Operations | Monitoring | ITSM | DevOps | Cloud

In a microservices setup, tracking a single request across services quickly gets complex. One service calls another, then a third, and your logs don’t line up. The traceparent header carries context between services, so all parts of a request connect back to the start. For example, when a frontend sends a request to an API, which then calls a database service, traceparent it links those calls in the trace. Without it, you’re left guessing how requests flow.

When an application functions flawlessly in your environment but crashes unpredictably on a client’s Windows server, the root cause is often buried in system logs—logs many developers overlook. Windows maintains comprehensive error records that document crashes, failures, and system events with precise detail. These Windows error logs serve as an invaluable resource for diagnosing issues in production environments.

If you manage a Linux server and notice something unusual, auditd logs can help you track exactly what’s happening. This built-in audit system records who accessed the system and what actions they performed. In this guide, we’ll cover setting up auditd, reading the logs, and using them to detect potential security issues early.

If you’ve worked with Kubernetes, you know logs are essential for understanding what’s happening inside your clusters. However, unlike traditional servers, Kubernetes logs present their unique challenges. Pods frequently start and stop, containers restart regularly, and logs stored locally can be lost quickly. Because of this, managing logs in Kubernetes requires a different approach.

You’ve probably run a lot of Docker containers, but do you know what happens behind the scenes? The Docker container lifecycle is the path a container follows from being created to running, stopping, and finally getting removed. Understanding these steps helps you figure out why a container might not start or when to restart it instead of creating a new one.

Server performance metrics help you figure out what’s going wrong, where your bottlenecks are, and how your system handles load. They give you the data to plan capacity, fix issues before they escalate, and build more reliable infrastructure. In this guide, we’ll go over the core metrics that matter, how to monitor them effectively, and the tools that can help along the way.

Logs are a key part of building and running software, but managing them can get complicated fast. As your apps grow and generate logs from many sources, choosing the right tool to store, search, and analyze those logs becomes important. Graylog and Loki are two popular options, each with a different way of handling logs. In this blog, we’ll break down the main differences between Graylog and Loki, how they work, and which types of projects they suit best.

A CDN delivers your content around the world, making sure users get it quickly and reliably. When it slows down or goes offline, users notice right away. Good CDN monitoring gives your team the information needed to fix issues before they affect users. This guide explains the basics of CDN monitoring and shows practical ways to set it up.

VPC Flow Logs come with a default format that gives you basic network traffic details. But you can tweak the format to capture exactly what you need. This can lower costs, speed up processing, and make your logs fit better with what you’re trying to monitor. If you want to improve security, keep an eye on performance, or save money, adjusting your VPC logs can make a big difference. Let’s take a look at some practical ways to customize your logs beyond the default settings.

Prometheus is supposed to help you monitor your stack, not become the thing you need to monitor. But if you’ve ever seen it spike in CPU and slow everything down, you know that’s not always the case. High Prometheus CPU usage usually shows up when you're scraping too many metrics, using expensive queries, or running with default configs that don’t fit your workload. This guide covers how to track Prometheus CPU usage, what typically causes it, and how to fix it.

In a distributed system, things break in unexpected ways. That’s why observability isn’t optional—it’s how you understand what’s going on under the hood. If you’re comparing tools to instrument your services, OpenTelemetry and Micrometer are two names you’ll run into. Both are used to collect metrics, but they take very different approaches—especially when it comes to flexibility, vendor support, and what you can do with the data.

Elasticsearch does a lot right—it's fast, scalable, and makes searches feel simple. But when things slow down or break, figuring out what’s going on can be frustrating. Especially if you’re not keeping an eye on the right metrics. This guide covers Elasticsearch metrics that are worth tracking and how they help you keep your cluster healthy without data overload.

Grafana is a popular choice for monitoring and visualizing metrics, but login issues can quickly block your access and slow you down. Forgot your password? Can’t get into the admin account? Problems after changing authentication settings? These are some of the most common hiccups—and they’re usually easy to fix. This guide covers the frequent login problems you might face and walks you through practical ways to resolve them.

Logs are essential, but managing them can be tedious. They quickly consume storage, slow down your searches, and make troubleshooting feel like an endless chore. Loki monitoring helps simplify this process, offering a more efficient approach to logging that developers can appreciate.

Debugging modern.NET apps isn’t as simple as scanning logs anymore. With services spread out and systems growing more complex, it's easy to miss the bigger picture. Serilog gives you clean, structured logs. OpenTelemetry brings in traces and metrics to connect the dots. This guide covers how to wire up Serilog with OpenTelemetry, send logs to traces, and build an observability setup that helps you troubleshoot, without digging through disconnected logs for hours.

When something breaks in production, logs are usually where you start. They help you figure out what happened, where, and why. But with microservices architecture, logging isn't simple anymore. In a traditional monolithic application, logs live in one place. With microservices, they're scattered across multiple services, containers, and sometimes even data centers. What used to be a simple grep command now feels like solving a mystery without most of the clues.

Both Grafana Tempo and Jaeger are distributed tracing tools designed for modern microservice architectures. Jaeger, released as an open-source project by Uber in 2015, has matured into a graduated CNCF project. Tempo, announced by Grafana Labs in October 2020, is a newer entrant focused on high-volume tracing with a unique storage architecture. Before comparing these tools in detail, let's quickly review what distributed tracing is and why it matters.

Effective microservices logging requires standardized formats, centralized storage, correlation IDs, and strong security measures. This guide walks you through setup strategies, best practices, and tool recommendations that won't break your budget.

Effective Node.js monitoring requires tracking runtime metrics (memory, CPU), application metrics (request rates, response times), and business metrics (user actions, conversion rates). This guide covers what to track, how to collect it, and how to set up meaningful alerts.

Your Java app slows down during peak load. A microservice crashes, but logs aren’t helpful. These aren’t rare events—they’re common signs something’s off inside the JVM. For Java developers and DevOps teams, JVM metrics offer clues to what’s going on. This blog covers the key metrics to track, what they tell you, and how to use them to troubleshoot performance issues in a practical, no-nonsense way.

Security logs are the quiet sentinels of your Linux systems, recording critical information that can mean the difference between detecting an intrusion and discovering a breach months too late. For most DevOps professionals and system administrators, these logs contain valuable insights that often go untapped. While they're essential for compliance, their real value lies in providing visibility into your system's security posture and operational health.

Troubleshooting failed cron jobs without proper logging can be frustrating. Ubuntu cron logs record the execution of scheduled tasks, helping you identify what's working and what isn't. This guide covers what engineers need to know about Ubuntu cron logs – from finding them to analyzing their contents and setting up effective monitoring solutions.

Implementing observability in Angular applications presents unique challenges. Understanding how users experience your application and identifying performance bottlenecks requires specialized tools and approaches. This guide covers implementing OpenTelemetry in Angular applications, with practical code examples for instrumentation, data collection, and integration with observability backends.

When Solr performance degrades, everyone notices - except maybe your monitoring system. The right metrics can alert you to problems before your users start complaining. This guide walks through the essential Solr metrics that matter for production deployments.

Choosing the right observability setup isn’t just a checkbox—it affects how quickly you can detect issues, debug them, and keep your systems reliable. CloudWatch and OpenTelemetry take different paths to that goal: one is a managed service tightly coupled with AWS, the other a flexible, open-source framework that's becoming a go-to in modern monitoring stacks.

Monitoring complex PHP applications can be challenging. When systems span multiple services and environments, traditional logging approaches often fall short. OpenTelemetry offers a solution - an open-source, vendor-neutral framework that standardizes how we collect and export telemetry data. This guide covers practical implementation steps for DevOps engineers working with PHP applications.

Message queues quietly power a lot of what happens behind the scenes in distributed systems. RabbitMQ is no exception—when it’s working, you don’t notice it. But when it’s not, things break in ways that are hard to trace. This guide walks through what you need to monitor in RabbitMQ, how to set it up, and how to troubleshoot when things go wrong—so you’re not stuck guessing when messages go missing.

When your MongoDB database slows down, it affects your entire application stack. Performance issues can range from minor inconveniences to major outages, making a solid understanding of MongoDB metrics essential for any DevOps engineer. This guide covers the key performance metrics you need to monitor in MongoDB, how to interpret what you're seeing, and practical steps to resolve common issues.

Python powers critical applications across countless organizations, from data processing pipelines to web services that handle millions of requests. While Python's readability and extensive ecosystem make it a developer favorite, its performance characteristics require thoughtful monitoring. As systems grow in complexity, understanding what's happening inside your Python applications becomes increasingly important.

Kubernetes production environments require robust alerting to catch problems before they impact users. While monitoring shows system state, proper alerting tells you when something needs attention. This guide outlines 15 key Kubernetes alerts that help DevOps teams avoid outages and minimize downtime. For each alert, we provide implementation guidance and troubleshooting steps to resolve common issues quickly.

Docker containers isolate application environments, making performance monitoring essential for visibility and stability — especially at scale. To manage production effectively, teams need clear insights into resource usage, bottlenecks, and failure points. This guide covers key Docker metrics, how to collect them, and how to use that data to keep your containerized systems running smoothly.

In modern distributed architectures, observability has shifted from optional to necessary. OpenTelemetry has emerged as the standard framework for telemetry data collection, with exporters serving as the critical bridge to your backend monitoring systems. For developers at any stage—those new to observability practices or those refining existing monitoring setups—a solid grasp of OpenTelemetry exporters will significantly reduce debugging time and improve system visibility.

For DevOps teams managing mission-critical databases, SQL Server observability is a fundamental capability that provides comprehensive insight into database performance and health. Effective observability practices enable teams to identify potential issues before they impact end users and provide the context necessary to resolve problems efficiently. SQL Server observability involves collecting and analyzing metrics, logs, and traces to build a complete picture of database behavior.

React logging is the practice of recording relevant information about your application's behavior during runtime. Unlike traditional server-side logging, React logging happens in the browser and focuses on frontend concerns: component lifecycle events, state changes, user interactions, performance metrics, and network requests. Effective logging creates breadcrumbs that help you understand application flow and quickly pinpoint problems.

Troubleshooting containerized applications can quickly become complex when logs are scattered across multiple systems. Most DevOps teams face this challenge daily—what starts as a simple container deployment often evolves into a complex logging puzzle. This guide explores Docker logging drivers in depth, covering configuration options, best practices, and practical solutions.

Running Ubuntu servers without proper monitoring can lead to unexpected issues. For DevOps engineers and SREs, effective tracking is crucial for maintaining system health and performance. This guide covers everything you need to know about monitoring Ubuntu servers, from the basics to advanced strategies, helping you keep your systems running smoothly, whether you manage a single server or a large fleet.

Apache logs are a critical tool for monitoring your web server, but they can often feel overwhelming. For DevOps teams, understanding these logs is essential for diagnosing issues and maintaining system reliability. In this guide, we'll explore the setup and analysis of Apache logs, offering practical tips to help you make sense of them and use them effectively for troubleshooting and optimization.

In monitoring setups, working with a single metric rarely tells the complete story. The real power of Prometheus lies in its ability to query multiple metrics simultaneously, creating connections between different data points that reveal the true state of your systems. This guide will walk you through everything you need to know about crafting effective multi-metric queries in Prometheus – from basic concepts to advanced techniques that will help you monitor and troubleshoot your infrastructure.