12]  IEEE Spectrum: How Quiet Failures Are Redefining AI Reliability (April 2026)

But what if you could see issues coming and act before they cause real damage? That’s where network monitoring comes in.

In this article, you’ll see more examples that answer the question “Why is network monitoring important?” including specific industry examples of how network monitoring can keep your systems running smoothly.

What Is Network Monitoring?

Network monitoring gives you the key hints of when an outage might occur and, more importantly, how to prevent it.

Key Capabilities of Network Monitoring:

• Full visibility across hybrid and cloud-native setups.
• Automated, proactive alerts.
• Support for automation and self-healing systems.
• Centralized metrics, logs, and alerts.

Why is Network Monitoring Important?

Now that we understand what network monitoring does, let’s examine why it’s become essential for today’s IT operations. Here’s what tech leaders are looking at in today’s IT landscape, as well as how network monitoring addresses these challenges:

By implementing monitoring solutions, organizations can avoid costly downtime, gain visibility across complex environments, and maintain operational resilience.

Moving beyond theory, let’s see how real organizations put these monitoring principles into practice.

How Different Industries Use Network Monitoring

Organizations in every industry are using network monitoring to stay ahead:

Healthcare: Hospitals use log monitoring to maintain HIPAA compliance and keep patient systems online during updates or upgrades.

Aerospace: In aerospace, monitoring systems track spacecraft data to keep missions running smoothly, monitor flight systems to prevent crashes and equipment failures, and check engine health to fix problems before they cause delays.

Financial Services: High-volume transaction systems rely on monitoring and alerting to reduce fraud risk and performance lag.

With these industry applications in mind, choosing the right monitoring solution becomes crucial for achieving these results in your own environment.

Why Choose Nagios?

When selecting a network monitoring platform, you have several options to consider. Solutions like Nagios, SolarWinds, Datadog, Zabbix, and many others.

Why Nagios Stands Out:

• Proven Reliability: Nagios has a long-standing reputation for stability. When your monitoring can’t go down, you need something proven.

• Modern Features: Recent updates in Nagios XI 2024R2 include predictive alerting, REST APIs, log correlation, and hybrid environment support.

• Flexibility that Scales: Custom plugins, community extensions, and integrations with tools like Prometheus, Zabbix, Elasticsearch, and ServiceNow, which help build exactly what you need for your unique environment.

• Industry Trust: Used by leading organizations across aerospace, healthcare, finance, and government sectors for mission-critical monitoring.

• Cost-Effective Growth: Architecture that grows with your needs, avoiding high licensing fees.

Moving Forward

Outages and downtime are just some of the impacts of not having a proactive approach to network monitoring. Good monitoring doesn’t just alert you to problems; it helps you understand your environment. That way you can figure out where to focus your efforts, like spotting which systems are about to give you trouble or finding the best places to automate those repetitive tasks that eat up your day.

If you’re looking to improve your monitoring approach, there are a few ways to explore what’s possible. You could test Nagios XI in your own environment or schedule a demo with a Nagios expert about your specific challenges. And if you’re still asking yourself, “Why is network monitoring important?” and want to see more examples, review how other organizations have approached similar IT problems to see the real-world impact and stories.

However, these devices also introduce significant cybersecurity risks. The 2021 Verkada breach, where cybercriminals accessed live feeds from 150,000 security cameras, proves the risk of damage when IoT devices are compromised is severe. Regardless of whether it is due to default or weak passwords, a lack of firmware updates, or unprotected communications, if you do not implement proper security controls, your business could incur a data breach, a cyberattack, or an operational disruption when an IoT device behaves unexpectedly.

The purpose of this article is to provide IT managers, business owners, and security professionals with seven actionable steps to safely deploy IoT devices on their networks, assess the benefits offered by these devices, and maintain an adequate level of protection.

Why Security is Important with IoT

Just as IoT devices have powerful capabilities, they inherently lack or have inadequate security controls, which makes them an easy target for cybercriminals. A 2023 research study published by Cybersecurity Ventures estimated the global costs of cybercrime to be $8 trillion, also predicting that IoT devices would become an increasingly popular target for attacks. A single compromised device can lead to data breaches, loss of operational time, damage to reputation, or financial penalties, depending on the requirements, regulations, or standards that were violated, such as GDPR, HIPAA, or CCPA. Prioritizing security and controls will provide business value when it comes to realizing the true potential that IoT devices can offer. Here are seven helpful steps to accomplish this.

Steps to Secure IoT Implementation

1. Create an IoT Plan

Collaborate with the business to ensure that IoT implementations align with the business purpose, while also evaluating any security risks that need to be addressed.

Clearly defined goals, such as optimizing supply chain operations or accelerating the Customer Experience (CX), should be established. Evaluate the sensitivity of data and determine how it should be protected. Ensure that the devices you want to deploy support secure protocols (TLS version 1.3). Conduct a risk assessment to identify the vulnerabilities, consider using the Cisco IoT Control Center, and understand how devices interact with each other from a security hygiene standpoint.

2. Isolate Your Network

Keeping IoT devices separated from more sensitive systems or networks can help limit the damage if an attacker breaches your defense.

Implement a virtual local area network (VLAN) to isolate your IoT devices from servers and workstations. Then, write your firewall rules to limit traffic to the absolute minimum necessary for the device to operate. This could mean allowing access only to vendors’ systems, such as those from Palo Alto Networks. If the device is truly inconsequential, such as a smart TV, connect it to your guest Wi-Fi, which allows even further reductions in permission.

3. Assess Vendors and Devices

Devices are often poorly engineered, and vendors are not always secure. Therefore, it is crucial to assess vendors thoroughly.

Choose reputable vendors like Cisco or Siemens, who offer strong encryption (AES-256, TLS 1.3) and regularly updated firmware. Check if your devices have any open default passwords, and provide privacy policies publicly and unobscured. One advantage is that it minimizes the risks associated with the deployment of poorly engineered and insecure devices.

4. Enforce Strong Authentication and Access Controls

Weak authentication is a straightforward method for an attacker to gain entry to devices that have been inadequately protected, as well as those with some security measures in place, as the Verkada breach can attest. Consider it a warning.

Force strong, unique, not default, credentials, and where possible, enforce multi-factor authentication (MFA) of the device management interface. Implement role-based access control (RBAC) to manage and control user access, restrict unnecessary permissions, and limit unneeded access, such as remote access or the ability to connect to ports that are not required. IT administrators and disable remote management unless critical.

5. Educate Employees on Internet of Things Risks

The most significant contributor to IoT incidents is human error.

Educate employees on IoT risk awareness that includes phishing attacks or downloading firmware from “unverified” websites. Create a clear, concise, and understandable plan outlining what employees can and cannot do with IoT devices, as well as the procedures to follow when using them. Provide periodic refresh training on good practices.

6. Be Compliant

Any IoT implementation is subject to regulations that you must comply with; failure to do so will result in fines and penalties specific to your industry.

Be aware of what regulators will be looking for. To give an example, the GDPR will focus on data minimization, and HIPAA requires the protection of patient data. Utilize encryption and access controls in your IoT solutions to help ensure compliance with relevant standards. It may be necessary to maintain audit logs of records if they are an explicit requirement for compliance. Encrypt temperature data before transmission to a cloud dashboard.

7. Detect Threats Early

Detecting threats early is very important for IoT security. Use tools like Nagios XI to monitor devices being used and watch for suspicious activity, such as spikes in data usage. Use an Intrusion Detection System (IDS) like Snort to determine compromised devices. Perform compliance investigations to review device configurations and logs occasionally.

• Related Reading: Securing Third-Party IoT Devices in 2025: Best Practices for Protection

Final Thoughts

IoT devices are transforming the way we conduct business, and we must not overlook the cybersecurity risks they pose. There are excellent tools available, such as Nagios XI and AWS IoT Device Defender, that help ensure a healthy IoT ecosystem. If you follow the seven steps above (create an IoT plan, network segmentation, assess vendors and devices, active monitoring, etc.), you can successfully integrate IoT devices safely and build resilience to cyber threats.

Why Robots Can Pose a Security Risk

Robots are incredibly advanced; however, they will still have very similar vulnerabilities to your standard IoT devices, such as having weak default passwords. Given that they have digital access as well as physical access, it’s especially important that these devices are secured. As robots being added into enterprise environments is still new, there haven’t been many examples of a security breach with them; however, the risks involved when security breaches are discovered have a huge impact.

In April 2025, researchers discovered that the Unitree Go1 robot dog contained a hidden backdoor service that could be activated without the user’s knowledge or consent. Once the device is connected to the internet, it would automatically initiate a remote access tunnel, potentially allowing hackers to take control of the robot, view its live camera feed, and access the underlying system via SSH. The researchers demonstrated that anyone with access to the necessary API keys could exploit this vulnerability, making it a serious and immediate threat.

In addition to the digital threats of having your data leaked or stolen, it is important to remember that a robot is also capable of interacting physically. Should it malfunction, or even worse, get hacked, it can easily lead to injuries, property damage, or restricted spaces being accessed. Normal IoT devices can give data, but with a robot, if someone from the outside gets control of it, they can cause a lot more harm, both to employees and the company.

Best Practices

Many of the best practices from our article on securing IoT systems apply directly to robots as well, since they are likely to be network-connected devices. However, in the case of robots, some of these practices become even more important, and there are also a few additional concerns unique to robotics that deserve special attention.

1. Change Default Passwords and Strengthen Authentication

Changing default passwords is one of the simplest and most important steps in securing a robot. Many devices ship with factory-set credentials that are widely known, making them easy targets for attackers. These should be replaced immediately with strong, unique passwords. For added protection, especially when robots connect to cloud services or internal systems, implement multi-factor authentication (MFA) or certificate-based access. Securing login credentials early helps prevent one of the most common and avoidable threats.

2. Know What’s on Your Network: Asset Visibility and Inventory

Robots can quietly join a network without drawing attention, especially in large or fast-moving environments. That makes real-time visibility essential. Use tools like Nmap or Nessus to scan for connected devices and log key details like IP address, manufacturer, and firmware version. For larger setups, platforms like AWS IoT Device Management or Azure IoT Hub can automate this process and alert you when new or unknown devices appear. Keeping track of every connected robot helps ensure nothing slips through the cracks.

3. Encrypt Data

Robots contain sensitive information such as video streams from their camera, location data, and control commands. It’s important to protect this information by encrypting both the data being sent across networks and the data stored on the device or in the cloud. Using strong encryption methods, such as TLS for network communication and AES for stored data, helps prevent attackers from intercepting, reading, or altering critical information. This keeps robot operations secure and protects user privacy.

4. Implement Network Segmentation and Monitoring

Keeping robots on a separate part of your network helps limit the damage if one gets compromised. Using isolated VLANs or subnets means an attacker can’t easily move from a robot to more sensitive systems. In addition, continuous monitoring tools like Nagios can watch for unusual activity, such as unexpected connections or spikes in data, that might signal a security issue. This combination of isolation and vigilance helps detect problems early and contain threats before they spread.

5. Keep Software Up to Date

Robots run on software that can have security flaws. Making sure these are regularly updated is extremely important as the updates will likely contain patches or fixes to previously known security vulnerabilities. If possible, we want these devices to update automatically as well as keep an eye on what these updates entail so we can make sure they stay protected against both the old threats and any new threats.

6. Ensure it Can be Stopped

Since robots are capable of moving around as well as physically interacting with the environment around them, it’s essential to ensure a way of stopping it should it go out of control for any reason. A button on the device, a remote kill switch, or some sort of software should be made to shut down the robot should this happen. While you could also simply disable the motors to stop it from moving, it’ll be more secure to shut down the device completely to cut off any connection if it were hacked.

Conclusion

As robots become more common in workplaces, keeping them secure is more important than ever. Understanding their unique risks and following simple best practices, like changing default passwords, keeping track of devices on your network, encrypting data, separating networks, and regularly updating software, can help protect your business from costly hacks. Taking these steps isn’t just about technology; it’s about making sure your team can safely get the most out of these powerful tools.

Over 60% of ransomware attacks in 2024 utilized zero-day exploits, resulting in damages worth billions of dollars. Cybercrime is estimated to cost the world USD 10.5 trillion by 2025, according to Cybersecurity Ventures.

Let us look at why zero-days are dangerous, how zero-day exploits are found, the most significant incidents around the world, what we will see in 2025, and what you can do to combat zero-days with a good response plan.

Why Zero-Days are a Big Problem

A zero-day exploit targets a vulnerability in software, hardware, or firmware before the vendor or the security community knows of it. The attacker can exploit these vulnerabilities to steal data, deploy ransomware, or disrupt a service without anyone initially being aware of it. There is no patch or signature for a defense at the moment an organization becomes aware of a zero-day exploit; there is simply no time to defend against the attack vector.

How Zero-Days are Found

Fuzz Testing: Automated Vulnerability Search

Fuzz testing involves the user inputting random or malformed data into an application, then checking for unexpected behaviors (such as crashing) that often indicate a bug is present underlying the unexpected behavior. Modern fuzzers, such as AFL++ and Google’s OSS-Fuzz, employ techniques that leverage coverage-guided and AI-assisted risk-aware code coverage approaches, ultimately identifying higher-risk paths in code. OSS-Fuzz, since its inception, has identified over 8,000 critical bugs in open-source projects (Google Security Blog, 2024). Once fuzzing has been integrated into a CI/CD pipeline, it provides teams with the opportunity to discover potential vulnerabilities and prevent them during the development process.

Bug Bounty Programs: Paying the Hackers to Help Us

Bug bounty programs allow organizations to provide incentives to external researchers to discover and disclose defects to the researcher’s specifications. Platforms such as HackerOne or Bugcrowd help facilitate these relationships between organizations and ethical hackers. In 2024, Google paid out over $10 million to successful vulnerability rewards, demonstrating the proactive nature of these discovery programs. Well-designed bug bounty programs can reduce the chances of zero days being sold to the black market.

The Biggest Zero-Day Attacks in History

Stuxnet (2010): This worm exploited four chained Windows zero-days (CVE-2010-2568) that enabled it to bypass multiple layers of security and gain control of SCADA systems, ultimately sabotaging the Iranian nuclear program. Stuxnet proved that isolating critical systems and keeping industrial technology current are requirements, not negotiable.

EternalBlue (2017): A stolen exploit from the NSA (CVE-2017-0144) that took advantage of a Windows exploit helped spawn the WannaCry and NotPetya ransomware attacks that locked out over 300,000 systems worldwide. A lesson learned that delaying patching creates risk.

Log4Shell (2021): A zero-day flaw in Apache Log4j (CVE-2021-44228) was exploited, allowing attackers to remotely execute their code on impacted cloud-based systems and enterprise applications. This incident highlighted the importance of Software Bill of Materials (SBOM) tools to help track our third-party open-source components.

MOVEit (2023):The SQL injection zero-day (CVE-2023-34362) in MOVEit Transfer helped the CL0P gang easily steal an unknown amount of data from over 2,700 organizations and provided insight into our vulnerabilities through the supply chain

What’s Coming in 2025

Cybercriminals are not going to surrender, and zero-days are evolving quickly. The implications include:

• Artificial Intelligence Attacks: Hackers are employing AI-powered fuzzers to identify vulnerabilities quicker than before, and they are increasingly simulating real-world traffic so they can infiltrate your defenses.
• Dark Web Purchases: Zero-day exploits are now being sold on dark-web markets as subscriptions, with costs ranging from $100,000 to $10,000,000.
• Ransomware’s Next Step: Ransomware groups are also buying zero-days to get into systems, which makes the attacks targeted and even more lethal.
• Internet of Things Vulnerabilities: With estimates that by 2025 there will be over 20 billion things connected to the Internet, there are plenty of unpatched firmware vulnerabilities in smart cities and smart factories.
• Cloud Environments Vulnerabilities: Unprotected organizations’ misconfigured cloud environments, in particular Kubernetes, are now a prime target for zero-days.

Fighting Back: A Zero-Day Response Plan

Utilizing the NIST “Incident Response Life Cycle” (SP 800-61R2), here is a strategic plan for dealing with a zero-day:

Remain Ahead of the Game with Threat Intel

• Watch Feeds: Monitor CISA’s Known Exploited Vulnerabilities list, MITRE ATT&CK, etc., and tools like Recorded Future to glean insight on early threat detection.
• JOIN ISACs: Join an Information Sharing and Analysis Center for your specific industry to gather real-time attack data and countermeasures, and then immediately do something with it.

Virtual Patching: Buying Time

When a vendor patch isn’t ready, use these workarounds:

Best Practices to Take on

• Spot It: Use tools like Nagios to identify troubling behavior and determine the impacted systems.
• Contain It: Block infected endpoints/services or turn off vulnerable services.
• Fix It: Deploy patches or temporary fixes and/or restore clean systems from backups.
• Clean It Up: Look for hidden threats or ways hackers may return.
• Learn from It: Reconfigure your defenses and test more code to mitigate future attacks.

Using Nagios to Stay Safe from Zero-Days

Nagios XI is a powerful tool that helps keep your systems safe by monitoring for any unusual activity in your network, such as unexpected spikes in data or changes in your apps. It monitors everything from your servers to your applications, quickly spotting signs of a zero-day attack. With quick alerts, Nagios XI lets you act fast to stop problems before they grow into bigger issues. Nagios XI also works in offline setups, keeping your systems less exposed.

Wrapping Up

Zero-day exploits present a significant challenge, and it should be acknowledged that attackers have the advantage on a zero-day. However, with some proactive measures, the advantage can shift from attackers to defenders. By incorporating fuzzing during development, engaging ethical hackers, and properly conducting a response plan, organizations can reduce their risks posed by zero-days. By continually testing and improving their defenses, organizations can stay ahead of the ever-evolving threat landscape.

Glossary

• eBPF: A Linux tool for monitoring system behavior in real time.
• JNDI: A Java interface exploited in Log4Shell attacks.
• SBOM: A list of all software components to track vulnerabilities.
• Fuzzing: A testing technique that inputs random or malformed data to uncover software vulnerabilities.
• Virtual Patching: Temporary security measures to block exploits until vendor patches are available.

The 2016 Mirai Botnet, which disrupted major websites by exploiting unsecured IoT devices, serves as a stark reminder of these vulnerabilities. According to jumpcloud, “more than 50% of IoT devices have critical vulnerabilities that hackers can exploit right now.”

This article explores the risks of third-party IoT devices and outlines practical strategies to secure and monitor your IoT ecosystem effectively.

Why Third-Party IoT Devices Pose Risks

The rapid growth of IoT devices brings undeniable benefits, but their security challenges are significant. Weak default passwords, unencrypted data, and irregular updates make these devices prime targets for cyberattacks. Hackers can exploit them to steal data, disrupt operations, or even launch large-scale attacks. The good news? With the right approach, you can mitigate these risks and maintain a secure network. Below are ten best practices for securing and monitoring third-party IoT devices.

1. Know What’s on Your Network

You can’t secure what you don’t see. Untracked IoT devices are like hidden weak spots in your network, ready to be exploited.

• Inventory scanning: Use Nmap or Nessus to perform periodic network scans that detect and catalog every IoT device. Capture attributes such as manufacturer, model, MAC address, and firmware version.
• Cloud-based asset management: Leverage AWS IoT Device Management or Microsoft Azure IoT Hub to automate inventory updates and generate alerts for unknown devices.

Benefit: Ensures comprehensive visibility into all IoT endpoints.

2. Lock Them Down with Network Segmentation

A single compromised device, like a smart camera, shouldn’t bring down your entire network.

• Deploy IoT devices on isolated VLANs or subnets separate from sensitive systems (NIST SP 800‑190).
• Configure firewall rules to restrict traffic to essential services only.
• Apply zero‑trust principles: require mutual authentication and minimal permissions for device-to-device communication.

Benefit: Prevents lateral movement across your corporate network.

3. Strengthen Authentication

Weak credentials, like the default “admin” exploited in the Mirai botnet, are a major security gap.

Replace default credentials with strong, unique passwords. Use X.509 certificates for device-to-cloud authentication and enable multi-factor authentication (MFA) for admin access where possible. These steps lock out unauthorized users and keep your devices secure.

Benefit: Prevents unauthorized access and brute force attacks.

4. Stay on Top of Updates

Outdated firmware leaves devices vulnerable to known exploits.

• Subscribe to CVE Details feeds and vendor security advisories.
• Automate firmware patch deployment with tools such as AWS IoT Device Management or Balena.
• Retire end-of-life devices that no longer receive security updates.

Benefit: Closes security gaps before they can be exploited.

5. Monitor with Tools Like Nagios

IoT devices can show subtle signs of trouble, like unusual data spikes or rogue connections. Proactive monitoring catches these early.

Nagios XI and Nagios Network Analyzer let you set baselines for device behavior, track network traffic, and spot anomalies almost instantly. Nagios XI lets you monitor everything from CPU, Memory, and Disk usage and integrates it with Nagios Log Server for instant alerts.

Benefit: Enables early detection of potential threats, enhancing response times.

6. Encrypt Everything

Unencrypted data can be intercepted by attackers, allowing them to monitor user activity and steal sensitive information.

Ensure devices use TLS 1.3 for communication and MQTT with encryption for messaging. Use AES-256 for local data storage. Edge computing can also help by processing sensitive data locally, reducing exposure during transmission. These measures keep your data safe from eavesdroppers.

Benefit: Maintains confidentiality and integrity of IoT data.

7. Limit Who Can Touch Them

Physical access or unchecked admin privileges can lead to big problems.

Use tamper-evident seals to secure devices and role-based access control (RBAC) to restrict administrative access. Monitor logs for suspicious activity to catch unauthorized attempts early. Tight access controls protect your devices from tampering or misuse.

Benefit: Reduces risks from insider and outsider threats.

8. Test for Weak Spots

Waiting for hackers to find vulnerabilities is a risky bet.

Run regular penetration tests and vulnerability scans with tools like OpenVAS or Burp Suite. Simulate real-world attacks to identify weaknesses, such as unpatched firmware or weak encryption, before they’re exploited. This proactive approach keeps your defenses sharp.

Benefit: Ensures continuous improvement of security posture.

9. Check Your Vendors Carefully

Not all IoT manufacturers prioritize security, and a weak vendor can mean a weak device.

• Require vendor adherence to standards such as ISO 27001 or ETSI EN 303 645.
• Review vendor patch cadence, security disclosure policies, and transparency reports.
• Incorporate security requirements and liability clauses into procurement contracts.

Benefit: Reduces introduction of vulnerable devices.

10. Have a Plan for When Things Go Wrong

Breaches, like the 2021 Verkada hack where attackers accessed 150,000 cameras, highlight the need for preparedness.

Develop IoT-specific incident response plans with isolation protocols and detailed logging for forensic analysis. Regularly test these plans to ensure rapid response and containment during an attack.

Benefit: Minimizes impact and recovery time during real-world incidents.

Quick Look at IoT Security Practices

Final Thoughts

Third-party IoT devices are key to modern operations but carry real security risks. Keep a tight inventory, segment networks, enforce encryption, vet vendors, and monitor with tools like Nagios. Cyber threats are a matter of “when,” not “if.” These steps keep your IoT ecosystem secure and ready for action.

In December 2020, hackers slipped malicious updates into SolarWinds’ Orion platform, hitting over 18,000 organizations with data breaches and ransomware attacks. A year later, the Log4j vulnerability put millions of systems at risk with just one line of Java code. A 2022 Security Magazine report says software quality issues cost the U.S. economy $2.41 trillion.

This article breaks down the risks of third-party software, explains what to look for, and shares practical steps to keep your systems secure.

Why Third-Party Software Risks Matter

Third-party software, including open-source libraries, commercial packages, and cloud services, is essential to modern applications but introduces significant vulnerabilities. Weaknesses in these components can lead to data breaches, operational disruptions, or regulatory penalties under standards like the General Data Protection Regulation (GDPR) or the California Consumer Privacy Act (CCPA). A 2023 Cybersecurity Ventures report noted that supply-chain attacks are a growing threat, with third-party software as a primary attack vector. By proactively managing these risks, businesses can safeguard their systems and maintain trust.

Steps to Assess and Mitigate Risks

1. Map Your Software Ecosystem

You can’t protect what you don’t know about. Start by listing all the software your applications use.

Make a Software Bill of Materials (SBOM) to track everything from open-source libraries to commercial tools and cloud services like APIs or SaaS platforms. Tools like CycloneDX or System Package Data Exchange (SPDX) create clear visuals of how your software connects, including hidden dependencies. Check this list every three months to catch any changes.

Benefit: Helps you see all the software you rely on.

2. Evaluate Risk Factors

Look closely at your software to find risks that could cause trouble.

Examine how often open-source projects are updated and who’s working on them using platforms like GitHub or GitLab. Active projects with many contributors are usually safer. Use the National Vulnerability Database (NVD) to check for known issues and their severity. Make sure software licenses, like General Public License (GPL) or Massachusetts Institute of Technology (MIT), won’t cause legal problems, using tools like FOSSA to verify.

Benefit: Pinpoints risky software so you can act fast.

3. Leverage Automated Scanning Tools

Integrate Software Composition Analysis (SCA) into your continuous integration/continuous deployment (CI/CD) pipeline for early detection.

Use tools like the Open Worldwide Application Security Project (OWASP) Dependency-Check to scan for known vulnerabilities or Snyk for real-time alerts and remediation guidance. Run scans on each pull request via GitHub Actions or Jenkins, adjusting severity thresholds to minimize false positives.

Benefit: Detects issues before they reach production.

4. Conduct Manual Reviews

Manual reviews complement automation for deeper insights.

Verify cryptographic signatures, such as GPG or Secure Hash Algorithms (SHA), for software binaries and updates to prevent tampering. Review open-source project commit histories for suspicious activity, such as unverified contributors or sudden contribution spikes.

Benefit: Uncovers risks that automated tools may miss.

5. Assess Vendor Security

Not all software or cloud services are built with security in mind.

Ask vendors about their security practices using questionnaires like Standardized Information Gathering (SIG) or the Cloud Security Alliance’s Consensus Assessment Initiative Questionnaire (CSA CAIQ), focusing on encryption, incident response, and access controls. Check for certifications like System and Organization Controls (SOC) 2 or information security standard (ISO) 27001, and look for weaknesses, like poor authentication. Review vendors yearly or after any security issues.

Benefit: Makes sure your vendors meet high security standards.

6. Prioritize and Remediate Risks

Not all vulnerabilities are equal. Sort them by how serious they are.

Focus on critical issues with high Common Vulnerability Scoring System (CVSS) scores (above 8.0) in widely used software that hackers already know how to exploit. Tackle moderate issues (CVSS 4.0–7.9) in less critical systems next. Ignore minor issues with no known exploits unless they’re easy to fix. You can patch problems, swap risky software for safer options like Simple Logging Facade for Java (SLF4J) instead of Logging for Java (Log4j), or isolate weak components using network separation or tools like Docker.

Benefit: Saves time by tackling the most dangerous threats first.

7. Implement Continuous Monitoring

Ongoing vigilance is essential to manage dynamic supply chain risks.

Sign up for vendor security alerts and Common Vulnerabilities and Exposure (CVE) updates through tools like Snyk or Black Duck. Use zero-trust principles to check every piece of software regularly. Try AI-powered tools like Synopsys Polaris to spot unusual patterns in software vulnerabilities.

Benefit: Maintains security in an evolving threat landscape.

Risk Assessment Checklist

Final Thoughts

Third-party software can expose your business to serious risks, but you can tackle them with the right steps: map your software, check for vulnerabilities, use automated tools, do manual reviews, review vendors, prioritize fixes, and keep monitoring for threats.

In today’s connected world, cyberattacks are inevitable. Take action now to strengthen your defenses and stay ahead of threats.

This guide will take you through key network monitoring insights and point you to the right Nagios documentation and video tutorials to help you obtain them.

Whether you’re monitoring, troubleshooting, or staying ahead of potential issues, you’ll find the tools and resources here:

The High Cost of Downtime: Why Predictive Monitoring Is Now Essential

Imagine if your IT system could warn you about issues before they turn into big problems. That’s what predictive analytics helps you do. Predictive analytics will analyze data trends to spot warning signs early, giving you a head start on fixing issues.

How Nagios Helps:

Nagios XI uses smart alerting that prioritizes the most critical issues, looking at historical data to help predict future outages and IT problems. With the right alerts in place, your team can focus on fixing real issues instead of getting bogged down by false alarms or minor glitches. Predictive analytics can also be used for capacity planning.

➤ Resources to Implement:

Navigating Complexity: Monitoring Across Hybrid and Multi-Cloud Environments

Many companies today have a mix of cloud services and local servers. Without a single view, it’s easy to miss outages or slowdowns.

How Nagios Helps:

Nagios XI gives you one dashboard to monitor everything. Physical servers, cloud platforms, network gear, and others. With a single customizable dashboard, you get a complete picture and can catch issues before they become big problems.

➤ The Nagios Documentation to Implement:

Bridging the Gap: Why IT Teams Combine Prometheus with Nagios

Many teams use Prometheus to gather metrics, but they still rely on Nagios for alerts and infrastructure checks. Merging these capabilities helps eliminate blind spots and simplifies monitoring across your entire environment.

How Nagios Helps:

Thanks to Nagios XI’s new Prometheus Monitoring Wizard, you can easily pull metrics from Prometheus into Nagios. No complicated scripts needed. Just click, set up with the wizard, and start monitoring.

➤ The Nagios Documentation to Implement:

Observability Without the Noise: Accelerating Troubleshooting at Scale

Looking at logs or metrics alone can slow you down. When you bring logs and performance data together, troubleshooting becomes much easier.

How Nagios Helps:

Nagios Log Server works hand-in-hand with Nagios XI to bring logs and metrics into one place. Finding the root cause is quicker and easier.

➤ The Nagios Documentation to Implement:

Self-Healing Infrastructure: Meeting the Demands of Always-On IT

Manual fixes can take a lot of time. Automation allows your systems to react instantly when problems happen, reducing downtime.

How Nagios Helps:

Nagios XI’s event handlers can run scripts automatically when issues are detected, helping your environment heal itself without waiting for someone to step in.

➤ The Nagios Documentation to Implement:

Stay Ahead with Nagios

Keeping your IT environment resilient, efficient, and secure might seem difficult, but with the right tools and guidance, it can be simplified. Nagios documentation provides all the resources you need to implement smarter monitoring strategies, from predictive analytics and automation to capacity planning and alerting.

Have questions or want to see it in action? We’re here to help! Contact sales@nagios.com or book a demo.

Extra Tip: Finding the Right Nagios Documentation

We recently revamped the Nagios Documentation page to make it easier for you to find exactly what you need. First, select your solution or project, then use filters to access the most relevant guides, videos, and docs.

If you don’t find what you need there, check out Nagios Support.

But here’s the challenge: IT infrastructures are growing more and more complex (cloud, on-prem, edge, hybrid setups, and others.) And because of that complexity, manually monitoring your network is becoming increasingly difficult, making it harder to keep track of everything.

That is where monitoring automation comes in.

In this article, we’ll explore what monitoring automation is, why it’s being used, and why Nagios remains a trusted solution for IT teams.

What Is Monitoring Automation?

Monitoring automation uses software, scripts, or integrations to automatically monitor network health. It’s all about letting software take care of routine checks, alerting you early to problems, and even fixing issues automatically. In other words, it’s monitoring your network without constant human intervention.

Let’s use an analogy to explain monitoring automation. Imagine a team working in a server room, manually configuring devices, updating settings, and managing network traffic to keep everything running smoothly. Without automation, they have to handle all these tasks by hand, which takes time and can lead to delays or errors. But with monitoring automation tools, these tasks are done automatically. This lets the team focus on bigger projects while the network runs efficiently on its own.

Why Monitoring Automation is Being Used

With hybrid environments spanning on-premises servers, cloud workloads, and remote devices, automated monitoring is more important than ever. It helps teams:

• Catch problems before they escalate.
• Resolve incidents faster.
• Use resources more efficiently.

As a result, IT teams can spend less time reacting and more time planning ahead.

Let’s look at a few of the benefits that show why automation is gaining such strong attention:

• Automatically detect new devices or services.
• Create alerts for when set thresholds are crossed.
• Run scripts to fix known problems (like restarting a crashed service).
• Auto-generate and distribute dashboards and reports automatically.

This kind of automation doesn’t just reduce manual work; it helps teams stay ahead of outages and scale as their environments grow.

Is Nagios Obsolete? Here’s Why It’s Still a Top Choice for Monitoring Automation

With so many monitoring solutions out there, some may ask, “Is Nagios obsolete?”

Not at all.

Nagios remains a trusted choice for many organizations. Here’s why:

1. Reliability

Nagios has been around for over 25 years, earning a reputation for stability. Aerospace companies use Nagios to launch rockets. Healthcare companies and clinical research labs use Nagios to monitor fridge temperatures, ensuring medicines remain stable within required ranges. When your systems are critical, you need a monitoring tool you can trust to keep working.

2. Automation That Fits Your Workflow

Nagios XI supports automation features like auto-discovery, intelligent alerting, and scripting for remediation. It integrates well into existing workflows, enabling your team to automate routine tasks like restarting services or scheduling updates.

3. Dashboards That Tell the Whole Story

Nagios dashboards bring together uptime stats, alert history, and performance trends, so you’re not just seeing that a server went down—you’re seeing when it happened, how often it’s happened before, and what factors may have caused it. With this full context, you can troubleshoot faster and prevent repeat issues.

4. Combines Automation with Human Insight

Some monitoring tasks require a little more context or judgment that automation can’t fully replace. Nagios XI includes tools like Business Process Intelligence (BPI) that take into account defined rules you can set up so that you are seeing the full picture as it relates to your business.

This helps teams focus on the most important issues while still automating much of the monitoring process.

Related Reading: Nagios XI BPI: Actionable Insights for IT Monitoring and Optimization

5. Reduces Noise with Smarter Alerting

One of the biggest challenges in IT monitoring is alert fatigue, getting so many notifications that teams start to overlook them, or worse, miss critical ones.

Nagios helps reduce this problem by giving you tools to control and fine-tune how alerts are generated and delivered:

• Parent-child Relationships: You can define relationships between hosts so that if a parent device (like a router) goes down, Nagios won’t flood you with alerts for every child device (like connected servers). This helps avoid excessive alerts and keeps the focus on the root issue.
• Threshold Tuning: Nagios allows you to define specific thresholds for warning and critical states, whether that’s CPU usage, disk space, or response time. You control when alerts are triggered, so you’re not getting notified for small fluctuations that don’t need immediate action.
• Custom Notification Rules: Notifications can be scheduled, escalated, or filtered based on user roles, time of day, or impact.

With these settings, teams can ensure they are getting relevant alerts that actually need attention.

6. Designed with Security and Access Control in Mind

Security is built into the Nagios ecosystem. These are features like role-based access controls and audit logging. This helps organizations maintain secure monitoring setups, especially when automation is involved.

Final Thoughts

Monitoring automation helps reduce manual tasks and makes it easier to keep systems running smoothly. With Nagios, teams can shift from reactive monitoring to a more proactive, automated approach.

If you would like to learn more about Nagios and its capabilities, visit our solutions page.

Nagios consistently proves its value in on-premises infrastructure monitoring software, trusted by IT teams for critical systems where cloud solutions fall short.

It has evolved to stay ahead of modern IT demands, remains flexible and reliable, and continues to make monitoring easier.

Let’s clear up the misconceptions, explore recent upgrades, and see why Nagios is still used today.

Why Some are Asking if Nagios is Obsolete — and Why that’s Not the Full Story

First, let’s clear up a few misconceptions about Nagios.

Misconception #1: “Nagios isn’t extensible.”

Some argue Nagios’s architecture is outdated, claiming plugin management is time-consuming and that configuration effort increases with each update. But Nagios was actually built for extensibility.

Why Nagios Remains Trusted: With its plugin-based architecture, you can monitor just about anything, from servers and switches to networks and custom applications, while community-contributed plugins keep it adaptable to evolving technologies.

Misconception #2: “It’s too manual.”

Host administration in Nagios used to sometimes be perceived as too complicated and labor-intensive. While earlier versions of Nagios involved more manual tasks, the platform has evolved significantly. Today’s platform offers streamlined tools and features that make host administration far easier and more efficient.

Why Nagios Remains Trusted: With Configuration Wizards, bulk management tools, and integrations, Nagios can be as automated as your team needs. This flexibility lets you streamline monitoring setup and maintenance without sacrificing control of your infrastructure.

Misconception #3: “Nagios is hard to set up and use.”

One reason why some may think Nagios is obsolete is because of the misconception that Nagios is hard to use. While the open-source Nagios Core has a steeper learning curve and requires manual configurations, Nagios also offers four enterprise-level solutions that eliminate much of the complexity of these tasks. The main differences between Nagios Core and XI are that XI is much easier to work with, helps you get things done faster, better meets business requirements, and comes with more features right out of the box.

Why Nagios Remains Trusted: Take Nagios XI, for example. XI includes a modern web interface, built-in Configuration Wizards, bulk management tools, and an intuitive layout that makes setup and use faster and far less technical. Even users with more limited IT knowledge can learn to navigate the interface, create checks, and manage alerts.

Misconception #4: “It isn’t scalable.”

Some claim Nagios struggles with scaling due to outdated manual processes, complex plugin management, and command-line reliance. However, this overlooks all the improvements Nagios has made that help simplify administration.

Why Nagios Remains Trusted: Nagios XI offers setup Wizards, intuitive GUIs, and bulk management tools that greatly reduce manual effort, making scalability easier. Whether you’re monitoring a few servers or thousands of devices across multiple locations, Nagios can handle the load.

Misconception #5: “It’s hard to train others on Nagios.”

While Nagios Core can be hands-on, tools like Nagios XI simplify onboarding in a few ways:

1. The user interface is straightforward and user-friendly.
2. User roles and permissions help simplify access for different team members.
3. There’s plenty of documentation, support, and video tutorials available to guide users step-by-step.

Why Nagios Remains Trusted: The Nagios ecosystem is structured enough that knowledge transfer is straightforward, even across teams.

Misconception #6: “Nagios hasn’t been updated in years.”

Despite the misconception, Nagios has seen consistent updates that stay ahead of evolving infrastructure needs.

Why Nagios Remains Trusted: Nagios is actively maintained and regularly updated. Recent releases (like Nagios Network Analyzer 2026R1 and Nagios Log Server 2024R2) show ongoing development aimed at modern infrastructure needs, including security updates, bug fixes, new Configuration Wizards, and more.

What’s New in Network Analyzer: NNA 2026R1 integrates the security tools Wireshark, Suricata, Nmap, for comprehensive network monitoring, including:

• Traffic volume and flow analysis.
• Rules-based threat detection.
• Network mapping and endpoint validation.

Learn More: Check out the changelog or the Network Analyzer product page for more details.

What’s New in Log Server: Enhanced User Interface. Log Server 2024R2 has a completely updated and easier to navigate user interface. Check out the changelog to view all the recent updates.

Learn More: This article covers all of what’s new: Ready to Rock: What’s New in Log Server 2024R2. Or if you’re a more visual learner, check out this Nagios Webinar: Nagios Log Server 2024R2 Showcase.

Misconception #7: “Nagios can’t be customized.”

Some might ask, “Is Nagios obsolete?” partly because they think it lacks customization options. This perception often comes from Nagios Core’s original design, which involves manual configuration that could seem complex. That complexity leads some to believe Nagios isn’t flexible enough for modern IT environments.

Why Nagios Remains Trusted: With Nagios, you can easily set alerts, adjust thresholds, and tailor monitoring to fit your unique environment and needs. Customization is not only possible, but easy. Hear it from Astiostech’s Director Alfred Chong:

“I think the key feature that Nagios XI presented to us is the ability for us to customize it for exactly what was needed.”   

— Alfred Chong, Director at Astiostech 

Related Readings:

Brief Overview

Nagios started in 1999 as an open-source Core focused on reliable monitoring. It’s still going strong today thanks to ongoing innovation and continuous improvements. Today, Nagios fits modern IT needs with:

1. High extensibility 
2. Automation support 
3. Ease of use 
4. Scalability 
5. Simplified onboarding 
6. Continuous updates
7. Flexible customization 

Curious how Nagios can support your infrastructure? Try Nagios XI free for 30 days.