  With the promise of reliability in cloud, more enterprises are migrating to
cloud. The process of continuous integration/deployment (CICD) in cloud
connects developers who need to deliver value faster and more transparently
with site reliability engineers (SREs) who need to manage applications
reliably. SREs feed back development issues to developers, and developers
commit fixes and trigger CICD to redeploy. The release cycle is more continuous
than ever, thus the code to production is faster and more automated. To provide
this higher level agility, the cloud platforms become more complex in the face
of flexibility with deeper layers of virtualization. However, reliability does
not come for free with all these complexities. Software engineers and SREs need
to deal with wider information spectrum from virtualized layers. Therefore,
providing correlated information with true positive evidences is critical to
identify the root cause of issues quickly in order to reduce mean time to
recover (MTTR), performance metrics for SREs. Similarity, knowledge, or
statistics driven approaches have been effective, but with increasing data
volume and types, an individual approach is limited to correlate semantic
relations of different data sources. In this paper, we introduce FIXME to
enhance software reliability with hybrid diagnosis approaches for enterprises.
Our evaluation results show using hybrid diagnosis approach is about 17% better
in precision. The results are helpful for both practitioners and researchers to
develop hybrid diagnosis in the highly dynamic cloud environment.
