Latest Release Notes
Created: | Updated:
z/IRIS 1.12.0
Features
All features created in this release culminate in users obtaining end-to-end workflow and performance insights where requests depend on IBM MQ for z/OS and CICS transactions. Find out more about these features below.

Example of end-to-end trace that includes MQ and CICS services
MQ for z/OS Trace
Traces are created from SMF 116 type 1 & 2 records to depict tasks/threads that initiated within a z/OS MQ Queue Manager to process messages in queues or topics. Each MQ for z/OS trace identifies how the task was initiated, the latency of the task, and whether the Queue Manager detected any errors. Child spans within the trace each identify an object (queue or a topic) that the task used to process messages. The time spent connected to the object is shown through the child spans' duration.

An overview of a MQ for z/OS trace in Jaeger
CICS Transaction spans
Spans are created from SMF 110 records to describe CICS transaction executed on z/OS. Each span identifies the transaction, its response time. Also contained within the spans are Resource and Trace attributes. Resource attributes identify the CICS subsystem as well as the z/OS LPAR and Sysplex that processed the transaction. Trace attributes provide additional performance and resource utilization metrics for the processing of the transaction.
See CICS Transaction Observability to find out more about the span design, and refer to CICS Transaction Spans for a detailed list of attributes provided.

An example of a span for an INBM CICS application transaction and a few attributes in Jaeger
Distributed MQ to MQ for z/OS Workflow Tracing BETA
A new function enables the correlation of APM traces from distributed IBM MQ clients with MQ for z/OS spans created by z/IRIS. This correlation reveals which client applications depend on MQ for z/OS queues and queue managers for digital business services. The insight provided by MQ for z/OS spans will help users identify how mainframe resources are consumed and how mainframe applications perform for distributed applications.
Below is an example of a trace composed of spans from various HTTP, and JMS applications on Linux, supplemented by MQ for z/OS spans from z/IRIS:

Mainframe Workflow Tracing for IBM MQ and CICS spans BETA
Users can identify CICS Transaction that use MQ for z/OS in a single logical unit of work. This enables visibility into the relationship between these services and enables holistic analysis and monitoring for users.
Below is an example of a trace composed of CICS and MQ for z/OS spans for a single transaction:

IBM MQ → CICS workflow trace
z/IRIS 1.11.0
Features
z/IRIS Mainframe Workflow Tracing for z/OS Work Batch Jobs BETA
This release supports correlating multiple SMF Type 30 records. As a result, z/IRIS users will get a single flame graph, composed of spans that each represent the phases and steps of a batch jobs.
See example below:

z/OS Work trace of a batch job
Clock Skew correction for mainframe spans TEST | POC
Differing system clocks diverge when not adequately synchronized. This “clock skew“ results in misaligned time-based data that deteriorates user experience on observability platforms and complicates analysis.

Clock Skew between distributed and mainframe systems
If clock synchronization over Network Time Protocol(NTP), System Time Protocol (STP)and/or an external time source is unavailable while trialing z/IRIS, it will impact the way relationships between distributed and mainframe applications are depicted. For testing purposes only, a clock skew correction can be configured in IronTap to simulate synchronized time between mainframe and open-systems. See Configure IronTap server for more information about the irontap.zos.global
parameter.

Clock skew correction activated in IronTap
z/IRIS 1.10.0
Feature
z/IRIS Mainframe Workflow Tracing for z/OS Connect and Db2 records BETA
This release contains the first version of the z/IRIS Mainframe Workflow Tracing, allowing z/IRIS to correlate multiple SMF records into meaningful spans and traces. The scope of this release encompasses our first use case, which is the correlation of related z/OS Connect and Db2 SMF records. This allows users to see true end-to-end workflows of traces involving these two mainframe services. See example flame graphs for Datadog and Jaeger below:

z/OS Connect Db2 workflow in Datadog

z/OS Connect Db2 workflow in Jaeger
See z/IRIS Mainframe Workflow Tracing to find out more about the z/IRIS SMF Correlation feature.
z/OS Connect Workflow Tracing contains details about the z/OS Connect and Db2 SMF correlations.
Bugfix
An issue causing warning logs regarding missing configuration parameters has been resolved.
z/IRIS 1.9.0
Feature
🌟 Datadog API integration support BETA
Datadog APM Traces
Datadog users can elect to stream traces via the Datadog Agent API. This integration is provided in addition to the existing OpenTelemetry support, to accelerate proof of concept/value projects for Datadog users.
Please refer to Configuring Irontap Datadog integration to find out more about using Datadog APIs to enable mainframe-inclusive observability.
Datadog API integration is currently BETA. Technical support is provided to selected customers only. Contact mainstorconcept support should your organization be interested in testing Datadog Trace API integration.

Example of z/OS Connect services streamed using Datadog’s Agent API
🎉 Datadog Events
To ensure DevOps teams can proactively address anomalies and errors to avoid major incidents and outages requires adequate visibility into application issues that may impact overall business performance. z/IRIS creates events that leverage Datadog’s Unified Tagging capabilities. Datadog’s Events Explorer is a powerful user interface to search, analyse, and filter events from any source in one place.

Example of JES2 Batch Job Events in the Datadog Events Explorer
Please refer to Configuring Irontap Datadog integration for guidance on how to enable Irontap to create Datadog Events using the Events API.
z/IRIS 1.8.0
Feature
🎉 z/OS MQ Metrics 🎉
IBM MQ plays a critical role in business application communication, this is why maintaining performance and resource availability for MQ components like queue managers and buffer pools is crucial.
Anomaly detection, issue analysis and health insights for your MQ systems facilitates planning, optimization and reliability efforts.
In this release, z/IRIS introduces z/OS MQ Metrics, that are streamed in real-time to ensure instantaneous access to performance indicators that signal changes in your MQ infrastructure, applications, or client behavior.
MQ statistics records (SMF Type 115) contains a multitude of statistics from various resources within the system. This release of z/OS MQ Metrics focuses on the most vital performance indicators for monitoring, analysis and alerting purposes. Customers may request support for additional fields contained in SMF 115 records by contacting support.
Grafana z/OS MQ Dashboard
Importable Grafana z/OS MQ Dashboards are designed to provide quick start assistance for users, by visualizing and summarizing the key performance indicators provided by z/OS MQ Metrics. To meet your organization’s requirements for enterprise monitoring, users can customize panels and thresholds, as well as create alerts.

Screenshot of z/OS MQ Message Manager Activity in Grafana
Datadog z/OS MQ Dashboard and Monitors
Datadog users are provided with importable dashboards and monitors that leverage Datadog's powerful APM capabilities, enriching your day-to-day enterprise monitoring activities, and removing mainframe monitoring silos.
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z/IRIS 1.7.2
Improvements
APM Traces
Common span attributes host.arch
and os.type
are now part of every z/IRIS span to improve overall usability.
Db2 Accounting Traces
Trace semantics has been adapted. The span’s duration is now set to the accounting elapsed time calculated via zos.db2.end.timestamp - zos.db2.start.timestamp
(QWACESC
-QWACBSC
).
z/OS Connect Metrics
The z/OS Connect metric's naming convention has been unified for SMF 123 subversion 1 and 2 to simplify their usage, enabling the user to filter more easily and create customized dashboards faster. In addition, the list of measurement for z/OS Connect has been expanded to include the zos.connect.timed_out.requests and zos.connect.successful.requests. See z/OS Connect Metrics Streaming for more information.
RMF Metrics
RMF metrics have been revamped, enabling more flexible querying as well as ensuring compatibility with telemetry pipeline processors (e.g. OpenTelemetry’s Contrib Collector). See RMF Metrics Streamingfor more information about how RMF metrics have been overhauled, and take a look at how an OpenTelemetry Contrib Cmore informationollector can be configured.
New z/OS Infrastructure Dashboard
RMF gathers data about z/OS resource usage and provides reports of system and sysplex. Using this dashboard, you can get a high-level view and understanding of your performance, and resource utilization on the mainframe. The RMF metrics are used to populate our z/OS Infrastructure Dashboard. In order to keep an eye on your performance and activity in mainframe you can track your CPU contention and mean usage by LPAR and MVS. Additionally, you obtain an overview of your In-Ready-Work-Unit-Queue distribution.
z/OS Infrastructure Dashboard in Datadog

Dashboards optimized for Grafana 8
z/OS Connect and z/OS infrastructure dashboards are now available for Grafana 8. DevOps teams can monitor and analyze how z/OS Connect and mainframe service providers perform for REST API requests. z/IRIS users can identify latencies and errors that impact REST API requests hosted and processed on mainframe systems. In addition, the z/OS infrastructure Dashboard provides information on mean usage, performance and activity, as well as In-Ready-Work-Unit-Queue distribution.
z/OS Connect Dashboard

z/OS Infrastructure Dashboard

z/IRIS 1.7.1
Feature
z/OS Connect tracing with Instana APM
Instana APM users can now activate z/IRIS z/OS Connect tracing with Instana APM. z/OS Connect traces represent REST API requests processed on z/OS Connect servers and provides the standard APM KPIs: call information, latency and errors. Each trace contains tags that provide additional context about the request and its processing within z/OS Connect.

Instana APM call tree enriched with z/OS Connect span by z/IRIS
The System-Of-Record (SOR) child span represents the call to the service provider for the REST API services hosted by the z/OS Connect server. The SOR spans also contain tags that provide additional information about the SOR.

Instana APM call tree enriched with SOR span by z/IRIS
See z/OS Connect traces for Instana APM for more information about this feature.
z/IRIS 1.7.0
Features
🎉 Datadog integration 🎉
z/IRIS mainframe observability support is now available with Datadog. Include mainframe observability to enable your team to analyze mainframe performance using traces and metrics. Furthermore, we provide pre-configured dashboards for z/OS Connect and Db2 for z/OS metrics and traces. Our dashboards are automatically created in your Datadog environment after activating z/IRIS integration. Users can activate a trial directly in Datadog by visiting the Marketplace.
See Mainframe-inclusive observability to find out more about all available features.
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z/OS Connect metrics dashboard in Datadog
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Db2 for z/OS JDBC trace metrics Dashboard
TraceId and SpanId format support
Datadog uses a custom (64 bit unsigned int) format for TraceIds and SpanIds. z/IRIS supports this format to facilitate the searchability of traces in Datadog. See how to configure z/IRIS Irontap to enable this feature.
Improvements
z/OS Connect telemetry
z/OS Connect metrics have been revamped, enabling more flexible querying as well as ensuring compatibility with telemetry pipeline processors (e.g. OpenTelemetry’s Contrib Collector). See z/OS Connect Metrics Streamingfor more information about how z/OS Connect metrics have been overhauled, and take a look at how a OpenTelemetry Contrib Collector can be configured.
Grafana
The importable z/OS Connect Grafana dashboards have also been updated to utilize the new metrics schemes.
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z/OS Connect metrics dashboard in Grafana
z/IRIS 1.6.5
Improvements
Distributed Db2 deadlock traces for Instana
Instana Db2 deadlock spans have been overhauled to deliver a clearer view of each deadlock, similar to our OpenTelemetry Db2 deadlock spans. Distinct Waiter and Holder child spans are now created for each Resource span.
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Db2 Deadlock trace with distinct Holder and Waiter child spans
z/OS Work traces (SMF30) for Instana
We provide error messages, enriched with additional information collected from the mainframe. These messages are now available directly from the Instana Trace View when spans are marked as erroneous to increase the visibility. Events are now created with either Warning or Critical severity and have been revamped to include the same information available in the error message. See Instana APM z/OS Work Traces for more information.
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Critical Event created by z/IRIS about a batch job that ended with return code 8
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Sample of a batch job trace with error information from z/OS
z/IRIS 1.6.4
Features
z/OS Work (SMF 30) telemetry
The z/OS work traces for subtype 1,4 and 5 are now available with OpenTelemetry.
A trace is created, when
A batch job, USS process or transaction starts or ends processing on z/OS.
A user logged onto or off from a z/OS system via TSO.
A step in a batch job has completed.
When a non-zero completion code occurs which results from a system or user Abnormal End (abend) in a job, step in a batch job, USS process or transaction, then the error will be signaled via the status of the corresponding span and an error message will be provided.
All traces are enriched with trace attributes that contain metadata about the mainframe system, processing, performance and resource consumption as well as to facilitate searching and filtering to easily locate mainframe traces for batch analysis. See z/OS Work trace attributes with OpenTelemetry for more information.
See z/OS Work OpenTelemetry Observability for detailed information.
Example of z/IRIS OpenTelemetry integration with Jaeger and z/OS Work tracing

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Improvements
Db2 deadlock linking
Featuring OpenTelemetry’s trace linking, you can now find all related participants of a deadlock even more easily in your favorite APM.
Example of z/IRIS Db2 Deadlock Participant links

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z/IRIS OpenTelemetry Java Agent Instrumentation Extension BETA
OpenTelemetry users can activate the ziris-instrumentation-extension module with the experimental agent extension feature, which was introduced with the Java Agent release 1.3.0.
ziris-instrumentation-extension adds behaviour to the Java agent to facilitate context propagation for JDBC calls to Db2 z/OS servers, enabling Distributed Db2 for z/OS Observability with OpenTelemetry.
z/IRIS 1.6.3
Features
z/IRIS IronTap Container
Introducing z/IRIS IronTap as a Docker container. Simply run z/IRIS IronTap anywhere with a single command:
docker run \
--name irontap \
mainstorconcept.jfrog.io/ziris-docker-release/irontap:latest-kafka-instana
Find out more about running and configuring your dockerized z/IRIS IronTap.
Improvements
Db2 Accounting telemetry
The Db2 Accounting traces are now available with OpenTelemetry.
Db2 Accounting traces provide resource consumption and performance information within the z/OS system and Db2 subsystem like CPU (total, in-Db2), zIIP processor or durations (elapsed time, response time). See Db2 Accounting trace attributes with OpenTelemetry for detailed information.
Kafka record extractor tool
An easily configurable Kafka record extractor tool to extract SMF records from an Apache Kafka cluster for a specified time interval is now available. See Collecting SMF records from an Apache Kafka topic for more information.
z/IRIS v 1.6.2
Improvements
z/OS Connect telemetry
An additional “system of record” (SOR) span is created for the services called by z/OS Connect allowing a more detailed end-to-end tracing and clearer visualization of latencies between the z/OS Connect REST API gateway and the SOR. See z/OS Connect Observability for more information.
Span status will be set to error for z/OS Connect timeouts and HTTP codes (400-502).
A useful error message will be provided.
Distributed Db2 deadlock telemetry
The Db2 deadlock traces are now available with OpenTelemetry.
Application traces are enriched with Db2 deadlock traces that contain information for root-cause analysis as well as identifiers to locate all applications impacted by the deadlock for simpler business impact analysis. See Db2 Deadlock Spans for more information.
The values of the custom attribute zos.db2.lock.type (QW0172FR), which represents Db2 deadlock types, have been improved for better searchability.
z/IRIS v 1.6.1
Improvements
Integration of Apache Kafka
Apache Kafka 2.7.0 compatibility testing passed. Additionally, since version 0.10.2 Apache Kafka provides a bi-directional compatibility policy which guarantees that customers can upgrade their cluster brokers in isolation to updating the Kafka libraries used by the consumers in z/IRIS IronTap and producers in z/OS clients respectively.
IronTap
Logging - Customers can configure IronTap logging to ignore sensitive data, to prevent accidental security leaks when customers share logs outside their organization for support.
z/IRIS v 1.6.0
Features
OpenTelemetry integration
Observability and Monitoring requirements vary greatly depending on the business case and customer requirements. This is why a uniform standard is needed, that would allow different APM products to interact with each other, resulting in custom solutions that meet the needs of our customers.
The Cloud Native Computing Foundation (CNCF) OpenTelemetry project is an observability framework that provides an open standard for telemetry data, including traces and metrics. The project has broad industry support and adoption from cloud providers, vendors and end users. With this release, the z/IRIS team acknowledges the importance of such an open standard, as its capabilities will ensure sustainable, vendor-neutral APM support for z/IRIS customers.
Example of z/IRIS OpenTelemetry integration with Jaeger and z/OS Connect tracing

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z/OS Connect telemetry
z/IRIS enables observability and monitoring capabilities for client REST API requests that are processed by IBM z/OS Connect servers hosted on mainframe systems. Observability capabilities are available to partner and open-source APM vendors that support the OpenTelemetry Protocol (OTLP) specification.
The real-time processing of z/OS Connect SMF type 123 records provides two new features for mainframe-inclusive observability support for mainframe-backed DevOps:
Metrics streaming for SMF type 123 subtype 1 version 1 and version 2
z/OS Connect metrics are streamed to a preconfigured data sink that is integrated with visualization and analysis software and tools. Official support for InfluxData's InfluxDB time series database is provided for all metric streaming features out-of-the-box. Additional adapters for streaming metrics to alternate data sinks or DBMS systems is available on request. See z/IRIS - z/OS Connect Metrics Streaming for more information.
z/OS Connect metrics allow DevOps to monitor:elapsed times (for all or selected z/OS Connect servers, by z/OS system or sysplex name),
latency between z/OS Connect servers and their System-Of-Records (SORs),
timeout frequency,
activity by user-name, service-name and types and more.
Trace streaming for SMF type 123 subtype 1 version 2
DevOps teams have access to vital performance data and identifiers related to their application's REST-API requests that are processed by IBM z/OS Connect servers on mainframe systems. z/IRIS appends z/OS Connect spans to the trace-tree of the calling application in the APM user-interface. This is our first mainframe trace streaming feature that adheres to the (OTLP) specification. OTLP compliance ensures vendor-neutral support for our customers and future-oriented integration and support for compatible APM products.
Importable Grafana dashboard JSON
For quick start-up assistance, z/IRIS provides users with an importable JSON file, that creates customizable panels in a Grafana dashboard. Our zosconnect Grafana dashboard queries z/IRIS z/OS Connect Metrics that are stored in an InfluxDB bucket.
Example of the z/IRIS zosconnect Grafana dashboard

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z/IRIS v 1.5.0
Features
CPU activity metrics (RMF SMF type 70 records)
Resource Measurement Facility (RMF) is IBM's strategic performance management product for z/OS and provides the ability to gather resource usage data with additional reporting and analysis functionality.
z/IRIS supports RMF SMF records, starting with record type 70, which provides CPU activity data. The RMF SMF records are streamed and parsed in real-time and integrated into open-source metric monitoring software.
z/IRIS RMF Metrics Streaming provides detailed documentation on the various metrics and data schemas created by z/IRIS.
InfluxDB integration support for metrics
z/IRIS supports streaming metrics to an InfluxDB 2.0 time series database for retention. InfluxDB instances can be used as data sources for analytics and visualization applications like Grafana.
Streaming metrics to an alternate DBMS through z/IRIS can be requested.
Example of z/IRIS InfluxDB 2.0 RMF 70 schema
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Grafana dashboard JSON
For quick start-up assistance, z/IRIS provides users with an importable .json file that creates the following panels in an RMF related Grafana dashboard:
Current in-ready work unit queue distribution per system

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CPU contention per system
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Mean CPU usage
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Accessing z/IRIS Software
All software packages and container images can be retrieved from the mainstorconcept JFrog repository.
Please note:
Licenses are obtained seperately. Contact technical support or your z/IRIS representative to for more information.