Get up to speed on everything that’s new and improved in the Coralogix platform!
Error Template View
Simplify error management with advanced templating of similar errors into definable issues. Effectively reduce unnecessary noise with drill-down based on customizable filters such as error type, username, URL, session ID, data source and more.
For extensive org-level data management, the Quota Manager now presents data consumption as both Coralogix Units and GB sent; with group by options: Pillar (Logs, Metrics, Traces) and Priority (Blocked, Low, Medium, High).
Our evolving extensions page simplifies data transfer to Coralogix. We’ve added new integration flows for GCP Spans, Azure ARM, Azure Metrics, and Slack. Plus, you can now preview flow alerts in Coralogix extensions.
Exciting dashboard updates include interlinked filters, stacked bar charts, and a new colour scheme for graphs. Plus, enjoy design flexibility with the new Markdown Widget and query archived data within custom dashboards.
Enable Real User Monitoring quickly with the RUM Integration Package. It automates RUM Browser SDK setup and source map uploads, capturing and sending network requests and errors to Coralogix once configured.
Coralogix’s ‘Unified Threat Intelligence’ relies on our Streama technology to provide you with built-in seamless integration with some of the world’s leading threat intelligence feeds. These feeds show hundreds and thousands of threat entities curated by our security experts, allowing you to discover malicious network activities.
API integration, special syntax, or format change is not required. You can automatically enrich your log data with malicious indicators in real time, letting you query, visualize, and set alerts on potential threats.
You can now leverage our powerful Kubernetes dashboard with greater ease, thanks to the newly added ‘Kubernetes Collector’ extension in Coralogix Apps. With the new collector, you can collect the exact data (metrics and K8s events) needed for the installation and install via OpenTelemetry, without the need to manually install each different component.
A preset of the OpenTelemetry collector, this collector is designed to enhance your open telemetry data and seamlessly push it to Coralogix and view it in the Kubernetes dashboard. The Kubernetes Collector is the first step towards simplifying the open telemetry configuration.
You can now use Coralogix’s DataPrime query language to enrich and filter your logs using additional context from a lookup table. With this feature, you can enrich old logs already ingested into Coralogix. Moreover, the on-demand log enrichment doesn’t increase the size of the stored logs.
This becomes immensely useful when you need to get more context into your existing logs. For example, assume you would like to explore all activity logs of all users in your Finance department, while your logs only include the user names. Enrichment of your existing user activity logs with the user’s department allows you to run such a query.
Custom dashboards now support multiple queries, allowing you to compare logs, metrics and spans on the same line chart. Each query gets a dedicated query panel at the bottom and a collapsible side panel on the right, with options to customize each query.
The side panel includes options to change the data source, add multiple group-by values, define data aggregation type, switch between linear and logarithmic scales, select time or data units and view only errors if required.
While adding group-by values for tracing graphs, you can now choose to display what aggregate value is shown, the options being ‘max, min and avg’. You can also share a tracing dependency graph as a shareable URL, that can be opened without changing the saved view.
A “Services” tab displays the execution time of the services in the selected trace. Clicking on the listed services takes you to the respective service catalog. An option to recenter the traces dependency view is also added as a part of the tracing enhancements.
The integrations on “Coralogix Apps” have been extended to include CloudTrail, S3 Log Collection, CloudWatch and VPC Flow Logs from AWS. When deploying, you must add all the required details to automatically collect data from your AWS account. These deployments execute a CloudFormation that adds your relevant resources. To remove an integration, you just need to delete the CloudFormation from your AWS console.
Apart from the AWS resources, Okta can also be integrated in a much easier way. All you have to do is add your Okta domain and the API key to kickstart the data ingestion. The extensions that can be applied to any integration are mentioned right below the integration details.
Bar charts in custom dashboards now have the option to group charts either by time buckets or multiple group-by values. The time buckets can either be auto-set on pre-defined time intervals or manually changed by specifying the required time interval.
You can also customize the bar chart visuals by defining the number of bars, slices per bar, stacking options, selecting time or data units, and switching between linear and logarithmic scales. When stacking, you can also define a custom stack name using free text and labels.
You can now see/update existing recording rules and create new ones using the new UI for Recording Rules. It allows you to easily define a recording rule and categorize it under rule sets and rule groups.
Rule group, with its evaluation interval and series limit, is applied to all the recording rules under it. Rule sets are a way for you to logically sort all of your recording rules.
You can also see a preview of the recording rules for the last 3 hours (limited to 100 permutations). Lastly, recording rules are also supported in extensions as read-only.
A new ‘Flame View’ is added to the existing Traces Dependency view and Gantt view. The flame view is particularly useful for large traces. Like the dependency view, the flame view also supports group-by with aggregation.
This view has the unique feature of zooming onto a specific span for more details and a reset button to return to the original chart view. The view also comes with a context menu that has follow-up actions to view related logs, pod, host, service map and service catalog.
Prioritize important traces and reduce up to two-thirds of your tracing costs. Assign high, medium and low priority levels and access a different range of features for each. Allocate data pipelines for your traces based on the importance of that data to your business. Priority levels will simplify assigning TCO pipelines and will capture any applicable future traces on ingestion.
‘High’ priority, frequent search traces will be fully ingested and all Coralogix capabilities will be available for the same. Monitoring traces will be processed and archived when a ‘Medium’ priority level is assigned. Compliance traces will be archived and assigned a ‘Low’ priority.
Admins can now enable the collection of data usage metrics as native Prometheus metrics, to get granular details on their data consumption. This feature requires the team to have a valid S3 metrics archive bucket configured. With these new metrics, you will be able to create custom dashboards, insights, alerts, and an overview of your data.
The Data Usage Metrics feature creates two new metrics – GB Sent and Counted Units – which count toward your team’s daily metrics quota. Metric names will appear as: ‘cx_data_usage_units’ and ‘cx_data_usage_bytes_total’ on dashboards.
It’s now easier to connect your applications to Coralogix with our new simplified process that lets you generate webhook URLs. This simplifies the process of generating a webhook URL to connect applications and systems with Coralogix, expanding your selection of connections.
Each webhook is associated with an API key and you can define whether the incoming data is plain text or JSON, application & subsystem names, and lastly the timestamp located in the log. This new integration flow will be available on CloudTrail to start with.
Custom Dashboards are now more powerful. Pie charts and bar charts have been added as new additions to widgets, along with pre-existing line charts, gauge and data tables. All 5 widget types will support all 3 data types (logs, metrics and spans) going forward.
In addition, for advanced filtering and customization, both pie charts and bar charts come with options like group-by, stack-by, linear and logarithmic scales, advanced visualization filters and more. Data tables have been upgraded too, with a ‘values over time’ graph which generates a small plot to understand the behavior over the dashboard’s query time.
Here are some of the new additions to the ‘Explore’ screen:
A ‘Group-by’ option has been added to the logs archive histogram to cluster the graph by any log field. You can access this option either by the graph menu at the top or by the key context menu. This is enabled only for customers who have moved to the datafusion query engine.
The traces dependency graph now supports a few 1,000s of spans instead of only 500. A context menu is added to each span which serves as a shortcut to the window containing details on related logs, events, pod and host. Lastly, a group-by option is added to focus on only relevant span tags at a time, producing a simpler traces graph. The two default group-by options are operationName and serviceName.
Lastly, a ‘Manage Keys’ pop-up is added to columns displaying objects in the Explore screen. This will allow you to pin, sort and exclude log keys of your choice; bring important log information to the top and stay focussed on the current context.
The service catalog now includes a filter panel, similar to the logs Explore screen. This allows you to filter services based on specific characteristics in the span tags. The selected filters are also passed on to any service you dive into.
Events2Metrics now includes a graph that displays the amount of permutations actually used and permutations left from the logs archive and the high tier for spans, for a 7-day period. You can choose up to 10 labels for the visualization and once the changes are made, hit refresh.
With the latest UI improvements in Recording Rules, it is now much easier to create new recorded metrics, from the existing ones in Coralogix. The new UI allows you to create new metrics either by importing a YAML file or creating a rule group.
This will simplify complex and resource-intensive PromQL queries into leaner and more quickly queried metrics, which can be used in various dashboard visualizations and high-performance analytics.
Service Catalog is a new feature added under Coralogix’s APM offering. It includes a list of all the services in your system and you can view details such as service type, number of requests sent by the service, the error rate, and the P95 latency by specifying a time range.
You can drill down on each service to look at a service map in the left pane and additional details in the right pane. The service map shows all the services connected to a root service and the right pane provides tabs for a detailed overview, actions taken by the services, health status of resources and logs of each service.
Under standard user-defined alerts, if the alert conditions are set for ‘More than’, you can now choose a new type of evaluation window to define the queried time window. You can choose between the newly added Rolling Window and the existing Dynamic Creation.
Rolling Window is a fixed timeframe and doesn’t change with alert triggers. Dynamic Duration changes the queried time period when an alert is triggered. Rolling Window is now the default choice of evaluation window and is recommended to be used when using ‘Group-by’ with an alert.
Pie Chart is added as a new visualization widget under custom dashboards. It comes with abilities to group-by, aggregate and stack-by data sources and other advanced controls to customize the visuals. Pie Chart is the 4th visualization widget added to custom dashboards.
In addition, ‘Metrics’ is added as a new filter type to make dashboards customizable by the source of data. A ‘Save As’ button is added to clone existing dashboards easily, and a ‘Show Only Errors’ button is added to highlight only errors in span-based widgets.
With the new feature and design improvements, you can now do more with Extensions on Coralogix. Prometheus recording rules can now be deployed as part of an extension. Security and AWS enrichments can be deployed in addition to Geo and Custom Enrichments. Also, selective deployment of enrichments is now possible, allowing you to select only specific enrichment rules when deploying an extension.
A notification will be displayed if deploying the extension will take you over the maximum enrichment quota. Also, hover backgrounds are now shown on dashboard screenshots. And lastly, design and UI improvements have been made to Extensions.
The flow of alerts can now be grouped by the common group-by keys used in the defined alerts. This allows you to examine all alert stages in the context of a single field value. The group-by options available for each alert can be viewed in the Flow Builder by hovering over the alerts.
The group-by fields that can be selected are automatically pulled from the list of fields (from Log-based alerts) and tags (from Span-based alerts), and only ones that show up throughout all alerts will be pulled out automatically for selection.
The K8S dashboard in Coralogix now supports OTEL metrics if you are using an OpenTelemetry collector with a Kubernetes orchestration together with Prometheus to send your data to Coralogix. You can use this feature along with our other application performance monitoring (APM) features, to get a full picture of your system performance.
The K8S dashboard gives you a comprehensive view of your system’s clusters, nodes and pods. In addition, the dashboard also shows the health status of your resources and displays all Kubernetes events. This guide can help you collect Kubernetes events using OpenTelemetry.
Custom Dashboards are now more flexible. Use spans as a new data source, along with logs and metrics. The data source is available across all existing visualizations including Line Chart, Data Table and Gauge visualizations.
Spans can also be added as a data source for filters on any Custom Dashboard, allowing you to apply filters on parameters such as Span Service. Filters in Custom Dashboards also support Span Tags, which can be added as fields in the filter. Spans filters will only affect spans widgets on a dashboard, and will not affect any widgets based on logs or metrics.
Alert notifications can now be grouped into multiple ‘Notification Groups’ for different keys. You can add multiple webhooks to split the alert triggers and customize the notification frequency for each webhook.
You can further activate the ‘Notify when Resolved’ trigger to stay on top of alert notifications.
In addition, an individual notification is sent to each value of the Group By key when the unique query conditions are met within the specified timeframe.
For example, if you have used “region” as a Group By key and let’s say, it has 2 values i.e. Region A and Region B; individual notifications will be sent to both A and B respectively.
A new Content Column is added to the ‘Explore’ screen grid, to improve visibility for content fields and distinguish them from the labels fields. Most logs will have content fields and it is now easy to extract these fields from logs, according to a predefined order list (message, log, k8s.log
You can edit the content list and truncate long keys and values in the label fields and show them flattened instead of JSON. With this new feature, you can define important/favourite labels that will be sorted first, have a default favourites list and allow an extension to update it.
Admins can now configure multiple private API keys to send data to their Coralogix teams. You can further customize these API keys and activate/deactivate them as required. After creating the new key, it is visible in the Send Your Data section.
Customizations are made available to the Send-Your-Data API key management to create, modify, activate, deactivate, reactivate and delete the private API keys created.
To enable this feature please contact your TAM or Coralogix’s support.
Managing your extensions is now easier as you will be notified about the updates available for your extensions through a notification bar found at the top of the Extensions screen. Further, an ‘Update’ button is added, that can be used to update an already deployed extension.
For some older extensions, you may have to remove and redeploy them by selecting the required applications and sub-systems. This way you can switch between versions and stay up to date with the extensions you are actively using.
Along with the Metrics Cardinality feature, the ‘Metrics Usage’ screen can offer you a visual representation of your metrics-related data. Expanding on this capability, we have now added a new visualization i.e. ‘Metrics Usage Trend’. This allows you to visualise 7 days of history for each metric value within the Metrics Usage screen.
The time history can help you identify the metrics that are using up your quota very frequently. Identifying such metrics can help you in cost optimization and get better insights into noisy or expensive applications.
Create unlimited, personalized custom dashboards. Use three new visualizations – Data Table, Line Chart, and Gauge – to define and create a dashboard catered to your specific observability needs. Then query across your widgets using our new Filter and Variable capabilities.
You can now acknowledge, assign, and resolve alerts directly from the Insights UI. Use Coralogix as a task allocation and process control UI to extend and consolidate your monitoring and alerting workflow.
Query your tracing data with Lucene syntax in the tracing UI. You can now build complex searches for specific fields and phrases contained within traces and spans.
The dependency view is now the default tracing view with the metadata about the trace now shown on the right-hand side of the screen. Hovering over a given node in the graph will reveal a tooltip with information about the trace and associated span.
Organization admins can now create new teams from the “My Teams” tab in the Settings page. To create a new team, fill in the 3-step wizard with your new team name, unit allocation, and team admins.
If you need help getting started, reach out to our support team using the in-app chat!
Extended Integration Support
Prometheus Recording Rules Prometheus Recording Rules can now be pulled from Coralogix using cURL commands. Use recording rules to pre-compute new timeseries based on existing ones. Once defined, the corresponding recording rules are automatically created as additional metrics in Coralogix. View Documentation >
AWS Lambda Metrics Our Lambda extension now supports collection of AWS Lambda metrics for essential invocation measurements. Additionally, CX_Metadata is included alongside incoming documents on the Coralogix platform to provide context around cloud provider, account ID, cloud region and more. View Documentation >
APM for Amazon EC2 Using Amazon Kineses Data Firehose, you can now send Amazon EC2 metrics to Coralogix and view them on your Coralogix dashboard correlated with relevant traces and spans. View Documentation >
JumpCloud SCIM Identity Management New SAML integration with JumpCloud allows you to manage groups and users from in JumpCloud. Once integrated, those changes will be automatically reflected in the Coralogix UI. View Documentation >
New AWS Resource Enrichment allows you to enrich your logs with tags from Amazon Web Services (AWS) EC2 instances. Use this feature to connect your business and operation metadata from AWS and gain greater insight into your data.
To get started, visit our documentation for setup and configuration.
Use our new integration with Telegraf Operator to simplify metric collection in Kubernetes. With Telegraf Operator, you only need to define the input plugin configuration for Telegraf when creating the pod annotations. Telegraf Operator then sets the configuration for the entire cluster, avoiding the need to configure a metrics destination when deploying applications.
We’ve updated our integration with Google Cloud Pub/Sub to use a push subscription to send logs to Coralogix.
We recommend to use the updated integration with push subscription as it avoids running any additional software (i.e. functions) in your GCP account which can contribute to operational overhead and costs.
New tooltips have been added to the dashboard widgets with an explanation of the information being displayed.
Top 3 Abnormal Errors – Above Normal / Newly Introduced
The Top 3 Abnormal Errors widget now differentiates between ‘Above Normal’ and ‘Newly Introduced’ errors. ‘Above Normal’ shows the amount above normal that is being seen (e.g. 3.2X normal levels), and ‘Newly Introduced’ shows the number of occurrences of the new errors.
Enhance your ‘Less Than‘ alerts using the ‘Group By’ option. Values under the ‘Group By’ fields are aggregated into a histogram, and an alert will trigger whenever the condition threshold is met for an aggregated value within the specified timeframe.
Some companies prefer separate teams to isolate data based on the environment it originates from like Dev, QA, and Production. While others prefer to isolate the data based on organizational units like Infrastructure, Security, and Application.
Coralogix supports multi-tenancy, allowing a single organization to contain multiple teams. The Org Admin can then manage quota, settings, users, and more at the organization level from a single interface.
Organizations can be created upon request. Please contact us through our in-app chat or via email at [email protected].
Use DataPrime to parse and query unstructured data fields on the fly. Plus, generate synthetic fields and run calculations from your archived data. From the query UI, view your query history and access a complete cheat sheet with documentation of the query format and operators.
Define a sequence of alerts in our Drag & Drop Flow Builder UI that combines Logs, Metrics, Tracing, and Security information to create a single alert flow that will trigger based on multiple conditions within defined timeframes.
Use Flow Alerts to generate actionable insights from your observability data:
Combine multiple alerts into a single, comprehensive flow to cover your security, infra, and business events with reduced noise and false positives.
Create alerts with the Root Cause built-in (e.g. Error elevation due to CPU, causing SLO breach) to track the entire chain of events leading to an error.
Identify potential security incidents and proactively remediate them with alert occurrences over time.
The DataMap allows you to build custom mappings of your infrastructure using metric data for monitoring system health and quickly identifying issues.
In the Group Editor, you’ll find new options to:
Sort the display by attributes (e.g. sort by severity for defined thresholds)
Scale threshold values to make metric graphs more readable
Limit the number of hexagons shown per group
In the DataMap display, use new ‘Compare to others’ functionality to compare an element with 10 others in the same group. Plus, expand and collapse specific groups to minimize the number of displayed elements.
New Execute Archive Query function allows you to review active filters before clicking ‘Run Query’. To prevent unexpected wait times, queries will no longer run automatically when switching from Logs to Archive.
Non-optimal archive queries (e.g. “hello”) will trigger a warning pop up recommending to improve the query conditions.
The option to snooze an alert, which was previously only available from the Insights screen, will now be available from within the main Alerts screen. This allows for centralized management of alert statuses across your team.
A new option on the Settings page gives users the ability to choose how much idle time will trigger a force logout from the system. In case of inactivity, a pop-up will appear to alert the user, prior to logout.