Operations | Monitoring | ITSM | DevOps | Cloud

Cloud environments like AWS can be a challenge for security monitoring services to operate in since assets tend to dynamically appear and disappear. Making matters more challenging, some asset identifiers that are stable in traditional IT environments like IP addresses are less reliable due to their transient behavior in a cloud service like AWS. Amazon GuardDuty protects your AWS environment with intelligent threat detection and continuous monitoring.

You can now monitor any metrics you’d like in your Node.js app with AppSignal. With custom metrics and minutely probes by your side, you’ll now have an excellent overview of your app. If you’ve ever thought “I wish we measured this specific thing so I could monitor better what is going on…”, then this feature is perfect for you.

There is a value perception gap in IT. It can be a struggle to get past the historical notion that IT is a cost center, rather than a strategic arm of the business. E&Y recently surveyed 300 senior IT professionals around the globe to understand how they are perceived by their C-level executives. The survey found that 67% of CIOs engage with executive peers on matters of budgetary issues and infrastructure management. Far fewer, only 36%, engage in matters of business performance and challenges.

Traditionally, IT service management was limited to legacy platforms and infrastructure. Due to a lack of process, interacting with IT teams was frustrating and difficult, resulting in the workforce becoming less engaged, and the gap between the IT team and business growing even further. Since IT service management was already a complicated task for most IT teams, COVID-19 only exacerbated the repercussions.

Deploying and monitoring performance for an entire Kubernetes cluster can be complex. To simplify the process, we’ve added service discovery functionality to eliminate complex configuration, in addition to more advanced monitoring for viewing activity inside containers. Service discovery identifies k8s pods running on a cluster and immediately starts monitoring system performance. All containers are identified, regardless of complexity.

We all know that Prometheus is a popular system for collecting and querying metrics, especially in the cloud native world of Kubernetes and ephemeral instances. But people forget that Java has been running enterprise software since 1995, while Prometheus is a relative newcomer to the scene. It was only created in 2012! Even though Java has had its own metric collectors since before Prometheus was born, none of our new environments speak its (metric) language. How can you bridge that gap?