ITRS Analytics Platform 1.x Release Notes
Overview Copied
ITRS Analytics Platform release notes contain the list of new features and known issues in the ITRS Analytics Platform.
For the latest highlights, see [What’s New in ITRS Analytics](/obcerv/ITRS Analytics-whats-new/).
Before you install ITRS Analytics, make sure to review the ITRS Analytics Compatibility Matrix. For details on installation, administration, and usage, you may refer to ITRS Analytics Documentation.
ITRS Analytics Platform 1.4.1 Copied
Released: 19 July 2023
Note
Upgrading to ITRS Analytics Platform version 1.4.1 is supported from version 1.3.2 and later.
New features and enhancements Copied
These are the new features and enhancements of this release:
Issue key | Release description |
---|---|
HP-1876 | The chunk tuner now automatically adjusts Timescale chunk sizes to optimize Postgres performance and mitigate resource exhaustion due to large chunks. A signal is created for large chunks that need manual attention. For more details, see Troubleshooting. |
HP-1937 | Certain table triggers were removed to allow late-arriving data to be inserted into Timescale chunks that were already compressed. |
HP-1981 | Relaxed task validation to allow multiple tasks that match the same entity. |
Issues fixed Copied
These are the issues we have fixed in this release:
Issue key | Release description |
---|---|
HP-1933 | Fixed an issue in sinkd where a data point may not be inserted due to stale configuration. |
HP-1950 | Entities and signals that were evicted but reappeared while still cached no longer cause sinkd to crash. |
HP-1951 | The timeseriesDiskSize can now be changed after the initial installation, since the parameter is now mutable. |
HP-1952 | Upgraded Snappy and Guava dependencies due to security issues. |
ITRS Analytics Platform 1.4.0 Copied
Released: 31 May 2023
Note
ITRS Analytics Platform version 1.4.0 requires you to upgrade to App Query Service 1.8.0, since its earlier versions are not compatible with ITRS Analytics Platform 1.4.0.
Upgrade notes Copied
Make sure to read and follow the steps in this section before upgrading the ITRS Analytics Platform.
ITRS Analytics configuration Copied
Before upgrading, you must compare your current configuration with the latest reference configurations to identify any changes that should be applied for compatibility with the new version.
While comparing, use these guidelines to determine which version of the configuration settings to use:
- For all disk sizes and
storageClass
parameters, keep your current settings. - For
timescale.retention
, replace the entire parameter with the new settings. - For
entityStream.final.resources
andentityStream.intermediate.resources
, use whichever is larger. - For parameters that exist only in the new configuration, copy those settings into your config.
- For all other parameters, keep your existing settings.
Data migration Copied
During the upgrade, a migration job will restructure large amounts of data in Timescale. This job will continue to run in the background after the upgrade is complete and may take several hours.
Caution
Running out of disk space is possible during the migration. Before initiating the upgrade, make sure that there is at least 60% free space on the Timescale data volumes.
If the migration fails due to insufficient capacity, you should expand those PVCs, and the migration will automatically resume. There may be gaps in metric queries until the migration is complete.
To check the free space:
$ kubectl exec -n itrs -it timescale-0 -c timescale -- df -h |grep postgres
/dev/sde 98G 1.2G 92G 2% /var/lib/postgresql
/dev/sdf 98G 4.4G 89G 5% /var/lib/postgresql/wal
/dev/sdg 503G 3.4G 475G 1% /var/lib/postgresql/tablespaces/timeseries_tablespace_2
/dev/sdd 503G 3.7G 474G 1% /var/lib/postgresql/tablespaces/timeseries_tablespace_1
If you see only the first two filesystems, ensure the usage percentage for /var/lib/postgresql
is at most 40% (which
means 60% free). The corresponding PVCs are named timescale-ha-data-timescale-X
. If you need to grow the PVCs, grow
all that match that name pattern (there should be 3).
If you see any filesystems named *tablespace*
, then ensure each of those is at most 40% used (which means
60% free). The corresponding PVCs are named timescale-ha-tablespace-data-X-timescale-Y
. If you need to grow the
PVCs, grow all that match that name pattern.
New features and enhancements Copied
These are the new features and enhancements of this release:
Issue key | Release description |
---|---|
HP-1197 | Improved support for multiple availability zones. |
HP-1519 | Multi-table metrics schema used for improved scalability. |
HP-1572 | Signal service subscriptions now include the last signal event for any signal that is active at the start of a signal subscription window. |
HP-1573 | The GetLatestSignals queries can now be filtered by severity and snooze status. |
HP-1574 | Attribute subscription starting from the past now returns the last known value before the beginning of the look-back period. |
HP-1592 | Signals data is now persisted in Postgres, while the GetLatestSignals API is now paginated. |
HP-1596 | Signal event timestamps are now preserved for signal events occurring while a signal is snoozed. |
HP-1662 | Entity and entity attribute subscriptions now return an indication that the end of the snapshot has been reached. |
HP-1703 | The Gateway name is now stored as a searchable label in Loki. |
HP-1710 | Signal subscription now supports retroactive subscription from a provided start time. |
HP-1713 | Ensured that DP headers contain valid events and observed timestamps during datapoint validation. |
HP-1723 | Enhanced hypertable retention configuration (phase one). |
HP-1731 | Scheduled job to defragment etcd. |
HP-1734 | Changed the default metric data retention in Timescale. |
HP-1767 | Datapoint validation ensures that dimensions are not empty. |
HP-1768 | Size metrics for non-hypertable Postgres tables are now collected. |
HP-1776 | Included namespace in the CA DaemonSet persistence path. |
HP-1779 | Datapoint validation is now performed at the edge CAs. |
HP-1780 | The schema version now matches the ITRS Analytics Platform version. |
HP-1806 | Enabled pg_rewind for recovery from missing timeline during replication. |
HP-1808 | Patroni config changes now correctly applied on upgrades. |
HP-1814 | Improved signal retention, TTL, and eviction. |
HP-1838 | Implemented a background job for the migration of pre-1.4 metrics data. |
HP-1842 | Supported configurable JVM override options for the DS stream. |
HP-1862 | Created a utility docker image for ITRS Analytics. |
HP-1867 | Minimum Timescale chunk sizes and retention configuration are now enforced. |
HP-1905 | Signal data is migrated from Kafka to Postgres during upgrade. |
HP-1906 | Added support for Geneos signals that contain geneos_signal/ or geneos_snooze/ prefixes to the signal name based on the type of event. These are now normalized to a geneos/ prefix. |
HP-1907 | IES events and entity severity updates are migrated during upgrade. |
HP-1912 | Changed IAM configuration to support offline_access tokens, which are used by the web platform to keep sessions open. |
Issues fixed Copied
These are the issues we have fixed in this release:
Issue key | Release description |
---|---|
HP-1763 | Datapoints with future timestamps are now rejected. |
HP-1761 | Added a missing Keycloak configuration for valid post-logout redirect URIs. |
HP-1765 | Fixed an issue where multiplexed DPD pipelines did not consider entity attribute mutations. |
HP-1772 | Fixed a platform-metrics error when parsing Kubernetes stats with a number that exceeded the maximum long value. |
HP-1789 | Having an externalHostname with more than 64 characters no longer results in an install error. |
HP-1798 | Kafka consumer now properly transitions to an error state upon leaving a consumer group. |
HP-1805 | KVS no longer throws an exception when accessing an entry with a name that is the prefix of another entry. |
HP-1855 | Fixed an issue where upon changing classification rules or re-installing the System Overview app, some entities could end up with an inconsistent or missing inactive-since or severity attribute. |
HP-1857 | Fixed an issue where DS Stream throws NPE on a null TimeBucket . |
HP-1861 | Resolved an issue where the DS stream fails if the status metric is too large. |
HP-1885 | Missing entity containment rules no longer cause entities without a hierarchy to be skipped by eviction. |
HP-1900 | Fixed an error where the Kubernetes CRI log collector parse fails if the message contains stderr or stdout . |
HP-1908 | Timeseries records are no longer duplicated. |
ITRS Analytics Platform 1.3.2 Copied
Released: 5 April 2023
Important
Upgrading to version 1.3.2 is mandatory for those using previous versions of the ITRS Analytics Platform. Depending on your configuration, the upgrade process may take some time to complete.
New features and enhancements Copied
These are the new features and enhancements of this release:
Issue key | Release description |
---|---|
HP-1760 | Pending or unscheduled pods for the CA DaemonSet are prevented from blocking deployment. |
Issues fixed Copied
These are the issues we have fixed in this release:
Issue key | Release description |
---|---|
HP-1816 | Corrected how TimestampNanos is used on entity-attributes-updates records. |
HP-1832 | Fixed an issue where the CA DaemonSet nodeSelector parameter failed to take effect. |
ITRS Analytics Platform 1.3.1 Copied
Released: 20 February 2023
New features and enhancements Copied
These are the new features and enhancements of this release:
Issue key | Release description |
---|---|
HP-1715 | The ETCD_SNAPSHOT_COUNT value has been reduced to 10000 . |
HP-1737 | The etcd quota size can now be configured to a maximum of 8GB . |
Issues fixed Copied
These are the issues we have fixed in this release:
Issue key | Release description |
---|---|
HP-1637 | Fixed an issue where out-of-order metrics caused DS metrics stream performance degradation. |
HP-1730 | Fixed an issue where NullPointerException collects Kubernetes fs usage percentage metrics. |
HP-1736 | maxPageSizenow works properly in GetMetricMetadata . |
HP-1743 | Resolved a false positive connection leak warning in sinkd . |
HP-1756 | The FES setting attribute now correctly updates the timestamp in nanoseconds instead of in milliseconds. |
HP-1762 | The FES setting attribute now correctly updates the timestamp in nanoseconds instead of in milliseconds. |
ITRS Analytics Platform 1.3.0 Copied
Released: 30 January 2023
New features and enhancements Copied
These are the new features and enhancements of this release:
Note
Upgrading to this version requires App Query Service version 1.6.0.
Issue key | Release description |
---|---|
HP-1623 | The usage of root user in Docker images has been audited. |
HP-1632 | Timescale has been upgraded to version 2.8.1, while PostgreSQL has been upgraded to version 14.6. |
HP-1661 | A new parameter, jvmOpts , has been added so the heap % can be overridden. While the default should be blank, these parameters should only be used in one-off scenarios when there is a necessity for changing the default % heap usage. |
Issues fixed Copied
These are the issues we have fixed in this release:
Issue key | Release description |
---|---|
HP-1589 | Data points affecting entity attributes and status metrics that are received out of order due to an upstream load-balancer are no longer getting applied. |
HP-1594 | Compiled entity expressions now support status metrics. This means that searches can now be performed on status metrics. |
ITRS Analytics Platform 1.2.0 Copied
Released: 24 October 2022
Highlights Copied
These are the highlights of this release:
- Several improvements to signals such as better storage and retrieval, subscription filtering, and increased history retention (up to 7 days).
- Open Telemetry ingestion is now supported.
- Various updates, including a fix to a known security vulnerability.
New features and enhancements Copied
These are the new features and enhancements of this release:
Issue key | Release description |
---|---|
HP-1405 | Signals now have the ability to filter subscriptions. |
HP-1450 | Timescale has been upgraded to version 2.7. |
HP-1452 | Kafka has been upgraded to version 3.2.0. This includes the upgraded RocksDB version 6.29.4.1, which adds support for ARM-based Macs. |
HP-1470 | Protobuf has been upgraded to version 3.21, while gRPC has been upgraded to version 1.47. |
HP-1511 | Open Telemetry is now supported with a new ingestion service in the ITRS Analytics Platform. |
HP-1582 | History retention for signals has been increased to 7 days. |
HP-1583 | Kafka has been upgraded to version 3.2.3 to address the security vulnerability: CVE-2022-34917. |
HP-1584 | SnakeYAML has been upgraded to version 1.32. |
HP-1586 | Keycloak has been upgraded to version 19.02. |
HP-1600 | Kubernetes node, pod, and container FS usage percent metric are now collected. |
Issues fixed Copied
These are the issues we have fixed in this release:
Issue key | Release description |
---|---|
HP-1532 | An internal server error for the Metric-forecastd pod is no longer encountered in the web console. |
HP-1533 | Fixed an issue where the Best Fit bucket size attempts to select an invalid bucket size (no bucket, such as with raw data) for a short-time window when forecasting is enabled. |
ITRS Analytics Platform 1.1.0 Copied
Released: 1 August 2022
Highlights Copied
These are the highlights of this release:
- The ITRS Analytics Platform now supports entity eviction to automatically purge entities from the system that have not been updated for a long period of time. Since the total number of entities is likely to grow over time, you can configure eviction rules to your particular use case.
New features and enhancements Copied
These are the new features and enhancements of this release:
Issue key | Release description |
---|---|
HP-791 | Support for automatic eviction of stale entities (those which have not received data for an extended period of time). Eviction rules can be configured using the ITRS Analytics operator. |
HP-1401 | When the count function is used, unit values are omitted from GetMetrics* responses. |
HP-1423 | Support for tablespaces within Postgres/Timescale. This is helpful for very large installations when there are constraints on the maximum volume sizes set by a cloud service provider. |
Issues fixed Copied
These are the issues we have fixed in this release:
Issue key | Release description |
---|---|
HP-1471 | Manually resizing WAL disks now also updates Postgres tuning settings. |
HP-1475 | Missing Kubernetes labels have been added to workload pods. |
HP-1507 | The PL/Java libjvm path setting is correctly replicated in Timescale secondaries. |
ITRS Analytics Platform 1.0.2 Copied
Released: 14 July 2022
Issues fixed Copied
These are the issues we have fixed in this release:
Issue key | Release description |
---|---|
HP-1455 | When an existing entity classification gets deleted, some entities can be left enriched with attributes defined in the classification. The issue is caused by how RocksDB handles its cache updates when used in conjunction with Kafka streams. |
HP-1468 | An error in deploying ITRS Analytics when the cluster can’t resolve the node hostname has been fixed. |
ITRS Analytics 1.0.0 Copied
Released: 1 June 2022
Highlights Copied
These are the highlights of this release:
-
Next-level observability platform — ITRS Analytics answers the complex data monitoring needs of today’s modern IT operations. As an observability platform for data storage and analytics, ITRS Analytics efficiently manages the volume, variety, and velocity of data from different sources. It is your one-stop shop for storing, accessing, and analysing critical monitoring data.
-
Flexibility for lower storage costs — ITRS Analytics collects data from multiple feeds and streams while giving you the ability to define rules and organise entities for targeted monitoring. Through meta-tagging, dimensionality is provided to stored data. Data compression lowers storage costs while ensuring that data fidelity is maintained.
Known issues Copied
These are the known issues affecting this release:
Issue key | Known issue description |
---|---|
CPPUB-114 | Connection attempts fail when the Capacity Planner app uses the Apache HTTP Proxy. This is due to LinkerD preventing the Capacity Planner app from publishing data to Capacity Planner. |
HP-1387 | Before successfully completing the setup, an error using the PL/Java extension can occur on the first set of queries for down-sampled metrics. This happens when the bucket_function is for percentiles and the time bucket is 5 minutes or more (down-sampled metrics). The PL/Java extension initialises a Java virtual machine (JVM) per connection, while the startup takes a few seconds to handle the first query in the connection. The query will fail due to the error. However, subsequent queries are likely to succeed since enough time may have passed for the connection’s PL/Java JVM to initialise. |
HP-1433 | When you manually set a Timescale multi-server cluster to only one server using kubectl , Timescale read operations will fail. |
HP-1434 | If no secondary Timescale is available in a multi-server cluster, Timescale read operations will fail. |
Disclaimer
The information contained in this document is for general information and guidance on our products, services, and other matters. It is only for information purposes and is not intended as advice which should be relied upon. We try to ensure that the content of this document is accurate and up-to-date, but this cannot be guaranteed. Changes may be made to our products, services, and other matters which are not noted or recorded herein. All liability for loss and damage arising from reliance on this document is excluded (except where death or personal injury arises from our negligence or loss or damage arises from any fraud on our part).