Operations | Monitoring | ITSM | DevOps | Cloud

Within distributed applications, data moves across many loosely connected endpoints, microservices, and teams, making it difficult to know when services are storing—or inadvertently leaking—sensitive data. This is especially true for governance, risk management, and compliance (GRC) or other security teams working for enterprises in highly regulated industries, such as healthcare, banking, insurance, and financial services.

It’s nearly here. The annual mad rush at the wee hours of the morning. The stampede into retail stores to claim really deep discounts on the latest toys, electronics, and gadgets makes headline news every year. It begins the day after Thanksgiving and is usually two of the biggest shopping days of the year. Yes, we’re talking about Black Friday and Cyber Monday.

In the last 2 installments (Part 1 & Part 2), we discussed the basics of IoT and an example of how the components can be connected and used to provide basic automation and alerting. These seemingly simple steps can build up to provide very advanced controls of all aspects of the physical world. The challenge can become managing situations that were not expected.

When monitoring a large IT infrastructure, there are multiple aspects you need to keep under control. Doing things manually and relying on people to ensure the infrastructure reliability can be a wrong decision and mislead you when resolving issues or troubleshooting problems. All these complexities faced while managing a large ecosystem can seem hard to overcome, but in reality, they can be handled.

NGINX is a popular web server featuring a wide range of capabilities, including reverse proxy, mail proxy, HTTP cache, and load balancing. It offers TLS offloading and a health check of the backends and supports gRPC, WebSocket, and HTTP/2. In short, NGINX is a one-stop solution for most of your web server needs. When using NGINX, monitoring its metrics is crucial for tackling issues.

Network monitoring tools gather and analyze network data to provide network administrators with information related to the status of network appliances, link saturation, the most active devices, the structure of network traffic or the sources of network problems and traffic anomalies.