In the world of DevOps, every second counts. Problems need to be fixed fast, but with the intention that it’s done with a legitimate purpose for when something’s wrong. Continuous monitoring helps with automation and setting up the right kinds of alerts. If the system is going haywire, every moment not acting can make things worse. That’s why intelligent alerting is critical for enabling observability and continuous effective monitoring.
Out-of-the-box intelligent alerting is a game changer
One of the most significant needs concerning practical, intelligent alerting is automation. To ensure systematic safety, everything should be monitored to check the health and dissect the complexities within those systems. Suppose a system is constantly monitored, built on the idea that fast action is possible. In that case, it makes for a stronger relationship with customers because they can trust you’re working around the clock for their best interests, no matter what product or service you’re selling.
Easy-to-read dashboards let DevOps teams know what’s happening and when, just the same as prescriptive workflows, guide users from the high to the low level without needing lots of training/education – a workflow that keeps IT informed thanks to escalation chains around evolving thresholds leads to strengthened application resiliency is one that makes ITOps job easier.
Adding severity levels to alerting
Setting severity levels can lead to more streamlined performance monitoring that shows how serious a problem is and how fast it needs to be addressed, and if it’s something that the system can monitor or if a human needs to get involved. What matters is a repository where this data lives and can be acted upon for future data collection.
Bringing down investigation time provides information and context to an incident. Collecting the data that shows what happened within a single incident offers a quick view of severity. When these incidents happen, it’s critical to know what services or service instances were running and what the recovery protocol will be.
Why Alerting is Important
Companies monitoring their system health don’t want constant alerts, which can happen due to structural and competing forces, such as:
- Overly sensitive systems that constantly alert with false positives
- When too many non-issues are alerted, and when one that matters happens, no one takes it seriously
- Keeping up with the pace of new tech can create knowledge gaps
- Siloed information due to using multiple systems that don’t talk to one another
Everything isn’t forever
Resources aren’t finite in any circumstance. Tracking resource metrics can be hard when resources appear and disappear. Teams need to be alerted throughout the stack, giving constant data check-ins on what’s moving through the system, whether hosts are shifting from five to fifteen in a matter of hours or if someone is attacking the system.
Critical Components to Smart Alerting
Data monitoring should give users a snapshot into metrics and information, which collect and calculate service maps and dependencies, as well as correlate issues:
- Cluster nodes and infrastructure
- Service Instances
- Built frameworks
- Distributed Traces across the landscape
- Process and Runtime Environments
- Service Dependencies
And even further offer the capability to:
- Log anomalies
- To trace (Metric Alerts -> traces -> to logs for a service)
- Synthetic Alerts based on dynamic thresholds -> to traces
- Be a hub for metric alerts to see metrics in context to identify troubleshooting
Because there’s a chance for real context, it will slash time down. Because the information is detailed, this should create a best-case scenario for the resolution process for the DevOps team who is then armed with information across distributed systems and applications.
Customization isn’t just for t-shirts at the mall
Software should be able to help teams do all of this and create customizable environments. (We can help with this.)
Developers should know what’s going on but also stay within a data repository so the information can be examined later down the road; it helps to create a playbook for future issue resolution. This methodology also helps create visibility into any bottlenecks and what to benchmark against.
What’s in a strategy?
Depending on the business need, systems can be set up for objective usage and, more importantly, customized, so they’re alerting based on a true issue at hand.
Common business goals often include seeking out bottlenecks where alerting should be targeted, prioritizing high functionality, identifying what’s important, and creating alerts that help DevOps teams achieve uptime while nailing business impact. Remember, we’re all serving customers, and that’s always the goal – to keep systems running as smoothly as possible.
Companies should set alerts for mobile crashes, Javascript errors, APIs, service alerting, page load time, and service latency. For the teams using Kubernetes, you could set alerts for uptime, pod health, containers, and network routing. If you don’t have a list of metrics, you could also use service level objectives (SLOs) to create metrics and KPIs reflecting team priorities.
This is about customers, not how deep a DevOps team can get lost within the processes. Serving your customers should always be the priority. Uptime is critical for success, and keeping processes streamlined for effectiveness separates the good from the bad in business.
Alerting is only helpful if teams pay attention. Set alerts that people will respond to correctly – if signs go unnoticed, what’s the point? Alerting serves your team. Balance severity and create guidelines to protect your teams as part of your culture.
Alerting is a method to keep customers’ businesses moving, so customer impact and business outcomes should be a priority. Customers don’t care about internal processes – they care how successful your services are.
After an incident, look at what worked and what didn’t. Craft alerts so they’re impactful and keep the DevOps teams informed and ready vs. labeling something just as an “informational warning.”
What happens after the alert flag goes in the air?
Setting up processes matter, especially ones that are transparent and effective. We suggest following this simple system to see results that aren’t lost within convoluted processes:
- Configure
Set up monitoring + AIOps which access, audit, and seek out anomaly detection, event correlation, automation, and coverage.
- Detect
If the flag is alerted, send it to a collaboration tool like Slack.
- Combine & Refine
Create a single, actionable incident to diagnose and troubleshoot the issue to get to the root cause.
- Triage & assign
Prioritize different root causes to determine resolution and route incidents to teams equipped to respond.
- Remediate & Retro
Execute the resolution: scheduling, routing, escalation, development, testing, and collaboration. Then review to prevent future problems with analytics, post-mortems, and processes.
Let’s talk if you’re interested in learning more about why alerting is crucial for long-term systematic health and managing growth. We’re always looking for the best ways to keep customers thriving, innovating, and focused on what matters the most.