Your alert system might be doing more harm than good. Too many alerts, false positives, and vague notifications are overwhelming teams, leading to missed issues and slower responses. Studies show up to 90% of alerts are false positives, and 28% go unanswered. This isn’t just frustrating - it’s risky. Burnout is on the rise, with 63% of SOC professionals reporting it in 2024.
The problem? Many alert systems are outdated, overly sensitive, or poorly configured. Alerts often lack context, prioritisation, and actionable details, turning them into noise rather than helpful tools. The result? Engineers ignore them, critical problems escalate, and businesses suffer.
Here’s how to fix it:
You don’t need expensive tools to improve alert management. Built-in cloud tools like AWS CloudWatch and Azure Monitor can help. Integrating alerts with Slack or Teams ensures notifications reach the right people quickly. If it’s too much to handle in-house, external experts can fine-tune your system for better results.
Fixing your alerts isn’t optional - it’s necessary to protect your team and your business.
Your alerting system might be doing more harm than good. For many cloud operations teams, what should be helpful notifications often turn into overwhelming distractions. Let’s break down the common problems that transform alerts from useful tools into time-wasting headaches.
Big organisations can receive over 15,000 alerts a day, but even smaller teams aren’t immune to the chaos. Low-priority Slack notifications flood channels, drowning out critical issues. Engineers often end up ignoring alerts altogether, leading to missed problems. Surveys reveal that over half of alerts are false, and nearly two-thirds are redundant. This means teams waste valuable time chasing non-issues, while real threats slip through the cracks.
"Alert fatigue is a state of mental and operational exhaustion caused by an overwhelming number of alerts - many of which are low priority, false positives or otherwise non-actionable." - IBM
This isn’t just an inconvenience - it’s a business risk. Around 28% of teams admit to overlooking critical alerts due to alert fatigue. Imagine a database outage at 3 AM being ignored because the on-call engineer assumes it’s just another false alarm. The root of the problem often lies in unfiltered telemetry and poorly configured alerts. Monitoring tools might capture every tiny fluctuation, but without proper filtering, they’ll keep flagging irrelevant noise.
Take an alert that simply says, "Database connection failed." It’s vague, unhelpful, and forces engineers into lengthy troubleshooting sessions when every second matters. System outages cost businesses an average of £4,480 per minute, so unclear alerts directly hit your bottom line.
Most alerts fail to provide actionable insights. They tell you something’s wrong but don’t explain the severity, the impact, or what to do next. Critical context - like which customers are affected or historical trends - is often missing, turning alerts into obstacles rather than solutions.
"Users don't care why something is not working, but that it is not working." - Aron Eidelman, Cloud Operations Advocate
Another issue is the lack of correlation. For instance, you might receive separate alerts for database slowness, API timeouts, and user complaints, all stemming from the same root cause. Without proper correlation, engineers waste time addressing symptoms instead of solving the underlying problem.
As your infrastructure grows, your alerting rules need to evolve too. A threshold set for 1,000 users won’t work when you’re serving 10,000. Outdated configurations lead to alerts being triggered by conditions that no longer reflect your current environment.
False alarms often spike when thresholds are based on old baselines. For example, migrating to a new cloud region or scaling your services might cause old rules to flag normal activity as issues. Updates from providers like AWS, Google Cloud, or Azure can also impact thresholds, leading to unnecessary alerts.
If you’re seeing a flood of false positives, it’s a sign your system needs tuning. Detection thresholds might be set too low, or outdated rules might miss critical issues entirely. This creates a dangerous scenario where real problems only become apparent after they’ve escalated into customer-facing failures.
"Alert fatigue in IT operations represents a significant challenge that can impact service quality, team effectiveness, and ultimately, the bottom line." - Adrian Talpa
A broken alerting system doesn't have to stay broken. Well-tuned alerts can make all the difference, helping your team respond faster and focus on what matters most. The key is to classify and prioritise alerts so your team can address the critical issues first.
Effective alerting starts with clear severity levels. Without prioritisation, teams often waste time treating minor issues as emergencies, while missing the truly critical ones. In fact, 60% of security professionals report experiencing alert fatigue.
A simple way to organise alerts is by using three categories: Critical, Warning, and Info.
For example, in a SaaS platform, critical alerts might focus on core services like authentication, payment systems, or key API endpoints, while development environment issues might remain at the info level.
To reduce noise, group similar alerts into one notification. For instance, if multiple nodes in a database cluster are having connection issues, send a single consolidated alert. This approach provides a clearer picture of the problem and avoids overwhelming your team with duplicate notifications.
Set thresholds based on Service Level Objectives (SLOs) and error budgets rather than arbitrary metrics. For example, if your SLO guarantees 99.9% uptime, configure alerts to trigger only when you're at risk of breaching that promise.
Once you've prioritised your alerts, make sure they include the right details for quick action.
Vague alerts waste precious time. To make alerts actionable, they need to include enough detail for your team to assess and respond immediately.
For instance, instead of a generic "Service Down" message, use something like: "Payment API: 500 errors affecting checkout flow, 15% of transactions failing since 14:30." Specific details, such as the affected service, the type of issue, and the impact, allow engineers to jump straight into problem-solving.
To further enhance clarity, enrich alerts with:
The goal is to minimise investigation time by providing all the necessary information up front.
Not every alert needs a human response. Automating fixes for predictable issues can save time and reduce alert fatigue.
For example, self-healing systems can automatically scale up resources or restart failing services. If application servers experience high CPU usage, automated scaling can spin up more instances before users are impacted. Similarly, if a container crashes due to a memory leak, an automated restart can restore service while logging the incident for review.
Here are some common tasks you can automate:
While these automated actions should still generate notifications, they can be assigned lower priority since the system is already handling them.
Automation can also streamline incident escalation. If an automated fix fails, the system should notify the appropriate team members with full context about the attempts made. For instance, Hyperglance allows you to set up rules for periodic cleanup in development environments, automatically removing unused resources to prevent unnecessary alerts.
"Automating routine and repetitive tasks can increase efficiency for SOC analysts, freeing up time for strategic activities".
However, automation isn't a "set it and forget it" solution. Each automated process should log its actions and success rates, so you can refine the system over time. If something goes wrong, the system should escalate the issue to prevent small problems from spiralling into major outages.
After fine-tuning your alerts, equipping your system with the right tools can make a big difference. You don’t need to invest in pricey platforms - built-in cloud solutions and simple integrations can simplify alert management, especially for smaller or growing teams.
Cloud providers like AWS and Azure offer powerful monitoring tools that are often underutilised. These tools, included with your cloud subscription, provide a cost-efficient way to improve alert management.
For example, AWS CloudWatch allows you to create custom metrics and define thresholds that align with your application’s specific behaviour. Instead of relying on generic CPU usage alerts, you can configure conditions that reflect your workload’s unique patterns. Similarly, Azure Monitor offers flexibility through action groups and smart detection features, which identify unusual performance patterns and alert you to anomalies that fixed thresholds might overlook.
Integrating alerts with collaboration platforms like Slack or Microsoft Teams can revolutionise how your team responds to incidents. This approach eliminates the need to juggle multiple tools, ensuring notifications reach your team where they already communicate.
Modern integrations go beyond simple notifications. They can create dedicated incident channels, notify the right people, and provide real-time updates. For instance, when a payment system alert is triggered, the system might automatically set up a channel (e.g., #incident-payment-api-27/06/2025), invite relevant team members, and pin essential resources like runbooks.
"Real-Time Collaboration is extremely important whilst resolving an incident. AlertOps helps resolve incidents faster by getting the right people involved and enabling them to communicate through Slack and Microsoft Teams in real-time."
- AlertOps
Automation plays a key role here, reducing Mean Time to Resolution (MTTR) by as much as 78%. Setting up these integrations may require some initial effort, but most monitoring tools provide pre-built connectors to simplify the process - even for teams without dedicated DevOps resources.
"Integrating alert and incident workflows into platforms like Slack, Microsoft Teams, and Zoom allows agile Dev and IT Operations teams to stay aligned and react swiftly."
If automation and integrations aren’t enough, external expertise can further optimise your system.
Sometimes, bringing in external expertise is the smartest move, especially for teams focused on product development that lack dedicated Site Reliability Engineering (SRE) experience.
Effective alert tuning demands ongoing attention and a deep understanding of your application’s architecture. An expert can help determine which alerts are genuinely useful and which ones just contribute to unnecessary noise. For instance, Critical Cloud’s Engineer Assist service offers alert tuning and error triage as part of its £400/month package. This includes up to four hours of proactive monthly support from experienced SRE professionals, helping you keep your alerting system sharp as your business scales.
"Automation in incident response is about codifying the practices that you've identified to make your process effective. Automation removes the guesswork for your responders by providing them with communication channels and an environment where they can dive into the incident without worrying about 'process'."
- Tony Holmes, Head of SRE at Affirm
Experts can also implement advanced practices like "alerts as code", which makes alert configurations version-controlled and testable. They can set up tiered alerting systems to minimise fatigue while ensuring critical issues are prioritised. Look for partners who optimise your existing tools rather than pushing new ones, so you can enhance your current monitoring stack without adding unnecessary complexity or vendor lock-in. The goal is straightforward: alerts that inform and assist, not overwhelm.
Building on the discussion about reducing alert noise, this section dives into the pros and cons of different alert management methods. The way you handle automation and support can significantly influence your incident response strategy. Once you've fine-tuned your alerts, the next step is deciding how and by whom they should be managed.
When it comes to alert tuning, choosing between manual and automated methods depends on your team's resources and workflow. Each has its own strengths and weaknesses, which can shape your day-to-day operations.
Manual alert tuning gives your team full control. You can monitor system performance, identify patterns, and adjust thresholds based on your deep knowledge of your systems. This approach is ideal for smaller setups where every component is well understood, enabling you to craft highly specific rules that align with your business needs.
But there’s a cost. Studies show that analysts spend over half their time on repetitive manual tasks during triage. This reactive approach often means issues are only caught after they’ve already impacted users. As your infrastructure grows, manual tuning can quickly become unmanageable.
Automated alert tuning, on the other hand, shifts much of this burden to technology. Automation tools monitor performance, detect anomalies, and send real-time notifications without requiring constant human intervention. This not only speeds up response times but also reduces the chance of human error, allowing you to scale monitoring across multiple systems effortlessly.
| Feature | Manual Alert Tuning | Automated Alert Tuning |
|---|---|---|
| Response Time | Reactive, often delayed | Instant notifications for faster action |
| Accuracy | Prone to human error | Consistent and reliable |
| Scalability | Struggles as infrastructure grows | Easily handles growing complexity |
| Customisation | Highly tailored to specific needs | Standardised but less flexible |
| Cost | Lower initial cost for small setups | Higher upfront investment, long-term savings |
Many teams find a hybrid approach works best. Automated systems handle routine monitoring and anomaly detection, while manual oversight is reserved for complex or edge-case scenarios that require human judgement. This balance ensures strong coverage without overwhelming your team with unnecessary alerts.
Once you’ve decided on tuning methods, the next step is to choose whether to manage alerts in-house or bring in external expertise.
Managing alerts internally gives you complete control over your monitoring strategy. Your team knows the context behind each alert, can make quick adjustments, and gains valuable insights into your systems. For smaller teams with manageable infrastructure, this approach can be effective.
However, as your operations grow, internal management can become a challenge. Larger setups demand specialised expertise and constant attention. Product-focused engineers may find themselves pulled away from their core responsibilities, and without regular tuning, your team risks missing critical threats amidst a flood of alerts.
Bringing in external experts can help ease this burden. Managed service providers (MSPs) act like an extension of your team, offering dedicated, round-the-clock support without the need to hire additional staff. They bring experience from working across various environments, enabling them to identify common alert patterns and fine-tune configurations for optimal performance.
For growing companies, outsourcing can often be more cost-effective than building an in-house team. MSPs provide proactive support, helping you stay ahead of issues while keeping operational costs in check.
The key is to find a partner who complements your existing tools rather than pushing you toward a completely new stack. Seek providers who can optimise platforms like Datadog, CloudWatch, or Azure Monitor without introducing unnecessary complexity or locking you into a specific vendor. The ultimate goal is the same: alerts that empower your team to act effectively, not overwhelm them.
Fine-tuning your alerts isn’t a one-and-done task - it’s a process that requires regular attention. Once you’ve adjusted your thresholds, the next step is ensuring every alert serves a clear purpose.
The key is to focus on what truly matters to your users. Alerts should highlight customer-impacting symptoms rather than flagging every minor technical hiccup. For instance, if your API response time spikes from 200ms to 2 seconds, that’s a red flag worth immediate attention. On the other hand, a slight delay in a background job that doesn’t affect the user experience might not need urgent action. Each alert should come with actionable details so responders know exactly what steps to take.
Prioritisation is essential. Break alerts into high, moderate, and low priorities:
Set aside time each month to review your alerts. Look for patterns: Are you getting too many false positives? Are there real issues being missed? Do threshold settings need an update? Regular reviews keep your system sharp and relevant.
When possible, automate responses to predictable problems. This reduces manual workload and frees up your team to handle more critical challenges.
Another important step is using evaluation windows smartly. Avoid triggering alerts for brief, self-resolving spikes. Instead, configure alerts to activate only if issues persist - say, 5 minutes for critical services or 15 minutes for less urgent ones. This approach ensures your alerts remain meaningful and don’t become a constant source of noise.
Striking the right balance between precision and minimal noise is the ultimate goal. A well-optimised alert system should act as a reliable early warning tool, not a constant distraction. Done correctly, every alert either drives immediate action or provides valuable insights for further investigation - anything else is just unnecessary clutter.
To keep your team focused on what truly matters, start by organising alerts based on their severity and impact on the business. Give priority to high-risk issues that could interfere with operations or affect customer experience, while filtering out low-priority or irrelevant alerts to cut down on unnecessary noise.
Using automation for alert routing and setting clear thresholds can significantly reduce alert fatigue, ensuring your team isn’t bogged down by constant, unnecessary notifications. By incorporating dynamic risk scoring and prioritising based on impact, you can streamline the response process. This approach allows your team to quickly address the most pressing issues without getting sidetracked by less important signals.
To cut down on routine alert responses and combat alert fatigue, consider using smart alerting systems. These systems can automatically adjust thresholds and group related alerts, helping to filter out unnecessary noise so your team can zero in on what truly matters.
You can also integrate automation tools like infrastructure as code (IaC) solutions, such as Terraform, to simplify response processes. These tools allow for quick and consistent actions without needing manual input, which not only boosts efficiency but also reduces the chance of errors. By automating repetitive tasks and fine-tuning your alert settings, your team can stay focused, reduce false alarms, and improve overall operational efficiency.
Integrating alerts with collaboration tools like Slack or Microsoft Teams can make a big difference in how quickly teams handle incidents. By streamlining communication, these tools ensure that real-time notifications reach the right people instantly, allowing them to take action, share updates, and coordinate without the hassle of jumping between multiple platforms.
What’s more, these integrations bring critical details - such as logs or incident reports - right into the communication tool. This means teams can diagnose and fix issues without wasting time searching for information elsewhere. With all discussions and actions happening in one centralised space, teams can stay on track and respond efficiently, helping to cut downtime to a minimum.