We’ve all experienced latency in some form. It’s unfortunately something we’re all too familiar with. We’ve even gone so far as to accept it as a regular albeit undesirable part of the user experience. Yet despite various steps taken over the years, it still exists and is as disruptive as ever.
Scaling to collect Windows Event logs with the Windows Event Forwarding Source can be tricky. Luckily, you can use a load balancer, and with some math to scale the number of workers to collect the amount of data you expect, you can use workers to collect Windows logs from a large number of endpoints. Endpoint logs are the lifeblood of observability in an incident response program.
Operating Kubernetes reliably and efficiently involves adhering to a set of best practices. These practices help ensure the stability, scalability and maintainability of your Kubernetes clusters and their applications. It's crucial for platform teams (responsible for the infrastructure) and software development teams (responsible for deploying applications) to work together in applying these practices.
If you’re using Sentry for JavaScript error monitoring, you may be familiar with a common challenge: sifting through noisy, low-value errors that hinder identifying high-priority issues for you and your team. Capturing errors in JavaScript browser project can be tricky. Why? Well, it’s not just a single environment.
Monitoring and optimizing IT infrastructure, applications, and networks is crucial for businesses in today's digital landscape. It allows them to proactively identify issues, ensure optimal performance, and deliver a seamless user experience. However, traditional monitoring methods often fall short when it comes to handling the increasing complexity and scale of modern systems. That's where hosted graphite and machine learning come into play.
