fmrsabino
commented
2 years ago Currently our services (especially the indexing service) requires a lot of database resources. This causes the following issues: Longer response time when service related issues occur
I would say that this is more related with https://github.com/gnosis/safe-pm/issues/3 since it's related to the performance of the service.
Regarding the issue: There are no notifications for service issues
We do have notifications in place to notify us about potential ongoing issue with the services. Unfortunately these issues are too broad and there's no real category to distinguish them – this leads to an increase of the number of issues reported (noise) which leaves most/all of them ignored until there's a more insightful report from our users.
Sub-problem 1 – Lack of issue Classification
The issues that are reported on to Kibana and Slack do not have any meaningful category that can distinguish its severity. Currently, evaluating a specific issue requires human intervention – this means reading the stream of error messages and filtering out what is considered normal behaviour – this does not scale well not only because of the number of messages that need to be evaluated but also because we need to keep track of the current alerts being sent.
Action: Therefore we first need to classify the issues that are reported by creating and assigning different categories to them.
When issues can be easily distinguished we can then move on to work on creating notifications and alerts.
Sub-problem 2 – Notify on issues that require immediate attention
After creating a classification system for the issues reported by our services we should then create rules to notify the team depending on the severity of those issues.
Some issues would require immediate attention (like service unavailability) while others might be more feature specific. Additionally we should consider rules that are triggered on different thresholds eg.: number of pending tasks > X or number of 500s returned in the last Y minutes.
Action Points (to be discussed)
Come up with categories for issues. Example:
- Availability and Basic Functionality
- Latency
- Correctness
- Feature specific issues
Evaluate Black Box monitoring and White Box monitoring
My personal take on this is that we should prioritise Black Box monitoring given our past incidents.
- Black box monitoring is performed by monitoring our systems from the perspective of a client ie.: it'd monitor the symptoms of all our services.
- Eg.: since our apps rely on the Safe Client Gateway as entry point we can monitor the Safe Client Gateway by having a fake client performing a number of different actions every X minutes and reporting the result of these actions.
- If that the correct rules and alerting are in place, this would report issues that are user-facing and thus might require immediate attention.
- White box monitoring is performed by monitoring internal metrics in our system ie.: it'd monitor the causes of the issues in our services
- Eg.: Disk space, memory usage, Disk IO, etc..
- This would provide valuable information in anticipating issues – ie.: the issues reported here might not be critical (from the user perspective) but might cause issues at some later stage if left unattended.
Evaluate tools to accomplish the above
After a brief discussion with the team we should look into Prometheus (https://prometheus.io) for the rule creation (as we are possibly moving away from Kibana).
As for alerting, we should consider email and slack since these tools are already available for us (but additional channels can be considered).
Problem Owner
@fmrsabino
What is the Problem
Currently our services (especially the indexing service) requires a lot of database resources. This causes the following issues:
Why is it relevant?
As the service issue normally persist this has a big impact on our user experience as the services are not available
How can we track the problem? (What is the KPI?)