When teams begin to analyze their logs, they almost immediately run into a problem and they’ll need some JSON logging tips to overcome them. Logs are naturally unstructured. This means that if you want to visualize or analyze your logs, you are forced to deal with many potential variations. You can eliminate this problem by logging out invalid JSON and setting the foundation for log-driven observability across your applications.
Kibana is the most popular open-source analytics and visualization platform designed to offer faster and better insights into your data. It is a visual interface tool that allows you to explore, visualize, and build a dashboard over the log data massed in Elasticsearch clusters. An Elasticsearch cluster contains many moving parts. These clusters need modern authentication mechanisms and they require security controls to be configured to prevent unauthorized access.
Log observability and monitoring are terms often used interchangeably, but really they describe two approaches to solving and understanding different things. Observability refers to the ability to understand the state of a complex system (or series of systems) without needing to make any changes or deploy new code.
A Content Delivery Network (CDN) is a distributed set of servers that are designed to get your web-based content into the hands of your users as fast as possible. CDNs produce CDN logs that can be analyzed, and this information is invaluable. Why? CDNs host servers all over the world and are designed to help you scale your traffic without maxing out your load balancers. A CDN also gives you added protection against many of the most common cyber attacks. This activity needs to be closely monitored.
Observability and its implementation may look different to different people. But, underneath all the varying definitions is a single, clear concept: Most software that’s run today uses microservices or loosely coupled distributed architecture. While this design makes scaling and managing your system more straightforward, it can make troubleshooting issues more difficult. The three pillars of observability are different methods to track software systems, especially microservices.
Observability is a term that is becoming commonplace in both startups and enterprises. Log observability is different from monitoring, as it provides visualized metrics from a variety of different systems in a single pane of glass view. This is invaluable for organizations to understand the interdependencies and links between external events and internal performance.
Logs play a key role in understanding your system’s performance and health. Good logging practice is also vital to power an observability platform across your system. Monitoring, in general, involves the collection and analysis of logs and other system metrics. Log analysis involves deriving insights from logs, which then feeds into observability. Observability, as we’ve said before, is really the gold standard for knowing everything about your system.
Modern computing has come a long way in the last couple of years and the introduction of new technologies is only accelerating the rate of advancements. From the immense compute power at our disposal to lightning-fast networks and ready-made services, the opportunities are limitless. In such a fast-paced world, we can’t ignore economics.
Within this blog post, we’re going to take a look at AWS Log Insights and cover some of the topics that you will find useful around what it is, how to use it, and how it can link in with our various solutions.
AWS CloudWatch is a service that allows you to monitor and manage deployed applications and resources within your AWS account and region. It contains tools that help you process and use logs from various AWS services to understand, troubleshoot, and optimize deployed services. I’m going to show you how to get an email when your Lambda logs over a certain number of events.
