Monitoring once provided straightforward insights into IT health: you collected data, identified metrics to monitor, and diagnosed issues as they arose. However, as IT infrastructure evolves with cloud, containerization, and distributed architectures, traditional monitoring can struggle to keep pace. Enter observability, a methodology that not only enhances visibility but also enables proactive issue detection and troubleshooting.
Is observability simply a buzzword, or does it represent a fundamental shift in IT operations? This article will explore the differences between monitoring and observability, their complementary roles, and why observability is essential for today’s IT teams.
In this blog, we’ll cover:
- What is monitoring?
- What is observability?
- Key differences between monitoring vs. observability
- How observability and monitoring work together
- Steps for transitioning from monitoring to full observability
What is monitoring?
Monitoring is the practice of systematically collecting and analyzing data from IT systems to detect and alert on performance issues or failures. Traditional monitoring tools rely on known metrics, such as CPU utilization or memory usage, often generating alerts when thresholds are breached. This data typically comes in the form of time-series metrics, providing a snapshot of system health based on predefined parameters.
Key characteristics of monitoring:
- Reactive by nature: Monitoring often triggers alerts after an issue has already impacted users.
- Threshold-based alerts: Notifications are generated when metrics exceed specified limits (e.g., high memory usage).
- Primary goal: To detect and alert on known issues to facilitate quick response.
An example of monitoring is a CPU utilization alert that may notify you that a server is under load, but without additional context, it cannot identify the root cause, which might reside elsewhere in a complex infrastructure.
What is observability?
Observability goes beyond monitoring by combining data analysis, machine learning, and advanced logging to understand complex system behaviors. Observability relies on the three core pillars—logs, metrics, and traces—to provide a holistic view of system performance, enabling teams to identify unknown issues, optimize performance, and prevent future disruptions.
Key characteristics of observability:
- Proactive approach: Observability enables teams to anticipate and prevent issues before they impact users.
- Unified data collection: Logs, metrics, and traces come together to offer deep insights into system behavior.
- Root cause analysis: Observability tools leverage machine learning to correlate data, helping identify causation rather than just symptoms.
An example of observability: In a microservices architecture, if response times slow down, observability can help pinpoint the exact microservice causing the issue, even if the problem originated from a dependency several layers deep.
For a deeper understanding of what observability entails, check out our article, What is O11y? Observability explained.
Key differences of monitoring vs. observability
Monitoring and observability complement each other, but their objectives differ. Monitoring tracks known events to ensure systems meet predefined standards, while observability analyzes outputs to infer system health and preemptively address unknown issues.
| Aspect | Monitoring | Observability |
| Purpose | To detect known issues | To gain insight into unknown issues and root causes |
| Data focus | Time-series metrics | Logs, metrics, traces |
| Approach | Reactive | Proactive |
| Problem scope | Identifies symptoms | Diagnoses causes |
| Example use case | Alerting on high CPU usage | Tracing slow requests across microservices |
Monitoring vs. observability vs. telemetry vs. APM
Monitoring and observability are not interchangeable terms, but they do work together to achieve a common goal. Monitoring is an important aspect of an observability workflow, as it allows us to track the state of our systems and services actively. However, monitoring alone cannot provide the complete picture that observability offers.
Observability encompasses both monitoring and telemetry as it relies on these components to gather data and analyze it for insights into system behavior. Telemetry provides the raw data that feeds into the analysis process, while monitoring ensures that we are constantly collecting this data and staying informed about any changes or issues in our systems. Without telemetry and monitoring, observability cannot exist.
Application Performance Monitoring (APM) tools give developers and operations teams real-time insights into application performance, enabling quick identification and troubleshooting of issues. Unlike traditional monitoring, APM offers deeper visibility into application code and dependencies.
How monitoring and observability work together
Monitoring and observability are complementary forces that, when used together, create a complete ecosystem for managing and optimizing IT systems. Here’s a step-by-step breakdown of how these two functions interact in real-world scenarios to maintain system health and enhance response capabilities.
Monitoring sets the foundation by tracking known metrics
Monitoring provides the essential baseline data that observability builds upon. Continuously tracking known metrics ensures that teams are alerted to any deviations from expected performance.
- Example: Monitoring tools track key indicators like CPU usage, memory consumption, and response times. When any of these metrics exceed set thresholds, an alert is generated. This serves as the initial signal to IT teams that something may be wrong.
Observability enhances monitoring alerts with contextual depth
Once monitoring generates an alert, observability tools step in to provide the necessary context. Instead of simply reporting that a threshold has been breached, observability digs into the incident’s details, using logs, traces, and correlations across multiple data sources to uncover why the alert occurred.
- Example: If monitoring triggers an alert due to high response times on a specific service, observability traces can reveal dependencies and interactions with other services that could be contributing factors. Analyzing these dependencies helps identify whether the latency is due to a database bottleneck, network congestion, or another underlying service.
Correlating data across monitoring and observability layers for faster troubleshooting
Monitoring data, though essential, often lacks the detailed, correlated insights needed to troubleshoot complex, multi-service issues. Observability integrates data from various layers—such as application logs, user transactions, and infrastructure metrics—to correlate events and determine the root cause more quickly.
- Example: Suppose an e-commerce application shows a spike in checkout failures. Monitoring flags this with an error alert, but observability allows teams to correlate the error with recent deployments, configuration changes, or specific microservices involved in the checkout process. This correlation can show, for instance, that the issue started right after a specific deployment, guiding the team to focus on potential bugs in that release.
Machine learning amplifies alert accuracy and reduces noise
Monitoring generates numerous alerts, some of which are not critical or might even be false positives. Observability platforms, particularly those equipped with machine learning (ML), analyze historical data to improve alert quality and suppress noise by dynamically adjusting thresholds and identifying true anomalies.
- Example: If monitoring detects a temporary spike in CPU usage, ML within the observability platform can recognize it as an expected transient increase based on past behavior, suppressing the alert. Conversely, if it identifies an unusual pattern (e.g., sustained CPU usage across services), it escalates the issue. This filtering reduces noise and ensures that only critical alerts reach IT teams.
Observability enhances monitoring’s proactive capabilities
While monitoring is inherently reactive—alerting when something crosses a threshold—observability takes a proactive stance by identifying patterns and trends that could lead to issues in the future. Observability platforms with predictive analytics use monitoring data to anticipate problems before they fully manifest.
- Example: Observability can predict resource exhaustion in a specific server by analyzing monitoring data on memory usage trends. If it detects a steady increase in memory use over time, it can alert teams before the server reaches full capacity, allowing preventive action.
Unified dashboards combine monitoring alerts with observability insights
Effective incident response requires visibility into both real-time monitoring alerts and in-depth observability insights, often through a unified dashboard. By centralizing these data points, IT teams have a single source of truth that enables quicker and more coordinated responses.
- Example: In a single-pane-of-glass dashboard, monitoring data flags a service outage, while observability insights provide detailed logs, traces, and metrics across affected services. This unified view allows the team to investigate the outage’s impact across the entire system, reducing the time to diagnosis and response.
Feedback loops between monitoring and observability for continuous improvement
As observability uncovers new failure modes and root causes, these insights can refine monitoring configurations, creating a continuous feedback loop. Observability-driven insights lead to the creation of new monitoring rules and thresholds, ensuring that future incidents are detected more accurately and earlier.
- Example: During troubleshooting, observability may reveal that a certain pattern of log events signals an impending memory leak. Setting up new monitoring alerts based on these log patterns can proactively alert teams before a memory leak becomes critical, enhancing resilience.
Key outcomes of the monitoring-observability synergy
Monitoring and observability deliver a comprehensive approach to system health, resulting in:
- Faster issue resolution: Monitoring alerts IT teams to problems instantly, while observability accelerates root cause analysis by providing context and correlations.
- Enhanced resilience: Observability-driven insights refine monitoring rules, leading to more accurate and proactive alerting, which keeps systems stable under increasing complexity.
- Operational efficiency: Unified dashboards streamline workflows, allowing teams to respond efficiently, reduce mean time to resolution (MTTR), and minimize service disruptions.
In short, monitoring and observability create a powerful synergy that supports both reactive troubleshooting and proactive optimization, enabling IT teams to stay ahead of potential issues while maintaining high levels of system performance and reliability.
Steps for transitioning from monitoring to observability
Transitioning from traditional monitoring to a full observability strategy requires not only new tools but also a shift in mindset and practices. Here’s a step-by-step guide to help your team make a seamless, impactful transition:
1. Begin with a comprehensive monitoring foundation
Monitoring provides the essential data foundation that observability needs to deliver insights. Without stable monitoring, observability can’t achieve its full potential.
Set up centralized monitoring to cover all environments—on-premises, cloud, and hybrid. Ensure coverage of all critical metrics such as CPU, memory, disk usage, and network latency across all your systems and applications. For hybrid environments, it’s particularly important to use a monitoring tool that can handle disparate data sources, including both virtual and physical assets.
Pro tip:
Invest time in configuring detailed alert thresholds and suppressing false positives to minimize alert fatigue. Initial monitoring accuracy reduces noise and creates a solid base for observability to build on.
2. Leverage log aggregation to gain granular visibility
Observability relies on an in-depth view of what’s happening across services, and logs are critical for this purpose. Aggregated logs allow teams to correlate patterns across systems, leading to faster root cause identification.
Choose a log aggregation solution that can handle large volumes of log data from diverse sources. This solution should support real-time indexing and allow for flexible querying. Look for tools that offer structured and unstructured log handling so that you can gain actionable insights without manual log parsing.
Pro tip:
In complex environments, logging everything indiscriminately can quickly lead to overwhelming amounts of data. Implement dynamic logging levels—logging more detail temporarily only when issues are suspected, then scaling back once the system is stable. This keeps log data manageable while still supporting deep dives when needed.
3. Add tracing to connect metrics and logs for a complete picture
In distributed environments, tracing connects the dots across services, helping to identify and understand dependencies and causations. Tracing shows the journey of requests, revealing delays and bottlenecks across microservices and third-party integrations.
Adopt a tracing framework that’s compatible with your existing architecture, such as OpenTelemetry, which integrates with many observability platforms and is widely supported. Configure traces to follow requests across services, capturing data on latency, error rates, and processing times at each stage.
Pro tip:
Start with tracing critical user journeys—like checkout flows or key API requests. These flows often correlate directly with business metrics and customer satisfaction, making it easier to demonstrate the value of observability to stakeholders. As you gain confidence, expand tracing coverage to additional services.
4. Introduce machine learning and AIOps for enhanced anomaly detection
Traditional monitoring relies on static thresholds, which can lead to either missed incidents or alert fatigue. Machine learning (ML) in observability tools dynamically adjusts these thresholds, identifying anomalies that static rules might overlook.
Deploy an AIOps (Artificial Intelligence for IT Operations) platform that uses ML to detect patterns across logs, metrics, and traces. These systems continuously analyze historical data, making it easier to spot deviations that indicate emerging issues.
Pro tip:
While ML can be powerful, it’s not a one-size-fits-all solution. Initially, calibrate the AIOps platform with supervised learning by identifying normal versus abnormal patterns based on historical data. Use these insights to tailor ML models that suit your specific environment. Over time, the system can adapt to handle seasonality and load changes, refining anomaly detection accuracy.
5. Establish a single pane of glass for unified monitoring and observability
Managing multiple dashboards is inefficient and increases response time in incidents. A single pane of glass consolidates monitoring and observability data, making it easier to identify issues holistically and in real-time.
Choose a unified observability platform that integrates telemetry (logs, metrics, and traces) from diverse systems, cloud providers, and applications. Ideally, this platform should support both real-time analytics and historical data review, allowing teams to investigate past incidents in detail.
Pro tip:
In practice, aim to customize the single-pane dashboard for different roles. For example, give SREs deep trace and log visibility, while providing executive summaries of system health to leadership. This not only aids operational efficiency but also allows stakeholders at every level to see observability’s value in action.
6. Optimize incident response with automated workflows
Observability is only valuable if it shortens response times and drives faster resolution. Automated workflows integrate observability insights with incident response processes, ensuring that the right people are alerted to relevant, contextualized data.
Configure incident response workflows that trigger automatically when observability tools detect anomalies or critical incidents. Integrate these workflows with collaboration platforms like Slack, Teams, or PagerDuty to notify relevant teams instantly.
Pro tip:
Take the time to set up intelligent incident triage. Route different types of incidents to specialized teams (e.g., network, application, or database), each with their own protocols. This specialization makes incident handling more efficient and prevents delays that could arise from cross-team handoffs.
7. Create a feedback loop to improve monitoring with observability insights
Observability can reveal recurring issues or latent risks, which can then inform monitoring improvements. By continually refining monitoring based on observability data, IT teams can better anticipate issues, enhancing the reliability and resilience of their systems.
Regularly review observability insights to identify any new patterns or potential points of failure. Set up recurring retrospectives where observability data from recent incidents is analyzed, and monitoring configurations are adjusted based on lessons learned.
Pro tip:
Establish a formal feedback loop where observability engineers and monitoring admins collaborate monthly to review insights and refine monitoring rules. Observability can identify previously unknown thresholds that monitoring tools can then proactively track, reducing future incidents.
8. Communicate observability’s impact on business outcomes
Demonstrating the tangible value of observability is essential for maintaining stakeholder buy-in and ensuring continued investment.
Track key performance indicators (KPIs) such as MTTR, incident frequency, and system uptime, and correlate these metrics with observability efforts. Share these results with stakeholders to highlight how observability reduces operational costs, improves user experience, and drives revenue.
Pro tip:
Translating observability’s technical metrics into business terms is crucial. For example, if observability helped prevent an outage, quantify the potential revenue saved based on your system’s downtime cost per hour. By linking observability to bottom-line metrics, you reinforce its value beyond IT.
Embrace the power of observability and monitoring
Observability is not just an extension of monitoring—it’s a fundamental shift in how IT teams operate. While monitoring is essential for tracking known issues and providing visibility, observability provides a deeper, proactive approach to system diagnostics, enabling teams to innovate while minimizing downtime.
To fully realize the benefits of observability, it’s important to combine both monitoring and observability tools into a cohesive, holistic approach. By doing so, businesses can ensure that their systems are not only operational but also resilient and adaptable in an ever-evolving digital landscape.
In today’s business climate, innovation is critical to business success, and IT leaders are pressed to consistently innovate at a pace that the business has come to expect. The expectations of IT leadership in the education space are no exception to this rule.
In this interview with Kyle Berger, CTO at Grapevine-Colleyville Independent School District, we break down just how complex the IT landscape has become, especially in light of the Covid-19 pandemic and its implications on education. GCISD is a school district of 14,000 students located in North Texas. In this interview, Berger discusses his expertise as an IT leader which spans over 21 years in K-12 technology leadership spread across districts of various sizes and demographics. Berger’s can-do, forward-thinking attitude has earned him marks such as Technology Director of the year for Texas, 2020 National Edtech Leadership winner, and Institutional Leadership award for interoperability. In 2022 Kyle was named one of the Top 100 Influencers in Edtech by Edtech Digest. His career has been centered on deploying a one-to-one program, revitalizing complete districts, and redefinition of technology for multiple districts all while promoting collaboration and teamwork.
In this interview, Berger discussed how he has watched the education IT landscape evolve over the last two decades and his thoughts on the future of this ever-changing space.
Following are edited excerpts of that conversation.
How did you get started in IT?
My career started in the corporate Information Technology world. It was a natural path for me as I studied IT. Unfortunately, I was entering the corporate world just as the dot com bust was happening, which presented its own challenges. My mother and father both spent their careers dedicated to education – mom, as a secretary, and dad as a corporate IT director. A CTO for a school district was a perfect mix of the two career paths for me. Technology in schools is typically overlooked in the education space which I see as an opportunity.
What has been your experience watching this industry evolve?
There’s been rapid change in the last couple of decades that has directly impacted the education space. Back in the day keeping email and internet going was the biggest concern – now it has evolved to an extent where technology is absolutely vital to student learning.
I see technology as a way to bridge the gap between the way kids learn and the way they live. If you can successfully execute that idea then they don’t even realize they are learning. The one-to-one tech program for our students was revolutionary in this regard. Technology will never replace the teacher in the classroom, but it’s opened the classroom up to the rest of the world.
Along with this technological revolution comes new challenges – cybersecurity being one of the major ones. Security is top of mind in the education technology space, and the majority of my job is based around that now. 24/7 x 365 availability is the new norm – it’s necessary to keep all of the school’s applications running. This has shifted our leaders to start thinking and evaluating everything through a more business-focused lens. ROI is more important than ever.
What are your thoughts on the future of the observability market?
In education, I think about observability through two different lenses. There’s the stuff inside the program, but there’s also the lens of the parent needing to be able to see into their children’s education. The ability to manage who has visibility into these systems has changed a lot. We need trend analysis because if we have reliability issues instruction can stop nowadays. When technology stops, learning stops. Being able to see inside all of that is tremendously important. More tech complexity does not come with more people to manage it. Ultimately, having a single pane of glass view allows us to do more with less.
You’ve been in this space for over 20 years – why have you decided to stay in IT?
The ability to press the limits for education. Effecting and empowering change starts in the schools. We are responsible for preparing these students for the real world and that is the responsibility we live with every day working in education. It excites me to continue to adapt to the future. If you don’t like change, technology is not for you. The field is huge, and there is endless opportunity. The future is in technology!
What advice would you give to someone just getting started in IT?
You have to come at this as a collaborative type of person – take suggestions and take feedback. Take time to prioritize networking and mind-sharing with other educators and districts. A true network will be more impactful than anything else in your career growth. Reading is very important to me – a leader once told me: “if you don’t have time to read you don’t have time to lead” and it’s stuck with me throughout my career.
What are your passions outside of work?
I’m passionate about many things – among those are traveling, experiencing the world, and tending to my family’s cattle ranch. Family is everything to me. If you can find a way to achieve the work-life balance that will allow you to go even further and accelerate your career.
What is the best advice you’ve been given in your career?
Realizing and harnessing the power of no – this has been vital to my success. If you are unable to master this you will inevitably end up taking on too many responsibilities which will lead to burnout. Take care of yourself first, be humble, and surround yourself with people who will challenge you. Always lean into the hard work and feedback.
You and your team were recently named the winners of Best Overall Implementation of Technology award – tell me about that? How did you prioritize the enablement of your classrooms in a virtual world?
When the transition to virtual classrooms happened, we were already in a good place because of the technology policies that we already implemented. We transitioned our entire district to fully virtual within 24 hours. Getting our stakeholders involved early and implementing their feedback into the design was extremely helpful. It was a chaotic time – everything was happening quickly and the goal was to not add additional work for our teachers. This was all new to the education sector. Our success was largely due to the fact that we were able to reach beyond education to learn how to roll this out, implement slow thoughtful training, and incorporate both teacher and parent feedback.
K-12 and higher education institutions experienced massive changes in 2020 with the shift to online learning. New challenges arose, such as an increase in cybersecurity threats, students and staff requiring 24/7 access to their computers, and the need to update and improve infrastructure and applications
IT infrastructure monitoring allows K-12 and higher education institutions to face common technology challenges both reactively and proactively. With legacy systems in the past, schools are able to keep IT costs down and minimize risks.
Trends in K-12
Hybrid Classroom Instruction
The pandemic required districts across the country to implement virtual learning, and while students have started to return to the classroom, this does not mark the end of online education. Digital resources are now and will remain to be an increasingly integral part of formal education.
Cybersecurity
2020 marked a record-breaking year for cyberattacks targeting school districts in the U.S. With the new environment of virtual classrooms and online learning, school districts are more focused on cybersecurity than ever before.
Broadband and Connectivity
The pandemic proved that the education system in the U.S. was not equipped to support a hybrid learning model as it requires students, teachers, and administrators to have 24/7 access. Districts are expanding their wireless infrastructure and placing emphasis on the importance of off-campus connectivity for students who lack service at home.
Trends in Higher Education
IT Adoption and Digital Learning Capabilities
Colleges and universities are starting to modernize legacy services and applications as students place an increased emphasis on digital capabilities as a deciding factor in choosing higher education. From class registration portals to online learning platforms, colleges and universities deploy services that millions of users rely on every day.
Hiring/Retaining IT Talent
Higher education is starting to focus on hiring and retaining top IT talent to support the importance of cutting-edge technology to students that is up and running 24/7. Talent needs to be able to draw useful insights and correlation from dynamic IT environments.
Enabling Cross-Team Collaboration to Quickly Resolve Platform Issues
Information silos are a common unintended consequence of growth at educational institutions, and they can slow down efforts to resolve issues in critical academic services. Teams need to ensure that academic services perform seamlessly for their students and faculty across the globe.
Challenges Faced by the Education Industry
The Need for 24/7 Access to Computers and Learning Tools
24/7 access to virtual desktops requires monitoring VDI environments reactively and proactively. The quality and reliability of services and the digital educational experience is key to the success of colleges and universities in attracting students and building and maintaining their reputations.
Modernizing Legacy Services and Applications
As higher education institutions seek to modernize their learning environments, they face the unique challenge of safely replacing legacy systems while learning how to manage new, highly distributed infrastructure at scale. Institutions need to significantly improve the speed and reliability of their services and deliver a better experience for their students, educators, and administrators—all while keeping their IT costs down and minimizing risks.
IT Services That Can Drive Cost
IT departments are tasked with providing more and more services to enhance user satisfaction and engagement. Large technology investments are needed in order to support synchronous classroom and remote learning initiatives.
Security Threats
Schools are more and more prone to phishing and ransomware attacks due to the increased adoption of virtual instructional models. In turn, institutions are required to comply with regulatory standards in order to keep their students’ data safe and secure.
LogicMonitor Solution for Education
Helping Education Institutions Drive Innovation by Consolidating and Standardizing Monitoring for On-Premise and Cloud Environments
LogicMonitor provides comprehensive visibility into dynamic IT environments for your networks, cloud, applications, servers, log data, and more. Data correlation provides insights for intelligent troubleshooting and predicting bottlenecks to scale IT investments and control operational costs enabling enterprises to consolidate and streamline their observability estates.
Extensive Breadth of Coverage Across Complex IT Infrastructure and Ensuring the Reliability of All Digital Capabilities and Services
LogicMonitor’s agentless approach delivers an extensible solution with over 2,000 workflow and ecosystem integrations and unlimited dashboards. Automated discovery of new devices paired with intelligent alerting maximizes infrastructure health and performance by providing automated resolutions for Ops. Monitor resource utilization, network usage and performance, and other critical infrastructure metrics with support for:
- Networks and networking gear
- Cloud and container resources
- Servers, storage, and databases
- Websites and synthetic transactions
- SaaS services essential for remote work
- Applications, IoT devices, and more
Rapid and Automatic Deployment and Configuration for Efficient Monitoring and Lessened Workloads
Get the answers you need to solve problems faster with LogicMonitor’s fully automated platform. Our agentless collectors automatically discover, map, and set baselines for complex and distributed infrastructure in a matter of minutes. Put the manual configuration and expensive hardware behind you and ensure quicker time to train and lessened workloads on IT staff.
Visibility for Teams to Modernize Services and Improve Application Performance at Scale
LogicMonitor prevents context switching with a single view of application services, performance, and infrastructure. LogicMonitor empowers teams to gather, track, trace, and measure application and infrastructure performance so they can achieve digital transformation initiatives with business outcomes – delivered via LogicMonitor’s Hybrid Observability Powered by AI Platform.
One Platform for Hybrid Observability
Metrics
Single platform for ITOps and DevOps that eliminates data silos and tracks metrics that matter. 100% built on OpenTelemetry and OpenMetrics allowing for a vendor-neutral approach to better understand the user experience and accelerate business transformation.
Logs
Log intelligence at scale – instant access to contextualized and correlated logs and metrics in a single, unified cloud-based platform. With tiered retention options, including unlimited retention, and hot storage to optimize data hygiene and internal compliance initiatives.
Traces
Gather application traces seamlessly with quick and simple implementation. Filter and highlight error occurrences or bottlenecks and transition to underlying resource performance for faster troubleshooting.
Working from home today? You’re not alone. Well, maybe you are alone, but hopefully, you catch my drift.
During these unusual times, many schools and businesses are keeping their students, employees, and customers safe at home while ensuring they can still work and study effectively. While this is excellent news for those who like to work in their PJs, it can be daunting for the people running IT infrastructure who are needed to support the sudden surge of online conferences and collaboration.
One of our customers (a prominent University I was not smart enough to get into) is moving all of their classes online out of an abundance of caution for their community. They reached out to their Customer Success Manager here at LogicMonitor, hoping to get better visibility into their cloud-based conferencing tool Zoom. FYI: For other educators looking for a remote conferencing solution for the next few weeks, Zoom is giving free video conferencing to K-12 schools affected by closures.
Here at LogicMonitor, our vision is to expand what’s possible for businesses by advancing the technology behind them, and we work hard every day to realize that vision. Our customer’s IT team needed to ensure that Zoom was working during the unexpected usage surge. More importantly, they needed to be able to show their leadership team that everything was working smoothly.
This university had already leveraged LogicMonitor’s infinite extensibility to create some basic monitoring for the Zoom service. They were able to pull in statistics on things like active users, inactive users, and storage usage for their plan. However, they still lacked some important insight into Zoom that has become critical for them given the volume of usage as their users go remote.
We brought some of our best engineers together to close these gaps and get our customer the visibility they required. Our Sales Engineering team took the lead and were able to crank out monitoring that covers account licensing information, Zoom component status, and overall Zoom status. These items are critical for our customer’s IT team to be able to show leadership that there is no need to panic. Anyone who needs an overview of the system can get it from the comfort and safety of their home, and they don’t need a LogicMonitor account to see it through a shared dashboard.
I wanted to share this story today to let other customers know that anyone relying on Zoom can get the same visibility as the university for no extra cost. It is available in the repository today and will be available in a Zoom package from the LM Exchange in the near future.
I recommend also checking out our recently released Microsoft Office 365 monitoring. If your company has shifted to working-from-home, LogicMonitor’s platform gives you visibility into your Outlook, OneDrive, Yammer, and Teams environment to ensure that your users and customers remain productive. If there is an issue, LogicMonitor will let you know so that you can provide business continuity and worry about what actually matters, your business, your users, and your customers.
As always, we’re here to help. Please reach out if there’s anything else we can do to help you and your environment stay up and running during these difficult times.