* log: change log format to JSON payload for better log in Stackdriver
change the log format in Go written service from text payload to
JSON payload using 3rd party logging library (logrus).
https://cloud.google.com/logging/docs/structured-logging33a1e118e1/json_formatter.go (L40-L49)
Effected services are frontend, productcatalogservice, checkoutservice,
and shippinservice.
Also change target container registry and locust scenario for testing.
* revert kubernetes manifests to point to the original container registry URLs
* revert skaffold.yaml to point to the original registry
* loadgenerator: revert locust settings
* align all function names and messages to the official product name "Stackdriver"
* Add Stackdriver Profiler Python agent to EmailService and
RecommendationService
* Update recommendation_server.py
* Moved Profiler init to a function
* Moved Profiler init to a function
* Delete key.json
* Delete key.json
* Delete key.json
This commit sets the new sampling decision field that is recognized by the
Stackdriver Logging agent, "logging.googleapis.com/traceSampled". The sampling
decision field was added in
https://github.com/GoogleCloudPlatform/fluent-plugin-google-cloud/pull/297, and
it won't be available until the new version of fluent-plugin-google-cloud is
used in GKE.
The Log4j JsonLayout puts the log entry timestamp in a field named "instant" by
default, but the Stackdriver Logging agent does not understand that field. The
logging agent instead uses the time that it received the log entry, which is
less accurate and has only second-level precision.
This commit adds a key-value pair to the JsonLayout pattern that can be
understood by the logging agent. It uses a "time" key as described in
https://cloud.google.com/logging/docs/agent/configuration#timestamp-processing
and formats the timestamp as described in the Protocol Buffer JSON mapping,
https://developers.google.com/protocol-buffers/docs/proto3#json.
Allowing the Stackdriver Logging agent to read the more accurate timestamps
inserted by Log4j is especially important in the adservice, because the logs are
correlated with traces, and it is important to see where each message was logged
on the timeline of the trace.
This PR does a few things:
1. **Removes unnecessary Python dependencies currently being installed for `emailservice`**
There are quite a few packages being installed that aren't actual dependencies.
2. **Removes a number of related, also unnecessary system-level dependencies for `emailservice`**
These were a result of the Python dependencies that are unnecessary.
3. **Pins all of the sub-dependencies for `loadgenerator`**
This is good practice to ensure that things don't break one day in the future when a newer version of an unpinned sub-dependenency is released.
4. **Compile all Python dependencies from `requirements.in` files**
This is mostly bookkeeping. It allows us to only specify the top-level dependencies we care about in the requirements.in files, which are then compiled to frozen dependencies in the requirements.txt files. This ensures that we only install the dependencies we need, and that we're not missing any unpinned sub-dependencies. It also makes it more clear where our sub-dependencies are coming from.
5. **Switch to -slim images from -alpine**
Python's built distribution format (wheel) is incompatible with alpine-based images, causing dependencies like `grpcio` to be compiled from scratch, rather than from a pre-built wheel.
This should improve or possibly fix #58, while keeping the image size roughly the same:
```
emailservice latest d1b818eabe05 6 seconds ago 286MB
loadgenerator latest 4d9b5acbfbbb 6 seconds ago 125MB
```
This is the first service that exports to jaeger. Others to follow.
Requires jaeger to be instantiated using
- helm install --name jaeger stable/jaeger-operator
- kubectl apply -f jaeger.yaml
=== jaeger.yaml Content ===
apiVersion: io.jaegertracing/v1alpha1
kind: Jaeger
metadata:
name: jaeger
Above steps will be added to README in subsequent PR.
Enables tracing in the email and recommendation services, which was disabled in 316db88 because of a memory leak in the stackdriver exporter.
We fixed the leak in https://github.com/googleapis/google-cloud-python/pull/6856. The fix is included in the [0.1.10 release of opencensus-python](https://github.com/census-instrumentation/opencensus-python/releases/tag/v0.1.10).
With this diff, traces show up as expected in stackdriver while running the demo on GKE. Using an `opencensus-python` package version before `0.1.10` causes the email and recommendation services to leak memory until they OOM. Memory use is back to normal (i.e. roughly constant) using the new package version.
* adservice: Reduced docker image size to ~165MB
(down from ~886MB) by switching to alpine and
using multi stage builds
* adservice: Changed install of glibc in builder to not require untrusted packages
* adservice: Refactored Dockerfile to be a multi stage build. The 'build' step runs from openjdk:8-slim, but the final image is alpine based. We can get away from this since java runs in a vm & the architecture of the images doesn't change between biuld steps
change the log format in Python and Node.js services.
Effected services are currencyservice, emailservice, paymentservice,
and recommendationservice. Loadgenerator is left as is because of
the diffculty to change the log format and log target in locust.
ref. #47
The ad service now returns ads matching the categories of the product that is
currently displayed. Changes in this commit:
- List all products' categories in products.json.
- Pass the current product's categories from the frontend to the ad service when
looking up ads.
- Store a statically initialized multimap from product category to ad in the ad
service.
- Return all ads matching the given categories when handling an ads request.
The ad service continues to return random ads when no categories are given or
no ads match the categories.
This field can be used as the context keys to look up relevant ads in the ad
service.
/cc @rghetia
I also ran the genproto.sh scripts for the Java and Go services and included those changes in the second commit. I encountered an issue when I ran genproto.sh for the recommendation service, and I'm still looking into it.
Upgrading grpc-java fixed an error that I encountered when I tried modifying the adservice to write logs to Stackdriver with google-cloud-logging ("`com.google.cloud.logging.LoggingException: io.grpc.StatusRuntimeException: UNAUTHENTICATED: Credentials require channel with PRIVACY_AND_INTEGRITY security level. Observed security level: NONE`").
Reduce loadgenerator's image size from ~972MB to ~117MB
* Changed loadgen.sh to execute with `/bin/sh` as opposed to `/bin/bash`
* Changed dockerfile to a multi stage build
* Changed base image to `python:3-alpine` as opposed to `python:3.6`
