AWS CloudWatch allows you to collect log files such as the Apache2 access or error logs from your AWS EC2 instances. This is especially useful if you have a scaling group of instances behind a load balancer. Rather than connecting to each instance and manually searching the logs with grep, CloudWatch centralises the logs into one log stream, allowing you to search all your log files from one place.

Launched at KubeCon North America last December, Loki is a Prometheus-inspired service that optimizes storage, search, and aggregation while making logs easy to explore natively in Grafana. Loki is designed to work easily both as microservices and as monoliths, and correlates logs and metrics to save users money. Less than a year later, Loki has almost 6,500 stars on GitHub and is now quickly approaching GA.

As your application grows in size and complexity, it becomes increasingly difficult to manage the number of logs it generates and the cost of ingesting, processing, and analyzing them. Organizations often have little control over fluctuations in the volume of logs generated—and the resulting costs of collecting them—so they are forced to limit the number of logs generated by their applications, or to pre-filter logs before sending them to their log management platform.

Network Performance Monitoring is currently available in private beta. Request access here. Your applications and infrastructure components rely on one another in an increasingly complex fabric, regardless of whether you run a monolithic application or microservices, and whether you deploy to cloud infrastructure, private data centers, or both.

At Dash 2019, we are excited to share a number of new products and features on the Datadog platform. With the addition of Network Performance Monitoring, Real User Monitoring, support for collecting browser logs, and single-pane-of-glass visibility for serverless environments, Datadog now provides even broader coverage of the modern application stack, from frontend to backend.

User Activity Monitoring (UAM) tracks the behavior of internal end-users—employees, subcontractors, partners, and so on—on a company’s networks, devices, and other IT resources. UAM, sometimes also called employee monitoring, may be deployed for a number of reasons, such as providing insight into the productivity of both individual employees and the company as a whole. Is Employee X spending too much time browsing the internet for non-business purposes during work time?

Penn National Insurance needed to adapt to its growing remote workforce and deliver a seamless user experience to increase employee satisfaction, performance and productivity. In response, the IT team rolled out its virtual workspace initiative, proving to be one of its most challenging IT projects.

It's 2019, so we decided it was time to take a more modern approach to the Honeybadger front end. We implemented Turbolinks! This is only the first step on an ambitious roadmap. In 2025 we plan to migrate to Angular 1, and we'll finish out the decade on React unless we run into any roadblocks! But let's get real. Honeybadger isn't a single page app, and it probably won't ever be. SPAs just don't make sense for our technical requirements.