Operations | Monitoring | ITSM | DevOps | Cloud

In 2024, simply having an observability practice is a given. In this era of observability, a high-functioning team will set leaders apart from their peers. Leading observability practitioners don’t fix issues by putting hundreds of people into a virtual room, or frantically messaging in a temporary Slack channel to find root causes. Because leaders embed observability into their development practices early, a feature launch is a quiet non-event.

Logs are a rich source of information, providing you with the minute details you need to troubleshoot a specific issue or perform extensive historical analysis. But with billions of logs being generated from your infrastructure every day, it isn’t practical to sift through them all to derive actionable insights. Firewall, CDN, network activity, and load balancer logs are especially high volume, requiring storage solutions that can be expensive and difficult to scale.

Let’s be real, we’ve never been huge fans of conventional unstructured logs at Honeycomb. From the very start, we’ve emitted from our own codestructured wide events and distributed traces with well-formed schemas. Fortunately (because it avoids reinventing the wheel) and unfortunately (because it doesn’t adhere to our standards for observability) for us, not all the software we run is written by us.

Generative AI has emerged as a powerful force for synthesizing new content—text, images, even music—with astounding proficiency. However, monitoring, optimizing, and maintaining the health of these complex AI systems is challenging, and traditional observability tools are struggling to keep pace. At Grafana Labs, we believe that every data point tells a story, and every story needs a capable narrator.

Application Performance Monitoring (APM) tools play a critical role in ensuring seamless user experiences for businesses. While Dynatrace has established itself as a leader in this field, there exists a range of alternative solutions in the market that may align more closely with the specific needs of your organization. This comprehensive guide delves into the diverse competitors of Dynatrace, offering valuable insights to empower you in making a well-considered choice when procuring an APM solution.

In a relatively short period of time, networks have grown much bigger, much more complex, and much more critical to the ongoing operation of the business. Quite simply, while ensuring optimized network services has never been more critical, it’s also never been more difficult. In many large enterprises, network operations teams are seeing tens of thousands of endpoints added to already complex internal environments.

You hear us at Percepio talking about Observability a lot. For customers using our award-winning Tracealyzer tool, this might sound a bit strange – isn’t Tracealyzer about diagnostics, debugging and profiling? Mostly, yes, but let me share why we are putting so much emphasis on our Continuous Observability solutions.

Predictive analytics has become a key goal in observability. If teams can foresee potential system failures, performance bottlenecks, or resource constraints before they happen, they can act preemptively to mitigate issues. AI holds the promise of making this possible. In this post, we explore how AI can push observability toward predictive analytics, the industry’s current hurdles, and practical use cases for leveraging AI today.

Monitoring application health is a lot like monitoring your personal health. Vital signs such as heart rate, blood pressure, and overall well-being can spot problems before they escalate, helping us maintain good health. Similarly, application health requires constant monitoring of performance indicators like CPU usage, memory consumption, and application response times.