In an ideal world software, once installed and configured, runs perfectly without ever needing attention. Of course reality tells a different story.
Software evolves, software has bugs, transient network issues, miss-configurations …
Many things can go wrong and the symptoms are often unclear. Distributed systems also mean that errors often propagate across processes and servers so the location an error is reported is far from the location where the error originated.
On top of all that, distributed systems are complex to follow and simple questions about correct functioning become hard to answer.
Replicante Core is a distributed system and as such it is subject to all the above complications. To help users and administrators understand and manage installations, as well as troubleshoot issues, Replicante Core provides a set of features to introspect the system and trace its activity.
In Replicante Core most activities of the system can be explained and monitored by looking at the events stream.
The events section has more details on Replicante Core Events.
Information about internal operation of replicante is exposed through metrics. These can be used to monitor the health and activity of a process as well as its performance.
Metrics are exposed in Prometheus
format by the API endpoint
Logging is a good way to see exactly what one system was doing at a precise point in time. Replicante provides structured logging so administrators can see what is happening and in what context.
By itself this is needed but not that great. The real power of structured logging comes in with centralised log collection: the logs from every server are collected and indexed in a central location along with other services.
Various logging backends are supported so that replicante can fit into your infrastructure
and some options are provided to user regardless of the backend of choice.
All options are under the
The details are documented in the configuration reference.
Below are the supported backends:
json(default) outputs logs to standard output in JSON format:
jqor crafted scripts).
journaldsends logs to journald directly (systemd’s logging facility):
journaldis available only if enabled at compile time.
journaldis requires a server running systemd.
Following the details of an operation from start to finish when it spans several servers can be a challenge. Thankfully there are tools to address this challenge: distributed tracers.
Distributed tracers are central systems that collect segments of operations from different servers and combine them together to show the entire story of a full operation.
Replicante supports integration with some distributed tracing tools compatible with the OpenTracing specification.
By default distributed tracing is disabled but it can be configured
with the options under the
Sentry is a really powerful, open source, tool to collect and understand errors reported by applications.
Replicante Core integrates with Sentry to inform operators about unexpected situations.
Not everything reported is an error, and not every error is critical. Some errors may not even require attention but are instead an indication of temporary issues: transient network issues and dependencies failover may lead to errors being reported to sentry. These are symptoms of an external conditions that you may or may not need to look into.
If what you need is not available among the tools above, a more machine-oriented introspection API is available.
Keep in mind that this API is meant for advanced operators and developers and may be useless, even missleading, without more context and a deeper knowledge of the code.