When using Nagios, the NRPE daemon has been the traditionnal solution to implement local checks (load, number of users, custom scripts, etc.). All other checks are performed remotely from the Nagios server. NRPE daemon has been a bit challenging as you need to keep it in sync with your Nagios server and sometimes backporting this daemon can be painful. As Glouton has been implemented in Go, when you need a Nagios NRPE daemon, you can just use the binary on any compatible system and voila.
If you’re running a fleet of containerized applications on Kubernetes, aggregating and analyzing your logs can be a bit daunting if you’re not equipped with the proper knowledge and tools. Thankfully, there’s plenty of useful documentation to help you get started; observIQ provides the tools you need to gather and analyze your application logs with ease.
With version 3.4, StackStorm code itself will only run on Python 3. For the v3.4 release, we have chosen to run on Python 3.6 across all of our supported platforms. For users still on Ubuntu 16.04, you will need to source your own Python 3.6 packages, but we have been using the Python 3.6 Ubuntu PPA without many issues. Looking forward to StackStorm 3.5, we will be removing the ability to install Python 2 packs.
As I’ve often talked about before, we have a “big tent” philosophy at Grafana Labs. We believe our users should determine their own observability strategy and choose their own tools; Grafana allows them to bring together and understand all their data, no matter where it lives. In practice, that means that we want to support data sources that our users are passionate about.
Get started with Gremlin's Chaos Engineering tools to safely, securely, and simply inject failure into your systems to find weaknesses before they cause customer-facing issues. API gateways are a critical component of distributed systems and cloud-native deployments. They perform many important functions including request routing, caching, user authentication, rate limiting, and metrics collection. However, this means that any failures in your API gateway can put your entire deployment at risk.