Operations | Monitoring | ITSM | DevOps | Cloud

Load balancing, traffic management, authentication and authorization, service discovery — these are just some of the interactions taking place between microservices. Collectively called a “service mesh”, these interconnections can become an operations headache when handling large‑scale, complex applications. Istio seeks to reduce this complexity by providing engineers with an easy way to manage a service mesh.

In the last post, we talked about how Fastly, a content delivery network, provides a global infrastructure footprint to enterprises, and enables them to move apps and websites closer to their end users. Using Fastly CDN, they can serve content and deploy updates quickly, optimize web performance, and improve overall user experience. In this post, we will discuss how to collect, analyze, and monitor Fastly logs.

Logspout is an open source log router designed specifically for Docker container logs. If you’ve ever looked into log management for Docker, chances are you’ve heard of it. Logspout is a container that collects logs from all other containers running on the same host, then forwards them to a destination of your choice. This lets you send logs to an HTTP/S server, syslog server, or other endpoint without having to monitor files or modify your host systems.

Log management solutions can make it easy to filter, aggregate, and analyze your log data. Whether you leverage JSON format or process your logs in order to extract attributes, you can slice and dice your logs using the information they provide such as timestamp, HTTP status code, or database user. But different technologies and data sources often label similar information differently, making it difficult to aggregate data across multiple sources.

So far in this blog series, we’ve seen how Log360 is simple to get up and running, allows you to receive a central view of multiple environments, provides deep auditing capabilities across these environments, and comes with advanced security features to deal with all manner of security incidents. In the concluding post of this blog series, we’ll look at another highly essential component of SIEM solutions: integrated compliance management.

Monitoring backend issues is critical for ensuring that requests are handled in a timely manner, and validating that your services are accessible to users. But if you’re not tracking client-side errors and events to get visibility into the frontend, you won’t have any idea how often these issues prompt users to refresh the page—or worse, abandon your website altogether.

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.

In part one of our introduction to NGINX “What is NGINX” , we went over the basic history of NGINX, the difference between Apache and NGINX, and why you would use NGINX over Apache in certain environments and web applications. Today we’ll be diving deeper into NGINX and going over topics such as web server performance, monitoring said performance, how to obtain and archive logs for deeper analysis, and how to even tell which web server you’re running on your environment.

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.

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.