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* Update to MQ 9.3.4
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* Fix Prometheus label cardinality when reporting disconnect (#245)
* Add hints about monitoring "large" queue managers in TUNING.md
* Make sure missing YAML configuration attributes have reasonable defaults
* Update all vendored dependencies
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ibmmqmet committed Oct 19, 2023
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7 changes: 6 additions & 1 deletion .dockerignore
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@@ -1,2 +1,7 @@
.git/
.github/
.git/

# We use a file in the .git/refs directory to try to extract current commit level
# so exclude that directory from the exclusions
!.git/refs

7 changes: 7 additions & 0 deletions CHANGELOG.md
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@@ -1,6 +1,13 @@
# Changelog
Newest updates are at the top of this file.

### Oct 19 2023 (v5.5.1)
* Update to MQ 9.3.4
* Fix Prometheus label cardinality when reporting disconnect (#245)
* Add hints about monitoring "large" queue managers in TUNING.md
* Make sure missing YAML configuration attributes have reasonable defaults
* Update all vendored dependencies

### Jun 20 2023 (v5.5.0)
* Update to MQ 9.3.3
* Update Dockerfile to support platforms without Redist client (#209)
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65 changes: 44 additions & 21 deletions Dockerfile
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Expand Up @@ -5,7 +5,7 @@
# material from the build step into the runtime container.
#
# It can cope with both platforms where a Redistributable Client is available, and platforms
# where it is not - copy the .deb install images for such platforms into the MQDEB
# where it is not - copy the .deb install images for such platforms into the MQINST
# subdirectory of this repository first.

# Global ARG. To be used in all stages.
Expand All @@ -21,7 +21,7 @@ ARG EXPORTER
ENV EXPORTER=${EXPORTER} \
ORG="github.com/ibm-messaging" \
REPO="mq-metric-samples" \
VRMF=9.3.3.0 \
VRMF=9.3.4.0 \
CGO_CFLAGS="-I/opt/mqm/inc/" \
CGO_LDFLAGS_ALLOW="-Wl,-rpath.*" \
genmqpkg_incnls=1 \
Expand All @@ -39,26 +39,31 @@ RUN mkdir -p /go/src /go/bin /go/pkg \
&& chmod -R 777 /go \
&& mkdir -p /go/src/$ORG \
&& mkdir -p /opt/mqm \
&& mkdir -p /MQDEB \
&& mkdir -p /MQINST \
&& chmod a+rx /opt/mqm

# Install MQ client and SDK
# For platforms with a Redistributable client, we can use curl to pull it in and unpack it.
# For other platforms, we assume that you have the deb files available under the current directory
# For most other platforms, we assume that you have deb files available under the current directory
# and we then copy them into the container image. Use dpkg to install from them; these have to be
# done in the right order.
# done in the right order.
#
# The Linux ARM64 image is a full-function server package that is directly unpacked.
# We only need a subset of the files so strip the unneeded filesets. The download of the image could
# be automated via curl in the same way as the Linux/amd64 download, but it's a much bigger image and
# has a different license. So I'm not going to do that for now.
#
# If additional Redistributable Client platforms appear, then this block can be altered, including the MQARCH setting.
#
# The copy of the README is so that at least one file always gets copied, even if you don't have the deb files locally.
# Using a wildcard in the directory name also helps to ensure that this part of the build should always succeed.
COPY README.md MQDEB*/*deb /MQDEB

# This is a value always set by the "docker build" process
ARG TARGETPLATFORM
RUN echo "Target arch is $TARGETPLATFORM"
# Might need to refer to TARGETPLATFORM a few times in this block, so define something shorter.
RUN T="$TARGETPLATFORM"; \
# Using a wildcard in the directory name also helps to ensure that this part of the build always succeeds.
COPY README.md MQINST*/*deb MQINST*/*tar.gz /MQINST

# These are values always set by the "docker build" process
ARG TARGETARCH TARGETOS
RUN echo "Target arch is $TARGETARCH; os is $TARGETOS"
# Might need to refer to TARGET* vars a few times in this block, so define something shorter.
RUN T="$TARGETOS/$TARGETARCH"; \
if [ "$T" = "linux/amd64" ]; \
then \
MQARCH=X64;\
Expand All @@ -69,35 +74,48 @@ RUN T="$TARGETPLATFORM"; \
&& tar -zxf ./*.tar.gz \
&& rm -f ./*.tar.gz \
&& bin/genmqpkg.sh -b /opt/mqm;\
elif [ "$T" = "linux/arm64" ] ;\
then \
cd /MQINST; \
c=`ls *$VRMF*.tar.gz 2>/dev/null| wc -l`; if [ $c -ne 1 ]; then echo "MQ installation file does not exist in MQINST subdirectory";exit 1;fi; \
cd /opt/mqm \
&& tar -zxf /MQINST/*.tar.gz \
&& export genmqpkg_incserver=0 \
&& bin/genmqpkg.sh -b /opt/mqm;\
elif [ "$T" = "linux/ppc64le" -o "$T" = "linux/s390x" ];\
then \
cd /MQDEB; \
c=`ls ibmmq-*$VRMF*.deb| wc -l`; if [ $c -lt 4 ]; then echo "MQ installation files do not exist in MQDEB subdirectory";exit 1;fi; \
cd /MQINST; \
c=`ls ibmmq-*$VRMF*.deb 2>/dev/null| wc -l`; if [ $c -lt 4 ]; then echo "MQ installation files do not exist in MQINST subdirectory";exit 1;fi; \
for f in ibmmq-runtime_$VRMF*.deb ibmmq-gskit_$VRMF*.deb ibmmq-client_$VRMF*.deb ibmmq-sdk_$VRMF*.deb; do dpkg -i $f;done; \
else \
echo "Unsupported platform $T";\
exit 1;\
fi

# Build Go application
# Build the Go application
WORKDIR /go/src/$ORG/$REPO
COPY go.mod .
COPY go.sum .
COPY --chmod=777 ./cmd/${EXPORTER} .
COPY --chmod=777 vendor ./vendor
COPY --chmod=777 pkg ./pkg
RUN go build -mod=vendor -o /go/bin/${EXPORTER} ./*.go
# This file holds something like the current commit level if it exists in your tree. It might not be there, so
# we use wildcards to avoid errors on non-existent files/dirs.
COPY --chmod=777 ./.git*/refs/heads/master* .
RUN buildStamp=`date +%Y%m%d-%H%M%S`; \
hw=`uname -m`; \
os=`uname -s`; \
bp="$os/$hw"; \
if [ -r master ]; then gitCommit=`cat master`;else gitCommit="Unknown";fi; \
BUILD_EXTRA_INJECT="-X \"main.BuildStamp=$buildStamp\" -X \"main.BuildPlatform=$bp\" -X \"main.GitCommit=$gitCommit\""; \
go build -mod=vendor -ldflags "$BUILD_EXTRA_INJECT" -o /go/bin/${EXPORTER} ./*.go

# --- --- --- --- --- --- --- --- --- --- --- --- --- --- #
### ### ### ### ### ### ### RUN ### ### ### ### ### ### ###
# --- --- --- --- --- --- --- --- --- --- --- --- --- --- #
FROM golang:1.19 AS runtime

ARG EXPORTER
ENV EXPORTER=${EXPORTER} \
LD_LIBRARY_PATH="/opt/mqm/lib64:/usr/lib64" \
MQ_CONNECT_TYPE=CLIENT \
IBMMQ_GLOBAL_CONFIGURATIONFILE=/opt/config/${EXPORTER}.yaml

# Create directory structure
RUN mkdir -p /opt/bin \
Expand All @@ -120,6 +138,11 @@ RUN mkdir -p /IBM/MQ/data/errors \
&& chmod -R 777 /IBM \
&& chmod -R 777 /.mqm

ENV EXPORTER=${EXPORTER} \
LD_LIBRARY_PATH="/opt/mqm/lib64:/usr/lib64" \
MQ_CONNECT_TYPE=CLIENT \
IBMMQ_GLOBAL_CONFIGURATIONFILE=/opt/config/${EXPORTER}.yaml

COPY --chmod=555 --from=builder /go/bin/${EXPORTER} /opt/bin/${EXPORTER}
COPY --from=builder /opt/mqm/ /opt/mqm/

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21 changes: 8 additions & 13 deletions Dockerfile.build
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Expand Up @@ -16,7 +16,7 @@ ARG BASE_IMAGE=ubuntu:20.04
FROM $BASE_IMAGE

ARG GOPATH_ARG="/go"
ARG GOVERSION=1.17
ARG GOVERSION=1.19
ARG GOARCH=amd64
ARG MQARCH=X64

Expand Down Expand Up @@ -61,7 +61,7 @@ RUN mkdir -p $GOPATH/src $GOPATH/bin $GOPATH/pkg \
# Location of the downloadable MQ client package \
ENV RDURL="https://public.dhe.ibm.com/ibmdl/export/pub/software/websphere/messaging/mqdev/redist" \
RDTAR="IBM-MQC-Redist-Linux${MQARCH}.tar.gz" \
VRMF=9.3.3.0
VRMF=9.3.4.0

# Install the MQ client from the Redistributable package. This also contains the
# header files we need to compile against. Setup the subset of the package
Expand All @@ -77,24 +77,19 @@ RUN cd /opt/mqm \
&& bin/genmqpkg.sh -b /opt/mqm

# Insert the script that will do the build
COPY scripts/buildInDocker.sh $GOPATH
RUN chmod 777 $GOPATH/buildInDocker.sh
COPY --chmod=777 scripts/buildInDocker.sh $GOPATH

WORKDIR $GOPATH/src/$ORG/$REPO
COPY go.mod .
COPY go.sum .
RUN chmod 777 go.*
COPY --chmod=777 go.mod .
COPY --chmod=777 go.sum .
COPY --chmod=777 config.common.yaml .

COPY config.common.yaml .
RUN chmod 777 config.common.yaml

#RUN /usr/lib/go-${GOVERSION}/bin/go mod download
# RUN /usr/lib/go-${GOVERSION}/bin/go mod download

# Copy the rest of the source tree from this directory into the container and
# make sure it's readable by the user running the container
ENV REPO="mq-metric-samples"
COPY . $GOPATH/src/$ORG/$REPO
RUN chmod -R a+rwx $GOPATH/src/$ORG/$REPO
COPY --chmod=777 . $GOPATH/src/$ORG/$REPO

# Set the entrypoint to the script that will do the compilation
ENTRYPOINT $GOPATH/buildInDocker.sh
2 changes: 1 addition & 1 deletion Dockerfile.run
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Expand Up @@ -34,7 +34,7 @@ RUN apt-get update \
# Location of the downloadable MQ client package \
ENV RDURL="https://public.dhe.ibm.com/ibmdl/export/pub/software/websphere/messaging/mqdev/redist" \
RDTAR="IBM-MQC-Redist-Linux${MQARCH}.tar.gz" \
VRMF=9.3.3.0
VRMF=9.3.4.0

# Install the MQ client from the Redistributable package. This also contains the
# header files we need to compile against. Setup the subset of the package
Expand Down
5 changes: 0 additions & 5 deletions MQDEB/README

This file was deleted.

9 changes: 9 additions & 0 deletions MQINST/README
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@@ -0,0 +1,9 @@
If you are using the Dockerfile in the root of this repository
to build and run an exporter/collector program:

For Linux platforms without a Redistributable Client package, but
with full install packages, copy the .deb installation files into
this directory.

For Linux/Arm64, copy the .tar.gz installation file into this
directory.
8 changes: 4 additions & 4 deletions README.md
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Expand Up @@ -31,7 +31,7 @@ file if you wish to reload all of the dependencies by running `go mod vendor`.

You will require the following programs:

* Go compiler - version 1.17 is the minimum defined here
* Go compiler - version 1.19 is the minimum defined here
* C compiler


Expand Down Expand Up @@ -88,9 +88,9 @@ containers. You still need to provide the configuration file at runtime, perhaps
```

### Platform support
This Dockerfile should work for a variety of platforms. For those with a Redistributable client, it uses
`curl` to automatically download and unpack the required MQ files. For other platforms, it assumes that
you have an `MQDEB` subdirectory under this root, and then copied the `.deb` files from your
This Dockerfile should work for a variety of platforms. For those with a Redistributable client, it uses `curl` to
automatically download and unpack the required MQ files. For other platforms, it assumes that you have an `MQINST`
subdirectory under this root, and then copied the `.deb` files (or the `.tar.gz` file for Linux/arm64 systems) from your
real MQ installation tree into it.

### Additional container scripts
Expand Down
121 changes: 121 additions & 0 deletions TUNING.md
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# Tuning hints for monitoring "large" queue managers

If you have a large queue manager - perhaps several thousands of queues - then a lot of data could be produced for
monitoring those queues. Some default configuration options might need tuning to get acceptable performance. Reducing
the frequency of generation and/or collection may be appropriate. There may be several places where tuning might be
done: in this collector, in the database configuration, and in the queue manager.

The following sections describe different pieces that you might want to look at.

The document is mostly written from the viewpoint of using Prometheus as the database. That is mainly because
Prometheus has the unique "pull" model, where the server calls the collector at configured intervals. Other databases and
collector technologies supported from this repository have a simpler way of "pushing" data to the various backends.
However much of the document is relevant regardless of where the metrics end up.

## Collector location
It is most efficient to run the collector program as a local bindings application, connecting directly to the queue
manager. That removes all the MQ Client flows that would have to be done for every message.

If you cannot avoid running as a client (for example, you are trying to monitor the MQ Appliance or z/OS), then keep the
network latency between the queue manager and collector as low as possible. For z/OS, you might consider running the
collector in a zLinux LPAR on the same machine. Or perhaps in a zCX container.

Also configure the client to take advantage of readahead when getting publications. This is done by setting
`DEFREADA(YES)` on the nominated ReplyQueue(s).

## Collection processing time
The collector reports on how long it takes to collect and process the data on each interval. You can see this in a debug
log. The Prometheus collector also has a `ibmmq_qmgr_exporter_collection_time` metric. Note that this time is the value
as seen by the main collection thread; the real total time as seen by Prometheus is usually longer. There is likely
still work going on in the background to send metrics to the database, and for it to be successfully ingested.

The first time that the collection time exceeds the Prometheus default `scrape_timeout` value, a warning message is
emitted. This can be ignored if you are expecting a scrape to take a longer period. But it can be helpful if you didn't
know that you might need to do some tuning.

The true total time taken for a scrape can be seen in Prometheus directly. For example, you can use the admininistrative
interface at `http://<server>:9090/targets?search=` and find the target corresponding to your queue manager.

For other collectors, there is no specific metric. But the timestamps on each collection block allow you to deduce the
time taken as the difference between successive iterations is the collection period plus the `interval` configuration
value.

## Ensuring collection intervals have enough time to run
The Prometheus `scrape_configs` configuration attributes can be configured for all or some collectors. In particular,
you will probably want to change the `scrape_interval` and `scrape_timeout` values for the jobs associated with large
queue managers. Use the reported collection processing time as a basis from which to set these values.

For other collector models, the collector-specific `interval` attribute determines the gap between each push of the
metrics. There is no "maximum" collection time.

## Reducing metric publication interval from queue manager
By default, the queue manager publishes resource metrics every 10 seconds. This matches fairly well with the Prometheus
default scrape interval of 15s. But if you increase the scrape interval, you might also want to reduce the frequency of
publications so that fewer "merges" have to be done when processing the subscription destination queues. Setting the
following stanza in the _qm.ini_ file changes that frequency:
```
TuningParameters:
MonitorPublishHeartBeat = 30
```
This value is given in seconds. And the attribute is case-sensitive. As increasing the value reduces the frequency of
generation, it may cause you to miss shorter-lived transient spikes in some values. That's the tradeoff you have to
evaluate. But having a value smaller than the time taken to process the publications might result in a never-ending
scrape. The publication-processing portion of the scrape can be seen in a debug log.

## Reducing subscriptions made to queue manager
Reducing the total number of subscriptions made will reduce the data that needs to be processed. But at the cost of
missing some metrics that you might find useful. See also the section in the [README](README.md) file about using
durable subscriptions.

* You can disable all use of published resource metrics, and rely on the `DISPLAY xxSTATUS` responses. This clearly
reduces the data, but you lose out on many useful metrics. It is essentially how we monitor z/OS queue managers as
they do not have the publication model for metrics. But if you want this approach, set the `global.usePublications`
configuration option to `false`

* You can reduce the total number of subscriptions made for queue metrics. The `filters.queueSubscriptionSelector` list
defines the sets of topics that you might be interested in. The complete set - for now - is
[OPENCLOSE, INQSET, PUT, GET, GENERAL]. In many cases, only the last three of these may be of interest. The smaller
set reduces the number of publications per queue. Within each set, multiple metrics are created but there is no way to
report on only a subset of the metrics in each set.

* You can choose to not subscribe to any queue metrics, but still subscribe to metrics for other resources such as the
queue manager and Native HA by setting the filter to `NONE`. If you do this, then many queue metrics become
unavailable. However, the current queue depth will still be available as it can also be determined from the
`DISPLAY QSTATUS` response.

## Reducing the number of monitored objects and status requests
Each object type (queues, channels etc) has a block in the collector configuration that names which objects should be
monitored. While both positive and negative wildcards can be used in these blocks, it is probably most efficient to use
only positive wildcards. That allows the `DISPLAY xxSTATUS` requests to pass the wildcards directly into the queue
manager commands; if there are any negative patterns, the collector has to work out which objects match the pattern, and
then inquire for the remainder individually.

## Other configuration options
The `global.pollInterval` and `global.rediscoverInterval` options may help to further reduce inquiries.

The first of these controls how frequently the `DISPLAY xxSTATUS` commands are used, assuming the
`global.useObjectStatus` is `true`. In some circumstances, you might not want all of the responses as regularly as the
published metrics are handled.

The second attribute controls how frequently the collector reassesses the list of objects to be monitored, and their
more stable attributes. For example, the `DESCRIPTION` or `MAXDEPTH` settings on a queue. If you have a large number of
queues that do not change frequently, then you might want to increase the rediscovery attribute. The default is 1 hour.
The tradeoff here is that newly-defined queues may not have any metrics reported until this interval expires.

## Dividing the workload
One further approach that you might like to consider, though I wouldn't usually recommend it, is to have two or more
collectors running against the same queue manager. And then configure different sets of queues to be monitored. So a
collector listening on port 9157 might manage queues A*-M*, while another collector on port 9158 monitors queues N*-Z*.
You would likely need additional configuration to reduce duplication of other components, for example by using the
`jobname` or `instance` as a filter element on dashboard queries, but it might be one way to reduce the time taken for a
single scrape.

## Very slow queue managers
The collectors wait for a short time for each response to a status request. If the timeout expires with no expected
message appearing, then an error is reported. Some queue managers - particuarly when hosted in cloud services - have
appeared to "stall" for a period. Even though they are not especially busy, the response messages have not appeared in
time. The default wait of 3 seconds can be tuned using the `connection.waitInterval` option.

For all collectors _except_ Prometheus, a small number of these timeout errors are permitted consecutively. The failure
count is reset after a successful collection. See _pkg/errors/errors.go_ for details. The Prometheus collector has an
automatic reconnect option after failures, so does not currently use this strategy.
2 changes: 1 addition & 1 deletion cmd/mq_json/main.go
Original file line number Diff line number Diff line change
Expand Up @@ -47,7 +47,7 @@ func printInfo(title string, stamp string, commit string, buildPlatform string)
if buildPlatform != "" {
log.Infoln("Build Platform: " + buildPlatform)
}
log.Infoln("MQ Go Version : " + cf.MqGolangVersion)
log.Infoln("MQ Go Version : " + cf.MqGolangVersion())
log.Println("")
}

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2 changes: 1 addition & 1 deletion cmd/mq_prometheus/README.md
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Expand Up @@ -111,4 +111,4 @@ to continually attempt to reconnect with the `keepRunning` parameter (provided t
and successfully connected once). In this
mode, the web server called by Prometheus to give the metrics continues to run. It will return a single
metric `qmgr_status` indicating that the queue manager is down. This may be the preferred
execution model when the collector is not running as a queue manager service.
execution model when the collector is not running as a queue manager service.
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