Initial Kingbird framework code base ( part5:test )

Fisrt patch to implement the framework of Kingbird, this is
the part5 for api test with readme files added.

Replace the Werkzeug wsgi server to oslo.service.wsgi to
reduce the requirements

Correct some invalid field in common/context.py

Blueprint: https://blueprints.launchpad.net/kingbird/+spec/kingbird-framework

Change-Id: Iebab2f554ac13ab653bf30adf021193b82a5e84b
Signed-off-by: Chaoyi Huang <joehuang@huawei.com>

kingbird/jobdaemon/README.rst

@@ -0,0 +1,46 @@
+===============================
+jobdaemon
+===============================
+
+Kingbird Job Daemon has responsibility for:
+    Divid job from Kingbird API to smaller jobs, each smaller job will only
+    be involved with one specific region, and one smaller job will be
+    dispatched to one Kingbird Job Worker. Multiple smaller jobs may be
+    dispatched to the same Kingbird Job Worker, it’s up to the load balancing
+    policy and how many Kingbird Job Workers are running.
+
+    Some job from Kingbird API  could not be divided, schedule and re-schedule
+    such kind of  (periodically running, like quota enforcement, regular
+    event statistic collection task)  job to a specific Kingbird Job Worker.
+    If some Kingbird Job Worker failed, re-balance the job to other Kingbird
+    Job Workers.
+
+    Monitoring the job/smaller jobs status, and return the result to Kingbird
+    API if needed.
+
+    Generate task to purge time-out jobs from Kingbird Database
+
+    Multiple Job Daemon could run in parallel, and also can work in
+    multi-worker mode. But for one job from Kingbird API, only one Kingbird
+    Job Daemon will be the owner. One Kingbird Job Daemon could be the owner
+    of multiple jobs from multiple Kingbird APIs
+
+    Multiple Kingbird Daemon will be designed and run in stateless mode,
+    persistent data will be accessed (read and write) from the Kingbird
+    Database through the DAL module.
+
+jdrpcapi.py:
+    the client side RPC api for JobDaemon. Often the API service will
+    call the api provided in this file, and the RPC client will send the
+    request to message-bus, and then the JobDaemon can pickup the RPC message
+    from the message bus
+
+jdservice.py:
+    run JobDaemon in multi-worker mode, and establish RPC server
+
+jdmanager.py:
+    all rpc messages received by the jdservice RPC server will be processed
+    in the jdmanager's regarding function.
+
+jdcfg.py:
+    configuration and initialization for JobDaemon