Casting the result of getPeerCertificates() to X509Certificate[] mirrors
what is done in the ActiveMQ "Classic" code-base.
A few tests which were imported from ActiveMQ "Classic" to verify our
OpenWire implementation were removed as they relied on a "stub"
implementation of javax.net.ssl.SSLSession that never would have worked
across multiple JDKs once javax.security.cert.X509Certificate[] was
removed. Furthermore, the tests appeared to be related to the OpenWire
*client* and not relevant to our broker-side implementation.
Previously, when during reconnect one session couldn't be transferred
to the new connection, we instantly returned and didn't execute failover
for the other sessions. This produced the issue that for sessions
where no failover was executed, their channels were still present on the
old connection. When the old connection was then destroyed, these channels
were closed although the reconnect was still ongoing, which lead to
"dead" sessions.
Now, if a session failover fails, for the remaining sessions the "client-side" part
of failover is executed, which removes the sessions from the old connection so that
they are not closed when the old connection is closed afterwards.
In 73c4e399d9 a description is added to DiskStoreUsage. It incorrectly describes the diskStoreUsage as a percentage. This commit changes it to a fraction which it is (also before the description change). A percentage would be better, since MaxDiskUsage is also specified as percentage.
The provider of an SSL key/trust store is different from that store's
type. However, the broker currently doesn't differentiate these and uses
the provider for both. Changing this *may* potentially break existing
users who are setting the provider, but I don't see any way to avoid
that. This is a bug that needs to be fixed in order to support use-cases
like PKCS#11.
Change summary:
- Added documentation.
- Consolidated several 2-way SSL tests classes into a single
parameterized test class. All these classes were essentially the same
except for a few key test parameters. Consolidating them avoided
having to update the same code in multiple places.
- Expanded tests to include different providers & types.
- Regenerated all SSL artifacts to allow tests to pass with new
constraints.
- Improved logging for when SSL handler initialization fails.
Change summary:
- Remove the existing Xalan-based XPath evaluator since Xalan appears
to be no longer maintained.
- Implement a JAXP XPath evaluator (from the ActiveMQ 5.x code-base).
- Pull in the changes from https://issues.apache.org/jira/browse/AMQ-5333
to enable configurable XML parser features.
- Add a method to the base Message interface to make it easier to get
the message body as a string. This relieves the filter from having
to deal with message implementation details.
- Update the Qpid JMS client to get the jms.validateSelector parameter.
If an application wants to use a special key/truststore for Artemis but
have the remainder of the application use the default Java store, the
org.apache.activemq.ssl.keyStore needs to take precedence over Java's
javax.net.ssl.keyStore. However, the current implementation takes the
first non-null value from
System.getProperty(JAVAX_KEYSTORE_PATH_PROP_NAME),
System.getProperty(ACTIVEMQ_KEYSTORE_PATH_PROP_NAME),
keyStorePath
So if the default Java property is set, no override is possible. Swap
the order of the JAVAX_... and ACTIVEMQ_... property names so that the
ActiveMQ ones come first (as a component-specific overrides), the
standard Java ones comes second, and finally a local attribute value
(through Stream.of(...).firstFirst()).
(In our case the application uses the default Java truststore location
at $JAVA_HOME/lib/security/jssecacerts, and only supplies its password
in javax.net.ssl.trustStorePassword, and then uses a dedicated
truststore for Artemis. Defining both org.apache.activemq.ssl.trustStore
and org.apache.activemq.ssl.trustStorePassword now makes Artemis use the
dedicated truststore (javax.net.ssl.trustStore is not set as we use the
default location, so the second choice
org.apache.activemq.ssl.trustStore applies), but with the Java default
truststore password (first choice javax.net.ssl.trustStorePassword
applies instead of the second choice because it is set for the default
truststore). Obviously, this does not work unless both passwords are
identical!)
Replaces direct jdbc connections with dbcp2 datasource. Adds
configuration options to use alternative datasources and to alter the
parameters. While adding slight overhead, this vastly improves the
management and pooling capabilities with db connections.
This reverts commit dbb3a90fe6.
The org.apache.activemq.artemis.core.server.Queue#getRate method is for
slow-consumer detection and is designed for internal use only.
Furthermore, it's too opaque to be trusted by a remote user as it only
returns the number of message added to the queue since *the last time
it was called*. The problem here is that the user calling it doesn't
know when it was invoked last. Therefore, they could be getting the
rate of messages added for the last 5 minutes or the last 5
milliseconds. This can lead to inconsistent and misleading results.
There are three main ways for users to track rates of message
production and consumption:
1. Use a metrics plugin. This is the most feature-rich and flexible
way to track broker metrics, although it requires tools (e.g.
Prometheus) to store the metrics and display them (e.g. Grafana).
2. Invoke the getMessageCount() and getMessagesAdded() management
methods and store the returned values along with the time they were
retrieved. A time-series database is a great tool for this job. This is
exactly what tools like Prometheus do. That data can then be used to
create informative graphs, etc. using tools like Grafana. Of course, one
can skip all the tools and just do some simple math to calculate rates
based on the last time the counts were retrieved.
3. Use the broker's message counters. Message counters are the broker's
simple way of providing historical information about the queue. They
provide similar results to the previous solutions, but with less
flexibility since they only track data while the broker is up and
there's not really any good options for graphing.
Both authentication and authorization will hit the underlying security
repository (e.g. files, LDAP, etc.). For example, creating a JMS
connection and a consumer will result in 2 hits with the *same*
authentication request. This can cause unwanted (and unnecessary)
resource utilization, especially in the case of networked configuration
like LDAP.
There is already a rudimentary cache for authorization, but it is
cleared *totally* every 10 seconds by default (controlled via the
security-invalidation-interval setting), and it must be populated
initially which still results in duplicate auth requests.
This commit optimizes authentication and authorization via the following
changes:
- Replace our home-grown cache with Google Guava's cache. This provides
simple caching with both time-based and size-based LRU eviction. See more
at https://github.com/google/guava/wiki/CachesExplained. I also thought
about using Caffeine, but we already have a dependency on Guava and the
cache implementions look to be negligibly different for this use-case.
- Add caching for authentication. Both successful and unsuccessful
authentication attempts will be cached to spare the underlying security
repository as much as possible. Authenticated Subjects will be cached
and re-used whenever possible.
- Authorization will used Subjects cached during authentication. If the
required Subject is not in the cache it will be fetched from the
underlying security repo.
- Caching can be disabled by setting the security-invalidation-interval
to 0.
- Cache sizes are configurable.
- Management operations exist to inspect cache sizes at runtime.
This is allowing journal appends to happen in burst
during replication, by batching replication response
into the network at the end of the append burst.
Emmanuel Hugonnet
Clebert Suconic
franz1981
Justin Bertram
Domenico Francesco Bruscino
gtully
Andy Taylor
Robbie Gemmell
Markus Meierhofer
Erwin Dondorp
Jacob Middag
dhawkins
AntonRoskvist
sebthom
Ingo Karkat
Tomas Hofman
Emmanuel Hugonnet
Mikko Uoti
Bernd Gutjahr
Stefan Krutzler
Michael Pearce