Skip to content
This repository has been archived by the owner on Sep 20, 2022. It is now read-only.

Latest commit

 

History

History
75 lines (59 loc) · 3.57 KB

README.rst

File metadata and controls

75 lines (59 loc) · 3.57 KB
Raw

Note: DepC is archived as of Sept 2022. It remains here in read-only mode for historical interest.

DepC logo

Build status Python versions License Code style: black

DepC Screenshots
View a larger version of the GIF

DepC (Dependency Checker) is a QoS Measurement & Dependency Graph Platform created by OVH. We use it to store and request our CMDB and to compute the QoS of our infrastructure, including our customers.

Overview

DepC provides a CMDB component to store and request related nodes into a graph structure. These nodes can be anything : servers, products, customers or even web services. A typical use case would be to create some customers nodes, related to their products. We can also link these products to servers, that way it would be very easy to display the impacted customers when a problem occurs on a server.

Once DepC knows your dependency graph, it then becomes possible to compute a QoS for every nodes. By taking up our previous example, Depc can compute the QoS of our customers, following the QoS of their servers.

Principles

  • Graph Dependency : We use the Neo4j database to manage the nodes and their relationships (we already handle several million of nodes in our OVH internal instance). DepC provides some API calls and WebUI to easily request a node and its relationships.
  • QoS Computation : DepC can compute a QoS for all nodes in the Graph, but of course we have to explain how we do it. We created different methods for that : some nodes will use the raw data stored in TimeSeries databases (for example a server node having a probe), other nodes will use their parents QoS to compute their own one. Finally the QoS can be displayed in Grafana or in the DepC WebUI (this last one allows some cool features, like display the worst nodes or even the root cause of a bad QoS).
  • Scalability : Apache Kafka is used to receive payloads and forward them to Neo4j, adding the wanted scalabily and high-availability management. Then Apache Airflow is responsible to automate the QoS computation, so DepC can benefit from its executors feature (Celery, Kubernetes..) to scale horizontally.

Installation

See https://ovh.github.io/depc/installation.html

Links

License

See https://github.com/ovh/depc/blob/master/LICENSE