Time Series Bridge is a tool that can be used to import metrics from one
monitoring system into another. It regularly runs a specific query against a
source monitoring system (currently Datadog & InfluxDB) and writes
new time series results into the destination system (currently only
Stackdriver).
Table of Contents
- Setup Guide
- metrics.yaml Configuration
- App Configuration
- Status Page
- Internal Monitoring
- Troubleshooting
- Development
- Support
Setup Guide
In brief, to set up the ts-bridge app:
- Create a GCP project that will host the app
- Configure metrics for import
- Deploy the app and let it auto-import your metrics every minute
The following sections will guide you through this process.
Create and Set Up a Google Cloud Project
We recommend making the project that hosts ts-bridge separate from the rest of
your infrastructure so infrastructure failures will not affect monitoring and
monitoring failues will not affect infrastructure.
- Log in to GCP and
create a new Google Cloud project
- Ensure the new project is
linked to a billing account
(Note that the Stackdriver free tier can accommodate up to about 220
metrics. If you have already consumed your free quota with other usage, the
incremental cost per metric is between US$2.32 and US$0.55 per month,
depending on which pricing tier you are already in.)
- Enable stackdriver monitoring
for the new project. When prompted:
- Create a new stackdriver account for the project
- Monitor only the new project (it should be selected by default)
- Skip AWS setup and agent installation
- Choose whether to receive email status reports for the project
Set Up A Dev Environment
We recommend using Cloud Shell to prepare
ts-bridge for deployment to ensure a consistent and stable working environment.
If you need a dev environment that you can share among multiple users, consider
using a git repository and
open-in-cloud-shell links.
- If you are not using Cloud Shell:
- Install go
- Download and install the
Cloud SDK
- Initialize with the following commands to set the linked project and
auth cookie:
gcloud init
gcloud auth application-default login
- Clone the ts-bridge source
go get github.com/google/ts-bridge/...
- The ts-bridge source code should appear in
$GOPATH/src/github.com/google/ts-bridge/
End To End Test (Dev Server)
-
Ensure that you either have Owner permissions for the whole Cloud
project, or at minimum the Monitoring Editor role
-
Create a ts-bridge config with no metrics
cd $GOPATH/src/github.com/google/ts-bridge; cp metrics.yaml.example metrics.yaml
- Edit the yaml file, remove the datadog_metrics and influxdb_metrics
sample content, and copy in the name of the project you just created
into the stackdriver_destinations section.
- Your
metrics.yaml
file should look like this:
datadog_metrics:
influxdb_metrics:
stackdriver_destinations:
- name: stackdriver
project_id: "your_project_name"
-
Turn on the status page (uncomment #ENABLE_STATUS_PAGE: "yes" in app.yaml
)
-
Update SD_PROJECT_FOR_INTERNAL_METRICS
in your app.yaml
to match the name of your GCP project.
-
Launch a dev server
dev_appserver.py app.yaml --port 18080
-
Test via localhost/sync
curl http://localhost:18080/sync
-
Verify that no error messages are shown. Troubleshooting guide:
Error message |
Remedy |
ERROR: StatsCollector: rpc error: code = PermissionDenied desc = The caller does not have permission |
Ensure the authenticating user has at least the "Monitoring Editor" role |
-
Configure metrics by following the instructions
below.
-
Test metric ingestion via localhost/sync
curl http://localhost:18080/sync
-
Verify that metrics are visible on status page
- In Cloud Shell, click the ‘web preview’ button and change the port to
18080
- If running on a local workstation, browse to http://localhost:18080/
-
Verify that metrics are visible in the
Stackdriver UI
-
Kill the local dev server
-
Revert SD_PROJECT_FOR_INTERNAL_METRICS
to ""
in app.yaml
Docker
Authorization
ts-bridge
relies on Google Cloud Go library to provide authorization
and should support all options available for it. Generally, there are 3 ways you can do it:
- Run
gcloud auth application-default login
(suitable for local development / dev environments)
- Use
GOOGLE_APPLICATION_CREDENTIALS="[PATH]"
variable to point at the credentials
- Using GCP platform-provided credentials, such as Workload identity for GKE
For more information, see:
Building the image
- Build the image from the supplied
Dockerfile
:
docker build -t tsbridge:VERSION -t some-other-tag .
Running the image
The image sets ts-bridge
binary as the entrypoint, so it can simply be run via cmd arguments with configuration files
in working directory (/ts-bridge
), e.g.:
docker run -p 8080:8080 \ (2)
-v ${PWD}/metrics.yaml:/ts-bridge/metrics.yaml \
-v ~/.gcp/my-account-key.json:/ts-bridge/gcp_account_key.json \
-e "GOOGLE_APPLICATION_CREDENTIALS=/ts-bridge/gcp_account_key.json" \
ts-bridge:VERSION \
--debug \
--storage-engine=boltdb \
--enable-status-page \
--stats-sd-project=my-project \
--update-parallelism=4 \
--sync-period=10s
Deploy In Production
- Ensure that you either have Owner permissions for the whole Cloud
project, or at minimum the App Engine Admin and Cloud Scheduler
Admin roles
- Disable the status page (comment out ENABLE_STATUS_PAGE: "yes" in
app.yaml
)
- See below if you'd like to keep the status page enabled
in prod.
- Create the App Engine application
gcloud app create
- Choose the App Engine region. If you are using ts-bridge to import
metrics originating from a system running on GCP, you should run
ts-bridge in a different Cloud region from the system itself to ensure
independent failure domains.
- Deploy app
gcloud app deploy --project <your_project_name> --version live
- Verify in the Stackdriver metrics explorer that metrics are being imported
once a minute
metrics.yaml Configuration
Metric sources and targets are configured in the app/metrics.yaml
file.
Metric Sources
See the READMEs for how to import metrics from supported metric sources:
Metric Destinations
Stackdriver
Imported metrics can be written to multiple destination Stackdriver projects,
even though in practice we expect a single instance of Time Series Bridge to
write to a single project (usually matching the GCP project where the ts-bridge
is running).
Stackdriver destinations are listed in the stackdriver_destinations
section of
the app/metrics.yaml
file. The following parameters can be specified for each
destination:
name
: name of the Stackdriver destination. It's only used internally by
ts-bridge to match imported metrics with destinations.
project_id
: name of the Stackdriver project that metrics will be written
to. This parameter is optional; if not specified, the same project where
ts-bridge is running will be used.
If you are using ts-bridge to write metrics to a different Stackdriver project
from the one it's running in, you will need to grant roles/monitoring.editor
IAM permission to the service account used by the ts-bridge App Engine app to
allow it to read and write Stackdriver metrics.
App Configuration
Importing period
Time Series Bridge attempts to import all configured metrics regularly. This is
driven by the
App Engine Cron Service
which is configured in app/cron.yaml
. By default metrics are imported every
minute.
Global settings
Some other settings can be set globally as environment variables or command-line flags.
In case of AppEngine variables are configured in the env_variables
section of app/app.yaml
.
DEBUG
(--debug
): enable debug logging.
PORT
(--port
): ts-bridge server port.
CONFIG_FILE
(--metric-config
): name of the metric configuration file (metrics.yaml
).
SD_LOOKBACK_INTERVAL
(--sd-lookback-interval
): time interval used while
searching for recent data in Stackdriver. This is also the default backfill
interval for when no recent points are found. This interval should be kept
reasonably short to avoid fetching too much data from Stackdriver on each update.
- You might be tempted to increase this significantly to backfill historic
values. Please keep in mind that Stackdriver
does not allow
writing points that are more than 24 hours old. Also, Datadog
downsamples values to
keep the number of points in each response below ~300.
This means that a single request can only cover a time period of 5 hours
if you are aiming to get a point per minute.
UPDATE_TIMEOUT
(--update-timeout
): the total time that updating all metrics
is allowed to take. The incoming HTTP request from App Engine Cron will fail if
it takes longer than this, and a subsequent update will be triggered again.
UPDATE_PARALLELISM
(--update-parallelism
): number of metric updates that
are performed in parallel. Parallel updates are scheduled using goroutines and
still happen in the context of a single incoming HTTP request, and setting this
value too high might result in the App Engine instance running out of RAM.
MIN_POINT_AGE
(--min-point-age
): minimum age of a data point returned by a
metric source that makes it eligible for being written. Points that are very
fresh (default is 1.5 minutes) are ignored, since the metric source might return
incomplete data for them if some input data is delayed.
COUNTER_RESET_INTERVAL
(--counter-reset-interval
): while importing counters,
ts-bridge needs to reset 'start time' regularly to keep the query time window
small enough. This parameter defines how often a new start time is chosen, and
defaults to 30 minutes. See Cumulative metrics section
below for more details.
STORAGE_ENGINE
(--storage-engine
): storage engine to use for storing metric
metadata, defaults to datastore
.
datastore
- use AppEngine Datastore
boltdb
- use BoltDB via BoltHold
BOLTDB_PATH
(--boltdb-path
) - path to BoltDB store, e.g. /data/bolt.db
(defaults to $PWD/bolt.db
)
ENABLE_STATUS_PAGE
(--enable-status-page
): can be set to 'yes' to enable
the status web page (disabled by default).
You can use --env_var
flag to override these environment variables while
running the app via dev_appserver.py
.
Cumulative metrics
Stackdriver supports cumulative metrics, which are monotonically increasing
counters. Such metrics allow calculating deltas and rates over different
alignment periods.
While neither Datadog nor InfluxDB have first-class support for cumulative
metrics, they both have cumulative functions that allow their queries to
retrive a cumulative sum. Time Series Bridge can use the results of such
queries and import them as cumulative metrics, but such queries need to be
explicitly annotated with a cumulative
option in metrics.yaml
being set to
true
.
For queries that are marked as cumulative
, ts-bridge will regularly
choose a 'start time' and then issue queries with from that time. As the
result, Datadog and InfluxDB will return a monotonically
increasing time series with a sum of all measurements since 'start time'. To
avoid processing too many points as the cumulative interval increases,
'start time' regularly gets moved forward, keeping the query time window short
(see COUNTER_RESET_INTERVAL
). Such resets are handled correctly by
Stackdriver, since it requires explicit start time to be provided for
cumulative metric points.
Status Page
If the ENABLE_STATUS_PAGE
environment variable is set to 'yes', the index page
of the App Engine app shows a list of configured metrics along with import
status for each metric. This might be useful for debugging, however it is
disabled by default to avoid publicly exposing a list of configured metrics
(App Engine HTTP endpoints are publicly available by default).
If you choose to leave the status page enabled, we recommend configuring
Identity-Aware Proxy
(IAP) for the Cloud project in which ts-bridge is running. You can use IAP to
restrict access to ts-bridge to a specific Google group or a list of Google
accounts.
Internal Monitoring
Time Series Bridge uses OpenCensus to report several
metrics to Stackdriver:
metric_import_latencies
: per-metric import latency (in ms). This metric
has a metric_name
field.
import_latencies
: total time it took to import all metrics (in ms). If
this becomes larger than UPDATE_TIMEOUT
, some metrics might not be
imported, and you might need to increase UPDATE_PARALLELISM
or
UPDATE_TIMEOUT
.
oldest_metric_age
: oldest time since the last written point across all
metrics (in ms). This metric can be used to detect queries that no longer
return any data.
All metrics are reported as Stackdriver custom metrics and have names prefixed
by custom.googleapis.com/opencensus/ts_bridge/
examples/
directory in this repository contains a suggested Stackdriver Alerting
Policy you can use to receive alerts when metric importing breaks.
Troubleshooting
This section describes common issues you might experience with ts-bridge.
Writing points to Stackdriver too frequently
If your query returns more than 1 point per minute, you might be seeing the
following error from Stackdriver:
One or more TimeSeries could not be written: One or more points were written more frequently than the maximum sampling period configured for the metric.
Stackdriver documentation
recommends
to not add points to the same time series faster than once per minute. If your
metric query returns multiple points per minute, it is recommended you use
aggregation to reduce the number of points.
Development
- Set up a dev environment as per the Setup Guide above.
- Create a
metrics.yaml
file in app/
- Run the app locally using dev_appserver:
cd app/ && dev_appserver.py app.yaml --port 18080
- The app should be available at http://localhost:18080/
- Note, dev_appserver does not support App Engine cron, so you'll need to
run
curl http://localhost:18080/sync
to import metrics
- Run tests:
go test ./...
- If you've changed interfaces, run
go generate ./...
to update mocks
- If you've changed dependencies, run
dep ensure
to update vendored
libraries and Gopkg.lock
If you'd like to contribute a patch, please see contribution guidelines in
CONTRIBUTING.md.
Support
This is not an officially supported Google product.